Enhancing Forest Management and Economic Assessment with Remote Sensing

Recent developments in active remote sensing have substantially enhanced our ability to assess both the economic and ecological functions of ecosystems.

We studied the use of active remote sensing intensively in a dynamic landscape on Sumatra, Indonesia - a frontier where rainforest is transformed into tree crops like oil palm and rubber. 

First, by combining spaceborne LiDAR on samples that supported estimation on a large scale with SAR data, we were able to estimate canopy height of tropical vegetation accurately in dynamic landscapes with oil palm, rubber and tropical forest. 

Second, the estimation of canopy height at different points in time allowed us to estimate aboveground biomass changes over time. We were therefore able to track aboveground biomass losses and the resulting carbon emissions that come from the conversion of tropical forest to oil palm plantations. We also studied the effect of forest fires on aboveground biomass losses and carbon emissions.

Third, with statistical models, we used the relationship between canopy height, derived from airborne and spaceborne LiDAR, and aboveground biomass to estimate it for a whole province in Indonesia. These recent developments of active remote sensing supported us in assessing the tree diversity of oil palm landscapes and the balance between economic and ecological functions in oil palm plantations.

The impact of LiDAR and SAR 

These developments highlight the growing role of LiDAR and SAR systems, which provide high-resolution data on forest structure, biomass, and carbon stocks.

By capturing detailed vertical and horizontal vegetation structure with active remote sensing, these technologies enable accurate estimations of forest carbon sequestration potential, biodiversity, and habitat quality.

This wealth of information, in turn, potentially supports sustainable land management practices, balancing ecological preservation with economic needs.

Moreover, the recent publications underscore the potential of integrating active remote sensing data with broader environmental models to assess ecosystem function and service provisioning.

This integrated approach enables the mapping and monitoring of ecological disturbances, such as deforestation or forest degradation, as well as restoration efforts, and their impacts on local economies that depend on these ecosystems for goods and services.

Header image by Achmad Rabin Taim from Jakarta, Indonesia, CC BY 2.0, via Wikimedia Commons