Preliminary Study on the Use of Digital Surface Models for Estimating Vegetation Cover Density in Mountainous Area

Projo Danoedoro (Remote Sensing Laboratory, Department of Geographical Information Science, Faculty of Geography, Universitas Gadjah Mada, Indonesia)
Diwyacitta Dirda Gupita (Department of Geography, NTNU (Norwegian University of Science and Technology), NO-7491, Trondheim.)
Muhammad Zayyanul Afwani (Remote Sensing Laboratory, Department of Geographical Information Science, Faculty of Geography, Universitas Gadjah Mada.)
Haeydar Anggara Hadi (Remote Sensing Laboratory, Department of Geographical Information Science, Faculty of Geography, Universitas Gadjah Mada.)
William Krista Mahendra (Remote Sensing Laboratory, Department of Geographical Information Science, Faculty of Geography, Universitas Gadjah Mada.)

Indonesian Journal of Geography
Vol 54, No 3 (2022): Indonesian Journal of Geography

Digital surface model (DSM) has been widely available for mapping and was also sometimes used for mapping vegetation height. The authors conducted a preliminary study to evaluate the potential use of DSMs derived from ASTER, ALOS, and SRTM for estimating vegetation cover density in mountainous area.  This study used NDVI and SAVI vegetation indices, in addition to forest cover density (FCD) model as references for evaluation.  A DSM-based volume index (Volindex) concept is introduced, which is the product of the canopy height model (CHM) and the pixel area. CHM was derived from the value difference between the DSM and the reference DEM. The Volindex model was then compared with the NDVI, SAVI and FCD.  We found that all DSM-based Volindex models are not accurate enough to represent the vegetation cover density, although the ALOS Palsar-based Volindex could reach 41.53% accuracy and was finally used to predict the vegetation cover density.