Study On Aeolian Desertification Remote Sensing Monitoring System In China Using MODIS Image Data

Aeolian desertification is one of the most serious ecological and environmental problems in the world. It directly influences regional economic development and social stability. This dissertation focused on Aeolian desertification area in the north China. According to the problems of high cost, labor consuming, long monitoring period and lacking uniform indicator system in Aeolian desertification monitoring, we broke through the choke point of quantitative remote sensing and auto discrimination and classification technique at large scale with the starting point of retrieving of surface characters, and developed a Aeolian desertification monitoring technique system by combining original and integrated innovation basing on low-cost MODIS data and combining other data, which would be used to satisfy the need of Aeolian desertification at national scale. Firstly, the methods to monitor Aeolian desertification were developed. Secondly, index system, spatial and temporal changes of Aeolian desertification are analyzed quantitatively using'3S'technology. Finally, the causes and environmental effects of Aeolian desertification are discussed. The objectives are to improve methodology for monitoring Aeolian desertification using remote sensing. The results were intended to provide scientific bases for decision-making processes in combating Aeolian desertification and restoring degraded ecosystem.Based on investigation of current research and previous efforts on Aeolian desertification and guided by the design principle, this dissertation proposed a monitoring Aeolian desertification index system of Aeolian desertification, which is suitable for large-scale desertification monitoring by using remote sensing techniques. First, five Aeolian desertification indices were retrieved from MODIS satellite data, four Aeolian desertification indexes have finally chosen to be our selection of suitable for large-scale Aeolian desertification monitoring. Then, the Aeolian desertification status in north China in 2007 Vernal and Autumn Equinox were analyzed.Main research results and initiatives in this thesis include as following:1. An integrated Aeolian desertification indexes are proposed and the construction of a Aeolian desertification monitoring index system using remote sensing techniques is recommended. According to the Aeolian desertification index design principle and the research aim of this dissertation, we selected five Aeolian desertification indexes (MSAVI, ALBEDO, LST, WET, FVC) suitable for large-scale Aeolian desertification monitoring using remote sensing technique. After applying different index and index combinations on Aeolian desertification monitoring and its precision evaluation in test area, the result shows that the precision of index combination of MSAVI, ALBEDO, LST, WET and FVC is superior to others. Four Aeolian desertification indexes(MSAVI,ALBEDO,LST and WET)have finally chosen to be our selection of suitable for large-scale Aeolian desertification monitoring using remote sensing technique on the base of correlation analysis. In term of the Aeolian desertification climate types, the potential extent of Aeolian desertification in north China was respectively divided into four categories: sub-humid area, sub-arid area, arid area, extremely arid area. Different Aeolian desertification index system was built for each area.2. Selection of a suitable method on remote sensing retrieval of Aeolian desertification indexes and the spatial distribution of Aeolian desertification were analyzed in study area.Based on analysis and comparison of current retrieval algorithms, we utilized a suitable algorithm on large scale to retrieve four Aeolian desertification indexes with 16-day MODIS image data set in 2007 Vernal and Autumn Equinox, and built the database of Aeolian desertification monitoring indexes in north China. At the same time, we analyzed the spatial distribution characteristic of the indexes in north China.3. A method of synchronous large-scale ground validation based on MODIS 1km image data was proposed.Because of lacking appropriate validation method in a large area, a method of synchronous large-scale ground validation was proposed on MODIS 1km image pixel to evaluate the precision of retrieved Aeolian desertification indexes. The research results showed that the method of synchronous large-scale ground validation was quite feasible, which was suitable for evaluation of the precision of retrieved Aeolian desertification indexes at large-scale by remote sensing.4. Because of much more complex parameters in normal methods of Vegetation fraction retrieving based on MODIS data and lacking appropriate validation method in a large area, a method of using the maximum and the minimum Vegetation fraction in studies region actual to be determination retrieving model and synchronous large-scale ground validation was proposed in this paper. After comparing retrieved Vegetation fraction of sandy desertification region in Mu Us sandy land and synchronous validation ground data, the accuracy was pretty high and the correlation coefficient between synchronous ground measured data and the retrieved Vegetation fraction also reached high. The research results showed that the method of retrieving Vegetation fraction in aeolian desertification from MODIS data and synchronous large-scale ground validation was feasible, which was suitable for Vegetation fraction quickly monitoring at large-scale by remote sensing.5. An optimal classifier for Aeolian desertification monitoring was determined and Aeolian desertification status in north China were evaluated and analyzed.In test area, by assessing the classification accuracies of three types of classifiers (unsupervised classifier, maximum likelihood classifier and decision tree classifier), we select decision tree classifier for Aeolian desertification monitoring. Supported by Aeolian desertification index system and the database of Aeolian desertification indexes, utilizing the cumulated MSAVI, albedo, land surface temperature and wet index in north China, the Aeolian desertification status in 2007 Vernal and Autumn Equinox was classified by decision tree classifier, and analysis of Aeolian desertification change in 2007 was also completed in study area.