A PROOF OF CONCEPT REMOTE SENSING METHOD FOR ASSESSING FOREST RESTORATION: A case study in the Dui-Sutpeh-Pui National Park in Thailand

Abstract

In the last century, the earth has lost almost half of its original forest cover. A problematic development, as forests are essential to maintain life of earth. There is urgent need for finding the best solutions to restore these forests. This research aimed to contribute to this need, by proofing a remote sensing method assessing forest restoration in Google Earth Engine. The Dui-Suthep-Pui National Park in Thailand was taken as a case study to illustrate and evaluate this RS method. The method consists of three indicators: Tree Canopy Cover measuring forest density, Normalized Difference Vegetation Index and Net Primary Production both measuring forest health. This triangulation of indicators was found to give a robust image changes in the forest over time, enabling to assess forest restoration. Google Earth Engine was found as an useful platform, because it stores RS products to measure the indicators. The RS method can be used to measure different restoration efforts, to identify which approach works best for restoring forests. Moreover, small communities or projects are enabled to do their own research without intervention of an instate, sharing bottom-up knowledge.