Vegetation cover mapping in India using multi-temporal IRS Wide Field Sensor (WiFS) data

Abstract

In this study, we explored the potential of multi-temporal IRS Wide Field Sensor (WiFS) data for mapping of vegetation cover types in India. A vegetation cover type map was generated from a hybrid approach (supervised and unsupervised) classification of 8–10 months IRS WiFS composite data (Raw bands, Max NDVI) over the period of 1998 to 1999. The study has identified 35 cover classes with a description of 22 vegetation cover including 14 forest cover types from 188 m spatial resolution WiFS data. India has a diverse range of forests: from the tropical evergreen in the south to the alpine meadows in the north, from the deserts in the west to the evergreen forests in the north-east and a diverse pattern of vegetation cover. More than half of the forest area in India is tropical-moist and dry-deciduous types distributed in central part. The WiFS vegetation cover map was compared to the estimates of forest cover area derived from IRS LISS III images (as per Forest Survey of India). There was a good agreement on spatial distribution and area of forest between the WiFS product and the LISS product, however, the WiFS product provided additional information on vegetation cover types and other land use/cover classes. Analysis of temporal NDVI profile allows identification of distinct growth pattern between the different vegetation cover types. It is evident that WiFS data can be used to provide timely and detailed vegetation cover type maps with limited ancillary data. The WiFS derived maps could be very useful as input to biogeochemical models that require timely estimation of forest area and type.