Tropical forest degradation monitoring using ETM+ and MODIS remote sensing data in the Peninsular Malaysia

8th International Symposium of the Digital Earth

地球科学;计算机科学

Hashim, M.^1 ; Pour, A.B.^1 ; Chong, K.W.^1

Institute of Geospatial Science and Technology (INSTeG), Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor Bahru, Malaysia^1

关键词: Accuracy assessment;    Enhanced thematic mappers;    Forest degradation;    Moderate resolution imaging spectroradiometer;    Radiometric corrections;    Remote sensing data;    Remote sensing technology;    Spatial resolution;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/18/1/012011/pdf
DOI  :  10.1088/1755-1315/18/1/012011

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

This study was undertaken in order to test the use of remote sensing technology to assess forest degradation in the Peninsular Malaysia. In order to analyse the effect of spatial resolution on forest degradation assessment, course and moderate spatial resolution remote sensing data were examined in this study. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used as coarse spatial resolution data, while Landsat Enhanced Thematic Mapper+(ETM+) imagery was used as moderate spatial resolution to compare the accuracy. Geometric and radiometric correction and re-sampling were performed in preprocessing section to enhance the analysis and results. Canopy fractional cover was used as an approach to assess the forest degradation in this study. Then, an optimum vegetation index was selected to apply on canopy fractional cover to enhance the detection of forest canopy damage. At the same time, accuracy assessment for the approach was referred to the location of Neobalanocarpus Heimii and correlate with global evapotranspiration rate. The forest degradation analysis was also applied and compared for all of the states in the Peninsular Malaysia. In conclusion, Landsat ETM+imagery obtained higher accuracy compare to MODIS using canopy fractional cover approach for forest degradation assessment, and can be more broadly applicable to use for forest degradation investigation.