Frequently Asked Questions

LANCE

What is LANCE?

LANCE is a group of three near real-time data systems serving the Land and Atmosphere science community.

What is near real-time (NRT) data?

Near real-time is data that is available to users 3 hours or less after observation.

What near real-time systems are a part of LANCE?

LANCE consists of the GES DISC and MODAPS Distributed Active Archive Centers and AMSR2 Science Investigator-led Processing System (SIPS) and OMI SIPS.

What are standard products?

Standard products are products that are used for standard science processing and are generally available between 8-40 hours after observation.

What is the difference between near real-time and standard products?

Near real-time and standard products differ in the amount of processing the raw data receives. Near real-time data is processed with different, less accurate ancillary data to make it available to users within 3 hours of observation. The main difference is in geolocation due to the use of predictive orbit information vs waiting for definitive orbit information.

Where can I obtain standard products?

Each LANCE element provides standard products as well as near real-time products. Go to the Standard Products page for the data centers where the standard products are archived.

What LANCE data products are available?

Currently AIRS, AMSR2, MLS, MODIS and OMI near real-time products are available under LANCE.

Where do I go online to search and order LANCE data?

AIRS, AMSR2, MLS, MODIS and OMI near real-time data are available through the individual elements. Go to the Near Real-Time Data page for more information.

Who can order LANCE data products?

All NASA Earth Observing System (EOS) mission data including LANCE data is freely available to the public.

How long are LANCE near real-time data sets are available?

The near real-time data sets stay for about 7 days from the time they are generated.

How soon are LANCE near real-time data sets available?

The near real-time data that LANCE provides is available to users within 3 hours of observation.

Do I need to register to access LANCE data?

Yes, registration is required to obtain LANCE data. Please visit the Earthdata Login to register for a username and password.

Will there be a fee associated with accessing data?

Typically, there is no cost associated with accessing NASA Earth Science data. However, please refer to the EOSDIS Data and Information Policy for more information.

Who do I contact for support with LANCE data?

For questions about LANCE or user registration, contact Earthdata Support.

How do I stay informed about updates, announcements, data issues and scheduled maintenance?

Subscribe to receive notifications from LANCE about updates, announcements, data issues and scheduled maintenance.

LANCE-MODIS mailing list (For updates regarding NRT data from MODIS on Terra and Aqua)

OMI SIPS mailing list

LANCE-AIRS mailing list

LANCE-MLS mailing list

LANCE FIRMS mailing list (For updates on the Fire Information for Resource Management System)

LANCE Users mailing list (For general updates about LANCE. Please note, if you wish to receive information about data issues, use the relevant list above.)

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Near Real-Time Data

MODIS Near Real-Time Data

What is MODIS?

MODIS stands for MODerate Resolution Imaging Spectroradiometer. The MODIS instrument is on board NASA’s Earth Observing System (EOS) Terra (EOS AM) and Aqua (EOS PM) satellites. The orbit of the Terra satellite goes from north to south across the equator in the morning and Aqua passes south to north over the equator in the afternoon resulting in global coverage every 1 to 2 days. The EOS satellites have a ±55 degree scanning pattern and orbit at 705 km with a 2,330 km swath width. For an artist’s visualization of “MODIS scans the globe” go to: http://aqua.nasa.gov/doc/viz/media/aqua_modis_soren.mov. (Higher resolution movie files can be found at: http://aqua.nasa.gov/about/instrument_modis.php). The MODIS instrument provides 36 spectral bands from wavelengths of 0.4µm to 14.4µm. For more information, please visit the NASA MODIS website.

When were the Terra and Aqua satellites launched?

Terra (EOS AM) was launched 18 December 1999 and Aqua (EOS PM) was launched 4 May 2002. High quality hotspot/active fire observations are available from the Terra satellite starting November 2000 and from the Aqua satellite starting 4 July 2002 onwards.

What time does the satellite pass over my area?

Terra (EOS AM) passes over the equator at approximately 10:30 am and 10:30 pm each day, Aqua (EOS PM) satellite passes over the equator at approximately 1:30 pm and 1:30 am. The sun-synchronous orbit allows the satellites to pass over the same area at the same time in every 24 hour period (at every 99 minute orbit the satellites cross the equator at the above mentioned times; every other spot on Earth has similarly constant overpass times). The time of satellite pass will vary according to your location. To estimate when the satellite will pass over your area, you can use the satellite overpass predictor provided by NASA.

Daily Terra and Aqua global and regional orbit tracks are provided by the Space Science and Engineering Center (SSEC) at University of Wisconsin-Madison. The maps show a series of white lines with tic marks showing what time the satellite will pass over a certain location on the Earth. The white lines represent the center of the swath and the tic marks and time show at what time in UTC the satellite has passed over that location. Please refer to the MODIS Rapid Response System FAQ for more information: What do the orbit track maps show?

For an artist’s visualization of “MODIS scans the globe” go to: http://aqua.nasa.gov/doc/viz/media/aqua_modis_soren.mov. (Higher resolution movie files can be found at: http://aqua.nasa.gov/about/instrument_modis.php).

How often are data acquired?

The MODIS instrument on board the Terra and Aqua EOS satellites acquire data continuously providing global coverage every 1-2 days. Therefore there are at least 4 daily MODIS observations for almost every area on the equator – with the number of overpasses increasing (due to overlapping orbits) the closer an area is to the poles. See What time does the satellite pass over my area?

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Rapid Response

Where can I find more information on usage guidelines for the Rapid Response images?

Please refer to the Rapid Response page.

Can I use an image from your gallery for…?

All Rapid Response images are in the public domain and can be freely used and reproduced for any purpose. Please credit: “NASA/GSFC, Rapid Response.” If publishing online, please link to Rapid Response. For more information on use and credit, visit the Citation Policy page or contact Earthdata Support.

What do the red boxes mean?

Sheveluch Volcano and other thermal anomalies
Thermal anomalies detected on the Kamchatka Peninsula, Russia. At top right is the heat signature from the Sheveluch Volcano; the remainder are fires.

The red boxes indicate the location of a thermal anomaly that was detected by MODIS using data from the middle infrared and thermal infrared bands. In most cases, this thermal anomaly is a fire, but sometimes it is a volcanic eruption, or even the flare from a gas well. We have no way of knowing which it is based on the MODIS data alone. In areas of known volcanic activity, we can verify an eruption using published reports of volcanic activity worldwide. The red outlines don’t represent the actual size of the fire. They indicate the perimeter of 1km-resolution pixels containing the thermal anomaly detected by MODIS.

What do the different band combinations mean?

A digital color image displayed on a monitor is composed of three different color channels: red, green, and blue. Satellite images are made by combining the reflected light detected by the sensor at various wavelengths (spectral bands) and making them into a single image. The Rapid Response System makes use of MODIS broad range of spectral observations by creating both true-color and false-color images, each tailored to highlight different land surface, atmospheric, and oceanic features. Some of the ways these bands can be combined are described below.

True-color

Long Answer
True-color imagery uses MODIS Bands 1, 4, and 3, respectively corresponding to the red, green, and blue range of the light spectrum, are assigned to the red, green, and blue channels of a digital image. These images are called true-color or natural color because this combination of wavelengths is similar to what the human eye would see.

Short Answer
Bands
1,4,3 (670 nm: 565 nm: 479 nm)
Colors
Fire detection=red outlines
Advantages
Natural-looking images of land surface, oceanic and atmospheric features.

Band 3,6,7 Combination

Long Answer
The 3-6-7 composite assigns Bands 3, 6, and 7 to the red, green, and blue components of a digital image. This combination is good for revealing snow and ice because they are very reflective in the visible part of the spectrum, and very absorbent in Bands 6 and 7, which are a part of the spectrum called the short-wave infrared, or SWIR.

Snow and Ice
Since the only visible light used in these images (Band 3) is assigned to red, snow and ice appear bright red. The more ice, the stronger the absorption in the SWIR bands, and the more red the color. Thick ice and snow appear vivid red (or red-orange), while small ice crystals in high-level clouds will appear reddish-orange or peach.

Vegetation
Vegetation is absorbent in Band 3 and Band 7, but reflective in Band 6, and so will appear greenish in this band combination. Bare soil will appear bright cyan in the image since it much more reflective in Band 6 and Band 7 than Band 3.

Water
Liquid water on the ground will be very dark since it absorbs in the red and the SWIR, but small liquid water drops in clouds scatter light equally in both the visible and the SWIR, and will therefore appear white. Sediments in water appear dark red.

Short Answer
Bands
3,6,7 (479 nm: 1,652 nm: 2,155 nm)
Colors
Vegetation=Green
Ice or snow=Red
Liquid water on the ground=Black or dark red
Liquid water clouds=White
Ice clouds=Peach
Desert=Light blue-green
Advantages
Distinguishing liquid water from frozen water, for example, clouds over snow, ice cloud versus water cloud; or floods from dense vegetation.

Band 7-2-1 Combination

Long Answer
In this composite, MODIS Bands 7, 2, and 1, are assigned to the red, green, and blue portions of the digital image. This combination is most useful for identifying burn scars.

Vegetation and bare ground
Vegetation is very reflective in the near infrared (Band 2), and absorbent in Band 1 and Band 7. Assigning that band to green means even the smallest hint of vegetation will appear bright green in the image. Naturally bare soil, like a desert, is reflective in all bands used in this image, but more so in the SWIR (Band 7, red) and so soils will often have a pinkish tinge.

Burned areas
If vegetation burns, bare soil in the area will become exposed. Band 1 slightly increases usually, but that may be offset by the presence of black carbon residue. The near infrared (Band 2) will become darker, and Band 7 becomes more reflective. When assigned to red in the image, Band 7 will show burn scars as deep or bright red, depending on the type of vegetation burned, the amount of residue, or the completeness of the burn.

Water
As with the 3-6-7 composite, water will appear black. Sediments in water appear dark blue.

Short Answer
Bands
7,2,1 (2,155 nm: 876 nm: 670 nm)
Colors
Vegetation=Green
Water=Black or dark blue
Desert/Naturally bare soil=Sandy pink
Burn scar=Red to reddish-brown, depending on the nature of the pre-fire vegetation and the severity of the burn.
Advantages
Distinguishing burn scars from naturally low vegetation or bare soil. Enhancing floods.

What do the orbit track maps show?

Orbit track map with UTC time stamps in white
A cut-away from an orbit track map showing the Terra satellite overpass time near the Great Lakes (daytime granule starting at 17:10 UTC, nighttime granule starting at 03:35 UTC).

The maps have a series of white lines with tick marks on them that show what time (using Coordinated Universal Time, or UTC) the satellite will be passing over a particular location on Earth on a given day. The white lines represent the center of the swath. The time stamps mark the start of the northern (Terra) or southern (Aqua) edge of each 5-minute data collection period. An image acquired at that location will span roughly 1150 kilometers on either side of the tick mark. Every day there are two passes over most areas: one daylight pass, and one nighttime pass. At this point the Rapid Response System produces images for the daylight passes only.

How can I tell when MODIS will capture an image of my area?

For Near Real Time (Orbit Swath) Images

  • A link to the day’s orbit track map appears next to the satellite/instrument name on the Near Real Time (Orbit Swath) Images page.
  • The orbit track maps have a series of white lines with tick marks on them that show the time in Coordinated Universal Time (UTC) at which the satellite passes over that location. To find your area of interest, find the closest swath and note the times of the nearest tick marks encompassing your area.
    • The image created at a particular time will encompass an equal area on either side of the line. Depending on how close the exact location you are interested in is to the actual orbital line (which represents the center of the swath), your image may be very sharp, if it is near the center, or degraded, if it is close to the edge.
    • For every region there will be a daylight and nighttime pass. Only the daytime (i.e. local daytime) passes appear on our real-time production page.
  • The Near Real Time (Orbit Swath) Images are labeled with a time stamp that is the start time of a five-minute data collection period or granule (its northern edge for Terra or southern edge for Aqua). They are arranged in their approximate geographical position on the earth.

For Geometrically Corrected Images

  • Select a subset group from the MODIS Subsets page.
  • Select a red square that covers your region of interest.

Why do the real-time images look different from the gallery images?

Typhoon Rusa browse image, showing bow-tie distortion (left) and geometric correction for bow-tie effect (right).
Matching images of Typhoon Rusa from the summer of 2002, showing the bow-tie effect (left) and geometric correction (right).

Bow-tie effect
Satellite sensors collect data by pixels. A pixel of data represents the electromagnetic energy reflected from or radiated by a given area of ground. All these pixels are like individual boxes in a grid, and they are put together to make the complete image. In a single rotation of its scan mirror, MODIS captures an area on Earth about 2300 kilometers wide by 10 kilometers tall (imagine a long, thin rectangle). An image is put together by stitching one scan–one strip–on to the next.

Stretch
Because the area is so large, MODIS is looking straight down at the Earth in the center, but is looking off to the side at an angle. Just like the spot illuminated by a flashlight becomes wider the farther away the beam is pointed, the pixels that make up the MODIS image get wider the farther they are from the center of the image. Each MODIS scan gets stretched out at the edges, making the shape of each scan–each strip of the image–look more like a bow-tie than a true rectangle.

Overlap
Because the strips are wider at the edge than the center, the scans don’t overlap in the center of the image, but they do overlap near the edges of the swath. This overlap creates a “double-vision” effect on the edges of the swath, as each point of the Earth’s surface appears in two adjacent scans. This geometric distortion also makes the line where scans come together more pronounced, essentially magnifying tiny differences between one side of the scan mirror and the other, especially at the edge of the swath.

Distortion
The real-time images are displayed as they are scanned by MODIS, without correction for geometric distortion. Since the observed pixels at the edge of the swath are bigger than they are in the center, they appear to be scrunched into a too-small grid box when displayed “as-is” in the real-time imagery. We select certain images for geometric correction, and hand tailor them for our image gallery.

How do you correct for the bow-tie effect and distortion?
The code we use to correct for the bow-tie effect and distortion is not documented for distribution, but there are several free tools that will give similar results. We recommend the MODIS Swath to Grid Toolkit (MS2GT), HDFLook, or HDF-EOS To GeoTIFF Conversion Tool (HEG).

How do I make true-color MODIS images?

To help you create your own true color MODIS images, we provide a tutorial (PDF) that tells you where to get the software you need, including a version of our corrected reflectance, fire detection, and vegetation index algorithms. Because of regulations on code distribution, code distribution is handled by the Direct Readout Laboratory.

Other alternatives for geometrically correcting MODIS data include MODIS Swath to Grid Toolkit (MS2GT), HDFLook, and HDF-EOS To GeoTIFF Conversion Tool (HEG).

I’ve tried making my own MODIS images from MOD09 data ordered from LAADS Web, but they don’t look like yours. Why not?

We make our imagery directly from the MODIS L1B data (the calibrated, geolocated radiances), not the standard MODIS surface reflectance product (MOD09). Our images are based on custom corrected reflectance code that has been developed with the specific aim of maintaining image integrity, as opposed to the standard MODIS surface reflectance product, which was developed with scientific integrity as the primary objective. For example, we do not use an atmospheric correction. In some cases, our images undergo additional hand-tweaking to enhance their appearance; for example, we may apply different color stretchs depending on the type of phenomenon (e.g. dust, phytoplankton bloom, clouds) we are highlighting.

Can you provide the full data file for an image I like in your gallery?

For data appearing on the Near Real Time (Orbit Swath) Images page, links are provided to the near real time full spectral resolution files HDF files on the LANCE MODIS FTP site. Links are also provided to the science quality full spectral resolution files HDF files on the LAADS Web site.

Can you send me geometrically corrected images and fire detections for my area of interest each day?

A substantial investment of time and resources is required to provide hand-tailored image processing for specific regions on a daily basis. The Rapid Response System provides these products daily to a small number of partner organizations, including the USDA Forest Service and Global Observation of Forest Cover partners. These images are available on the MODIS Subsets page. As time and resources permit, we can occasionally respond to requests for coverage of significant events, and we are always interested in discussing the potential for meaningful scientific collaborations. If you are interested in proposing such a collaboration, please contact Earthdata Support.

Do you produce fire detections at night?

Nighttime fire detections are currently being collected for land regions across the world and are available from the Fire Information for Resource Management System (FIRMS).

What is the Julian day?

The Julian day, as we mean it, is the day of year (from 1 to 365 or 366). Most remote sensing data sets are identified using this julian date rather than the calendar date, because it is a more straightforward time scale for automatic processes. Note this is different from the common meaning of Julian Day as in Julian calendar.

Where do you get the data used to draw political boundaries and coastlines on your gallery images?

This vector information comes from the National Geospatial-Intelligence Agency’s (NGA) Vector Map (VMap) Level 0. It is available from the NGA web site.

Where can I find the georeferencing information for your subset and gallery images?

The georeferencing information is contained in two places, the More information page and the JPEG worldfile. They are accessible from links on each image page.

More information
This page describes the projection used to georeference the image, the latitude and longitude of the image center and corners, and some additional information about the image. If the image is rotated, the “rotation angle” field will be given. Counterclockwise rotation is positive; the image is first projected then rotated. If the pixel sizes are not equal in the X and Y direction. the “x scale factor” will be given; it can also be calculated: x_scale_factor = y_pixel_size / x_pixel_size.

Note that the coordinates given for the image corners are for the outside corner of the pixel, and thus will differ by one half of the pixel size from the numbers given in the JPEG World File.

JPEG worldfile
This file has the file extension .jgw and is an ASCII text file consisting of 6 lines, each containing a single number:

Value Parameter Description
250.000000000000 A Pixel size in X direction
0.000000000000 D Rotation term for Y
0.000000000000 B Rotation term for X
-250.000000000000 E Negative of pixel size in Y direction
-692125.000000000000 C X location of center of upper left pixel
544375.000000000000 F Y location of center of upper left pixel

The following equations will calculate the map coordinates of the center of pixel (x,y) when the coordinates of the upper left pixel are (0,0):

Map_X = Ax + By + C

Map_Y = Dx + Ey + F

Note that the pixel size in the Y direction is negative because the map origin is at the lower left and the image origin is at the upper left. The pixel size is in degrees for the Plate Carree projection and in meters for all other projections.

Some GIS and Image Processing software packages will not correctly handle images whose rotation terms (the second and third lines) are not 0.0.

How do I use your subset and gallery images in my GIS or Image Processing software package?

We are only able to do limited testing with subset and gallery images using GIS and Image Processing software packages and would greatly appreciate any questions, comments, corrections, clarifications, etc. on these instructions from our users. Please send them to Earthdata Support.

The “Download JPG image with ancillary files (.zip)” link on the individual subset image pages produces a zip file which includes 4 files – the subset image (.jpg), a worldfile with coordinate information (.jgw), a file with projection information (.prj), and a file with the projection information wrapped in XML tags for ArcGIS (.jpg.aux.xml). It is hoped that these ancillary files will allow the subset images to be loaded into GIS and image processing software packages without the user having to manually set the projection information. Again, feedback and corrections would be greatly appreciated. (This zip file is not yet available for Gallery images.)

NOTE: The global fire maps do not have georeferencing information.

NOTE: When downloading the worldfile (it is a .jgw file) on Windows computers, some versions of Windows append a “.txt” to the “.jgw” when you download it with “Save as type:” set to “Text Document.” If the worldfile is saved with a “.txt” extension, the GIS program will not be able to find the worldfile. The name of the worldfile must match the name of the image file except with “.jgw” in place of “.jpg.” To prevent this problem when downloading the worldfile in a Windows environment, change “Save as type”: to “All Files”. Also be aware that, when checking the worldfile name using Windows Explorer, in some versions you can’t see the “.txt” if the “Hide extensions for known file types” box is checked in Folder Options. In this case, the file name looks correct when it is not.

ArcMap

To use subset and gallery images in ArcMap:

  • First download the image (it is a .jpg file) and the worldfile (it is a .jgw file). You will also need to have some of the information from the “Display metadata” link handy. The “Display metadata” link is above the image on the left.
  • Either before or after opening the image in ArcMap, you must set the Layer Coordinate System. The projection is specified by the “projection” in the “Display metadata” page.
    • Plate Carree
      • NOTE: Images in mid to high latitudes will appear wider than on our web site because our pixels are narrowed to approximate equal area while ArcMap forces the pixels to be square. (The “x scale factor” can be found in the “Display metadata” page, the x_pixel_size is the first line of the .jgw file, the y_pixel_size is the fourth line of the .jgw file (with a “-” prepended) and x_scale_factor = y_pixel_size / x_pixel_size)
      • Right-click on “Layers”, select “Properties…” then the “Coordinate System” tab
      • Select “Predefined” in the “Select a Coordinate System” box, then “Geographic Coordinate Systems” -> “World” -> WGS_1984
      • Click “OK” for “Data Frame Properties”
    • Lambert Azimuthal – Sinusoidal – Stereographic
      • Right-click on “Layers”, select “Properties…” then the “Coordinate System” tab
      • Select “<custom>” in the “Select a Coordinate System” box
      • Click the “New” button then select “Projected Coordinate System…”
      • Enter a name in the “Name” box
      • Projection-specific instructions:
        • Lambert Azimuthal
          • In the “Projection” panel, under “Name” select “Lambert_Azimutal_Equal_Area”
          • Set “False_Easting” and “False_Northing” to 0
          • Set “Central_Meridian” to the value from the “projection center lon” in the “Display metadata” page
          • Set “Latitude_Of_Origin” to the value from the “projection center lat” in the “Display metadata” page
        • Sinusoidal
          • In the “Projection” panel, under “Name” select “Sinusoidal”
          • Set “False_Easting” and “False_Northing” to 0
          • Set “Central_Meridian” to the value from the “projection center lon” in the “Display metadata” page
        • Stereographic using Stereographic_South(North)_Pole
          • In the “Projection” panel, under “Name” select “Stereographic_South(North)_Pole”
          • Set “False_Easting” and “False_Northing” to 0
          • Set “Central_Meridian” to the value from the “projection center lon” in the “Display metadata” page
          • Set “Standard_Parallel_1″ to the value from the “standard parallel” in the “Display metadata” page
        • Stereographic using Stereographic
          • In the “Projection” panel, under “Name” select “Stereographic”
          • Set “False_Easting” and “False_Northing” to 0
          • Set “Central_Meridian” to the value from the “projection center lon” in the “Display metadata” page
          • Set “Scale_Factor” to the value from the “scale at natural origin” in the “Display metadata” page
          • Set “Latitude_of_Origin” to the value from the “projection center lat” in the “Display metadata” page
      • In the “Linear Unit” panel, under “Name” select “Meter”
      • If if the value of “ellipsoid” is “WGS84″ in the “Display metadata” page, then in the “Geographic Coordinate System” panel, click the “Select” button, then “World” then “WGS84.prj” (Now skip to the “Click OK for New Projected Coordinate System” step)
      • If if the value of “ellipsoid” is “Sphere” in the “Display metadata” page, then in the “Geographic Coordinate System” panel, click the “New…” button
      • Enter a name in the “Name” box
      • In the “Datum” panel, under “Name” select “<custom>”
      • In the “Spheroid” panel, under “Name” select “<custom>”
      • Set both “Semimajor Axis” and “Semiminor Axis” to the value from the “Earth radius (km)” in the “Display metadata” page. You will need to move the decimal point 3 digits to the right to convert from kilometers to meters.
      • In the “Angular Units” panel, under “Name” select “Degree”
      • In the “Prime Meridian” panel, under “Name” select “Greenwich”
      • Click “Finish” for “New Geographic Coordinate System”
      • Click “Finish” for “New Projected Coordinate System”
      • Click “OK” for “Data Frame Properties”

ArcView

NOTE: Some gallery images cannot be used in ArcView because they are rotated in order to capture more of the scene in a rectangular image. You can determine if an image is rotated or not by checking for the existance of the “rotation angle” keyword under the “Display metadata” link for that image.

To use subset and unrotated gallery images in ArcView:

  • First download the image (it is a .jpg file) and the worldfile (it is a .jgw file). You will have to replace all the periods in the file names (“.”), except the final one before the extension, with underscores (“_”). You can do this during the download process or afterwards. (Or you can completely rename the files, making sure that the portion before the .jpg and .jgw are identical.) You will also need to have some of the information from the “Display metadata” link handy. The “Display metadata” link is above the image on the left.
  • Make sure the ArcView JPEG Extension is enabled by going to File->Extension and checking “JPEG (JFIF) Image Support”.
  • Either before or after opening the image in ArcView, you must set the View Projection. The projection is specified by the “projection” in the “Display metadata” page.
    • Plate Carree
      • NOTE: (1) The settings below will most likely be the default settings. (2) Images in mid to high latitudes will appear wider than on our web site because our pixels are narrowed to approximate equal area while ArcView forces the pixels to be square. (The “x scale factor” can be found in the “Display metadata” page, the x_pixel_size is the first line of the .jgw file, the y_pixel_size is the fourth line of the .jgw file (with a “-” prepended) and x_scale_factor = y_pixel_size / x_pixel_size)
      • Go to View->Properties
      • Set “Map Units” to “decimal degrees”
      • Click the “Projection…” button
      • Click the “Standard” button
      • Set “Category” to “Projections of the World”"
      • Set “Type” to “Geographic”
    • Lambert Azimuthal
      • Go to View->Properties
      • Set “Map Units” to “meters”
      • Click the “Projection…” button
      • Click the “Custom” button
      • Set “Projection” to “Lambert Equal-Area Azimuthal”
      • “Spheroid” will be forced to a value of “Sphere”
      • Set “Central Meridian” to the value from the “projection center lon” in the “Display metadata” page
      • Set “Reference Latitude” to the value from the “projection center lat” in the “Display metadata” page
    • Sinusoidal
      • Go to View->Properties
      • Set “Map Units” to “meters”
      • Click the “Projection…” button
      • Click the “Custom” button
      • Set “Projection” to “Sinusoidal”
      • “Spheroid” will be forced to a value of “Sphere”
      • Set “Central Meridian” to the value from the “projection center lon” in the “Display metadata” page

ENVI

NOTE: Some gallery images cannot be used in ENVI because they are rotated in order to capture more of the scene in a rectangular image. You can determine if an image is rotated or not by checking for the existance of the “rotation angle” keyword under the “Display metadata” link for that image.

To use subset and unrotated gallery images in ENVI:

  • First download the image (it is a .jpg file) and the worldfile (it is a .jgw file). You will also need to have some of the information from the “Display metadata” link handy. The “Display metadata” link is above the image on the left.
  • In order to save the new projections you will create, for projections other than Plate Carree, you will need to have a writeable copy of the file “map_proj.txt”. First make a copy of the original ENVI file in your own directory space. (In our SGI installation, the file was found in the directory /usr/local/lib/idl_5.5/products/envi_3.5/map_proj.) Second, you must make this copy of “map_proj.txt” your default copy by selecting File -> Preferences -> User Defined Files… and using “Choose” to select “Default Map Projection File”. You must restart ENVI for the change to take effect.
  • Due to a bug (in some ENVI versions) in specifying some parameters for Lambert projections, you may need to create the projection in the “map_proj.txt” file. Instructions are provided below.
  • The projection is specified by the “projection” in the “Display metadata” page.
    • Plate Carree
      • NOTE: Pixels in images from mid to high latitudes will not be square in degrees because they are narrowed to approximate equal area. (The “x scale factor” can be found in the “Display metadata” page, the x_pixel_size is the first line of the .jgw file, the y_pixel_size is the fourth line of the .jgw file (with a “-” prepended) and x_scale_factor = y_pixel_size / x_pixel_size)
      • Open the JPEG file with Open External File -> Generic Formats -> JPEG. Select the filename and click “OK”
      • The “JPEG World File Input Projection” dialog will appear.
      • In the “Select Input projection” box, select “Geographic Lat/Lon”
      • In the “Datum…” box, select “WGS-84″
      • In the “Units…” box, select “Degrees”
      • Click “OK” for “JPEG World File Input Projection”
    • Lambert Azimuthal (using “map_proj.txt” file)
      • Edit your “map_proj.txt” file and add a new line containing the following:
      • A “36″ for Lambert Azimuthal Equal Area (sphere), followed by a comma
      • The value from the “Earth radius (km)” in the “Display metadata” page, followed by a comma. You will need to move the decimal point 3 digits to the right to convert from kilometers to meters.
      • The value from the “projection center lat” in the “Display metadata” page, followed by a comma
      • The value from the “projection center lon” in the “Display metadata” page, followed by a comma
      • Finally, “0.0,0.0,” (for false easting and northing) followed by a unique name for the projection
      • Save the file with the new projection definition and restart ENVI for the change to take effect.
      • Open the JPEG file with Open External File -> Generic Formats -> JPEG. Select the filename and click “OK”
      • The “JPEG World File Input Projection” dialog will appear.
      • In the “Select Input projection” box, select the name of your new projection
      • In the “Datum…” box, select “<none>”
      • In the “Units…” box, select “Meters”
      • Click “OK” for “JPEG World File Input Projection”
    • Lambert Azimuthal (using “Customized Map Projection Definition”)
      • Open the JPEG file with Open External File -> Generic Formats -> JPEG. Select the filename and click “OK”
      • The “JPEG World File Input Projection” dialog will appear.
      • In the “Select Input projection” box, select “New…”
      • Enter a unique name in the “Projection Name” box
      • In the “Projection Type” box, select “Azimuthal Equal Area (sphere)”
      • Set “Sphere Radius” to the value from the “Earth radius (km)” in the “Display metadata” page. You will need to move the decimal point 3 digits to the right to convert from kilometers to meters.
      • Set “False easting” and “False northing” to 0
      • Set “Latitude of projection origin” to the value from the “projection center lat” in the “Display metadata” page
      • Set “Longitude of central meridian” to the value from the “projection center lon” in the “Display metadata” page
      • Click “OK” for “Customized Map Projection Definition”
      • You will asked if you want to save the customized projection to the “map_proj.txt” and, if so, to select a filename and if you want to overwrite.
      • If you saved the projection, the next time you open the JPEG file, you can simply select the customized projection name from the “Select Input projection” box.
      • In the “Datum…” box, select “<none>”
      • In the “Units…” box, select “Meters”
      • Click “OK” for “JPEG World File Input Projection”
    • Sinusoidal
      • Open the JPEG file with Open External File -> Generic Formats -> JPEG. Select the filename and click “OK”
      • The “JPEG World File Input Projection” dialog will appear.
      • In the “Select Input projection” box, select “New…”
      • Enter a unique name in the “Projection Name” box
      • In the “Projection Type” box, select “Sinusoidal”
      • Set “Sphere Radius” to the value from the “Earth radius (km)” in the “Display metadata” page. You will need to move the decimal point 3 digits to the right to convert from kilometers to meters.
      • Set “False easting” and “False northing” to 0
      • Set “Longitude of central meridian” to the value from the “projection center lon” in the “Display metadata” page
      • Click “OK” for “Customized Map Projection Definition”
      • You will asked if you want to save the customized projection to the “map_proj.txt” and, if so, to select a filename and if you want to overwrite.
      • If you saved the projection, the next time you open the JPEG file, you can simply select the customized projection name from the “Select Input projection” box.
      • In the “Datum…” box, select “<none>”
      • In the “Units…” box, select “Meters”
      • Click “OK” for “JPEG World File Input Projection”

How do I use the “Search by keyword” feature in your gallery?

Each Rapid Response Gallery image is annotated with keywords to aid in finding images of interest. The keywords fall into two categories, geographic, such as country, US state, Canadian province, and water body names, and image subject, such as “fire”, “hurricane”, “phytoplankton bloom”, “volcano”, “dust”, “smoke”, “iceberg”, “snow”, etc.

This is a very simple search which searches on a literal string. The search is not case sensitive and the string can contain blanks (e.g. “new mexico”) or partial words. The search input can be multiple literal strings seperated by upper case “OR” (e.g., “hurricane OR typhoon OR tropical storm”). Similarly the search input can be a pair of strings separated by upper case “AND” (e.g., “canada AND fire”). The matching images are displayed with the most recent images at the top of the page. If no matches are found, only the search boxes will be displayed.

Some examples of keywords which will not work are city names and continent names. Continent names will return some images from that continent but it will not be a complete list.

How can I tell what time a subset image was acquired?

To find out when MODIS collected the data used in the subset image, click on “Display metadata (including time of input data)” above the image. Under “5 minute swath data used for this image”, there is a list of the MODIS granules that are included in the image. Click on the time of the overpass in UTC to see the real-time browse image for each granule.

The subset images may be composited from data collected in different MODIS overpasses at different times. Because the images cover set geographic regions, not a particular MODIS swath, the automated system that generates the subset images takes data from the overpasses that are closest to being directly overhead. Where overpasses overlap in the high latitudes of the north and the south, data from two or more overpasses (100 minutes apart) may be used to create the subset image. In these cases, a faint line may be visible where the two overpasses meet. White shows where data are not available either because MODIS has not imaged that region yet or because the area is out of the instrument’s range for that day. In equatorial regions, where overpasses do not overlap, MODIS data may not be available for the entire region every day. In these cases, a white wedge where no data were available may separate two MODIS overpasses.

How can I set up a direct broadcast system to receive data from the MODIS sensor?

The Direct Readout Laboratory can provide more information about setting up a direct broadcast system. You can also find additional information on the MODIS home page.

How do I convert to NDVI values from the colors in your NDVI images?

The colors used for the ndvi subset images (since June 2, 2004 (2004154), except NewMexico) can only be converted back to one-tenth NDVI ranges, as follows:

Color NDVI
R G B  
153 204 255 <=0.0
225 175 100 0.0-0.1
255 225 150 0.1-0.2
225 255 175 0.2-0.3
152 255 152 0.3-0.4
102 255 102 0.4-0.5
51 204 51 0.5-0.6
0 153 0 0.6-0.7
0 102 0 >0.7
255 255 255 no data

For realtime images, subset images before June 2, 2004 (2004154), and the NewMexico subset, use the following conversion table:

Color NDVI
R G B  
140 190 255 <=0.0 (includes missing data)
255 245 225 0.00-0.05
255 225 200 0.05-0.10
245 201 140 0.10-0.15
255 221 85 0.15-0.20
235 190 55 0.20-0.25
250 255 180 0.25-0.30
230 250 155 0.30-0.35
205 255 105 0.35-0.40
175 240 90 0.40-0.45
160 245 165 0.45-0.50
130 225 135 0.50-0.55
120 200 120 0.55-0.60
158 198 108 0.60-0.65
140 175 70 0.65-0.70
70 185 40 0.70-0.75
50 150 20 0.75-0.80
20 120 80 0.80-0.85
30 80 0 0.85-0.90
120 20 20 >0.90

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Fire Information for Resource Management System (FIRMS)

The Fire Information for Resource Management System (FIRMS) delivers global MODIS hotspots / fire locations in easy to use formats

FIRMS distributes both:

For updates, announcements, data issues and scheduled maintenance, subscribe to the LANCE FIRMS mailing list.

For the most current information about the Terra and Aqua MODIS fire products, use the MODIS Collection 5 Active Fire Product User’s Guide, v2.5 (Updated 31 March 2013).

Who do I acknowledge if I use data from FIRMS?

The data and graphics from FIRMS can be used freely. Please use the acknowledgement found on the Citation Policy page.

Please read the About FIRMS page, the Citation Policy page and the Disclaimer for more information about using FIRMS and LANCE data.

What caveats should be considered when using active fire data from FIRMS?

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About MODIS and MODIS Active Fire Data

About MODIS

Please refer to the Near Real-Time Data FAQ section for more information about MODIS.

If you wish to view the MODIS swath image that corresponds to the active fire detections, please go to Worldview.

How often are active fire data acquired?

The MODIS instrument on board the Terra and Aqua EOS satellites acquire data continuously providing global coverage every 1-2 days. Terra (EOS AM) passes over the equator at approximately 10:30 am and 10:30 pm each day, Aqua (EOS PM) satellite passes over the equator at approximately 1:30 pm and 1:30 am. There are at least 4 daily MODIS observations for almost every area on the equator, with the number of overpasses increasing (due to overlapping orbits) closer to the poles. See: “When will the satellite pass over my area?”.

LANCE data are available in Near Real Time (NRT), 3 hours or less after observation.

What is a MODIS active fire detection?

A MODIS active fire detection represents the center of a 1km (approx.) pixel flagged as containing one or more actively burning hotspots/fires. The fires are detected using data from the MODIS instrument, on board NASA’s Aqua and Terra satellites. The satellites take a ‘snapshot’ of events as it passes over the earth. In most cases, MODIS fires are vegetation fires, but sometimes it is a volcanic eruption or the flare from a gas well. There is no way of knowing which type of thermal anomaly is detected based on the MODIS data alone.

How are fires detected by the satellite?

The active fire detections are processed by LANCE using the same algorithm as the standard MODIS MOD14/MYD14 Fire and Thermal Anomalies product. Fire detection is performed using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. The algorithm examines each pixel of the MODIS swath, and ultimately assigns to each one of the following classes: missing data, cloud, water, non-fire, fire, or unknown. More information can be found in: Giglio, L., Descloitres, J., Justice, C. O. and Kaufman, Y. 2003. An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87:273-282. doi: 10.1016/S0034-4257(03)00184-6

What does a MODIS hotspot/active fire detection mean on the ground?

Each hotspot/active fire detection represents the center of a 1km (approx.) pixel flagged as containing one or more fires, or other thermal anomalies (such as volcanoes). The “location” is the center point of the pixel (not necessarily the coordinates of the actual fire). The actual pixel size varies with the scan and track (see: “What does scan and track mean?”). The fire is often less than 1km in size (see: “What size fires can be detected?”). We are not able to determine the exact fire size, what we do know is that at least one fire is located within that 1km pixel. Sometimes you will see several active fires in a line. This generally represents a fire front.

What size fires can be detected?

In any given scene the minimum detectable fire size is a function of many different variables (scan angle, biome, sun position, land surface temperature, cloud cover, amount of smoke and wind direction, etc.), so the precise value will vary slightly with these conditions. MODIS routinely detects both flaming and smoldering fires 1000 m2 in size. Under very good observing conditions (e.g. near nadir, little or no smoke, relatively homogeneous land surface, etc.) flaming fires one tenth this size can be detected. Under pristine (and extremely rare) observing conditions even smaller flaming fires 50 m2 can be detected. It is not recommended to estimate burned area from the active fire data, see: “Can I estimate burned area using the active fire data?”.

Unlike most contextual fire detection algorithms designed for satellite sensors that were never intended for fire monitoring (e.g. AVHRR, VIRS, ATSR), there is no upper limit to the largest and/or hottest fire that can be detected with MODIS.

Example of the day and night relationship of fire size and fire temperature

The diagram shows the day and night relationship of fire size and fire temperature, in different biomes, to the probability of being detected by MODIS (Giglio et al. (2003)).

I only see fire data available for the last 7 days on your website. How can I get older data?

Data for the last 2 months can be downloaded as text (TXT) files and older data can be obtained through the MODIS Fire Archive Download Tool.

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Factors that Affect Fire Detections

Why did MODIS not detect a particular fire?

There are several reasons why MODIS may not have detected a certain fire. The fire may have started and ended between satellite overpasses. The fire may have been too small or too cool to be detected in the 1 km2 MODIS footprint. Cloud cover, heavy smoke, or tree canopy may completely obscure a fire. Occasionally the MODIS instruments are inoperable for extended periods of time (e.g. the Terra MODIS outage in September 2000) and can observe nothing during these times.

How do I know if a fire detection was missed due to cloud or missing data?

An indication of cloud cover or missing data is not yet included in FIRMS, however latest near real-time browse images can be viewed in Worldview. To take cloud and missing data in to account, it may be more appropriate to use one of the 1km Level 3 or CMG fire products (see: MODIS Fire User Guide).

Why do you not see the same fire twice in subsequent overpasses?

This is due to the dynamic and diurnal patterns associated with fire. Fires move across the landscape at varying rates, depending on multiple factors including, for example, the underlying vegetation type and the specific characteristics of the fire, and therefore may be present in different locations when the satellites pass overhead. In addition, the inherent diurnal burn-up and die-down patterns of a fire can impact whether one can see the same fire twice.

Do cloud shadows affect fire detections?

Cloud shadows do not significantly affect fire detections.

Can MODIS detect fires below the forest canopy?

The likelihood of detecting a fire beneath the tree canopy is unknown, but likely to be very low. Understory fires are typically small, and with the tree canopy obstructing the view of the fire, detection will be very unlikely.

How does the view angle of the MODIS instrument affect fire detections?

The wider the view, the larger the pixel field of view (the ground space covered). As a result, you would need a proportionately larger fire area to achieve the same likelihood of detection at nadir for most algorithms. This necessity is incorporated into quality control reporting.

How does air temperature affect fire detection?

Differences in air temperature have a negligible effect on fire detection. Differences in surface temperature, however, have a much larger impact as warmer areas like sandbeds, rock outcrops, etc., can cause false positives. Filters incorporated into the algorithms attempt to correct for this.

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Using FIRMS Active Fire Data

How appropriate are the 1km MODIS fire locations for my research?

The MODIS fire locations are good for determining the location of active fires, providing information on the spatial and temporal distribution of fires and comparing data between years. The 1km (approx.) MODIS active fire pixel locations may not always be the most appropriate source of fire related information. The data do not provide any information on cloud cover or missing data. Depending on the analysis you are performing, it is sometimes possible to derive misleading or even incorrect results by ignoring the other types of pixels. In some cases it is more appropriate to use one of the 1km Level 3 or CMG fire products. For more information, refer to the MODIS Collection 5 Active Fire Product User's Guide, v2.5 (Updated 31 March 2013).

What is the Climate Modeling Grid (CMG) fire product?

The CMG fire products are gridded statistical summaries of fire pixel information intended for use in regional and global modeling. The products are currently generated at 0.5 degree spatial resolution for time periods of one calendar month (MOD14CMH/MYD14CMH) and eight days (MOD14C8H/MYD14C8H). Higher resolution 0.25 degree CMG fire products will eventually be produced as well. More information can be found in the MODIS Collection 5 Active Fire Product User's Guide, v2.5 (Updated 31 March 2013).

Fire Pixel Locations vs. Gridded Fire Products

We urge caution in using fire pixel locations in lieu of the 1-km gridded MODIS fire products (CMG fire product). The former includes no information about cloud cover or missing data and, depending on the sort of analysis that is being performed; it is sometimes possible to derive misleading (or even incorrect) results by not accounting for these other types of pixels. It is also possible to grossly misuse fire pixel locations, even for regions and time periods in which cloud cover and missing observations are negligible.

Some caveats to keep in mind when using MODIS fire pixel locations:

  • The fire pixel location files allow users to temporally and spatially bin fire counts arbitrarily. However, severe temporal and spatial biases may arise in any MODIS fire time series analysis employing time intervals shorter than about eight days.
  • Known fires for which no entries occur in the fire-pixel location files are not necessarily missed by the detection algorithm. Cloud obscuration, a lack of coverage, or a misclassification in the land/sea mask may instead be responsible, but with only the information provided in the fire location files this will be impossible to determine.

Can I estimate burned area using the active fire data?

It is not recommended to use active fire locations to estimate burned area due to spatial and temporal sampling issues. Determining this to an acceptable degree of accuracy is generally not possible due to nontrivial spatial and temporal sampling issues. For some applications, however, acceptable accuracy can be achieved, although the effective area burned per fire pixel is not simply a constant, but rather varies with respect to several different vegetation and fire-related variables. See Giglio et al. (2006) for more information.

FIRMS provides monthly burned area images for visualization via Web Fire Mapper.

Please refer to the MODIS Active Fire & Burned Area Products web site for more information on the MODIS Burned Area Product and instructions on how download the monthly burned area HDF and GeoTIFF files.

What are the attributes/fields of the active fire data?

View the Attribute table on the About FIRMS page.

What is the brightness temperature?

The brightness temperature of a fire pixel is measured (in Kelvin) using the MODIS channels 21/22 and channel 31. Brightness temperature is actually a measure of the photons at a particular wavelength received by the spacecraft, but presented in units of temperature.

What does scan and track mean?

The scan value represents the spatial-resolution in the East-West direction of the scan and the track value represents the North-South spatial resolution of the scan.

It should be noted that the pixel size is not always 1km across the scan track. The pixels at the “Eastern” and the “Western” edges of the scan are bigger than 1km. It is 1km only along the nadir (exact vertical from the satellite). Thus, the values shown for scan and track represent the actual spatial resolution of the scanned pixel.

What is the detection confidence?

A detection confidence is intended to help users gauge the quality of individual active fire pixels. This confidence estimate, which ranges between 0% and 100%, is used to assign one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire) to all fire pixels within the fire mask. The confidence field should be used with caution; it is likely that it will vary in meaning in different parts of the world. Nevertheless some of our end users have found such a field to be useful in excluding false positive occurrences of fire.

What are Collections?

Reprocessing of the entire MODIS data archive is periodically performed to incorporate better calibration, algorithm refinements, and improved upstream products into all MODIS products. The updated MODIS data archive resulting from each reprocessing is referred to as a collection. Later collections supersede all earlier collections. For Terra MODIS, Collection 1 consists of the first products generated following launch. Terra MODIS data were first reprocessed for the first time in June 2001 to produce Collection 3. Note that this first reprocessing was numbered Collection 3, rather than Collection 2, as one would expect. Collection 3 was also the first produced for the Aqua MODIS products. Collection 4 reprocessing was initiated in December 2002 for Terra MODIS, and somewhat later for the Aqua MODIS. Collection 5 began reprocessing in early 2007, and it forms the current archive of the MODIS products. Improvements in Collection 5 included adding the Fire Radiative Power value to the fire detections and refining the detection confidence to more accurately identify questionable active fire pixels. Collection 6 will be released later this year (2014). Some of the key differences between Collection 5 and Collection 6 will be that Collection 6 will extend processing to oceans and other large bodies, including detection of off-shore gas flaring, there will be a reduction in false alarms in the Amazon caused by small forest clearings and there will be an improved cloud mask.

Are there any missing MODIS fire data?

Terra was launched 18 December 1999 and Aqua was launched 4 May 2002. High quality active fire observations are available from the Terra satellite starting November 2000 and from the Aqua satellite starting 4 July 2002 onwards.

In the Collection 5 fire data archive, there are several days where data was not collected and days with lower than usual fire counts due to reasons such as sensor outage. These include, but are not limited to: 15 April 2001, 15 June – 3 July 2001 and 19 – 28 March 2002.

Can you use the MODIS active fire product for detecting volcanoes or volcanic eruptions?

The algorithm routinely detects active volcanoes but the active fire product has not been validated against independent data for its ability to detect volcanoes. There is a separate near-real time MODIS product specifically for volcanoes: MODVOLC.

What validation of the MODIS active fire products has been performed?

Validation of the Terra MODIS Fire Product has primarily been performed using coincident observations from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER); see the MODIS Land Team Validation page, and publications by Csiszar et al. (2006) and two publications from Morisette et al. (2005) for details. A very brief discussion of the general validation procedure, with some preliminary results, can be found in the Justice et al. (2002) publication.

Where can I get more information on the MODIS Fire Products?

For more information on the active fire product and other MODIS fire products, please refer to the MODIS Active Fire & Burned Area Products web site and the MODIS Burned Area User Guide (Updated May 2013) and the MODIS Collection 5 Active Fire Product User's Guide, v2.5 (Updated 31 March 2013).

What other types of fire data are available?

AVHRR: Advanced Very High Resolution Radiometer. AVHRR is a passive optical sensor that measures electromagnetic radiation (light reflected and heat emitted) from our planet. AVHRR was originally intended only as a meteorological satellite system but it does have applications for fire monitoring. AVHRR remotely senses cloud cover and sea surface temperature, enabling its visible and infrared detectors to observe trends in vegetation, clouds, shorelines, lakes, snow and ice. The visible bands can detect smoke plumes from fires as well as burn scars. The thermal infrared band can detect actual hotspots and active fires. Its ability to detect fires is greater at night, since the system can confuse active fires with heated ground surfaces, such as beach sand and asphalt.

Active fire mapping on a global scale using a single satellite system has been coordinated by the International Geosphere Biosphere Program (IGBP) using AVHRR data for 1992-93 from international ground stations.

In addition, a small number of countries have developed their own regional AVHRR satellite fire monitoring systems using direct read-out; e.g., Brazil, Russia, and Senegal. Research groups have provided regional examples of trace gas and particulate emissions from fires for Brazil, Southern Africa and Alaska.

GOES: Geostationary Operational Environmental Satellite
The Geostationary Operational Environmental Satellites (GOES) house a five-channel (one visible, four infrared) imaging radiometer designed to sense radiant and solar reflected energy from sample areas of the Earth. They are stationed in orbits that remain fixed over one spot on the equator, providing continuous coverage of one hemisphere. GOES satellites acquire images every 15–30 minutes, at up to 1km resolution in visible light, for the detection of smoke, and 4km resolution in thermal infrared to directly detect the heat of fires.

MSG SEVIRI: Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI)
The Meteosat Second Generation (MSG) satellite houses the optical imaging radiometer called the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The sensor features 12 spectral channels and will provide cloud imaging and tracking, fog detection, measurement of the Earth surface and cloud top temperatures, tracking ozone patterns, as well as active fire monitoring.

The nominal coverage of the satellite includes the whole of Europe, all of Africa and locations at which the elevation to the satellite is greater than or equal to 10°. The various channels provide measurements with a resolution of 3 km at the sub-satellite point. The High Resolution Visible (HRV) channel provides measurements with a resolution of 1km.

The service, which commenced operations in January 2004, is due to continue until at least 2018.

What projection are the shapefiles in?

The shapefiles are in the Geographic WGS84 projection.

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FIRMS Web Fire Mapper

Why can’t I open Web Fire Mapper in my browser?

If you are having trouble accessing Web Fire Mapper, your Internet Service Provider or organization may be blocking port 8080. Web Fire Mapper runs on port 8080 and blocking this port will effectively prevent the service from loading in your browser. Please contact your network administrator to remedy the situation. However, if you have determined that port 8080 is NOT blocked on your end, the WFM service may be experiencing technical interruptions. Please contact Earthdata Support, and let us know about this issue.

When trying to access Web Fire Mapper, I get an error that reads “Service not available. Please try again”. What does this mean?

The “Service not available” message is displayed in the event there is an error with the internal workings (e.g. database) of the Web Fire Mapper system. Please wait for a few minutes and try to refresh the page (Ctrl + F5). If you still get the error, please contact Earthdata Support.

What open source components are used in Web Fire Mapper?

The Web Fire Mapper was developed using Open Source web-GIS technologies, including UMN Mapserver, Google Web Toolkit, PHP and PostgreSQL with the spatial database add-on, PostGIS. The Servers utilized at the University of Maryland have Linux operating systems and Apache/Tomcat web-servers, making the entire system completely based on free and open source software.

Can I download the fire data from Web Fire Mapper?

Active fire data are not currently available for download via Web Fire Mapper. However, active fire locations are available for download for the last 24 hours, last 48 hours and last 7 days on the Active Fire Data page. Older data can be obtained through the Archive Download Tool.

Can I get information on burned areas from Web Fire Mapper?

FIRMS currently offers visualization of monthly burned area images in Web Fire Mapper. Please refer to the MODIS Active Fire & Burned Area Products web site for more information regarding the MODIS Burned Area Product.

What is the difference between FIRMS data sourced from LANCE FIRMS and University of Maryland?

There are 3 key differences between data processed by LANCE FIRMS (MCD14DL) and University of Maryland (MCD14ML). The first is the time taken to process the data: data from LANCE are processed in near real-time (within 3 hours of satellite overpass), while FIRMS data from University of Maryland will generally available after a three month lag. The second is the “quality assurance” of Level 1B data used to generate the fire product – data from the University of Maryland are quality checked, and sometimes reprocessed at a later date if some problems are found with specific granules (the reason for the 3 month lag in making the collection from University of Maryland available via LANCE FIRMS is to allow for any reprocessing of granules before the fire product is generated). The third reason is that University of Maryland Aqua data are processed with the definitive ephemeris downloaded from the satellite (this provides the actual location of the satellite, which in turn affects the geolocational accuracy of the MODIS granules). Aqua data processed by LANCE FIRMS uses a predicted ephemeris (updated daily using definitive data). The difference in geolocations from the definitive and predicted is checked daily by the LANCE FIRMS. The difference is usually in the range of 50-100m. In cases where it exceeds 400m (only happens during certain spacecraft maneuvers), affected data are reprocessed with the definitive data the next day. Users are encouraged to use the University of Maryland Collection 5 for any historical analysis.

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Email Alerts

Can you notify me when a fire occurs in my area of interest?

We have developed a global fire email alert system to notify users when a fire occurs in, or near, a specified area of interest, country or protected area. You can subscribe to receive near-real time, daily or weekly email alerts in English, Spanish or French.

To subscribe, or learn more about the email based alert system, please see the FIRMS Email Alerts page.

Do you provide mobile/cell phone text messages?

No, we do not currently provide SMS text messages. In the past, we helped develop such a service in collaboration with ESKOM and CSIR Meraka in South Africa for the protection of power lines in remote areas from wildfires informing operators in the field about fire events in near-real time. For more information see: Davies, D. K., H. F. Vosloo, et al. (2008). Near real-time fire alert system in South Africa: from desktop to mobile service http://doi.acm.org/10.1145/1394445.1394479 Proceedings of the 7th ACM conference on Designing interactive systems Cape Town, South Africa ACM: 315-322

What are the near-real time email alerts?

The near-real time alerts provide fire locations of fires that have occurred in your area within 3 hours of satellite overpass. They are subscribed to and managed by the user just the same way as the daily and weekly detection summaries.

How do I subscribe or edit email alerts?

Go to the FIRMS Email Alerts page.

  1. Enter the email address where you want to receive the email alerts and click “Proceed”.
  2. If you have not yet subscribed you will be asked to enter your Name, Organization, and Country. Click on “Save” after you have entered your information.
  3. You will be taken to the subscription summary page, where the user can create a new subscription or view existing subscriptions. The user can create several subscriptions, and they will be added to their subscription summary profile.
  4. Click on the “Create a New Subscription” link to take the user to the interface to subscribe to an email alert.
    Creating a new subscription:
    • Choose your area of interest: The user can choose to select an area from a map (by defining a rectangular area), from a country drop down list or a drop down list of protected areas.
    • Customize your email alert by changing your subscription preferences:
      1. Name your alert (optional): The user can choose to give your alert a name for you to easily reference.
      2. Output map size: The user may choose to receive a map in the email and different sized maps are available.
      3. Background image: This refers to the background image on which the fires will be overlaid in the map in the email.
      4. Language preference: English, Spanish and French.
      5. Alert type: Daily, Weekly or Near-Real Time.
        • Daily: Fire detections are sent in a summary email every morning EDT (USA) with fire detections from the previous 24 hours.
        • Weekly: A week’s worth of fire points detected for the specified area are sent to the user on Monday mornings EDT (USA).
        • Near-real time: The fire points are sent out in an email as soon as they are processed by LANCE (within 3 hours of satellite overpass). The number of email varies depending on whether or not there was a fire in the specified area, whether or not it was detected, and the geographical location of the area (there are more frequent overpasses at high latitudes, and 4 daily overpasses for most places on the equator).
    • Email preferences: The user can choose to receive an email with a map and text, or text only.
    • Attach .CSV file: By default this option is flagged, meaning that the subscriber will also receive a CSV file containing the fire location information.
    • Help with subscription preferences: Clicking on the hyperlinked text of the subscription preferences will open pop-up messages containing the description and usage of the preference.
    • Email confirmation and final subscription: The user can choose not to receive an email confirming that he/she has subscribed successfully to an alert. The final signoff is completed by clicking either “Save Subscription” or “Cancel” (deletes all selections).
    • Subscription confirmations: The successful subscription is identified by two steps, the first of which is the confirmation page and a confirmation email (if this was selected). The confirmation page provides a link to let you return to the ‘Add, view or edit your subscription’ page.

I requested a map image with my email alert but I can’t see the map in my email alert, where is it?

Please check the settings in your email client. Your email client may be blocking images from being displayed in your email as a security measure. You will have to enable the choice to view images in your email. Your email client may also be sending the email alert to your spam/junk folder as a security measure and it is likely that you will also not be able to view the map image if the email is in your spam/junk folder. You should add the FIRMS email address and/or email domain to the safe senders list, so it will deliver the email to your inbox and display images. You can also view the map by clicking on the link below the map image “View Map Image on FIRMS server”; this will open the map in your browser.

I have received a CSV file as part of my Email Alert, how do I add it as a layer in a Desktop GIS software?

A CSV or Comma Separated Value file, is a text file in which separate fields are delimited by commas. This type of file can be used to store simple tabular data efficiently, minimizing file size. CSV files are easily opened with DB administration software such as PostgreSQL or MS Access, or by spreadsheet software such as MS Excel. This type of file can also be used to easily plot point data on desktop GIS software, given, as the active fire data does, that the tabular data contains X and Y coordinate information. The active fire data contains latitude and longitude location coordinates and the attributes of the detected fires. For instructions on how to use CSV files in a desktop GIS please see the Email Alerts.

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Worldview

How do I share a view I have created?

To share a view, keeping the dates and layers selected, click on the white "link" icon in the upper right corner. This will generate a link you can copy and paste.

Why is there no imagery of the U.S. on Worldview for the current day?

Depending on the time you access Worldview, imagery is probably not shown for the U.S because the satellite has not yet passed over the country. You can look at previous days' imagery by using the date slider at the bottom of the screen.

What are the large data gaps or missing areas near the equator?

The regularly spaced gaps near the equator are due to lack of coverage between orbits. Terra, Aqua and Aura are polar orbiting satellites, traveling from pole to pole. The Terra satellite travels north to south, passing over the equator at 10:30am local time (and 10:30pm local time). Aqua and Aura move in the opposite direction, south to north, passing over the equator at 1:30pm local time (and 1:30am local time). At high latitudes, adjacent imaging swaths overlap significantly but at the equator gaps occur between adjacent swaths. As a result, complete global coverage is achieved every one to two days. Geostationary satellites, such as weather satellites, do not move and remain pointed at one area of the Earth. As these satellites do not orbit the orbit the earth, they do not experience gaps, but they are also unable to provide global coverage.

How do I know what time of day the image was taken?

To find out what time of day an image was taken for the Terra, Aqua, Aura, and Global Precipitation Measurement (GPM) satellites, you must activate the corresponding Orbital Track layer.

  • In the Layer Picker, display the desired imagery by clicking on the eye icon, e.g. Corrected Reflectance (True Color) Terra / MODIS
  • In the Layer Picker, click on the + tab.
  • Type “Orbital Tracks” in the search box.
  • Add the corresponding Orbital Track overlay, e.g. Orbital Track (Descending/Day) Space-Track.org / Terra. Example

The orbital tracks represent when the satellite will be passing over a particular location on Earth on that day. The orbital tracks show a series of dots, each dot representing 1 minute, along the satellite orbit path with time stamps shown every 5 minutes. The time is shown in Coordinated Universal Time, or UTC.

Orbital Track layers include ascending and descending satellite orbits for day and nighttime orbits. Terra’s descending/day time orbit (North-South) will cross the equator at 10:30 a.m. local time during each orbit and ascending/night time orbit will pass over the equator at 10:30pm local time.  Aqua’s ascending/day time orbit crosses the equator at 1:30 p.m. local time and descending/night time orbit passes over the equator at 1:30am local time. Aura and GPM are on the same orbit track as Aqua and the satellites follow each other closely, passing over the equator within minutes of each other at 1:30pm local time and 1:30am local time. These satellites, as well as a few others, form the Afternoon Constellation or the “A-Train” for short. The A-Train flies in the following order: Orbiting Carbon Observatory 2 (OCO-2), Global Change Observation Mission-Water 1 (GCOM-W1), Aqua, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation(CALIPSO), CloudSat and Aura.

Not all products are available for the night time orbit.  For MODIS surface/corrected reflectance imagery, you must pick a day time orbit as it is not possible to create a surface reflectance image without sunlight.

Why are there so many clouds?

Approximately 70% of the earth's surface is covered by clouds at any given time. That means there is a good chance that the region you want to see will have some cloud cover. Use the time slider at the bottom of Worldview to view other dates.

Is there a list of products displayed in Worldview and GIBS?

Most imagery served by the Global Imagery Browse Services (GIBS) is in Worldview. See the "GIBS Available Imagery Products” page for a complete listing.

Does it work on mobile devices?

Yes, we do our best to keep it usable on both desktop and mobile devices.

What browsers does it work on?

Chrome, Firefox, Safari, Internet Explorer 9+

Can I get the source code to Worldview?

Worldview is available on GitHub and along with simple web mapping examples which use the same imagery.

Are there any restrictions on using imagery downloaded from Worldview?

NASA supports an open data policy and we encourage publication of imagery from Worldview; when doing so, please cite it as "NASA Worldview" and also consider including a permalink (such as this one) to allow others to explore the imagery.

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Global Imagery Browse Services (GIBS)

What is GIBS?

The Global Imagery Browse Services (GIBS) are a set of standard services to deliver global, full-resolution satellite imagery in a highly responsive manner. GIBS currently serves LANCE near real-time imagery and will be extended in 2015 to include MODIS science imagery from the beginning of the Terra and Aqua missions to present. Its goal is to enable interactive exploration of NASA's Earth imagery for a broad range of users. Technical Information / Wiki. Stay up-to-date with GIBS with the GIBS Blog.

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