Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics o...Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion.展开更多
Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotem...Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotemporal responses of broad-scale landscape connectivity to reforestation.By using a typical agro-pastoral ecotone in northern China as a case study,we addressed this issue based on an innovative integration of circuit theory approach and counterfactual analysis.The forest connectivity through multiple dispersal pathways was measured using the circuit theory approach,and its spatiotemporal changes after reforestation were evaluated by counterfactual analysis.The results showed that from 2000–2015,the reforested farmland occupied 2095 km^2,and 12.5% was on steeply sloped land.Farmland reforestation caused a greater increase in ecological connectivity by adding new ecological corridors and stepping stones in scattered forest areas rather than in areas with dense forest distributions.The newly added corridors and stepping stones were fragmented,short and narrow and thus deserve powerful protection.Future reforestation to improve landscape connectivity should highlight pinch point protection and obstacle removal as well as the tradeoff between farmland loss and farmer survival.Our findings are expected to inform the optimization of the Grain for Green policy from the perspective of broad-scale biodiversity conservation.展开更多
Forest resource management and ecological assessment have been recently supported by emerging technologies.Terrestrial laser scanning(TLS)is one that can be quickly and accurately used to obtain three-dimensional fore...Forest resource management and ecological assessment have been recently supported by emerging technologies.Terrestrial laser scanning(TLS)is one that can be quickly and accurately used to obtain three-dimensional forest information,and create good representations of forest vertical structure.TLS data can be exploited for highly significant tasks,particularly the segmentation and information extraction for individual trees.However,the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness,and hence do not lead to satisfactory results for natural forests in complex environments.In this paper,we propose a trunk-growth(TG)method for single-tree point-cloud segmentation,and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan,China.First,the point normal vector and its Z-axis component are used as trunk-growth constraints.Then,the points surrounding the trunk are searched to account for regrowth.Finally,the nearest distributed branch and leaf points are used to complete the individual tree segmentation.The results show that the TG method can effectively segment individual trees with an average F-score of 0.96.The proposed method applies to many types of trees with various growth shapes,and can effectively identify shrubs and herbs in complex scenes of natural forests.The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.展开更多
Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information belo...Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control points.The ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.展开更多
The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass...The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.展开更多
Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43,...Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.展开更多
Stable and continuous remote sensing land-cover mapping is important for agriculture,ecosystems,and land management.Convolutional neural networks(CNNs)are promising methods for achieving this goal.However,the large nu...Stable and continuous remote sensing land-cover mapping is important for agriculture,ecosystems,and land management.Convolutional neural networks(CNNs)are promising methods for achieving this goal.However,the large number of high-quality training samples required to train a CNN is difficult to acquire.In practice,imbalanced and noisy labels originating from existing land-cover maps can be used as alternatives.Experiments have shown that the inconsistency in the training samples has a significant impact on the performance of the CNN.To overcome this drawback,a method is proposed to inject highly consistent information into the network,to learn general and transferable features to alleviate the impact of imperfect training samples.Spectral indices are important features that can provide consistent information.These indices can be fused with CNN feature maps which utilize information entropy to choose the most appropriate CNN layer,to compensate for the inconsistency caused by the imbalanced,noisy labels.The proposed transferable CNN,tested with imbalanced and noisy labels for inter-regional Landsat time-series,not only is superior in terms of accuracy for land-cover mapping but also demonstrates excellent transferability between regions in both time series and cross-regional Landsat image classification.展开更多
Rapid estimates of impact areas following large earthquakes constitute the cornerstone of emergency response scenarios.However,collecting information through traditional practices usually requires a large amount of ma...Rapid estimates of impact areas following large earthquakes constitute the cornerstone of emergency response scenarios.However,collecting information through traditional practices usually requires a large amount of manpower and material resources,slowing the response time.Social media has emerged as a source of real-time‘citizen-sensor data’for disasters and can thus contribute to the rapid acquisition of disaster information.This paper proposes an approach to quickly estimate the impact area following a large earthquake via social media.Specifically,a spatial logistic growth model(SLGM)is proposed to describe the spatial growth of citizen-sensor data influenced by the earthquake impact strength after an earthquake;a framework is then developed to estimate the earthquake impact area by combining social media data and other auxiliary data based on the SLGM.The reliability of our approach is demonstrated in two earthquake cases by comparing the detected areas with official intensity maps,and the time sensitivity of the social media data in the SLGM is discussed.The results illustrate that our approach can effectively estimate the earthquake impact area.We verify the external validity of our model across other earthquake events and provide further insights into extracting more valuable earthquake information using social media.展开更多
As a material carrier contributing to human survival and social sustainable development,the ecological environment is declining in its integrity and overall health.With the rapid development of society and economy,it ...As a material carrier contributing to human survival and social sustainable development,the ecological environment is declining in its integrity and overall health.With the rapid development of society and economy,it is currently very necessary to carry out ecological security evaluation research to provide scientific guidance and suggestions for the construction of ecological civilization and the harmonious co-existence between man and nature.Taking Altay region as the research area,this paper collected and integrated regional geological,geographical,cultural,socio-economic,and statistical data,as well as previous research results.Combined with DPSIR and EES framework model,the evaluation index system of land resource ecological security in Altay region was constructed by using the analytic hierarchy process,entropy method and linear weighted summation function method.Using this index system,the evaluation research work was carried out to determine the current state of the security situation and the major threats which should be addressed.(1)The overall ecological security situation of Altay region was relatively safe,while the local ecological security situation was relatively fragile.Among them,the areas with safe and safer ecological environment accounted for 38.72%,while the areas with critically safe status accounted for 30.83%,and the areas with a less safe and unsafe environment accounted for 30.45%.In terms of spatial characteristics,the areas with unsafe ecological environment were mainly distributed in the west and east of the study area,while the areas with good ecological environment were distributed in the north of the study area.(2)Large-scale mining activities,frequent geological disasters,large-scale reclamation and long-term cultivation of arable land,and long-term large-scale grazing activities resulting in the destruction of grassland and vegetation were the main factors leading to the prominent ecological security problems of land resources in the Altay region.Therefore,in the process of the continuous development of the urban economy,we should pay more attention to the harmony between man and nature,and also actively and effectively advocate and implement certain policies and measures,such as returning farmland to forest,returning grazing land to grassland and integrating the mining of mineral resources.展开更多
基金National Natural Science Foundation of China,No.41571384Land Resources Survey and Evaluation Project of Ministry of Land and Resources of China,No.DCPJ161207-01+2 种基金Fund for Fostering Talents in Basic Science of National Natural Science Foundation of China,No.J1103409Key Program of National Natural Science Foundation of China,No.71433008Programme of Excellent Young Scientists of the Institute of Geographic Sciences and Natural Resources Research,CAS。
文摘Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion.
基金National Natural Science Foundation of China,No.41771429National Key Research and Development Project,No.2017YFB0503505。
文摘Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotemporal responses of broad-scale landscape connectivity to reforestation.By using a typical agro-pastoral ecotone in northern China as a case study,we addressed this issue based on an innovative integration of circuit theory approach and counterfactual analysis.The forest connectivity through multiple dispersal pathways was measured using the circuit theory approach,and its spatiotemporal changes after reforestation were evaluated by counterfactual analysis.The results showed that from 2000–2015,the reforested farmland occupied 2095 km^2,and 12.5% was on steeply sloped land.Farmland reforestation caused a greater increase in ecological connectivity by adding new ecological corridors and stepping stones in scattered forest areas rather than in areas with dense forest distributions.The newly added corridors and stepping stones were fragmented,short and narrow and thus deserve powerful protection.Future reforestation to improve landscape connectivity should highlight pinch point protection and obstacle removal as well as the tradeoff between farmland loss and farmer survival.Our findings are expected to inform the optimization of the Grain for Green policy from the perspective of broad-scale biodiversity conservation.
基金The work was supported by the National Natural Science Foundation of China(Grant Number 41961060)the Key Program of Basic Research of Yunnan Province,China(Grant Number 2019FA017)+1 种基金the Multi-government International Science and Technology Innovation Cooperation Key Project of National Key Research and Development Program of China(Grant Number 2018YFE0184300)the Program for Innovative Research Team in Science and Technology research and innovation fund(ysdyjs 2020058)in the University of Yunnan Province.
文摘Forest resource management and ecological assessment have been recently supported by emerging technologies.Terrestrial laser scanning(TLS)is one that can be quickly and accurately used to obtain three-dimensional forest information,and create good representations of forest vertical structure.TLS data can be exploited for highly significant tasks,particularly the segmentation and information extraction for individual trees.However,the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness,and hence do not lead to satisfactory results for natural forests in complex environments.In this paper,we propose a trunk-growth(TG)method for single-tree point-cloud segmentation,and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan,China.First,the point normal vector and its Z-axis component are used as trunk-growth constraints.Then,the points surrounding the trunk are searched to account for regrowth.Finally,the nearest distributed branch and leaf points are used to complete the individual tree segmentation.The results show that the TG method can effectively segment individual trees with an average F-score of 0.96.The proposed method applies to many types of trees with various growth shapes,and can effectively identify shrubs and herbs in complex scenes of natural forests.The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.
基金supported by the National Natural Science Foundation of China,Grant Number 41961060by the Program for Innovative Research Team (in Science and Technology) in the University of Yunnan Province,Grant Number IRTSTYN+1 种基金by the Scientific Research Fund Project of the Education Department of Yunnan Province,Grant Numbers 2020J0256 and 2021J0438by the Postgraduate Scientific Research and Innovation Fund Project of Yunnan Normal University,Grant Number YJSJJ21-A08
文摘Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control points.The ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.
基金supported by the National Natural Science Foundation of China(42101382 and 42201407)the Shandong Provincial Natural Science Foundation China(ZR2020QD016 and ZR2022QD120)。
文摘The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.
基金This research was funded by the Multigovernment International Science and Technology Innovation Cooperation Key Project of the National Key Research and Development Program of China(Grant No.2018YFE0184300)Erasmus+Capacity Building in Higher Education of the Education,Audiovisual and Culture Executive Agency(EACEA)(Grant No.586037-EPP-1-2017-1-HU-EPPKA2CBHE-JP)+3 种基金the National Natural Science Foundation of China(Grant No.41561048)the Technical Methods and Empirical Study on Ecological Assets Measurement in County Level of Yunnan Province(Grant No.ZDZZD201506)the Young and Middleaged Academic and Technical Leaders Reserve Talents Training Program of Yunnan Province(Grant No.2008PY056)the Program for Innovative Research Team(in Science and Technology)at the University of Yunnan Province,IRTSTYN。
文摘Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.
基金supported by National Natural Science Foundation of China[41801233,41761087]Ningbo Science and Technology Innovation Project[2020Z019]Natural Science Foundation of Guangxi Province[2020GXNSFBA159012].
文摘Stable and continuous remote sensing land-cover mapping is important for agriculture,ecosystems,and land management.Convolutional neural networks(CNNs)are promising methods for achieving this goal.However,the large number of high-quality training samples required to train a CNN is difficult to acquire.In practice,imbalanced and noisy labels originating from existing land-cover maps can be used as alternatives.Experiments have shown that the inconsistency in the training samples has a significant impact on the performance of the CNN.To overcome this drawback,a method is proposed to inject highly consistent information into the network,to learn general and transferable features to alleviate the impact of imperfect training samples.Spectral indices are important features that can provide consistent information.These indices can be fused with CNN feature maps which utilize information entropy to choose the most appropriate CNN layer,to compensate for the inconsistency caused by the imbalanced,noisy labels.The proposed transferable CNN,tested with imbalanced and noisy labels for inter-regional Landsat time-series,not only is superior in terms of accuracy for land-cover mapping but also demonstrates excellent transferability between regions in both time series and cross-regional Landsat image classification.
基金supported by National Natural Science Foundation of China[grant number 41271399].
文摘Rapid estimates of impact areas following large earthquakes constitute the cornerstone of emergency response scenarios.However,collecting information through traditional practices usually requires a large amount of manpower and material resources,slowing the response time.Social media has emerged as a source of real-time‘citizen-sensor data’for disasters and can thus contribute to the rapid acquisition of disaster information.This paper proposes an approach to quickly estimate the impact area following a large earthquake via social media.Specifically,a spatial logistic growth model(SLGM)is proposed to describe the spatial growth of citizen-sensor data influenced by the earthquake impact strength after an earthquake;a framework is then developed to estimate the earthquake impact area by combining social media data and other auxiliary data based on the SLGM.The reliability of our approach is demonstrated in two earthquake cases by comparing the detected areas with official intensity maps,and the time sensitivity of the social media data in the SLGM is discussed.The results illustrate that our approach can effectively estimate the earthquake impact area.We verify the external validity of our model across other earthquake events and provide further insights into extracting more valuable earthquake information using social media.
基金The Key Program of Basic Research of Yunnan Province,China(2019FA017)The Multi-Government International Science and Technology Innovation Cooperation Key Project of National Key Research and Development Program of China(2018YFE0184300)The Postgraduate Scientific Research Fund Project of Yunnan Provincial Department of Education(2021Y501)。
文摘As a material carrier contributing to human survival and social sustainable development,the ecological environment is declining in its integrity and overall health.With the rapid development of society and economy,it is currently very necessary to carry out ecological security evaluation research to provide scientific guidance and suggestions for the construction of ecological civilization and the harmonious co-existence between man and nature.Taking Altay region as the research area,this paper collected and integrated regional geological,geographical,cultural,socio-economic,and statistical data,as well as previous research results.Combined with DPSIR and EES framework model,the evaluation index system of land resource ecological security in Altay region was constructed by using the analytic hierarchy process,entropy method and linear weighted summation function method.Using this index system,the evaluation research work was carried out to determine the current state of the security situation and the major threats which should be addressed.(1)The overall ecological security situation of Altay region was relatively safe,while the local ecological security situation was relatively fragile.Among them,the areas with safe and safer ecological environment accounted for 38.72%,while the areas with critically safe status accounted for 30.83%,and the areas with a less safe and unsafe environment accounted for 30.45%.In terms of spatial characteristics,the areas with unsafe ecological environment were mainly distributed in the west and east of the study area,while the areas with good ecological environment were distributed in the north of the study area.(2)Large-scale mining activities,frequent geological disasters,large-scale reclamation and long-term cultivation of arable land,and long-term large-scale grazing activities resulting in the destruction of grassland and vegetation were the main factors leading to the prominent ecological security problems of land resources in the Altay region.Therefore,in the process of the continuous development of the urban economy,we should pay more attention to the harmony between man and nature,and also actively and effectively advocate and implement certain policies and measures,such as returning farmland to forest,returning grazing land to grassland and integrating the mining of mineral resources.
