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ABSTRACT:Assessment of Trees outside forests (TOF) is widely being recognized as a pivotal theme, in sustainable natural resource management, due to their role in offering variety of goods, such as timber, fruits and fodder as well as services like water, carbon, biodiversity. Forest Conservation efforts involving reduction of deforestation and degradation may have to increasingly rely on alternatives provided by TOF in catering to economic demands in forest edges. Spatial information systems involving imaging, analysis and monitoring to achieve objectives under protocols like REDD+, require incorporation of information content from areas under forest as well as trees outside forests, to aid holistic decisions. In this perspective, automation in retrieving information on area under trees, growing outside forests, using high resolution imaging is essential so that measuring and verification of extant carbon pools, are strengthened. Retrieval of this tree cover is demonstrated herewith, using object based image analysis in a forest edge of dry deciduous forests of Eastern Ghats, in Khammam district of Telangana state of India. IRS high resolution panchromatic 2.5 m data (Cartosat-1 Orthorectified) used in tandem with 5.8 m multispectral LISS IV data, discerns tree crowns and clusters at a detailed scale and hence semi-automated approach is attempted to classify TOF from a pair of image from relatively crop and cloud free season. Object based image analysis(OBIA) approach as implemented in commercial suite of e-Cognition (Ver 8.9) consists of segmentation at user defined scale followed by application of wide range of spectral, textural and object geometry based parameters for classification. Software offers innovative blend of raster and vector features that can be juxtaposed flexibly, across scales horizontally or vertically. Segmentation was carried out at multiple scales to discern first the major land covers, such as forest, water, agriculture followed by that at a finer scale, within cultivated landscape. Latter scale aimed to segregate TOF in configurations such as individual or scattered crowns, linear formations and patch TOF. As per the adopted norms in India for defining tree cover, units up to 1 ha area were considered as candidate TOF. Classification of fine scale (at 10) segments was accomplished using size, shape and texture. A customised parameter involving ratio of area of segment to its main skeleton length discerned linear formations consistently. Texture of Cartosat-1 2.5 m data was also used segregate tree cover from smoother crop patches in patch TOF category. In view of the specificity of the landscape character, continuum of cultivated area (b) and pockets of cultivation within forest (c) as well as the entire study area (a) were considered as three envelopes for evaluating the accuracy of the method. Accuracies not less than 75.1 per cent were reported in all the envelopes with a kappa accuracy of not less than 0.58. Overall accuracy of entire study area was 75.9 per cent with Kappa of 0.59 ...

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The monsoon based climate system, diverse land use and land cover distribution and cultural practices poses complex issues in monitoring, assessment and simulation of Indian carbon cycle. Several studies reported lack of spatially and temporally consistent databases, need for calibration and validation of models, and development of national frame work to maintain consistency and completeness in efforts and reduction of uncertainty. Considering the need, as part of ISRO Geosphere Biosphere Programme, National Carbon Project (NCP) initiative was taken up to understand and assess land, atmosphere and oceanic components of carbon cycle with a significant scope for integration of remote sensing, geospatial and process based models. The results from the initial studies are discussed in the paper. An increase of the country's forest carbon stocks from 6244.8 to 6621.6 Mt with an annual increment of 37.7 Mt of the carbon from 1995 to 2005 is reported. In the national scale, CASA model based average annual NPP is estimated to be 1.5 Pg C Yr -1 and is increasing at the rate of 0.005 Pg C Yr -2 during past 25 years from 1981-2006. Analysis of Mid tropospheric CO 2 levels retrieved from AIRS data since 2002 till now revealed increasing rate of CO 2 at 2.14 ppmv yr -1. It was also o found that biosphere uptake over India and oceanic uptake over the south Indian Ocean could play positive role on the control of seasonal variability of atmospheric carbon dioxide growth rate The paper presents further details on different sub components, recent results and challenges ahead of the project.