Deforestation Detection in Kinabalu Area, Sabah, Malaysia by using Multi-sensor Remote Sensing Approach

スポンサーリンク

概要

• 論文の詳細を見る

• This paper examines use of multi-sensor remote sensing approach for deforestation detection in the tropics. Multi-sensor satellite data of Landsat-MSS of 1973 and Landsat-TM of 1991 and 1996 were employed. Accuracy of image-to-image registration was below 1 pixel. Relative radiometric normalization of Landat-MSS 1973 and Landsat-TM 1991 to Landsat-TM 1996 as the reference image was carried out to remove the unwanted variabilities between all the satellite images. Image differencing algorithm with Normalized Difference Vegetation Index (NDVI) was examined for deforestation detection. The performance of the NDVI image differencing algorithm for deforestation detection between 1973 and 1996 was investigated at three test sites covered with reliable ground truths. The accuracy of detection was satisfactory that the algorithm was used in deforestation detection of the whole study area in two change periods i.e. I: 1973-1991 and II: 1991-1996. Although false deforestation pixels in period I were also detected, it can easily be rectified using a land use map of 1984. In total, 2,445ha of forest, which is almost 1% of the study area, were cleared from 1973-1996 and most of them were deforested in period I (2,090ha). This study concludes that the multi-sensor approach is a useful solution for deforestation detection because of better temporal coverage. It can also provide more satellite data for the application and thus lessen data acquisition problem due to cloud cover which is a consistent problem for the tropics.

• 森林計画学会の論文

著者

• Tsuyuki Satoshi

  Graduate School Of Agricultural And Life Sciences The University Of Tokyo

• Phua Mui-How

  School of International Tropical Forestry, Universiti Malaysia Sabah

• Phua Mui-how

  School Of International Tropical Forestry Universiti Malaysia Sabah

関連論文

• Stand Parameter Estimation of Artificial Evergreen Conifer Forests Using Airborne Images : An Evaluation of Seasonal Difference on Accuracy and Best Wavelength
• Reviewer Acknowledgements
• Recognition of Spectral Pattern Characteristic of Land Cover for Assisting Visual Interpretation of Landsat ETM^+ :A Forest Degradation Mapping in Tropical Rain Forest of Sabah, Malaysia
• Monitoring Agricultural Expansion during the Economic Crisis in Indonesia: A Case Study of the Rawa Danau Nature Reserve
• Deforestation Detection in Kinabalu Area, Sabah, Malaysia by using Multi-sensor Remote Sensing Approach

スポンサーリンク