{"title":"从卫星图像数据进行植被时间分析的工具","authors":"A. Rodrigues, A. Marçal, M. Cunha","doi":"10.1109/MULTI-TEMP.2011.6005044","DOIUrl":null,"url":null,"abstract":"The availability of temporal satellite image data has increased considerably in recent years. A number of satellite sensors currently observe the Earth with high temporal frequency thus providing a tool for monitoring/understanding the Earth-surface variability more precisely, for several applications such as the analysis of vegetation dynamics. However, the extraction of vegetation phenology information from Earth Observation Satellite (EOS) data is not easy, requiring efficient processing algorithms to properly handle the large amounts of data gathered. The purpose of this work is to present a new, easy-to-use software tool that produces phenology information from EOS vegetation temporal data — PhenoSat. This paper describes PhenoSat, focusing on two new features: the determination of the beginning and maximum of a double growth season, and the selection of a temporal sub-region of interest in order to reduce and control the data evaluated.","PeriodicalId":254778,"journal":{"name":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"PhenoSat — A tool for vegetation temporal analysis from satellite image data\",\"authors\":\"A. Rodrigues, A. Marçal, M. Cunha\",\"doi\":\"10.1109/MULTI-TEMP.2011.6005044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The availability of temporal satellite image data has increased considerably in recent years. A number of satellite sensors currently observe the Earth with high temporal frequency thus providing a tool for monitoring/understanding the Earth-surface variability more precisely, for several applications such as the analysis of vegetation dynamics. However, the extraction of vegetation phenology information from Earth Observation Satellite (EOS) data is not easy, requiring efficient processing algorithms to properly handle the large amounts of data gathered. The purpose of this work is to present a new, easy-to-use software tool that produces phenology information from EOS vegetation temporal data — PhenoSat. This paper describes PhenoSat, focusing on two new features: the determination of the beginning and maximum of a double growth season, and the selection of a temporal sub-region of interest in order to reduce and control the data evaluated.\",\"PeriodicalId\":254778,\"journal\":{\"name\":\"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"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.2011.6005044\",\"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.2011.6005044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PhenoSat — A tool for vegetation temporal analysis from satellite image data
The availability of temporal satellite image data has increased considerably in recent years. A number of satellite sensors currently observe the Earth with high temporal frequency thus providing a tool for monitoring/understanding the Earth-surface variability more precisely, for several applications such as the analysis of vegetation dynamics. However, the extraction of vegetation phenology information from Earth Observation Satellite (EOS) data is not easy, requiring efficient processing algorithms to properly handle the large amounts of data gathered. The purpose of this work is to present a new, easy-to-use software tool that produces phenology information from EOS vegetation temporal data — PhenoSat. This paper describes PhenoSat, focusing on two new features: the determination of the beginning and maximum of a double growth season, and the selection of a temporal sub-region of interest in order to reduce and control the data evaluated.