蒸散量是水资源相互转化过程中非常重要但又难以定量确定的要素之一。SEBS(Surface Energy Balance System)模型是通过遥感数据计算区域蒸散量的重要模型,该模型可以在较少地面信息的情况下获得蒸散量的区域分布信息,同时具有较高的精...蒸散量是水资源相互转化过程中非常重要但又难以定量确定的要素之一。SEBS(Surface Energy Balance System)模型是通过遥感数据计算区域蒸散量的重要模型,该模型可以在较少地面信息的情况下获得蒸散量的区域分布信息,同时具有较高的精度。采用SEBS模型,利用NOAA/AVHRR数据对我国重要的商品粮基地三江平原区域蒸散发量进行了研究,并通过实测数据对估算结果进行了验证。结果表明:从时间分布来看,三江平原蒸散量总体上表现为从4月开始逐渐上升,7月达到最高值,8月后不断下降。在此基础上,探讨了三江平原蒸散量时间分布的原因。同时,结合研究区的土地利用类型,对三江平原区域蒸散量空间分布进行了分析,各种土地利用类型生长季平均蒸散量从大到小可以排列为:林地>水域>湿地>水田>旱田>草地>居工地。展开更多
近年来,由于气候变化和人类活动的共同影响,生态环境,特别是草地资源发生了较大的变化。本文利用美国地球资源观测系统数据中心探路者数据库(Pathfinder Data Sets)的1981～1999年序列的NOAA/AVHRR NDVI资料,阐述了该资料的处理方法、...近年来,由于气候变化和人类活动的共同影响,生态环境,特别是草地资源发生了较大的变化。本文利用美国地球资源观测系统数据中心探路者数据库(Pathfinder Data Sets)的1981～1999年序列的NOAA/AVHRR NDVI资料,阐述了该资料的处理方法、研究草地生产力动态变化的原理和计算方法,并分析了近20a来青海省草地生产力变化的空间和时间特征以及地区差异性。展开更多
The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the...The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive ( R 2=0.80, R 2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982-1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990-2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998.展开更多
文摘蒸散量是水资源相互转化过程中非常重要但又难以定量确定的要素之一。SEBS(Surface Energy Balance System)模型是通过遥感数据计算区域蒸散量的重要模型,该模型可以在较少地面信息的情况下获得蒸散量的区域分布信息,同时具有较高的精度。采用SEBS模型,利用NOAA/AVHRR数据对我国重要的商品粮基地三江平原区域蒸散发量进行了研究,并通过实测数据对估算结果进行了验证。结果表明:从时间分布来看,三江平原蒸散量总体上表现为从4月开始逐渐上升,7月达到最高值,8月后不断下降。在此基础上,探讨了三江平原蒸散量时间分布的原因。同时,结合研究区的土地利用类型,对三江平原区域蒸散量空间分布进行了分析,各种土地利用类型生长季平均蒸散量从大到小可以排列为:林地>水域>湿地>水田>旱田>草地>居工地。
文摘近年来,由于气候变化和人类活动的共同影响,生态环境,特别是草地资源发生了较大的变化。本文利用美国地球资源观测系统数据中心探路者数据库(Pathfinder Data Sets)的1981～1999年序列的NOAA/AVHRR NDVI资料,阐述了该资料的处理方法、研究草地生产力动态变化的原理和计算方法,并分析了近20a来青海省草地生产力变化的空间和时间特征以及地区差异性。
基金Supported by the National 973 Program of China (No2006CB701300)the National Natural Science Foundation of China (No40721001)the Sino-Germany Joint Project (No 2006DFB91920)
文摘The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive ( R 2=0.80, R 2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982-1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990-2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998.
