Remote sensing and GIS approach to assess Tre...

Remote sensing and GIS approach to assess Trees outside Forest (TOF) and Forest area in vikarabad district, Telangana state, India

Author Name : Sabavath Srinu, Dr. V. Venkateswara Reddy

ABSTRACT

Trees outside forest (TOF) are trees available on agricultural land, roadsides, railways, canals, ponds, orchards, parks, gardens and homesteads. In India, TOF defines all trees growing outside the registered forest area, irrespective of patch size, as non-forest trees. Mapping and monitoring trees outside forests (ToF) is gaining importance in the scientific community because they provide critical ecosystem services such as protecting soil and water resources. Wildlife habitat and aesthetics, including food, fuel and fiber. The Intergovernmental Panel on Climate Change (IPCC) classification of forests, trees and other land uses can also provide useful information for emissions estimation. Despite the importance of ToF quantification, very few studies have attempted to quantify them in India's natural resource inventory programs. In this study, we focused on Vikarabad District Telangana State, India, ToF list Using very high-resolution (VHR) Indian Remote Sensing (IRS) satellite data. We specifically used Cartosat-1 panchromatic (2.5 m) and multispectral LISS-IV (5.8 m) datasets to quantify vegetation and create a much-needed database for ToF. We used a new classification scheme based on geometry, i.e. point, line or polygon formation, to quantify ToF at 1:10,000 scale. The results obtained indicate that the forest area is 1390 sq. km. ToF with linear and block formations extending up to 1501 sq.km , respectively, accounting for ~1.43% of the Total Geographical study Area of in vikarabad district while point formations established area is 104903 sq.km. The results will help address important ecosystem services in the ToF, including quantifying greenhouse gas emissions from agriculture, forests and other land use categories.

Key words: Trees outside forest, cartosat-1, LISS-4, forest cover, Remote sensing, GIS,