Demand-based urban forest planning using high-resolution remote sensing and AHP

Srinivasa Raju Kolanuvada; Muneeswaran Mariappan; Vani Krishnan

doi:10.1117/12.2223832

5 May 2016 Demand-based urban forest planning using high-resolution remote sensing and AHP

Srinivasa Raju Kolanuvada, Muneeswaran Mariappan, Vani Krishnan

Proceedings Volume 9879, Lidar Remote Sensing for Environmental Monitoring XV; 98790P (2016) https://doi.org/10.1117/12.2223832
Event: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India

Abstract

Urban forest planning is important for providing better urban ecosystem services and conserve the natural carbon sinks inside the urban area. In this study, a demand based urban forest plan was developed for Chennai city by using Analytical Hierarchy Process (AHP) method. Population density, Tree cover, Air quality index and Carbon stocks are the parameters were considered in this study. Tree cover and Above Ground Biomass (AGB) layers were prepared at a resolution of 1m from airborne LiDAR and aerial photos. The ranks and weights are assigned by the spatial priority using AHP. The results show that, the actual status of the urban forest is not adequate to provide ecosystem services on spatial priority. From this perspective, we prepared a demand based plan for improving the urban ecosystem.

Citation Download Citation

Srinivasa Raju Kolanuvada, Muneeswaran Mariappan, and Vani Krishnan "Demand-based urban forest planning using high-resolution remote sensing and AHP", Proc. SPIE 9879, Lidar Remote Sensing for Environmental Monitoring XV, 98790P (5 May 2016); https://doi.org/10.1117/12.2223832

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