Spatio-temporal variations of vegetation phenology, e.g. start of green-up season（SOS） and end of vegetation season（EOS）, serve as important indicators of ecosystems. Routinely processed products from remotely sen...Spatio-temporal variations of vegetation phenology, e.g. start of green-up season（SOS） and end of vegetation season（EOS）, serve as important indicators of ecosystems. Routinely processed products from remotely sensed imagery, such as the normalized difference vegetation index（NDVI）, can be used to map such variations. A remote sensing approach to tracing vegetation phenology was demonstrated here in application to the Inner Mongolia grassland, China. SOS and EOS mapping at regional and vegetation type（meadow steppe, typical steppe, desert steppe and steppe desert） levels using SPOT-VGT NDVI series allows new insights into the grassland ecosystem. The spatial and temporal variability of SOS and EOS during 1998–2012 was highlighted and presented, as were SOS and EOS responses to the monthly climatic fluctuations. Results indicated that SOS and EOS did not exhibit consistent shifts at either regional or vegetation type level; the one exception was the steppe desert, the least productive vegetation cover, which exhibited a progressive earlier SOS and later EOS. Monthly average temperature and precipitation in preseason（February, March and April） imposed most remarkable and negative effects on SOS（except for the non-significant impact of precipitation on that of the meadow steppe）, while the climate impact on EOS was found to vary considerably between the vegetation types. Results showed that the spatio-temporal variability of the vegetation phenology of the meadow steppe, typical steppe and desert steppe could be reflected by the monthly thermal and hydrological factors but the progressive earlier SOS and later EOS of the highly degraded steppe desert might be accounted for by non-climate factors only, suggesting that the vegetation growing period in the highly degraded areas of the grassland could be extended possibly by human interventions.展开更多
Monthly mean surface air temperatures and precipitation at 20 meteorological stations in the Jinsha River Valley(JRV) of southwest China were analyzed for temporal-spatial variation patterns during the period 1961-201...Monthly mean surface air temperatures and precipitation at 20 meteorological stations in the Jinsha River Valley(JRV) of southwest China were analyzed for temporal-spatial variation patterns during the period 1961-2010.The magnitude of a trend was estimated using Sen's Nonparametric Estimator of Slope approach.The statistical significance of a trend was assessed by the MK test.The results showed that mean annual air temperature has been increasing by 0.08℃/decade during the past 50 years as a whole.The climate change trend in air temperature was more significant in the winter(0.13℃/decade) than in the summer(0.03℃/decade).Annual precipitation tended to increase slightly thereafter and the increasing was mainly during the crop-growing season.Both the greatest variation of the annual mean temperature and annual precipitation were observed at the dry-hot valley area of middle reaches.Significant warming rates were found in the upper reaches whereas the dry-hot basins of middle reaches experienced a cooling trend during the past decades.Despite of the overall increasing in precipitation,more obvious upward-trends were found in the dry-hot basins of middle reaches whereas the upper reaches had a drought trend during the past decades.展开更多
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05050402)the Key Laboratory for Geographic State Monitoring of the National Administration of Surveying, Mapping and Geoinformation (2014-04)the National Natural Science Foundation of China (41071249, 41371371)
文摘Spatio-temporal variations of vegetation phenology, e.g. start of green-up season（SOS） and end of vegetation season（EOS）, serve as important indicators of ecosystems. Routinely processed products from remotely sensed imagery, such as the normalized difference vegetation index（NDVI）, can be used to map such variations. A remote sensing approach to tracing vegetation phenology was demonstrated here in application to the Inner Mongolia grassland, China. SOS and EOS mapping at regional and vegetation type（meadow steppe, typical steppe, desert steppe and steppe desert） levels using SPOT-VGT NDVI series allows new insights into the grassland ecosystem. The spatial and temporal variability of SOS and EOS during 1998–2012 was highlighted and presented, as were SOS and EOS responses to the monthly climatic fluctuations. Results indicated that SOS and EOS did not exhibit consistent shifts at either regional or vegetation type level; the one exception was the steppe desert, the least productive vegetation cover, which exhibited a progressive earlier SOS and later EOS. Monthly average temperature and precipitation in preseason（February, March and April） imposed most remarkable and negative effects on SOS（except for the non-significant impact of precipitation on that of the meadow steppe）, while the climate impact on EOS was found to vary considerably between the vegetation types. Results showed that the spatio-temporal variability of the vegetation phenology of the meadow steppe, typical steppe and desert steppe could be reflected by the monthly thermal and hydrological factors but the progressive earlier SOS and later EOS of the highly degraded steppe desert might be accounted for by non-climate factors only, suggesting that the vegetation growing period in the highly degraded areas of the grassland could be extended possibly by human interventions.
基金Strategic Priority Research Program"of the Chinese Academy of Sciences(XDA0505040702)Chinese Academy of Sciences"Light of West Program"
文摘Monthly mean surface air temperatures and precipitation at 20 meteorological stations in the Jinsha River Valley(JRV) of southwest China were analyzed for temporal-spatial variation patterns during the period 1961-2010.The magnitude of a trend was estimated using Sen's Nonparametric Estimator of Slope approach.The statistical significance of a trend was assessed by the MK test.The results showed that mean annual air temperature has been increasing by 0.08℃/decade during the past 50 years as a whole.The climate change trend in air temperature was more significant in the winter(0.13℃/decade) than in the summer(0.03℃/decade).Annual precipitation tended to increase slightly thereafter and the increasing was mainly during the crop-growing season.Both the greatest variation of the annual mean temperature and annual precipitation were observed at the dry-hot valley area of middle reaches.Significant warming rates were found in the upper reaches whereas the dry-hot basins of middle reaches experienced a cooling trend during the past decades.Despite of the overall increasing in precipitation,more obvious upward-trends were found in the dry-hot basins of middle reaches whereas the upper reaches had a drought trend during the past decades.
