Data Set Help

• NOAA Raw Data
• NOAA TDF Data
• NOAA / AVHRR Level3
• NOAA / MCSST Image
• NOAA / MCSST Daytime Composite Image (10 days)
• NOAA / MCSST Nighttime Composite Image (10 days)
• NOAA / MCSST Nighttime Composite Image (daily)
• NOAA / NDVI Month Composite Image
• FY-1 RAW Data
• FY-1 MVISR Data
• MODIS / Chlorophyll-a
• MODIS/ SST Day Composite Image

To order the data

• Level 3 BSQ Output Data Value
• Contents of Information File

AVHRR ( Advanced Very High Resolution Radiometer )

 One(1) pass capacity of raw data varies depending on satellite orbit with maximum of 120 MB.
 HRPT data format is available from NOAA’s home page.

 The browse images for retrieval are acquired through AVHRR channel 2(near infra-red:0.725-1.10 micro-meter) during daytime and channel 4 (thermal infra-red: 10.3-11.3 micron-meter) during night-time and after reduction to 500(sample) x 2000(line) with top of the image being fixed to “North” regardless of satellite orbit, the land area is displayed in greenish color and ocean in bluish color.

Because of this, the greater the number of lines, the longer the images be displayed, but the horizontal swath width of any image is same with 2,048 pixels.

 During daytime, the greater the reflectance, the whiter the color of the browse image becomes and the smaller the reflectance, the more greenish or bluish it becomes.

During night-time, it covers temperature range of approx. -70 to 30 degreeC and lower the temperature, the whiter the image color, and higher the temperature, the more greenish or bluish the color becomes. The images are overlaid with the shore-lines and longitude/latitude lines (with 10 degree interval).

 The amount of clouds for total image, land and ocean are approximated and are shown in ratio proportionate to cloud area.

Output Data Type

BSQ (Band Sequential) band by band binary data + information data

HDF(Hierarchical Data Format; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign.)

TDF(TeraScan common Data Format; SeaSpace TeraScan Dataset)

Output Image

TIFF

JPEG

PNG

PPM

GIF

GEOTIFF

MCSST Algorithm Calculation Formula
# Split window ( mc ):

SST = A*T4 + B*(T4-T5) + C*(T4-T5)*(SEC(sza)-1) + D*(SEC(sza)-1) + E

In addition to above, another algorithm to distinguish cloud area(Bernstein 1982) based on data from AVHRR channel 2(daytime use) and channel 3 (night-time use) is also used.
In order to reduce the cloud area during composite image production period, the effects of cloud area is eliminated by selecting the maximum value of MCSST in each element of the image.
The temperature range is -10 degreeC to 10.5 degreeC in 0.1 degreeC steps.
Output of the processed data is an annotated 2-byte data.
Value for land area is “-12” and “-32768” for cloud area and area outside of swath.

   NDVI = (NIR – RED) / (NIR + RED)

where,
   NIR : AVHRR Channel 2 (Near Infra-red)
   RED : AVHRR Channel 1 (Reflectance of red light wavelength)

NDVI values are taken as the range of -1 to 1. The value of -0.5 can be identified as cloud, so the range is put as -0.5 to 1, and calcurates following value transfer:

   INDVI = NDVI * 100 + 50

As far as the image output, the transfer is follows to represent color as 240 colors:

   INDVI = NDVI * 160 + 50

The value which is out of observation range is “INDVI = 255”, and the value of sea or lake is “INDVI = 0”.

The NDVI data is composite of solar azimuth with over 20 degree, and generates each month period.

MVISR ( Multispectral Visible and IR Scan Radiometer)

These are comprised of 5 NOAA AVHRR channels and 5 visible range channels, total 10 channel sensors.

   One(1) pass capacity of raw data varies depending on satellite orbit with maximum of 240 MB.
   HRPT data Format is available from NOAA home page.

   The browse images for retrieval are acquired through AVHRR channel 2(near infra-red : 0.725-1.10 micron meter) during daytime and channel 4 (thermal infra-red:10.3-11.3 micron meter) during night-time. The image is reduced to 500 (sample)x 2000(line) with top of the image being fixed to north regardless of satellite orbit and the land area is displayed in greenish color and the ocean in bluish color.Because of this, the greater the number of received lines, the longer the displayed image but the right to left swath width has 2,048 pixels which is same with every image.
   The greater the reflectance during daytime, the whiter the browse image is displayed, and smaller the reflectance, the darker the greenish or bluish color becomes.During night-time, the browse image covers temperature range of -70 to 30 degreeC and lower the temperature, the whiter the image and higher the temperature, the darker the greenish or bluish .The images are overlaid with shorelines and latitude/longitude lines(10 degree interval).
The amount of clouds covering overall image, land and ocean area are approximated and are shown in ratio proportionate to cloud area.

 The green, yellow, and red colors reflect the density of the chlorophyll as it rises. The black color reflect the cloud cover, as well as, possible data processing problems, etc.. The blue color represents areas where data is not available.

 Please note that a possibility exists where the data does not accurately show the density of the chlorophyll around tidal flats in the bay’s interior area, etc.

 The AQUA/MODIS and TERRA/MODIS utilize sensors of the same specifications.

 A possibility exists where the same observation value (brightness) may not be the same even though the same target is observed due to differences such as the observation’s wave length or deterioration of a sensor.

 Various coefficients used by the algorithm and the radiation transmission’s calculation values are matched to specific response characteristics for each sensor. The latter values are then calculated. After changes in the sensor’s sensitivity are evaluated by using a variety of methods, the observation radiance values are then adjusted and used for processing by the algorithm. Problems associated with the presumption value of the physical quantity should be minimal.

 However, factors peculiar to each sensor cannot be completely corrected.

 There is a possibility that combinations causes errors in the data, and it is believed that differences could be reflected in both sensor’s data presumption values.

 Please consider the above discussed error conditions before utilizing the data. These data are provided on an ‘as is’ basis, and we are not responsible for any errors in the data nor how the data is ultimately used by the user.

NOAA/AVHRR

The calibration algorithm is based on information contained in Techniques for Data Extraction and Calibration of TIROS-N/NOAA Series Satellite Radiometers for Direct Readout Users by Levin Lauritson and Gary Nelson (NOAA-NESS Publication #107, July 1979).

FY-1/MVISR