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題名 Analyzing vegetation phenology in Yilan using multisource remote sensing images
作者 詹進發
Li, Liang Yun
Tsai, Jung-en
Chang, Chung-te
Jan, Juhn-fa
貢獻者 地政系
關鍵詞 Biology; Forestry; Image analysis; Image reconstruction; Radiometers; Remote sensing; Time series; Vegetation; ESTARFM; LANDSAT; MODIS; TIMESAT; Vegetation phenology; Climate change
日期 2015-10
上傳時間 14-Aug-2017 15:54:39 (UTC+8)
摘要 Land surface vegetation phenology reflects the responses of a terrestrial ecosystem to climate change. It is effective for monitoring the vegetation phenology of larger-scale area using time-series remotely sensed dataset. In this study, we used MODIS-NDVI and Landsat TM images for vegetation phenology analysis between 2001 and 2010 in Yilan. First, the monthly maximum value (MVC) images of MODIS were generated from 16-day NDVI time-series data. Second, the synthetic Landsat NDVI data were created using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm for all dates when Landsat images were either unavailable or too cloudy. The monthly temperature and precipitation data during 2001 and 2010 and climate spatial layer were generated in ArcGIS 10.1 for vegetation-climate analysis. Then, the MODIS and Landsat images were provided as input for the phenology analysis toolbox TIMESAT, from which the phenological metrics including onset) start of growing season), offset) end of growing season) and the length of growing season were derived. The results was used to analyze the phonological parameters of vegetation, and used the climate data to know the relationship between the vegetation phenology and the climate change. In the end, the result of MODIS NDVI data and the synthetic Landsat NDVI data will be compared.
關聯 ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings
36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015; Crowne Plaza Manila GalleriaQuezon City, Metro Manila; Philippines; 24 October 2015 到 28 October 2015; 代碼 118634
資料類型 conference
dc.contributor 地政系zh_Tw
dc.creator (作者) 詹進發zh_TW
dc.creator (作者) Li, Liang Yunen_US
dc.creator (作者) Tsai, Jung-enen_US
dc.creator (作者) Chang, Chung-teen_US
dc.creator (作者) Jan, Juhn-faen_US
dc.date (日期) 2015-10en_US
dc.date.accessioned 14-Aug-2017 15:54:39 (UTC+8)-
dc.date.available 14-Aug-2017 15:54:39 (UTC+8)-
dc.date.issued (上傳時間) 14-Aug-2017 15:54:39 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111950-
dc.description.abstract (摘要) Land surface vegetation phenology reflects the responses of a terrestrial ecosystem to climate change. It is effective for monitoring the vegetation phenology of larger-scale area using time-series remotely sensed dataset. In this study, we used MODIS-NDVI and Landsat TM images for vegetation phenology analysis between 2001 and 2010 in Yilan. First, the monthly maximum value (MVC) images of MODIS were generated from 16-day NDVI time-series data. Second, the synthetic Landsat NDVI data were created using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm for all dates when Landsat images were either unavailable or too cloudy. The monthly temperature and precipitation data during 2001 and 2010 and climate spatial layer were generated in ArcGIS 10.1 for vegetation-climate analysis. Then, the MODIS and Landsat images were provided as input for the phenology analysis toolbox TIMESAT, from which the phenological metrics including onset) start of growing season), offset) end of growing season) and the length of growing season were derived. The results was used to analyze the phonological parameters of vegetation, and used the climate data to know the relationship between the vegetation phenology and the climate change. In the end, the result of MODIS NDVI data and the synthetic Landsat NDVI data will be compared.en_US
dc.format.extent 177 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedingsen_US
dc.relation (關聯) 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015; Crowne Plaza Manila GalleriaQuezon City, Metro Manila; Philippines; 24 October 2015 到 28 October 2015; 代碼 118634zh_TW
dc.subject (關鍵詞) Biology; Forestry; Image analysis; Image reconstruction; Radiometers; Remote sensing; Time series; Vegetation; ESTARFM; LANDSAT; MODIS; TIMESAT; Vegetation phenology; Climate changeen_US
dc.title (題名) Analyzing vegetation phenology in Yilan using multisource remote sensing imagesen_US
dc.type (資料類型) conference