In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by ...In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.展开更多
The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorologica...The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorological Forcing Data(PMFD)and the high spatial resolution and upscaled China Meteorological Forcing Data(CMFD)were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(SSiB4/TRIFFID)and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau(TP),a region with complex topography and sparse observations.By comparing the monthly Leaf Area Index(LAI)and Gross Primary Production(GPP)against observations,we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP,reducing RMSEs by 24.3%and 20.5%,respectively.The multi-year averaged GPP decreased from 364.68 gC m^(-2)yr^(-1)to 241.21 gC m^(-2)yr^(-1)with the percentage bias dropping from 50.2%to-1.7%.When using the high spatial resolution CMFD,the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5%and 9.5%,respectively.This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.展开更多
This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vege...This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.展开更多
Vegetation plays a significant role in global terrestrial ecosystems and in combating desertification.We analyzed vegeta tion change in Inner Mongolia of northern China using the Normalized Difference Vegetation Index...Vegetation plays a significant role in global terrestrial ecosystems and in combating desertification.We analyzed vegeta tion change in Inner Mongolia of northern China using the Normalized Difference Vegetation Index(NDVI)from 1998 to 2013,which is an important composite of Chinese National Ecological Security Shelter.The correlation between vegeta tion growth and drought quantified using the Standardized Precipitation Evapotranspiration Index(SPEI)was also ex plored.Results show that vegetation in most of the study area has been rehabilitated to various degrees,especially in re gions such as most of the Horqin Sandy Land,eastern Ordos Plateau,Hetao Plain,as well as the middle-northern Da Hing gan Ling Mountains.Vegetation improvement in spring was significant in most of the study area.Vegetation degradation was centrally distributed in Xilingol grassland close to the Sino-Mongolia border and abandoned croplands in Ulanqab Meng.Vegetation change trends and seasonal differences varied among different vegetation types.The biggest vegetation variation in the growing season was the belt-like distribution along those grasslands close to the precipitation isoline of 200 mm and the Sino-Mongolia border,but also variation in summer and autumn exist in obvious spatial differences be tween grasslands and forests.Drought largely influenced vegetation change of Inner Mongolia at 6-month scale or 12-month scale,except for forests of eastern Hunlun Buir Meng and deserts or gobi deserts of western Alxa Meng.Moreover,drought in the previous winter and early spring seasons had a lag effect on growing-season vegetation.Desert grassland was the most easily affected by drought in the study area.Anthropogenic activities have made great progress in improving local vegetation under the lasting drought background.展开更多
[Objective] The aim was to study the dynamic variation of vegetation and its response to economic factors in the border area of Heilongjiang Province.[Method] Based on SPOT Vegetation NDVI data in each 10 days from 19...[Objective] The aim was to study the dynamic variation of vegetation and its response to economic factors in the border area of Heilongjiang Province.[Method] Based on SPOT Vegetation NDVI data in each 10 days from 1998 to 2007,the dynamic variation of vegetation in the border area of Heilongjiang Province in recent 10 years was studied,and the response of vegetation variation to economic factors was analyzed in the paper.[Result] On the whole,vegetation coverage was high in the border area of Heilongjiang Province from 1998 to 2007,and showed increasing trend.Except for parts of Huma County showing degrading trend,the whole vegetation condition in the border area of Heilongjiang Province was basically constant or improved,and the region with constant vegetation accounted for 71.00%,while the region with slight improved vegetation occupied 26.81%.Meanwhile,vegetation index and GDP increased on the whole from 1998 to 2007,but there was no complete consistency in their trends.In addition,MNDVI was significantly positively correlated with the average salary of local workers (P<0.01),but significantly negatively correlated with farmland area (P<0.01),and the negative correlation was delayed,that is to say,the decrease of farmland area in the first year would affect MNDVI in the second and third year.[Conclusion] The study could provide scientific references for the establishment of policies about economic development and ecological environment in Heilongjiang River basin.展开更多
基金Supported by the National Natural Science Foundation of China(No.40675071)~~
文摘In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.
基金the National Natural Science Foundation of China(Grant Nos.42130602,42175136)the Collaborative Innovation Center for Climate Change,Jiangsu Province,China.
文摘The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorological Forcing Data(PMFD)and the high spatial resolution and upscaled China Meteorological Forcing Data(CMFD)were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(SSiB4/TRIFFID)and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau(TP),a region with complex topography and sparse observations.By comparing the monthly Leaf Area Index(LAI)and Gross Primary Production(GPP)against observations,we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP,reducing RMSEs by 24.3%and 20.5%,respectively.The multi-year averaged GPP decreased from 364.68 gC m^(-2)yr^(-1)to 241.21 gC m^(-2)yr^(-1)with the percentage bias dropping from 50.2%to-1.7%.When using the high spatial resolution CMFD,the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5%and 9.5%,respectively.This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.
基金Under the auspices of National Natural Science Foundation of China(No.41001363)
文摘This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.
基金supported by the Project of National Key Research and Development Program of China (Grant number 2016YFC0500902)the National Natural Science Foundation of China (Grant number 40801003)the National Basic Research Program of China (Grant number 2009CB421308)
文摘Vegetation plays a significant role in global terrestrial ecosystems and in combating desertification.We analyzed vegeta tion change in Inner Mongolia of northern China using the Normalized Difference Vegetation Index(NDVI)from 1998 to 2013,which is an important composite of Chinese National Ecological Security Shelter.The correlation between vegeta tion growth and drought quantified using the Standardized Precipitation Evapotranspiration Index(SPEI)was also ex plored.Results show that vegetation in most of the study area has been rehabilitated to various degrees,especially in re gions such as most of the Horqin Sandy Land,eastern Ordos Plateau,Hetao Plain,as well as the middle-northern Da Hing gan Ling Mountains.Vegetation improvement in spring was significant in most of the study area.Vegetation degradation was centrally distributed in Xilingol grassland close to the Sino-Mongolia border and abandoned croplands in Ulanqab Meng.Vegetation change trends and seasonal differences varied among different vegetation types.The biggest vegetation variation in the growing season was the belt-like distribution along those grasslands close to the precipitation isoline of 200 mm and the Sino-Mongolia border,but also variation in summer and autumn exist in obvious spatial differences be tween grasslands and forests.Drought largely influenced vegetation change of Inner Mongolia at 6-month scale or 12-month scale,except for forests of eastern Hunlun Buir Meng and deserts or gobi deserts of western Alxa Meng.Moreover,drought in the previous winter and early spring seasons had a lag effect on growing-season vegetation.Desert grassland was the most easily affected by drought in the study area.Anthropogenic activities have made great progress in improving local vegetation under the lasting drought background.
基金Supported by Special Fund for Scientific Research Fee of Central Higher Education ( 507275871)
文摘[Objective] The aim was to study the dynamic variation of vegetation and its response to economic factors in the border area of Heilongjiang Province.[Method] Based on SPOT Vegetation NDVI data in each 10 days from 1998 to 2007,the dynamic variation of vegetation in the border area of Heilongjiang Province in recent 10 years was studied,and the response of vegetation variation to economic factors was analyzed in the paper.[Result] On the whole,vegetation coverage was high in the border area of Heilongjiang Province from 1998 to 2007,and showed increasing trend.Except for parts of Huma County showing degrading trend,the whole vegetation condition in the border area of Heilongjiang Province was basically constant or improved,and the region with constant vegetation accounted for 71.00%,while the region with slight improved vegetation occupied 26.81%.Meanwhile,vegetation index and GDP increased on the whole from 1998 to 2007,but there was no complete consistency in their trends.In addition,MNDVI was significantly positively correlated with the average salary of local workers (P<0.01),but significantly negatively correlated with farmland area (P<0.01),and the negative correlation was delayed,that is to say,the decrease of farmland area in the first year would affect MNDVI in the second and third year.[Conclusion] The study could provide scientific references for the establishment of policies about economic development and ecological environment in Heilongjiang River basin.
