Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significan...Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significance of this knowledge, a comprehensive quantification of the influence of regional topographical and geological factors on the spatial heterogeneity of debris-flow-prone areas has been lacking. This study selected the Hengduan Mountains, an earthquake-prone region characterized by diverse surface conditions and complex landforms, as a representative study area. An improved units zoning and objective factors identification methodology was employed in earthquake and fault analysis to assess the impact of seismic activity and geological factors on spatial heterogeneity of debrisflow prone areas. Results showed that the application of GIS technology with hydrodynamic intensity and geographical units analysis can effectively analyze debris-flow prone areas. Meanwhile, earthquake and fault zones obviously increase the density of debrisflow prone catchments and make them unevenly distributed. The number of debris-flow prone areas shows a nonlinear variation with the gradual increase of geomorphic factor value. Specifically, the area with 1000 m-2500 m elevation difference, 25°-30° average slope, and 0.13-0.15 land use index is the most favorable conditions for debris-flow occurrence;The average annual rainfall from 600 to 1150 mm and landslides gradient from 16° to 35° are the main causal factors to trigger debris flow. Our study sheds light on the quantification of spatial heterogeneity in debris flow-prone areas in earthquake-prone regions, which can offer crucial support for post-debris flow risk management strategies.展开更多
The purpose of this study was to estimate the spatial and temporal variation of microalgae in the South China Sea and to demonstrate the environmental factors controlling the diversity of microalgae by GIS (geographic...The purpose of this study was to estimate the spatial and temporal variation of microalgae in the South China Sea and to demonstrate the environmental factors controlling the diversity of microalgae by GIS (geographic information system)-based analysis of 18S rDNA sequences. Six 18S rDNA libraries were constructed from environmental samples collected at different sites in the study area, and more than 600 18S rDNA sequences were determined. The rDNA sequence data were then analyzed by DIVA-GIS software to display the spatial and temporal variation of phytoplankton’s composition. It was shown that the autotrophic eukaryotic plankton dominated over the heterotrophic cells in most of our clone libraries, and the dominating phytoplankton was Dinophyceae except for Bacillariophyta at the Xiamen harbor. The percentages of these two groups were controlled by water temperature and salinity. Our results also revealed that the species composition of Chlorophyta showed a close relationship with latitude, changing from Prasinophyceae at the high latitude to Trebouxiophyceae at the low latitude. Several newly classified picoplankton lineages were first uncovered in the South China Sea, including the pico-sized green alga Ostreococcus sp. and Picochlorum eukaryotum, and picobiliphytes, which was just discovered in 2007 with unknown affinities to other eukaryotes. Their spatial and temporal variation were also analyzed and discussed.展开更多
Studies on the characteristics of urban villages have attracted much interest in urban geography.However,how to advance the development of further theoretical analysis and quantitative methodologies,especially in the ...Studies on the characteristics of urban villages have attracted much interest in urban geography.However,how to advance the development of further theoretical analysis and quantitative methodologies,especially in the era that GIS and digital-urban technologies develop rapidly and provide precious resources on spatial issues,has always been a heated debate and difficulty.In this paper,a mathematical model based on spatial analysis is introduced to deal with the categorization and characterization of urban villages.A total of 89 urban villages in the Shenzhen Special Economic Zone(SEZ)are used in this case study.Using ArcGIS tools on buffer analysis,distance and density calculation,and socio-economic and spatial attributes conjunction,urban villages’31 spatial variables in 4 aspects—social,economic,locational,and physical—are extracted,and 6 principal factors are concluded by principal components analysis to indicate the spatial characteristic of urban villages.Based on the 6 principal factors,6 types of urban villages,including rapidly sprawling,large,rapidly industrializing periphery,overcrowded,intensively mobile and economically backward,are divided through the Hierarchical Clustering method.Moreover,the spatial features and formation mechanisms of each type of urban villages are provided.Finally,the advantages and the shortcomings of the methodology for this specific application are also given.Furthermore,several guidelines on urban village management and renewal are provided based on the result of type classification.The outcome of the paper depends on the informational and technological support from the development of digital-city management,and is able to in turn provide basis on monitoring and improving urban villages which can further digital urban framework.展开更多
Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale at- mospheric Weather Research and Forecasting...Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale at- mospheric Weather Research and Forecasting （WRF） model combining them with ground-based and satellite observations for modeling snow accumulation and snowmelt processes in the Votkinsk reservoir basin （184,319 km2）. The method is tested during three winter seasons （2012-2015）. The MODIS-based vegetation map and leaf area index data are used to calculate the snowmelt intensity and snow evaporation in the studied basin. The GIS-based snow accumulation and snowmelt modeling provides a reliable and highly detailed spatial distribution for snow water equivalent （SWE） and snow-covered areas （SCA）. The modelling results are validated by comparing actual and estimated SWE and SCA data. The actual SCA results are derived from MODIS satellite data. The algorithm for assessing the SCA by MODIS data （ATBD-MOD 10） has been adapted to a forest zone. In general, the proposed method provides satisfactory results for maximum SWE calculations. The calculation accuracy is slightly degraded during snowmelt periods. The SCA data is simulated with a higher reliability than the SWE data. The differences between the simulated and actual SWE may be explained by the overestimation of the WRF-simulated total precipitation and the unrepresentativeness of the SWE measurements （snow survey）.展开更多
Finland’s national aim for annual consumption of forest chips is 25 terawatt hours (TWh) (equivalent to 13.5 million solid cubic metres) in combined heat and power (CHP) production and heat production in 2020. On ave...Finland’s national aim for annual consumption of forest chips is 25 terawatt hours (TWh) (equivalent to 13.5 million solid cubic metres) in combined heat and power (CHP) production and heat production in 2020. On average, the techno-economic potential of forest chips enables reaching the target at the national level. However, there is a geographical mismatch between the supply and demand regions. In this study, the regional balance of potential and demand from 2012 until 2020 was assessed using GIS-based methods. Economical, technical and ecological constraints were taken into account when different scenarios for municipality-level potentials were calculated. The forest chips’ consumption scenarios for plant-level were determined statistically (2012) or predicted (2020) by assuming that the total consumption of forest chips will reach the 13.5 Mm<sup>3</sup>. With help of procurement model, the use of different forest energy fuel types (stumps, logging residues and small-sized thinning wood) was spread to the procurement ring with the help of GIS coding. The forest chips’ regional balance map was made by subtracting the use of heat and combined heat and power plants’ (CHP) forest chips’ consumption from the municipality level potential data. The GIS-based method for balance calculation requires a significant amount of computer power but works well for local, municipality, regional and national-level balance calculations. The study showed that there are enough forest chips to supply the current and future demand when all forest energy assortments are used efficiently and in a sustainable manner. However, the results indicate that already at the present rate of forest chip consumption, in some areas there will not be any extra potential left. When consumption increases, the zero-potential area, in particular on the coast, expands. The highest free potential can be found in eastern and northern areas of Finland while the western and southern areas lack free potential.展开更多
The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper...The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.展开更多
Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact ...Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact of land cover(especially forest cover),environment and human usage on runoff,chemical water quality and macroinvertebrate fauna in a river basin under discontinuous permafrost conditions in an arid,sparsely populated region of Mongolia.To verify our hypotheses that different landuses and environmental impacts in permafrost headwaters influence water quality,we investigated 105 sampling sites,37 of them at intermittent stream sections without water flow.Discharge was positively impacted by land cover types steppe,grassland and forest and negatively by shrubland,forest burnt by wild fires(indicating a reduction of permafrost)and slope.Water quality was affected by altitude,longitude and latitude,shrub growth and water temperature.Shannon diversity of macroinvertebrates was driven by water temperature,iron content of the water,flow velocity,and subbasin size(adjusted R^(2)=0.54).Sample plots clustered in three groups that differed in water chemistry,macroinvertebrate diversity,species composition and bio-indicators.Our study confirms that steppes and grasslands have a higher contribution to runoff than forests,forest cover has a positive impact on water quality,and diversity of macroinvertebrates is higher in sites with less nutrients and pollutants.The excellent ecological status of the upper reaches of the Kharaa is severely threatened by forest fires and human-induced climate change and urgently needs to be conserved.展开更多
基金supported by the Hubei Provincial Engineering Research Center of Slope Habitat Construction Technique Using Cement-based Materials Open Research Program (Grant No. 2022SNJ112022SNJ12)+4 种基金National Natural Science Foundation of China (Grant No. 42371014)Hubei Key Laboratory of Disaster Prevention and Mitigation (China Three Gorges University) Open Research Program (Grant No. 2022KJZ122023KJZ19)CRSRI Open Research Program (Grant No. CKWV2021888/KY)the Key Laboratory of Mountain Hazards and Earth Surface Processes, Chinese Academy of Sciences (Grant No. KLMHESP20-0)。
文摘Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significance of this knowledge, a comprehensive quantification of the influence of regional topographical and geological factors on the spatial heterogeneity of debris-flow-prone areas has been lacking. This study selected the Hengduan Mountains, an earthquake-prone region characterized by diverse surface conditions and complex landforms, as a representative study area. An improved units zoning and objective factors identification methodology was employed in earthquake and fault analysis to assess the impact of seismic activity and geological factors on spatial heterogeneity of debrisflow prone areas. Results showed that the application of GIS technology with hydrodynamic intensity and geographical units analysis can effectively analyze debris-flow prone areas. Meanwhile, earthquake and fault zones obviously increase the density of debrisflow prone catchments and make them unevenly distributed. The number of debris-flow prone areas shows a nonlinear variation with the gradual increase of geomorphic factor value. Specifically, the area with 1000 m-2500 m elevation difference, 25°-30° average slope, and 0.13-0.15 land use index is the most favorable conditions for debris-flow occurrence;The average annual rainfall from 600 to 1150 mm and landslides gradient from 16° to 35° are the main causal factors to trigger debris flow. Our study sheds light on the quantification of spatial heterogeneity in debris flow-prone areas in earthquake-prone regions, which can offer crucial support for post-debris flow risk management strategies.
基金Supported by the National Natural Science Foundation of China (Grant No. U0631001)Funds from the Ministry of Education of China (Grant No. NCET-04-0788)the Reserve Key Projects of Sun Yat-Sen University (IRT0447)
文摘The purpose of this study was to estimate the spatial and temporal variation of microalgae in the South China Sea and to demonstrate the environmental factors controlling the diversity of microalgae by GIS (geographic information system)-based analysis of 18S rDNA sequences. Six 18S rDNA libraries were constructed from environmental samples collected at different sites in the study area, and more than 600 18S rDNA sequences were determined. The rDNA sequence data were then analyzed by DIVA-GIS software to display the spatial and temporal variation of phytoplankton’s composition. It was shown that the autotrophic eukaryotic plankton dominated over the heterotrophic cells in most of our clone libraries, and the dominating phytoplankton was Dinophyceae except for Bacillariophyta at the Xiamen harbor. The percentages of these two groups were controlled by water temperature and salinity. Our results also revealed that the species composition of Chlorophyta showed a close relationship with latitude, changing from Prasinophyceae at the high latitude to Trebouxiophyceae at the low latitude. Several newly classified picoplankton lineages were first uncovered in the South China Sea, including the pico-sized green alga Ostreococcus sp. and Picochlorum eukaryotum, and picobiliphytes, which was just discovered in 2007 with unknown affinities to other eukaryotes. Their spatial and temporal variation were also analyzed and discussed.
基金supported by the National Natural Science Foundation of China(Grant Nos.40901080,40830747)the Post-doctor ResearchFoundation of China(Grant No.20080440237)
文摘Studies on the characteristics of urban villages have attracted much interest in urban geography.However,how to advance the development of further theoretical analysis and quantitative methodologies,especially in the era that GIS and digital-urban technologies develop rapidly and provide precious resources on spatial issues,has always been a heated debate and difficulty.In this paper,a mathematical model based on spatial analysis is introduced to deal with the categorization and characterization of urban villages.A total of 89 urban villages in the Shenzhen Special Economic Zone(SEZ)are used in this case study.Using ArcGIS tools on buffer analysis,distance and density calculation,and socio-economic and spatial attributes conjunction,urban villages’31 spatial variables in 4 aspects—social,economic,locational,and physical—are extracted,and 6 principal factors are concluded by principal components analysis to indicate the spatial characteristic of urban villages.Based on the 6 principal factors,6 types of urban villages,including rapidly sprawling,large,rapidly industrializing periphery,overcrowded,intensively mobile and economically backward,are divided through the Hierarchical Clustering method.Moreover,the spatial features and formation mechanisms of each type of urban villages are provided.Finally,the advantages and the shortcomings of the methodology for this specific application are also given.Furthermore,several guidelines on urban village management and renewal are provided based on the result of type classification.The outcome of the paper depends on the informational and technological support from the development of digital-city management,and is able to in turn provide basis on monitoring and improving urban villages which can further digital urban framework.
文摘Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale at- mospheric Weather Research and Forecasting （WRF） model combining them with ground-based and satellite observations for modeling snow accumulation and snowmelt processes in the Votkinsk reservoir basin （184,319 km2）. The method is tested during three winter seasons （2012-2015）. The MODIS-based vegetation map and leaf area index data are used to calculate the snowmelt intensity and snow evaporation in the studied basin. The GIS-based snow accumulation and snowmelt modeling provides a reliable and highly detailed spatial distribution for snow water equivalent （SWE） and snow-covered areas （SCA）. The modelling results are validated by comparing actual and estimated SWE and SCA data. The actual SCA results are derived from MODIS satellite data. The algorithm for assessing the SCA by MODIS data （ATBD-MOD 10） has been adapted to a forest zone. In general, the proposed method provides satisfactory results for maximum SWE calculations. The calculation accuracy is slightly degraded during snowmelt periods. The SCA data is simulated with a higher reliability than the SWE data. The differences between the simulated and actual SWE may be explained by the overestimation of the WRF-simulated total precipitation and the unrepresentativeness of the SWE measurements （snow survey）.
文摘Finland’s national aim for annual consumption of forest chips is 25 terawatt hours (TWh) (equivalent to 13.5 million solid cubic metres) in combined heat and power (CHP) production and heat production in 2020. On average, the techno-economic potential of forest chips enables reaching the target at the national level. However, there is a geographical mismatch between the supply and demand regions. In this study, the regional balance of potential and demand from 2012 until 2020 was assessed using GIS-based methods. Economical, technical and ecological constraints were taken into account when different scenarios for municipality-level potentials were calculated. The forest chips’ consumption scenarios for plant-level were determined statistically (2012) or predicted (2020) by assuming that the total consumption of forest chips will reach the 13.5 Mm<sup>3</sup>. With help of procurement model, the use of different forest energy fuel types (stumps, logging residues and small-sized thinning wood) was spread to the procurement ring with the help of GIS coding. The forest chips’ regional balance map was made by subtracting the use of heat and combined heat and power plants’ (CHP) forest chips’ consumption from the municipality level potential data. The GIS-based method for balance calculation requires a significant amount of computer power but works well for local, municipality, regional and national-level balance calculations. The study showed that there are enough forest chips to supply the current and future demand when all forest energy assortments are used efficiently and in a sustainable manner. However, the results indicate that already at the present rate of forest chip consumption, in some areas there will not be any extra potential left. When consumption increases, the zero-potential area, in particular on the coast, expands. The highest free potential can be found in eastern and northern areas of Finland while the western and southern areas lack free potential.
文摘The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.
基金This research was financially supported by the German Federal Ministry for Economic Cooperation and Development(grant number:BMZ 81212690)and a‘Forschung vor Ort’grant for G.K.of the Max Weber-Program of the State of Bavaria.Special thanks are due to the Deutsche Gesellschaft für Internationale Zusammenarbeit(GIZ)GmbH,especially Klaus Schmidt-Corsitto,at that time Programme Director for“Biodiversity and Adaptation of Key Forest Ecosystems to Climate Change II Program”of GIZ and many employees of GIZ Mongolia.
文摘Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact of land cover(especially forest cover),environment and human usage on runoff,chemical water quality and macroinvertebrate fauna in a river basin under discontinuous permafrost conditions in an arid,sparsely populated region of Mongolia.To verify our hypotheses that different landuses and environmental impacts in permafrost headwaters influence water quality,we investigated 105 sampling sites,37 of them at intermittent stream sections without water flow.Discharge was positively impacted by land cover types steppe,grassland and forest and negatively by shrubland,forest burnt by wild fires(indicating a reduction of permafrost)and slope.Water quality was affected by altitude,longitude and latitude,shrub growth and water temperature.Shannon diversity of macroinvertebrates was driven by water temperature,iron content of the water,flow velocity,and subbasin size(adjusted R^(2)=0.54).Sample plots clustered in three groups that differed in water chemistry,macroinvertebrate diversity,species composition and bio-indicators.Our study confirms that steppes and grasslands have a higher contribution to runoff than forests,forest cover has a positive impact on water quality,and diversity of macroinvertebrates is higher in sites with less nutrients and pollutants.The excellent ecological status of the upper reaches of the Kharaa is severely threatened by forest fires and human-induced climate change and urgently needs to be conserved.
