Abstract
Abstract. Land use and land cover plays an important role in biogeochemical cycles, global climate and seasonal changes. Mapping land use and land cover at various spatial and temporal scales is thus required. Reliable and up to date land use/land cover data is of prime importance for Uttarakhand, which houses twelve national parks and wildlife sanctuaries and also has a vast potential in tourism sector. The research is aimed at mapping the land use/land cover for Uttarakhand state of India using Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The study also incorporated smoothening of time-series plots using filtering techniques, which helped in identifying phenological characteristics of various land cover types. Multi temporal Normalized Difference Vegetation Index (NDVI) data for the year 2010 was used for mapping the Land use/land cover at 250m coarse resolution. A total of 23 images covering a single year were layer stacked and 150 clusters were generated using unsupervised classification (ISODATA) on the yearly composite. To identify different types of land cover classes, the temporal pattern (or) phenological information observed from the MODIS (MOD13Q1) NDVI, elevation data from Shuttle Radar Topography Mission (SRTM), MODIS water mask (MOD44W), Nighttime Lights Time Series data from Defense Meteorological Satellite Program (DMSP) and Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) data were used. Final map product is generated by adopting hybrid classification approach, which resulted in detailed and accurate land use and land cover map.
Highlights
Land Use and Land Cover (LULC) play a vital role in understanding the complex earth’s ecosystem processes, biogeochemical cycles (Achard et al, 2004; Liu et al, 2008; Sellers et al, 1997), climate change studies (Liu et al, 2004) and deforestation studies(Hansen et al, 2008; Skole and Tucker, 1993; Steininger et al, 2002)
Different land cover classes portray dissimilar temporal characteristics at various stages of the year. This helps in identification and classification of land use/land cover using multi-temporal remotely sensed satellite imagery
Time-series plots of various land use/land cover classes and their corresponding smoothened plots were shown in the Figure. 2 (a)-(h)
Summary
Land Use and Land Cover (LULC) play a vital role in understanding the complex earth’s ecosystem processes, biogeochemical cycles (Achard et al, 2004; Liu et al, 2008; Sellers et al, 1997), climate change studies (Liu et al, 2004) and deforestation studies(Hansen et al, 2008; Skole and Tucker, 1993; Steininger et al, 2002). Land use and land cover information is extensively used by various governmental and non-governmental organizations and placing a great demand on detailed, reliable and up to date LULC maps (Perera and Tsuchiya, 2009). Before the era of satellite remote sensing, mapping of land resources started with manual interpretation of aerial photographs (Colwell, 1960). These techniques were tedious and time consuming. Global land cover data sets were first prepared using various published maps, atlases, national sources and ground level surveys (Matthews, 1983; Olson et al, 1983). The global land cover maps generated by this method suffered lack of consistency in classification schema used, differences in spatial resolutions and variables in measurement techniques(Running et al, 1994; Townshend et al, 1991)
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