Minbin Jiang, Zhuowei Hu, Yi Ding, Dan Fang, Yang Li, Lai Wei, Meichen Guo, Shuo Zhang
{"title":"基于MODIS的植被含水量估算:在森林火险评估中的应用","authors":"Minbin Jiang, Zhuowei Hu, Yi Ding, Dan Fang, Yang Li, Lai Wei, Meichen Guo, Shuo Zhang","doi":"10.1109/Geoinformatics.2012.6270322","DOIUrl":null,"url":null,"abstract":"Forest fire is one of serious and universal natural disasters with the characteristics of wide distribution, high frequency, and uncertainty. Because of these features, the traditional manual methods to monitor forest fire become difficult. With the development of the remote sensing monitoring techniques, the forest fire monitoring becomes more effective. The ignition of forest fire needs some special weather and forest conditions concerned. Fuel moister content is a critical factor to induce the occurrence of forest fires. It is decided by the vegetation water content. In This paper the Great Khingan Mountains Region which locate in Heilongjiang Province were taken as the study area. And it includes the flowing contents: 1.Using MODIS NDVI data to reveal the growth situation of vegetation, and its relationship with vegetation water. 2. Using the band 2 and band 6 of MODIS data to calculate the global vegetation moisture index. 3. Using global vegetation moisture index to retrieve vegetation water content. 4. Considering the relation of NDVI, and vegetation water content comprehensively, obtained high fire risk period and areas of experimental area.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Estimation of vegetation water content based on MODIS: Application on forest fire risk assessment\",\"authors\":\"Minbin Jiang, Zhuowei Hu, Yi Ding, Dan Fang, Yang Li, Lai Wei, Meichen Guo, Shuo Zhang\",\"doi\":\"10.1109/Geoinformatics.2012.6270322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forest fire is one of serious and universal natural disasters with the characteristics of wide distribution, high frequency, and uncertainty. Because of these features, the traditional manual methods to monitor forest fire become difficult. With the development of the remote sensing monitoring techniques, the forest fire monitoring becomes more effective. The ignition of forest fire needs some special weather and forest conditions concerned. Fuel moister content is a critical factor to induce the occurrence of forest fires. It is decided by the vegetation water content. In This paper the Great Khingan Mountains Region which locate in Heilongjiang Province were taken as the study area. And it includes the flowing contents: 1.Using MODIS NDVI data to reveal the growth situation of vegetation, and its relationship with vegetation water. 2. Using the band 2 and band 6 of MODIS data to calculate the global vegetation moisture index. 3. Using global vegetation moisture index to retrieve vegetation water content. 4. Considering the relation of NDVI, and vegetation water content comprehensively, obtained high fire risk period and areas of experimental area.\",\"PeriodicalId\":259976,\"journal\":{\"name\":\"2012 20th International Conference on Geoinformatics\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 20th International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Geoinformatics.2012.6270322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 20th International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Geoinformatics.2012.6270322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of vegetation water content based on MODIS: Application on forest fire risk assessment
Forest fire is one of serious and universal natural disasters with the characteristics of wide distribution, high frequency, and uncertainty. Because of these features, the traditional manual methods to monitor forest fire become difficult. With the development of the remote sensing monitoring techniques, the forest fire monitoring becomes more effective. The ignition of forest fire needs some special weather and forest conditions concerned. Fuel moister content is a critical factor to induce the occurrence of forest fires. It is decided by the vegetation water content. In This paper the Great Khingan Mountains Region which locate in Heilongjiang Province were taken as the study area. And it includes the flowing contents: 1.Using MODIS NDVI data to reveal the growth situation of vegetation, and its relationship with vegetation water. 2. Using the band 2 and band 6 of MODIS data to calculate the global vegetation moisture index. 3. Using global vegetation moisture index to retrieve vegetation water content. 4. Considering the relation of NDVI, and vegetation water content comprehensively, obtained high fire risk period and areas of experimental area.