{"title":"利用年度土地覆盖动态(YLCD)方法监测全球植被","authors":"Y. Julien, J. Sobrino","doi":"10.1109/MULTI-TEMP.2011.6005063","DOIUrl":null,"url":null,"abstract":"Global vegetation has been traditionally monitored mainly through the use of the Normalized Difference Vegetation Index (NDVI). Land surface temperature (LST) provides additional information, and is generally less affected by atmospheric conditions when water vapor is taken into account. The Yearly Land Cover Dynamics (YLCD) method can then be used to retrieve 3 parameters which allow for a good differentiation between biomes at the global and local levels. Using NASA's Long Term Data Record (LTDR), the YLCD method has been applied to IDR (iterative Interpolation for Data Reconstruction) reconstructed LTDR data, in order to account for atmospheric contamination of part of the dataset for a few selected pixels. The evolution of the retrieved YLCD parameters is monitored throughout the 20-year span of the LTDR dataset.","PeriodicalId":254778,"journal":{"name":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Monitoring global vegetation with the Yearly Land Cover Dynamics (YLCD) method\",\"authors\":\"Y. Julien, J. Sobrino\",\"doi\":\"10.1109/MULTI-TEMP.2011.6005063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Global vegetation has been traditionally monitored mainly through the use of the Normalized Difference Vegetation Index (NDVI). Land surface temperature (LST) provides additional information, and is generally less affected by atmospheric conditions when water vapor is taken into account. The Yearly Land Cover Dynamics (YLCD) method can then be used to retrieve 3 parameters which allow for a good differentiation between biomes at the global and local levels. Using NASA's Long Term Data Record (LTDR), the YLCD method has been applied to IDR (iterative Interpolation for Data Reconstruction) reconstructed LTDR data, in order to account for atmospheric contamination of part of the dataset for a few selected pixels. The evolution of the retrieved YLCD parameters is monitored throughout the 20-year span of the LTDR dataset.\",\"PeriodicalId\":254778,\"journal\":{\"name\":\"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MULTI-TEMP.2011.6005063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MULTI-TEMP.2011.6005063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monitoring global vegetation with the Yearly Land Cover Dynamics (YLCD) method
Global vegetation has been traditionally monitored mainly through the use of the Normalized Difference Vegetation Index (NDVI). Land surface temperature (LST) provides additional information, and is generally less affected by atmospheric conditions when water vapor is taken into account. The Yearly Land Cover Dynamics (YLCD) method can then be used to retrieve 3 parameters which allow for a good differentiation between biomes at the global and local levels. Using NASA's Long Term Data Record (LTDR), the YLCD method has been applied to IDR (iterative Interpolation for Data Reconstruction) reconstructed LTDR data, in order to account for atmospheric contamination of part of the dataset for a few selected pixels. The evolution of the retrieved YLCD parameters is monitored throughout the 20-year span of the LTDR dataset.