Challenges of Mapping the Land Cover of Illinois

1. Challenges of Mapping the Land Cover of Illinois Tari A. Weicherding, Brooke A. Bahnsen, Leonardo Chapa, and Patrick W. Brown Center for Wildlife Ecology Illinois Natural History Survey Champaign, Illinois 12th Annual Gap Analysis Program Meeting Shepherdstown, West Virginia August 1, 2002

2. Land Cover of Illinois (IDNR, 1996) Illinois Facts • Population of 12.5 million; 8.1 million in 6-county metro Chicago area; 4th ranked state economy. • Area of 56,400 sq. mi. or 36,096,000acres. • Approx. 1.7 % water & 3.9% wetland habitat. • Approx. 7.0% urban & built-up land. • Approx. 14.83% forest and woodland. • Approx. 74.6% agricultural land. • Illinois ranks 2nd in soybean and 2nd in corn production. Top 10 in wheat, oats, & sorghum. • During the past decade, Illinois cropland has been decreasing in area at the rate of approx. 1 township each year. • During the past decade, developed land has been increasing in area at the rate of 2+ townships each year. Sources: IDNR, IDOA, USDA/NASS

3. Land Cover of Illinois (IDNR, 1996) Introduction • The Land Cover of Illinois was released by the Illinois Department of Natural Resources (IDNR) in 1996. • This widely used, statewide land use/land cover inventory contains 19 land cover categories and was developed with Landsat 4 and 5 Thematic Mapper satellite imagery acquired principally during the Spring and Fall of 1991-1993. • The wetlands in this statewide inventory came from the National Wetlands Inventory (NWI) which was surveyed in Illinois around 1980. • With portions of this statewide inventory approaching a decade old, IDNR desired to have an update and revision of the Land Cover of Illinois.

4. Land Cover of Illinois (IDNR, 1996) Introduction The difficulty in accurately characterizing approximately 74.63 % agricultural lands posed a significant problem to IDNR due to insufficient ground reference data.

5. IDNR Office of Realty and Environmental Planning Illinois Interagency Landscape Classification Project In October 1999, the USDA-National Agricultural Statistics Service (NASS), the Illinois Department of Agriculture (IDA), and agencies within the Illinois Department of Natural Resources (IDNR) co-signed an Memorandum of Understanding (MOU) to establish an interagency initiative for the development of statewide land cover information on a recurring basis. Source: Don Luman

6. Illinois Interagency Landscape Classification Project IILCP was mutually beneficial to NASS because the IDNR already had experience characterizing non-agricultural lands, including urban and built-up lands, … IILCP benefited the Illinois Gap Analysis Project (IL-GAP) because it provided the opportunity to update our landcover database with a newer and more detailed product. Land Cover of Illinois (IDNR, 1996)

7. Source: USDA/NASS Illinois Interagency Landscape Classification Project Illinois became part of the 1999 NASS Cropland Data Layer Program which now includes a total of 11 states: Arkansas, Illinois, Indiana, Iowa, Maryland, Mississippi, Missouri, New Mexico, North Dakota, Nebraska and Wisconsin.

8. Approach Used in Creating the IL-GAP Land Cover • NASS Cropland Data Layer • Illinois Interagency Landscape Classification Project (IILCP) Preliminary Data Layer • Illinois Gap Analysis Project (IL-GAP) Data Layer • Illinois Interagency Landscape Classification Project (IILCP) Final Data Layer

9. 1 sq. mi. JAS segment annotated by enumerator on a 1:8,000-scale NAPP photo Source: USDA/NASS NASS Cropland Data Layer Methodology Several hundred Illinois farms are visited annually by enumerators as part of the USDA/NASS June Agricultural Survey (JAS). These farmers are asked to report acreage for each crop that has been planted or that they intend to plant, and acreage they expect to harvest.

10. Source: USDA/NASS NASS Methodology(Continued) The land use and acreage information collected by the field enumerator is placed onto a JAS segment questionnaire and subsequently entered into a database at the Illinois NASS field office.

11. Source: USDA/NASS NASS Methodology(Continued) • Each field is digitized by the NASS field office staff. • Data obtained by interviewing the farmer is compared digitized acreage to remove acreage discrepancies. • A modified supervised classification based on LARSYS ISODATA clustering algorithms is performed using the digitized JAS segments as training samples. Landsat 5 & 7 TM scenes acquired in the April/May and July/August are used for the classification.

12. NASS Classification 1999 2000 Source: USDA/NASS

13. NASS Classification Accuracy Source: USDA/NASS

14. IILCP Preliminary Data Layer • An urban mask for the Chicago area scene was created using a buffered roads coverage. • An unsupervised ISODATA clustering classification was run using exact same 1999 and 2000 imagery as NASS. • Because ground truth data NASS uses is confidential, we used other methods to replicate the classification in the agriculture areas.

15. IILCP Preliminary Data Layer(Continued) • Direct visual inspection of the NASS supervised classification was compared to the frequency histogram of the unsupervised ISODATA classification. • A threshold value was then used as a cutoff for determining which classes spatially coincided with the NASS classification. • The USGS Digital Elevation Model (DEM) was used for post level classification of forest and wetland areas.

16. 1999-2000 IILCP Preliminary Data Layer

17. IL-GAP Data Layer • Forest and wetland masks were created from the IILCP Preliminary Data Layer. • A Slope Aspect Index (SAI) was created from the DEM. • An unsupervised ISODATA classification was run separately on forest areas and wetlands areas using raw imagery from the same 3 dates and the SAI layer. • Land cover classes were labeled according to categories found in the Illinois Natural Area Inventory Technical Report, 1978.

18. IL-GAP Data Layer (Continued) • Ancillary data such as aerial photos and soil surveys were used in interpretation of forest and wetlands. • A cloud affected ag land mask, which was only found in one scene, was created from the IILCP Preliminary Data Layer. • An unsupervised ISODATA classification was run on cloud affected ag areas using spring and fall dates -- allowing us to eliminate this category. • The forest, wetland, and cloud affected ag classifications were then mosaicked back onto IILCP Preliminary Data Layer.

19. 1999-2000 IL-GAP Draft Data Layer

20. IILCP Final Data Layer • Concerns over accuracy assessment structured our approach for the final IILCP Data Layer. • Forest categories in each scene were aggregated to broader categories. • Each scene was then manually edited using ancillary data sources such as the TM 15 meter panchromatic band, aerial photos, and DEM.

21. IILCP Final Data Layer(Continued) • Each of the 10 TM scenes were then mosaicked together by NASS, which uses EarthSat Inc’s GeoCover mosaic. • This mosaicking process produces an exact pixel mapping between all scenes and allows the user to set overlap priorities based on county boundaries or scene edges. Clouds are lowest priority. • A smoothing filter is then run on the final mosaic to get rid of salt and pepper pixels. • The final data layer is then accuracy assessed using stratified random sampling method.

22. Row 31 Row 32 Row 33 Path 24 Path 23 Path 22 IILCP Statewide Mosaic

23. 1999-2000 IILCP Final Data Layer

24. IL-GAP Categories IILCP Final Categories

25. Summary of Final IL-GAP Product • The final GAP Data Layer contains an attribute table similar to Wisconsin’s WISCLAND. • 3 levels for accuracy and different uses by various agencies. • Level 2 represents the IILCP categories. • Level 3 represents the IL-GAP categories. • Level 1 represents a simple aggregation of Level 2 and Level 3. • Accuracy Assessment will be conducted at Level 2 and Level 3.

26. IDNR 1991-1995Land Cover of Illinois

27. NASS 1999 Cropland Data Layer

28. IILCP 1999Integrated Classification

29. IL-GAP 1999Classification

30. IILCP Preliminary Classification – Lake County, IL Urban & Wetland Areas

31. IILCP Final Classification – Lake County, IL Urban & Wetland Areas

32. IILCP Preliminary & IILCP Final Classification

33. Primary source data is 1999 and 2000 Landsat 5 TM and Landsat 7 ETM+ imagery. Conclusions • IILCP classification maps produced from multidate TM imagery acquired at key phenological time periods during the spring, summer, and fall seasons. • Integrated classification produced from combination of supervised and unsupervised approaches. • Attribute table consists of 3 levels of coding. • USDA-NASS 1999, 2000, and 2001 Cropland Data Layer data are available on-line at: http://www.nass.usda.gov/research/Cropland/cdorderform.htm

34. NASS Ordering Information http://www.nass.usda.gov/research/Cropland/cdorderform.htm