Study On Technologies Of Remote Sensing Feature Analysis And Information Extaction Of Earthquake Disaster

An earthquake (also known as a quake or tremor) is the result of a sudden release of energy in the Earth's crust that creates seismic waves. It is one kind of multiple serious natural disasters, with a wide range of impact and causing serious destruction. Current technologies cannot accurately predict an earthquake, in some sense, it is unpredictable. Once it happens, an earthquake will bring people a great loss of life and property. China is located in the intersection parts of world's two major seismic zones, where earthquake fault zones are well developed, resulting in an earthquake-prone country. With the existing level of earthquake prediction, it becomes very important that how to fast get accurate disaster information control the situation, analyze disaster damage after the earthquake. Remote sensing technology has some prominent features like a wide range of observation, high frequency of repeated measures, all-weather, all-time observations and access to information quickly and accurately. Also it can be observed in areas where it is difficult to reach by anyone. And these prominent features make it possible for its application in acquisition of earthquake disaster information.In this paper, the research is based on the 5.12 Wenchuan and Beichuan Earthquake disaster areas and other disaster areas. It uses the principles and methods of analysis remote sensing feature for earthquake, information extraction and identification classification, and it elaborates method of information extraction based on multi-temporal remote sensing. On the basis of researching different information extraction, this paper analyzes features of remote sensing and extracts information, and finally gets a disaster information extraction map with briefly analysis of ecological environmental monitoring.The main achievement and acknowledge is stated bellow:(1) A monitoring method based on NDVI and supervised classification was proposed to monitor changes in vegetation distribution before and after 5.12 Earthquake. With the analysis of spectral feature of vegetation and the information of data bands, on the basis of the best band index, using four typical supervised classification method and Normalized Difference Vegetation Index i.e. NDVI to extract and to gather statistics of the information of vegetation before and after earthquake, thus the corresponding figure that shows the change of vegetation change data and before and after earthquake can be achieved.(2) Band Decision Model of Water (BDMW) is brought up to extract the information of water. The complex environment of post-earthquake makes the phenomenon that foreign bodies owe the same spectrum increases. Through the research on the current remote sensing information extraction of water (such as multi-band spectral relation method, water index, vegetation index decision tree analysis and so on) and the analysis of spectrum of similar materials and water, by using BDMW the information of water can be accurately extracted.(3) Building information extraction method is brought up that using the Contrastive Analysis of Abnormal NDVI (CAAN) to contrastive analyze before and after the earthquake. Serious damage to the earth's surface makes the imaging features of the earth more complex. On the basis of buildings'spectral analysis before and after the earthquake, and the research of the NDVI's anomaly before and after the earthquake, post-earthquake building information is initially extracted.(4) An information extraction of low-resolution images landslides and debris flows is initially proposed. At present, relying on high resolution data is the main method to recognize landslides and debris flows, low-resolution data is not yet applied too much in this field. But high resolution data costs more and has a small range of observation. Given the above, based on terrain features of the earthquake zone and remote sensing image features of landslide and debris in low-resolution case. And combined with the spectral feature and textural features of landslide and debris, the initial extraction of landslides and debris flows is carried on.