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Remote Sensing and GIS Techniques for Forest Ecosystem Monitoring
Submission DeadlineJul. 1, 2020

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Lead Guest Editor
Avinash Kumar Ranjan
Department of Land Resource Management, Ranchi, Jharkhand, India
Guest Editors
  • Li Zhisheng
    School of Civil and Transportation Engineering, Guangdong University of Techology, Guangzhou, Guangdong, China
  • Melaku Tafese Awulachew
    Department of Food Science and Nutrition Research ProcessEthiopian Institute of Agricultural Research, Kulumsa Agricultural Research Center, Assela, Ethiopia
  • Ritambhara Upadhyay
    Jimma Institute of Technology, Jimma University, Jimma, Oromia, Ethiopia
  • Gaurav Tripathi
    Central University of Jharkhand, Ranchi, India
Forest ecosystems have an imperative role to balance the biogeochemical cycles, maintains the ecological equilibrium, and life-supporting systems. However, the forest ecosystem has been drastically exaggerated during last few decades by dramatic increment in urbanization, industrialization, huge mining activities, forest fire, and various anthropogenic interferences. Thereby, it is very crucial to monitor the forest ecosystem for sustainable development and decision making. The traditional methods of forest monitoring i.e. surveying, sampling, report analysis, etc. are too costly, time-taking, cumbersome, required huge manpower, etc. In this regard, availability of remote sensing data since 1972 has provided a new angle of forest monitoring and management. The remote sensing methods are very cost-effective, time-saving, required less man power, etc., over traditional methods. In addition, development in spectral, spatial, temporal resolution of various satellite sensors data have also aided the new dimension of forest monitoring. So, qualitative and quantitative assessment of forest ecosystem is very needful for updating the forest inventory database at various scale.
Aims and Scope:
  1. Forest cover change detection
  2. Forest fragmentation
  3. Biomass and carbon sequestration estimation
  4. Forest biophysical parameters (i.e. LAI, Chlorophyll, Nitrogen, FAPAR, etc.) estimation
  5. Forest Health assessment
  6. Tree species identification
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