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Land Cover of Illinois 1999-2000


In late 1999, the U. S. Department of Agriculture National Agricultural Statistics Service (NASS), the Illinois Department of Agriculture (IDA), and the Illinois Department of Natural Resources (IDNR) began a cooperative, interagency initiative to produce statewide land cover information on a recurring basis. The Illinois Interagency Landscape Classification Project (IILCP) completed Cycle 1 of this initiative in the summer of 2002, resulting in the Land Cover of Illinois 1999-2000 inventory and associated database.

It should be noted that there are contrasts between the 1991-1995 and the 1999-2000 land cover inventories, and the principal differences are as follows:

  • The most significant change has been within agricultural lands, in that all of the major field crops have been differentiated. The USDA-NASS collected field-by-field ground reference data for 425 sites (each approximately 1 mi2) across Illinois during the 1999 and 2000 crop years, and these reference data were then digitized onto same year Landsat 5 Thematic Mapper (TM) or Landsat 7 Enhanced Thematic Mapper (ETM+) satellite imagery. Using these reference data as training sites, USDA-NASS remote sensing scientists then employed a directed supervised classification approach to identify the same field crops across the entire state.

    Cover Map
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    Cover Map

  • In the 1991-1995 land cover inventory, two dates of Landsat 4 and 5 TM imagery for each of the ten Path/Row scene areas were acquired during the spring and fall seasons and used as the basis for the classification analysis. Six of the ten Path/Row scene areas contained TM imagery from different years (see 1991-1995 TM Coverage Map). In contrast, the 1999-2000 land cover inventory used three dates of same year Landsat 5 TM and/or Landsat 7 ETM+ imagery for each Path/Row scene area acquired during the spring-summer-fall periods (see 1999-2000 TM Coverage Map). In addition, the time span of the primary Landsat TM imagery was four years for the 1991-1995 land cover inventory and only two years of TM/ETM+ imagery were used for the 1999-2000 inventory.

  • The National Wetlands Inventory (NWI) was largely used as the surrogate for wetland cover in the 1991-1995 inventory. Because portions of the source information are now twenty years old, the NWI was not used in the 1999-2000 land cover inventory. Instead, the delineation was accomplished through a combination of unsupervised classification of same year, spring-summer-fall Landsat TM/ETM+ imagery and photo-interpretation of 1998-1999 U.S. Geological Survey (USGS) National Aerial Photography Program (NAPP 3) photographic prints.

  • Forested lands were given additional attention in that these areas were characterized as part of the Illinois portion of the USGS National Gap Analysis Project. The initial classification of forested lands by TM Path/Row scene areas were used as masks to segregate these forest areas for further analysis by remote sensing scientists at the Illinois Natural History Survey.

  • A comprehensive accuracy assessment procedure was conducted for the 1999-2000 land cover inventory. Field specific ground reference data were provided by the USDA-NASS for agricultural lands, the IDNR CTAP program provided ground reference data for forested tracts, and a number of additional areas were checked using photo-inspection and interpretation of NAPP 3 aerial photography. Consult the Accuracy Assessment Section for details. No accuracy assessment was conducted for the 1991-1995 land cover inventory.
Data Products

The Land Cover of Illinois 1999-2000 database includes four distinct, but closely interrelated products, and each of these products is described in more detail below. These data products are available for download at this web site. They are as follows:


Download datasets Land Cover of Illinois 1999-2000 Classification

This is the primary product of the IILCP initiative and is the result of integrating the directed supervised classification of agricultural lands and the unsupervised classification and spectral class labeling of non-agricultural lands. The primary source information for the computer classification is Landsat 5 TM and Landsat 7 ETM+ satellite imagery acquired for three dates (triplicates) during the spring, summer, and fall seasons of 1999 and 2000. Ten TM Path/Row scene areas are required to cover Illinois, and same year imagery was acquired for the TM/ETM+ triplicates to ensure seasonal consistency for the computer classification. The satellite imagery for four of the TM scene areas was acquired in 1999, and the remaining six scene areas were acquired in 2000 (see 1999-2000 TM Coverage Map).

All of the TM/ETM+ satellite imagery were geometrically corrected and co-registered to a transverse Mercator projection with a UTM zone 16 grid and NAD83 datum. The 1999 TM/ETM+ imagery is a mixture of simple geometric correction and terrain correction, while all of the 2000 imagery was terrain corrected using USGS 3 arc-second digital elevation model (DEM) data to correct relief displacement. The TM/ETM+ multispectral imagery possesses a 30x30 meter (98.4x98.4 feet) ground spatial resolution, which means that the resulting Land Cover of Illinois 1999-2000 Classification data is suitable for GIS and mapping applications at a scale of approximately 1:100,000 (1"=8,333') or smaller.

The computer classifications of the geometrically corrected and co-registered TM/ETM+ triplicates were conducted on a scene-by-scene basis. Spectral signatures were extracted from each TM/ETM+ triplicate data set utilizing an Isodata K-means clustering procedure (Duda and Hart 1973) and experimentation indicated that 200-250 spectral classes should be derived for each data set. The performance of several standard classifiers including minimum Euclidean distance, minimum Mahalanbois distance, and non-thresholding maximum likelihood have been evaluated and the results indicated greater improvement in classification accuracy can be achieved from the use of a maximum likelihood classifier, and this is supported by other research (Luman and Ji 1995; and Gong and Howarth 1990). The labeling and reduction of the spectral classes from the unsupervised classification procedures into the final information classes (water, wetland, etc.) was accomplished by photo-interpretation of NAPP 3 aerial photography. The supervised classification of agricultural lands, which used USDA-NASS ground reference data as training data collected the same year for 425 sites across the state, directly resulted in information classes and therefore no additional class labeling was necessary. The resulting integrated classification contains 23 land cover categories, which are as follows:

Value: Land Cover Category:
11 Corn
12 Soybeans
13 Winter Wheat
14 Other Small Grains and Hay
15 Winter Wheat/Soybeans
16 Other Agriculture
17 Rural Grassland
21 Upland
25 Partial Canopy/Savannah Upland
26 Coniferous
31 High Density
32 Low/Medium Density
35 Urban Open Space
41 Shallow Marsh/Wet Meadow
42 Deep Marsh
43 Seasonally/Temporarily Flooded
44 Floodplain Forest
48 Swamp
49 Shallow Water
51 Surface Water
52 Barren and Exposed Land
53 Clouds
54 Cloud Shadows

Upon completion of the integrated classifications for each of the ten TM Path/Row scene areas, a seamless mosaic was created using image processing software developed by the USDA-NASS. Careful attention was made to develop the mosaic along county boundaries to ensure that the land cover information within each county area was derived from the same Landsat TM/ETM+ triplicate. Because of the orientation and overlap of adjacent Landsat TM scene areas, a few counties are a combination of 1999 and 2000 TM/ETM+ imagery. Compare the 1999-2000 TM Coverage Map with the Landsat TM Scene Coverage Map. Lastly, a formal assessment of the accuracy of the final integrated classification was conducted, and the detailed explanation of that procedure is contained in the Accuracy Assessment Section.

Download datasets  
Landsat 7 ETM+ Panchromatic Image Mosaic

The Landsat 7 ETM+ sensor contains a Panchromatic channel sensitized to the green, red, and a portion of the near infrared reflected wavelengths, which corresponds to 0.52-0.90 micrometers within the electromagnetic spectrum (EMS). This broad band channel somewhat mimics a black-and-white (panchromatic) photograph, with the exception that traditional panchromatic photography is restricted to the visible portion of the EMS, extending from 0.38-0.74 micrometers.

As previously mentioned, the multispectral channels of the Landsat 5 TM and Landsat 7 ETM+ sensors possess a ground spatial resolution of 30x30 meters (98.4x98.4 feet). In contrast, the Landsat 7 ETM+ Panchromatic channel possesses a ground spatial resolution of 15x15 meters (49.2x49.2 feet), which means that it is suitable for GIS and mapping applications at a scale of approximately 1:50,000 (1"=4,167'') or smaller.

A review of the TM/ETM+ triplicates used for the IILCP initiative revealed that 1999 or 2000 Landsat 7 ETM+ Panchromatic imagery was available for all ten TM Path/Row scene areas within a one month fall period in 1999 or 2000 (compare fall season acquisition dates on the 1999-2000 TM Coverage Map). This narrow time span ensured consistency in ground conditions, creating the optimum conditions for development of a statewide mosaic. Wherever possible, the Panchromatic imagery was mosaicked along county boundaries, and each county area was individually contrast balanced. The final version of the Landsat 7 ETM+ Panchromatic Image Mosaic was compressed using MrSID for purposes of distribution.

Download datasets TM Path/Row Pseudocolor Spectral Class Maps


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The result of the unsupervised Isodata K-means clustering procedures imposed on each TM/ETM+ triplicate data set was a classification map containing 200-250 spectral classes. These data sets are intermediate products between the original satellite imagery and the final classification. They are typically utilized only by remote sensing analysts for the class labeling procedures, a process of aggregating the 200-250 spectral classes to a fewer number of information classes that eventually results in the final classification.

These single band, spectral class maps can be color coded (pseudocolor) to simulate any 3-band RGB rendition from the original TM/ETM+ satellite imagery for the spring, summer, and fall seasons. The large number of spectral classes combined with the landscape complexity within each of the Path/Row scene areas results in Pseudocolor Spectral Class Maps that contain a large amount of detailed information. Since they mimic the original TM/ETM+ triplicates, this data product can also be used as an image map base for use in GIS and mapping applications.

An example will serve to demonstrate the potential for this data product. To the right is a small portion of the Pseudocolor Spectral Class Map for the Peoria, Illinois area. This fall season (October 10, 2000) image has been color coded to simulate a false color infrared photograph. Note the amount of feature detail that is afforded with the 200+ spectral classes. In the second view, two spectral classes (#6 and #86) have been highlighted in bright blue and yellow, respectively, in order to discriminate them from all of the remaining spectral classes. Spectral class #6 represents Peoria Lake, Upper Peoria Lake, and a portion of the mainstem of the Illinois River. Spectral class #86 represents one category of upland forest. Resource analysts can therefore derive their own variation of a land cover map for selected study areas by simply altering the colormap using a variety of GIS or graphics software.


Campbell, James B., 1987. Introduction to Remote Sensing, The Guilford Press, 551 p.

Duda, R.D. and P.E. Hart, 1973. Pattern recognition and scene analysis, John Wiley and Sons, New York, 482 pp.

Gong, Peng and P.J. Howarth, 1990. An Assessment of Some Factors Influencing Multispectral Land Cover Classification@, in Photogrammetric Engineering and Remote Sensing, Vol. 56, No. 5, pp. 597?603.

Illinois Department of Natural Resources, 1996. Illinois Land Cover: An Atlas, and Illinois Land Cover: An Atlas on Compact Disc, Illinois Department of Natural Resources, Springfield, IL, IDNR/EEA-96/05, 157 p.

Luman, D.E. and J. Minhe, 1995. "The Lake Michigan Ozone Study: The Application of Satellite?Based Land Use and Land Cover Mapping to Large-Area Emissions Inventory Analysis", in Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 8, pp. 1021-1032.

Stoms, D.M. and J.E. Estes, 1993. "A Remote Sensing Research Agenda for Mapping and Monitoring Biodiversity", in International Journal of Remote Sensing, Vol. 14, No. 10, pp. 1839-1860.

Scott, J.M., F. Davis, B. Csuti, R. Noss, B. Butterfield, C. Groves, H. Anderson, S. Caicco, F. D'Erchia, T.C. Edwards, Jr., J. Ulliman, and R.G. Wright, 1993. "Gap Analysis: A Geographic Approach to Protection of Biological Diversity", Wildlife Monograph, No. 123, 41 p.

Questions or comments.

Copyright © 2001
State of Illinois Department of Agriculture
P.O. Box 19281, State Fairgrounds
Springfield, IL 62794-9281
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