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Investigation:

LC-15 (Saatchi / Alvala)

LBA Dataset ID:

LC15_GRFM_JERS1_Mosaic

Originator(s):

Saatchi, Dr. Sassan S.

Point(s) of Contact:

Saatchi, Dr. Sassan S. (Saatchi@congo.jpl.nasa.gov)

Dataset Abstract:

This data set contains two image mosaics of L-band radar backscatter and two image mosaics of first order texture. The two backscatter images are mosaics of L-band Radar Backscatter at Horizontal-Horizontal (HH) Polarization created from 1,500 images collected by the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) over the Amazon River Basin as part of the Global Rainforest Mapping Project (GRMP). These backscatter image mosaics were developed using data collected over 62 days from August to November of 1995 for the peak of the dry season and for 62 days from May to June of 1996 during the peak of the wet season. The two image mosaics are at 3 arc-sec resolution. Data provided under this project are resampled images at 30 arc-sec resolution (or about 1 km resolution). For each radar backscatter image, first order texture statistical information was derived and is distributed along with the image mosaic. This data set contains four images each in both geotiff and ENVI formats, provided in eight zip files. The four files in ENVI file format contain __envi in their file name and when extrapolated contain an envi image (*_envi.dat) and an envi image header file (_envi.hdr). The four files in geotiff format contain _geotiff in their file name and when extrapolated contain *.tif and *.tfw file pairs. See Section 2 for more information about the characteristics of these data files.

Beginning Date:

1995-08-01

Ending Date:

1996-06-30

Metadata Last Updated on:

2011-10-25

Data Status:

Archived

Access Constraints:

Public

Data Center URL:

http://daac.ornl.gov

Distribution Contact(s):

ORNL DAAC User Services (ornldaac@ornl.gov)

Access Instructions:

Public

Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.
Datafile(s):

Access data via ORNL DAAC User Interface:  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1024
Access data via ORNL DAAC ftp site:  ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/LC15_GRFM_JERS1_Mosaic/data/

Documentation/Other Supporting Documents:

Data Set User's Guide (pdf):  ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/LC15_GRFM_JERS1_Mosaic/comp/
^4^:  http://daac.ornl.gov/LBA/guides/LC15_GRFM_JERS1_Mosaic.html

Citation Information - Other Details:

Saatchi, S.S., B. Nelson, E. Podest, and J. Holt. 2011. LBA-ECO LC-15 JERS-1 Synthetic Aperture Radar, 1- km Mosaic, Amazon Basin: 1995-1996. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. http://dx.doi.org/10.3334/ORNLDAAC/1024

Keywords - Theme:

Parameter Topic Term Source Sensor
RADAR BACKSCATTER RADIANCE OR IMAGERY RADAR JERS-1 (JAPANESE EARTH RESOURCES SATELLITE-1) SAR (SYNTHETIC APERTURE RADAR)
LAND USE CLASSES LAND SURFACE LAND USE/LAND COVER JERS-1 (JAPANESE EARTH RESOURCES SATELLITE-1) SAR (SYNTHETIC APERTURE RADAR)

Uncontrolled Theme Keyword(s):  Forest Structure Biomass Wetlands, Image Data, L-band Radar

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
Amazon Basin Amazon Basin 13.85830 -23.42680 -47.02310 -82.72083

Related Publication(s):

Saatchi, S.S., B. Nelson, E. Podest, and J. Holt. 2000. Mapping land cover types in the Amazon Basin using 1 km JERS-1 mosaic. International Journal of Remote Sensing 21(6-7):1201-1234.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Data were collected in two campaigns: the dry season images were collected over 62 days from August to November of 1995 for the peak of dry season, and the wet season images were collected over 62 days from May to June of 1996 for the peak of wet season.



Data Values: Values range from 0 - 255 (8 bit).



Projection: Geographic with WGS84 datum



Data Files: This data set contains four images, each in both ENVI standard format and GeoTIFF format and are provided in eight zipped files.



The four zip files with ENVI files contain _envi in their file name and when unzipped contain an ENVI image (*_envi.dat) and an ENVI image header file (*_envi.hdr).

The four zip files with GeoTIFF files contain _geotiff in their file name and when unzipped contain a GeoTIFF image (*_geotiff.tif) and a GeoTIFF header file (*_geotiff.tfw) file.



Dry season: 1 km resolution backscatter:



dry_back2_1km_envi.dat

dry_back2_1km_envi.hdr

dry_back2_1km_geotiff.tif

dry_back2_1km_geotiff.tfw

Dry season texture:



dry_txt2_1km._envi.dat

dry_txt2_1km_envi.hdr

dry_txt2_1km_geotiff.tif

dry_txt2_1km.dat_geotiff.tfw



Wet season: 1 km resolution backscatter:

wet_back2_1km_envi.dat

wet_back2_1km_envi.hdr

wet_back2_1km_geotiff.tif

wet_back2_1km_geotiff.tfw

Wet season Texture:



wet_txt2_1km_envi.dat

wet_txt2_1km_envi.hdr

wet_txt2_1km_geotiff.tif

wet_txt2_1km_geotiff.tfw





Header File: Example, dry_back2_1km_envi.hdr



ENVI

description = {File Resize Result, x resize factor: 0.100000, y resize factor: 0.100000. [Fri Dec 27 14:55:29 2002]}

samples = 4318

lines = 4432

bands = 1

header offset = 0

file type = ENVI Standard

data type = 1

interleave = bsq

sensor type = Unknown

byte order = 1

map info = {Geographic Lat/Lon, 1.0000, 1.0000, -83.00083333, 13.50083330, 8.33300000e-03, 8.33300000e-03, WGS-84,units=Degrees}

band names = {Resize (Band 1:low_back2_1.dat)}

Data Application and Derivation:

Understanding human or climate-induced changes in the tropical landscape requires knowledge of the current status of the ecosystem and the extent of the land cover types susceptible to change. Optical remote sensing has been used successfully for the classification of land cover types on local to regional scales. There are, however, limitations to current remote sensing techniques and methodologies used in both defining land cover types and identifying the parameters to be monitored. While optical remote sensing data is commonly used to classify land cover, microwave sensors such as radar remain unexploited for the most part. Radar data offers two distinct advantages to optical remote sensing: 1) it is insensitive to atmospheric conditions and sun angle allowing frequent acquisition and 2) radar backscatter signal carries information about forest structure and moisture conditions by penetrating the forest canopy. With this data users can explore the abilities and limitations of using radar data (specifically JERS-1 images) to classify land cover (Saatchi et al., 2000).

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

Geometrical accuracy of the mosaic was checked against 41 control points from Brazilian and Peruvian 1:100,000 scale topographical maps. Ninety-five percent of the control points were found within one pixel (100 m) of their correct position. The mosaic image shows orbital stripes which are due to slight radiometric discrepancies between the calibration of the orbital data takes. These discrepancies are usually less than 0.5 dB in intensity and do not affect the texture measures and classification of the image at a resampled resolution of 1 km. The use of a large window (10 x 10 pixels) for transforming 100 m resolution images to 1 km may reduce the accuracy of subsequent land cover mapping by introducing mixed information and errors in the definition of edges of land parcels.

Process Description:

Data Acquisition Materials and Methods:

JERS-1 SAR is an L band spaceborne SAR system operating at 1.275 GHz with horizontal polarization for both transmission and reception. The spatial resolution of the system is 18 m in both azimuth and range and the swath width is 75 km. The single-look images have 4.2 m pixel spacing in both azimuth and range and the standard three-look image has 12.5 m pixel spacing in both azimuth and range. In late 1995 the JERS-1 satellite entered into its GRFM phase and over a period of 62 days from August to November of 1995 (dry season) and for 62 days from May to June of 1996 (wet season) obtained wall to wall coverage of the Amazon basin. One hundred m resolution JERS-1 data (8 x 8 averaging of high-resolution 12.5 m three-look data) was used to generate a map of the entire basin from 1,500 images. The spatial mosaicing technique was based on a mathematical wallpapering approach that minimizes propagation of errors (Siqueira et al., 1999).



Radar backscatter signals contain two components: speckle, due to randomly distributed scatterers in a pixel, and texture which is a result of spatial variability of the scene. The backscatter data was filtered to reduce the speckle and enhance the texture (Ulaby et al., 1986). Texture measures were developed from the 100 m JERS-1 mosaic over a 10 x 10 pixel window resulting in 1 km resolution texture images with independent pixel information as the windows were shifted in a blockwise fashion in 10 pixel increments. The amplitude mosaic image was used to quantify eight texture measures from the first-order histogram of a 10 x 10 pixel window: mean, variance entropy, energy, contrast, skewness, kurtosis, and coefficient of variation.

References:

Saatchi, S.S., B. Nelson, E. Podest, and J. Holt. 2000. Mapping land cover types in the Amazon Basin using 1 km JERS-1 mosaic. International Journal of Remote Sensing 21(6-7):1201-1234.



Siqueira, P., S. Hensley, S. Shaffer et al. 2000. A continental scale mosaic of the Amazon basin using JERS-1 SAR IEEE Transactions on Geoscience and Remote Sensing 38: 2638-2644.



Ulaby, F.T., F. Kouyate, B. Brisco, and T.H.L. Williams. 1986. Textural information in SAR images. IEEE Transactions on Geoscience and Remote Sensing, vol. GRS-24,no. 2: 235-245.

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