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Data Set ID:
NSIDC-0276

SMEX02 Land Surface Information: Land Use Classification, Version 1

This data set consists of land use classification data collected for the Iowa Soil Moisture Experiment 2002 (SMEX02) study region. The land use classification image provides information about vegetation present in the study area.

Geographic Coverage

Parameter(s):
  • Land Use/Land Cover > Land Use Classes
Spatial Coverage:
  • N: 42.04, S: 41.7, E: -93.2, W: -93.8

Spatial Resolution: Not Specified
Temporal Coverage:
  • 14 May 2002 to 17 July 2002
Temporal Resolution: Not specified
Data Format(s):
  • Binary
Platform(s) LANDSAT-5, LANDSAT-7
Sensor(s): ETM+, TM
Version: V1
Data Contributor(s): Paul Doraiswamy, Alan Stern
Data Citation

As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Doraiswamy, P. C. and A. J. Stern. 2004. SMEX02 Land Surface Information: Land Use Classification, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/6IX22IHXNWBT. [Date Accessed].

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Detailed Data Description

Format

Data are provided as one flat binary file, 3831 rows by 1851 columns with no header.

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File and Directory Structure

Land use classification data are located under the SMEX02 ancillary data directory on the FTP site, as shown in this image:

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File Naming Convention

Data are in a single file named "classification.bil."

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File Size

6.925 MB

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Spatial Coverage

Southernmost Latitude: 41.7° N
Northernmost Latitude: 42.04° N 
Westernmost Longitude: 93.8° W
Easternmost Longitude: 93.2° W

Projection Description

Universal Transverse Mercator (UTM), Zone 15, Spheroid WGS84, Datum WGS84

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Temporal Coverage

Data were collected for three dates: 14 May, 1 July, and 17 July 2002.

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Parameter or Variable

Parameter Description

The parameters in this study are land use (vegetation) classifications. Land use classification distinguishes between crop types, water, roads, and urban areas. Pixels have a resolution of 30 m. The following table describes the values assigned to the vegetation and other elements in the land use classification file:

Value Class
0 Unclassified
1 Alfalfa
2 Corn
3 Grass
4 Soybean
5 Trees
6 Urban
7 Water
10 Overlaid roads

Sample Image

A sample image from the data is shown below:

Sample of land use classification image

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Software and Tools

Quality Assessment

Corn and soybean accuracies are good, but due to the large sample size of the corn and soybeans, accuracies in other land features are not as good. Small misclassifications in the soybean or corn areas can create larger inaccuracies in other classes. The following table shows the image readings and ground truth readings, and the accuracies calculated.

Image Alfalfa Corn Grass Soybean Trees Urban Water Total Accuracy
Alfalfa 66 - 3 20 1 - - 90 73.33333333
Corn 12 19291 209 379 17 - 10 19918 96.85209358
Grass 50 97 472 93 104 4 46 866 54.5034642
Soybean 136 66 63 14429 14 14 1 14723 98.00312436
Trees 18 100 45 72 77 - 63 375 20.53333333
Urban 3 2 7 20 1 2 0 35 5.714285714
Water - 7 5 1 6 - 56 75 74.66666667
Total 285 19563 804 15014 220 20 176
Accuracy 23.15789474 98.6096202 58.70646766 96.10364 35 10 31.81818 36082 95.319

Accuracies on the right in the chart are based on the image being the correct class for the ground truth. For example, of 90 classified alfalfa pixels, 66 of them are in the ground truth data for alfalfa, for 73 percent accuracy. The accuracy at the bottom of the chart is the ground truth compared to the image. For example, of the 285 pixels that were deemed to be alfalfa on the ground, only 66 of them were classified by Landsat Thematic Mapper (TM) to be alfalfa, while 136 of them were classified as soybean.

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Data Acquisition and Processing

Data Acquisition Methods

The land use classification data were derived from Landsat TM imagery and ground truth data. Landsat TM data were collected for three dates: 14 May, 1 July, and 17 July 2002. Data were used from Path 26, Row 30 and the southern portion of Path 26, Row 31, to cover the SMEX02 area. Ground truth data was collected on two separate trips in June and July 2002.

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Derivation Techniques and Algorithms

Processing Steps

The Landsat TM data was imported into ERDAS software for processing and classification. The land use classification image was registered to the road network provided by the Iowa Department of Transportation. The road network was converted into an image that showed each road as 60 meters wide. This image was embedded onto the classified image to remove the speckle along the roadways and to improve the image quality.

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References and Related Publications

Contacts and Acknowledgments

Paul C. Doraiswamy
US Department of Agriculture (USDA) Hydrology and Remote Sensing Lab
Beltsville, MD
USA

Alan J. Stern
US Department of Agriculture (USDA) Hydrology and Remote Sensing Lab
Beltsville, MD
USA

Acknowledgments: 

The investigators thank the Soil Moisture Experiment 2002 Science Team, the National Soil Tilth Laboratory, the National Aeronautics and Space Administration (NASA), NASA Aqua AMSR Terrestrial Hydrology and Global Water Cycle Programs, and all those who collected and analyzed the data, including: Rogier Van der Velde, Ann Hsu, and Laura Kimes. They also want to thank the many graduate students and volunteers who collected field photographs.

Document Information

DOCUMENT CREATION DATE

November 2005

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