In the field of global changes, the relationship between plant phenology and climate, which reflects the response of terrestrial ecosystem to global climate change, has become a key subject that is highly concerned. U...In the field of global changes, the relationship between plant phenology and climate, which reflects the response of terrestrial ecosystem to global climate change, has become a key subject that is highly concerned. Using the moderate-resolution imaging spectroradiometer (MODIS)/enhanced vegetation index(EVI) collected every eight days during January- July from 2005 to 2008 and the corresponding remote sensing data as experimental materials, we constructed cloud-free images via the Harmonic analysis of time series (HANTS). The cloud-free images were then treated by dynamic threshold method for obtaining the vegetation phenology in green up period and its distribution pattern. And the distribution pattern between freezing disaster year and normal year were comparatively analyzed for revealing the effect of freezing disaster on vegetation phenology in experimental plot. The result showed that the treated EVI data performed well in monitoring the effect of freezing disaster on vegetation phenology, accurately reflecting the regions suffered from freezing disaster. This result suggests that processing of remote sensing data using HANTS method could well monitor the ecological characteristics of vegetation.展开更多
This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extra...This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extracted multiple cropping index （MCI） on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer （MODIS） enhanced vegetation index （EVI） value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.展开更多
It has a great significance to combine multi-source with different spatial resolution and temporal resolution to produce high spatiotemporal resolution Normalized Difference Vegetation Index (NDVI) time series data se...It has a great significance to combine multi-source with different spatial resolution and temporal resolution to produce high spatiotemporal resolution Normalized Difference Vegetation Index (NDVI) time series data sets. In this study, four spatiotemporal fusion models were analyzed and compared with each other. The models included the spatial and temporal adaptive reflectance model (STARFM), the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), the flexible spatiotemporal data fusion model (FSDAF), and a spatiotemporal vegetation index image fusion model (STVIFM). The objective of is to: 1) compare four fusion models using Landsat-MODIS NDVI image from the Banan district, Chongqing Province;2) analyze the prediction accuracy quantitatively and visually. Results indicate that STVIFM would be more suitable to produce NDVI time series data sets.展开更多
文摘In the field of global changes, the relationship between plant phenology and climate, which reflects the response of terrestrial ecosystem to global climate change, has become a key subject that is highly concerned. Using the moderate-resolution imaging spectroradiometer (MODIS)/enhanced vegetation index(EVI) collected every eight days during January- July from 2005 to 2008 and the corresponding remote sensing data as experimental materials, we constructed cloud-free images via the Harmonic analysis of time series (HANTS). The cloud-free images were then treated by dynamic threshold method for obtaining the vegetation phenology in green up period and its distribution pattern. And the distribution pattern between freezing disaster year and normal year were comparatively analyzed for revealing the effect of freezing disaster on vegetation phenology in experimental plot. The result showed that the treated EVI data performed well in monitoring the effect of freezing disaster on vegetation phenology, accurately reflecting the regions suffered from freezing disaster. This result suggests that processing of remote sensing data using HANTS method could well monitor the ecological characteristics of vegetation.
基金supported by the National Natural Science Foundation of China (41001277)the National 973 Program of China (2010CB95090102)
文摘This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extracted multiple cropping index （MCI） on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer （MODIS） enhanced vegetation index （EVI） value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
文摘It has a great significance to combine multi-source with different spatial resolution and temporal resolution to produce high spatiotemporal resolution Normalized Difference Vegetation Index (NDVI) time series data sets. In this study, four spatiotemporal fusion models were analyzed and compared with each other. The models included the spatial and temporal adaptive reflectance model (STARFM), the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), the flexible spatiotemporal data fusion model (FSDAF), and a spatiotemporal vegetation index image fusion model (STVIFM). The objective of is to: 1) compare four fusion models using Landsat-MODIS NDVI image from the Banan district, Chongqing Province;2) analyze the prediction accuracy quantitatively and visually. Results indicate that STVIFM would be more suitable to produce NDVI time series data sets.
