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Production of Land Cover Map of Asia, Central Asia, and Middle East with Emphasis on Ground Truth Database Development

This study focuses on the production of a land cover map for Asia, Central Asia, and the Middle East, with an emphasis on developing a ground truth database. The study outlines the production process, the development of the ground truth database, and the validation methods used. The study concludes that the refinement of ground truth data is necessary for accurate land cover mapping and recommends the development of a global land cover ground truth database.

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Production of Land Cover Map of Asia, Central Asia, and Middle East with Emphasis on Ground Truth Database Development

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  1. Production of land cover map of Asia, Central Asia, and Middle East with emphasis of the development of ground truth database Ryutaro Tateishi, Hiroshi Sato, and Zhu Lin Center for Environmental Remote Sensing (CEReS), Chiba University Japan E-mail: tateishi@ceres.cr.chiba-u.ac.jp URL: http://asiaserv.cr.chiba-u.ac.jp/frame.htm

  2. Outline Production of land cover map - Geographic area - Legend - Ground truth data - Classification - Validation Development of ground truth database - Global Land Cover Ground Truth Databases

  3. Geographic areas for the mapping Central Asia Middle East Asia

  4. ST (Sato & Tateishi) land cover guideline legend - based on LCCS (FAO) - modified Stibig’s minimum requirement - include 65 crop names from FAOSTAT

  5. ST Land Cover Guideline Legend (1/3) Yellow: classes of GT collection 1. Broadleaf Evergreen Forest 101 ~ 111 [Crop list] 2. Broadleaf Deciduous Forest 112 ~ 117 [Crop list] 3. Needleleaf Evergreen Forest 4. Needleleaf Deciduous Forest 5. Mixed Forest 6. Tree Open 31. Broadleaf Evergreen Woodland 32. Broadleaf Deciduous Woodland 33. Needleleaf Evergreen Woodland 34. Needleleaf Deciduous Woodland

  6. ST Land Cover Guideline Legend (2/3) 7. Shrub 118, 119 [Crop list] 8. Herbaceous, single layer 9. Herbaceous with Sparse Tree/Shrub 10. Sparse Herbaceous / Shrub 11. Cropland 120 Rice, paddy 121 ~ 166 [Crop list] ( 104 Coconuts 165 Wheat ) 12. Cropland / Natural Vegetation Mosaic 13. Tree-Water (Mangrove) 14. Wetland 15. Lichens / Mosses

  7. ST Land Cover Guideline Legend(3/3) 16. Bare 35. Consolidated 36. Bare rock 37. Gravels, stones and boulders 38. Hardpan 39. Unconsolidated 40. Bare soil / Other unconsolidated materials 41. Loose and shifting sands 17. Urban 18. Snow / Ice 19. Water

  8. Additional classes 201. Forest fire 202. Water (60-70%) and many small islands with sand and salt (30-40%)

  9. Ground Truth of the whole area 338 sites, 31 classes (17 classes out of them are at global level)

  10. 5 105 1 2 Global Land Cover Ground Truth database (GLCGT database) The GLCGT database consists of regional land cover ground truth (RLCGT) data. The geographical size of a RLCGT data is flexible, from a city size to a continental size. --- metadata of RLCGT data (text) --- GT land cover code data (raster) --- GT site code data (raster) --- description of GT sites (text) --- optional data (text, raster, or any)

  11. Regional Land Cover Ground Truth Area

  12. Ground Truth of the whole area 338 sites, 31 classes (17 classes out of them are at global level)

  13. Used data VEGETATION S-10 NDVI data sets Classification Maximum Likelihood method for monthly NDVI (January to November)

  14. Land Cover Classification Result of Asia

  15. Confusion matrix of training data for 17 global level classes (producer’s accuracy) 11 clases are better than 90 % 3 classes are 80-90 % 3 classes are 60-80 % - shrub(75 %), the other parts were classified to  bare areas, sparse herbaceous/shrub - herbaceous, single layer (69 %)  shrub, herbaceous with sparse tree/shrub, cropland natural vegetation mosaic, needleleaf deciduous forest - herbaceous with sparse tree/shrub (61 %)  sparse herbaceous/shrub, cropland natural vegetation mosaic, needleleaf deciduous forest

  16. Validation by Mayaux’s method (for 31 classes, not for 17 global level classes) Reason of “unacceptable” - three classes of difficult training data - urban - detail classes in bare areas

  17. Conclusions • Asia, Central Asia and Middle East were classified to 31 land cover types (17 types at global level) by Maximum Likelihood method of monthly NDVI. - 338 GT sites (1-66 sites for each land cover class) were collected. - Geographic coverage of GT data is not enough because one type of land cover may have different data characteristics in different regions.

  18. Conclusions (continued) • Refinement of ground truth data is necessary, especially shrub, herbaceous, and herbaceous with sparse tree/shrub • Accumulation of ground truth data makes land cover map more accurate. Recommendation: development of global land cover ground truth (GLCGT) database

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