New logic for large-scale land cover classification based on remote sensing

• Published in: 2009 17th International Conference on Geoinformatics pp. 1 - 5
• Main Authors: Quanfang Wang, Haiwen Zhang, Hangzhou Sun, Jiayong Li
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-08-2009
• Subjects: Biomass; Crops; land cover classification logic; Land surface; Large-scale systems; Logic; MODIS; Reflectivity; regional scale; Remote sensing; Rivers; time-series MODIS 250 m data; Vegetation mapping
• ISBN: 1424445620; 9781424445622
• ISSN: 2161-024X
• DOI: 10.1109/GEOINFORMATICS.2009.5292826

Nowadays it's still very difficult to find accurate information on land-cover areas and types, which mainly results from the confusion between land use types and land cover types (e.g., many researchers equated land cover with land use and land use types were often employed for the replacements of land cover types) and the absence of a standard land cover classification system with an unambiguous, repeatable definition of land cover and quantificational classification criteria so as to the classification result comparable. In this study, a new logic for land cover classification at regional scale has been introduced. The critical features of this classification are that: it's indeed distinguished from land use classification system and driven by remote sensing so that repeatable and efficient re-classifications of existing land cover will be possible; spectrum and primary attributes of plant canopy structure (i.e. permanence of aboveground live biomass, leaf longevity and leaf type) are adopted as the primary criterions of land cover classification; based on the phonological difference among broadly defined vegetation, some typical land cover is easily distinguished by using the characteristics of seasonal dynamic; mixed land cover is differentiated by its constituent characteristics and influence on land surface processes. Taking the areas between Yangtze River Basin and Weihe River Basin in China as a case and using time-series MODIS 250 m data (i.e. NDVI and reflectance), a two-level hierarchical land cover classification scheme was produced for the areas. At the initial stage, the entire study area was mapped into seven classes, i.e. evergreen cover (woody), seasonal green cover (woody), seasonal green cover (herbaceous), seasonal green cover (crops), seasonal green cover (mixed), grey cover (non-vegetated and terrestrial) and blue cover (aquatic or regularly flooded). The sub-classes includes Coniferous evergreen forest, Broadleaf deciduous forest, single cropping in one year, continuous double cropping in one year, grassland, wetland, urban or built-up land, barren or sparsely land, river, lake, mixed cover of crop and tree, etc.