Application of Satellite Based Remote Sensing for Monitoring and Mapping of India’s Forest and Tree Cover Forest Cover Assessment 2001 
Figure 2- Forest cover in India Tree Cover Assessment: TOF is assessed in rural as well as urban areas, although the greater part exists in rural areas. Initially, conventional field method was used for TOF assessment in rural areas. The state or a group of districts is considered as the study area. Since this area is fairly large there is every possibility of heterogeneity of the study variable i.e. growing stock. TOF being planted along with agricultural crops is likely to be influenced by the Agro-ecological variables. Therefore, study area is stratified according to agro-ecological zones (AEZ), which has already been demarcated by other agencies. Districts, in India, are the basic planning and administrative units, which influence the TOF and therefore, is considered for further stratification of AEZs. Villages are treated as sampling units. Optimum number of sample villages is selected randomly from different districts proportionate to the TOF area of the same. Complete enumeration of all the trees with diameter of 10 cm and above at breast height in the randomly selected villages in each district is carried out. Data is collected on pre-designed formats following prepared instructions for fieldwork and collected data is processed following appropriate formula. The above-mentioned methodology was providing accurate estimates but was very time consuming. It was not able to provide precise information at district level, which is the basic unit for economic planning. Methodology Using Remote Sensing Data To do away with these constraints many alternatives were tried and finally a methodology based on digital image processing and GIS analysis using multi spectral and panchromatic data for mapping of trees outside forests (TOF) was devised. The remote sensing data is used to provide stratification of the TOF resources, which is utilized to increase the precision and is time effective. In addition, sometimes the objectives of TOF resource assessment may require spatial distribution of resources on maps along with several other features. This objective can also be appropriately tackled by this methodology. High-resolution satellite imageries provide information even up to identification of a single tree but these are cost prohibitive. The IRS LISS III data, which is multi spectral, and has a resolution of 23.5 m ×23.5 m, provide information on vegetation cover. There are techniques available through which tree vegetated land can be segregated from agriculture land if the tree vegetated patch is about one ha and more. However, LISS data cannot be used for smaller patches or scattered trees. The IRS PAN data, which is monochromatic, having resolution of 5.8 m × 5.8 m can identify a tree vegetated land even less than 0.1 ha. Therefore, both LISS III and PAN imageries are used for stratification of TOF resources on the basis of geometrical formation of trees i.e. block plantation (group of trees), linear plantation and scattered trees. 
Raw images of IRS IC/D PAN and LISS III data for the period between Oct.-Dec. 2002 are acquired from National Remote Sensing Agency, Hyderabad. Thereafter, the PAN image is geometrically rectified with the help of Survey of India toposheets on 1:50,000 Scale. The LISS III image is then co registered with the rectified PAN images. PAN and LISS III images are fused using appropriate algorithm. Since mapping of TOF areas is the objective, the boundary of forest area is digitized and masked out. The remaining fused image are classified into settlement, water bodies, burnt areas, tree cover and agriculture area using appropriate classifier viz. Maximum likelihood. This classification enables the interpreter to distinguish between tree cover and other classes on fused image. This classified image is visually analyzed with respect to fused images for editing and refinement for inclusion and omissions. Since a cluster of trees having 0.1 ha area or more is defined as block plantation, pixels are clumped and cluster of pixels having area less than 0.1 ha are eliminated. After editing of the classified image the final classified map is generated which is done by taking the PAN, LISS-III and the fused images. Incorporating these corrections final classified image is prepared having three classes in TOF areas, namely, Block, Linear and Scattered. From the classified TOF map information pertaining to area under Block, Linear, Scattered and water bodies can be calculated. In addition, such areas, which do not support tree vegetation, like rivers and water bodies, snow covered mountains, marshes,etc. which is termed as Culturable Non Forest Area (CNFA)can also be calculated. Such information is very helpful for district level planning. Flow chart of methodology of Tree Cover mapping using remote sensing is shown in Figure-3  Figure 3- Flow chart of methodology of Tree Cover mapping |