利用多时相MODIS数据检测西伯利亚中部地区西伯利亚蚕蛾危害

International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005. Pub Date : 2005-05-16 DOI:10.1109/AMTRSI.2005.1469833

K. Kovacs, K. Ranson, V. Kharuk

{"title":"利用多时相MODIS数据检测西伯利亚中部地区西伯利亚蚕蛾危害","authors":"K. Kovacs, K. Ranson, V. Kharuk","doi":"10.1109/AMTRSI.2005.1469833","DOIUrl":null,"url":null,"abstract":"As part of a NASA supported Siberian disturbance mapping project, the capabilities of multi- temporal MODIS data to detect insect damage in the boreal forest were evaluated. Multi-temporal in the context of this study includes both multi-annual and multi- seasonal data. More specifically, the aim of this study was to ascertain what combination of multi-temporal MODIS Enhanced Vegetation Index (EVI) and Middle Infrared (MIR) data is best for detecting insect disturbance with or without a priori knowledge.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Detecting siberian silk moth damage in central siberia using multi-temporal MODIS data\",\"authors\":\"K. Kovacs, K. Ranson, V. Kharuk\",\"doi\":\"10.1109/AMTRSI.2005.1469833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As part of a NASA supported Siberian disturbance mapping project, the capabilities of multi- temporal MODIS data to detect insect damage in the boreal forest were evaluated. Multi-temporal in the context of this study includes both multi-annual and multi- seasonal data. More specifically, the aim of this study was to ascertain what combination of multi-temporal MODIS Enhanced Vegetation Index (EVI) and Middle Infrared (MIR) data is best for detecting insect disturbance with or without a priori knowledge.\",\"PeriodicalId\":302923,\"journal\":{\"name\":\"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AMTRSI.2005.1469833\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AMTRSI.2005.1469833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 8

摘要

作为美国国家航空航天局支持的西伯利亚扰动测绘项目的一部分，评估了多时相MODIS数据在北方森林中探测昆虫损害的能力。在本研究的背景下，多时间包括多年和多季节的数据。更具体地说，本研究的目的是确定在有或没有先验知识的情况下，MODIS增强型植被指数(EVI)和中红外(MIR)数据的哪种组合最适合用于检测昆虫干扰。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Detecting siberian silk moth damage in central siberia using multi-temporal MODIS data

As part of a NASA supported Siberian disturbance mapping project, the capabilities of multi- temporal MODIS data to detect insect damage in the boreal forest were evaluated. Multi-temporal in the context of this study includes both multi-annual and multi- seasonal data. More specifically, the aim of this study was to ascertain what combination of multi-temporal MODIS Enhanced Vegetation Index (EVI) and Middle Infrared (MIR) data is best for detecting insect disturbance with or without a priori knowledge.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.

自引率

0.00%

发文量