SAR-Optical Remote Sensing Based Forest Cover and Greenness Esti-Mation over India

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Abstract

Indian natural forest has a high ecological significance as it holds much biodiversity and is primarily affected due to deforestation. The present study exhibits the forest cover change on Global Forest Non-Forest (FNF) data for India and greenness trend using MOD15A2H LAI product, which is the best product available till date. JAXA uses of SAR datasets for forest classification based on FAO definitions. Later, Forest Survey of India (FSI) used different definitions for forest classification from FAO and was to compare with JAXA based forest cover. The global FNF study exhibited that total forest cover was reduced from 568249 Km2 to 534958 Km2 during 2007-17 in India. The significant loss of forest cover (33291.59 Km2; by-5.85% change) was primarily evident in Eastern Himalayas followed by Western Himalayas. Whereas forest cover increase was observed in Eastern and the Western Ghats from 2007 to 2017. The state of forest report by FSI states an increase in the forest cover from 690889 Km2 to 708273 Km2 during 2007-17 by 2.51%. The difference in forest cover as estimated by JAXA global FNF datasets and FSI report is attributed to differences in forest cover mapping definitions by both the agencies and use of varied datasets (SAR datasets by JAXA and optical datasets by FSI). It is to note that SAR is highly sensitive to forest cover and vegetation's as compare to optical datasets. Recent satellite-based (2000-2018) LAI product reveals the increase in leaf area of vegetation during 2000-18. It may be attributed to proper human land use management and implications of green revolutions in the region. The greening in India is most evident from the croplands with insignificant contribution from forest cover.

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APA

Lal, P., Dubey, A. K., Kumar, A., Kumar, P., & Dwivedi, C. S. (2019). SAR-Optical Remote Sensing Based Forest Cover and Greenness Esti-Mation over India. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Vol. 4, pp. 49–56). Copernicus GmbH. https://doi.org/10.5194/isprs-annals-IV-5-W2-49-2019

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