Remotely sensing images are now available for monitoring vegetation dynamics over large areas.In this paper,an improved logistic model that combines double logistic model and global function was developed.Using this m...Remotely sensing images are now available for monitoring vegetation dynamics over large areas.In this paper,an improved logistic model that combines double logistic model and global function was developed.Using this model with SPOT/NDVI data,three key vegetation phenology metrics,the start of growing season (SOS),the end of growing season (EOS) and the length of growing season (LOS),were extracted and mapped in the Changbai Mountains,and the relationship between the key phenology metrics and elevation were established.Results show that average SOS of forest,cropland and grassland in the Changbai Mountains are on the 119th,145th,and 133rd day of year,respectively.The EOS of forest and grassland are similar,with the average on the 280th and 278th,respectively.In comparison,average EOS of the cropland is relatively earlier.The LOS of forest is mainly from the 160th to 180th,that of the grassland extends from the 140th to the 160th,and that of cropland stretches from the 110th to the 130th.As the latitude increases for the same land cover in the study area,the SOS significantly delays and the EOS becomes earlier.The SOS delays approximately three days as the elevation increases 100 m in the areas with elevation higher than 900 m above sea level (a.s.l.).The EOS is slightly earlier as the elevation increases especially in the areas with elevation below 1200 m a.s.l.The LOS shortens approximately four days as the elevation increases 100 m in the areas with elevation higher than 900 m a.s.l.The relationships between vegetation phenology metrics and elevation may be greatly influenced by the land covers.Validation by comparing with the field data and previous research results indicates that the improved logistic model is reliable and effective for extracting vegetation phenology metrics.展开更多
运用SWAT (Soil and Water Assessment Tool)模型模拟国际界河鸭绿江流域(中国侧) 1988—2017年的蓝、绿水资源量,明确其时空变化特征,并设置多种气候变化与土地利用变化情景对流域蓝、绿水资源时空变化进行归因分析。研究结果表明:(1)...运用SWAT (Soil and Water Assessment Tool)模型模拟国际界河鸭绿江流域(中国侧) 1988—2017年的蓝、绿水资源量,明确其时空变化特征,并设置多种气候变化与土地利用变化情景对流域蓝、绿水资源时空变化进行归因分析。研究结果表明:(1)鸭绿江流域(中国侧)蓝、绿水资源丰富,年均蓝水资源量是绿水的1.45倍,蓝、绿水资源均有增长趋势但并不显著,季节蓝、绿水资源量均为夏季>秋季>春季>冬季;(2)鸭绿江流域(中国侧)年均蓝水资源在基准期和变化期均从上游至下游逐渐增加,而年均绿水资源则呈现从上游至下游先增后减的空间分布特征;(3)气候变化是鸭绿江流域(中国侧)蓝、绿水资源时空变化的主导因素,其对蓝、绿水资源变化量的贡献率分别为83.57%和195.51%。研究结果可为鸭绿江流域跨境水资源合理分配、国际合作提供依据。展开更多
基金Under the auspices of Major State Basic Research Development Program of China (No.2009CB426305)Cultivation Foundation of Science and Technology Innovation Platform of Northeast Normal University (No.106111065202)
文摘Remotely sensing images are now available for monitoring vegetation dynamics over large areas.In this paper,an improved logistic model that combines double logistic model and global function was developed.Using this model with SPOT/NDVI data,three key vegetation phenology metrics,the start of growing season (SOS),the end of growing season (EOS) and the length of growing season (LOS),were extracted and mapped in the Changbai Mountains,and the relationship between the key phenology metrics and elevation were established.Results show that average SOS of forest,cropland and grassland in the Changbai Mountains are on the 119th,145th,and 133rd day of year,respectively.The EOS of forest and grassland are similar,with the average on the 280th and 278th,respectively.In comparison,average EOS of the cropland is relatively earlier.The LOS of forest is mainly from the 160th to 180th,that of the grassland extends from the 140th to the 160th,and that of cropland stretches from the 110th to the 130th.As the latitude increases for the same land cover in the study area,the SOS significantly delays and the EOS becomes earlier.The SOS delays approximately three days as the elevation increases 100 m in the areas with elevation higher than 900 m above sea level (a.s.l.).The EOS is slightly earlier as the elevation increases especially in the areas with elevation below 1200 m a.s.l.The LOS shortens approximately four days as the elevation increases 100 m in the areas with elevation higher than 900 m a.s.l.The relationships between vegetation phenology metrics and elevation may be greatly influenced by the land covers.Validation by comparing with the field data and previous research results indicates that the improved logistic model is reliable and effective for extracting vegetation phenology metrics.
文摘运用SWAT (Soil and Water Assessment Tool)模型模拟国际界河鸭绿江流域(中国侧) 1988—2017年的蓝、绿水资源量,明确其时空变化特征,并设置多种气候变化与土地利用变化情景对流域蓝、绿水资源时空变化进行归因分析。研究结果表明:(1)鸭绿江流域(中国侧)蓝、绿水资源丰富,年均蓝水资源量是绿水的1.45倍,蓝、绿水资源均有增长趋势但并不显著,季节蓝、绿水资源量均为夏季>秋季>春季>冬季;(2)鸭绿江流域(中国侧)年均蓝水资源在基准期和变化期均从上游至下游逐渐增加,而年均绿水资源则呈现从上游至下游先增后减的空间分布特征;(3)气候变化是鸭绿江流域(中国侧)蓝、绿水资源时空变化的主导因素,其对蓝、绿水资源变化量的贡献率分别为83.57%和195.51%。研究结果可为鸭绿江流域跨境水资源合理分配、国际合作提供依据。
