Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number （CN） is a key factor in determining runoff in the SCS （Soil Conservation Serv...Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number （CN） is a key factor in determining runoff in the SCS （Soil Conservation Service） based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems （G/S） are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.展开更多
The negative effects of traditional methods of electricity generation on the<span style="font-family:;" "=""><span style="font-family:Verdana;"> environment have created ...The negative effects of traditional methods of electricity generation on the<span style="font-family:;" "=""><span style="font-family:Verdana;"> environment have created the need for strategic planning and development of renewable and sustainable energy systems. This paper presents the analysis of the suitability of wind farm sites using a Boolean decision-making approach </span><span style="font-family:Verdana;">based on geographic information system (GIS) modeling. This analysis is </span><span style="font-family:Verdana;">based on different climatic, geographical, economic and environmental criteria such </span><span style="font-family:Verdana;">as wind resource, slope, accessibility by road, proximity to the electricity</span><span style="font-family:Verdana;"> network and optimal distance from airports. The results of the study show that the most favorable sites are mainly located in the northern part of the country, particularly in the Far North and North regions. There are also favorable </span><span style="font-family:Verdana;">sites in the North-West, South-West, West, Littoral and very little in the</span><span style="font-family:Verdana;"> South while the central and eastern regions are not suitable. This is mainly due to the tropical forest that covers the entire region of East Cameroon and the low wind speed in these regions which is the determining factor for the installation of wind farms. The appropriate land for the installation of wind </span><span style="font-family:Verdana;">farms is </span><span style="font-family:Verdana;">approximately 2.56% corresponding to an area of </span></span><span style="font-family:Verdana;">11</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">602</span><span style="font-family:Verdana;">.494414</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">km<span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span><span style="font-family:Verdana;">. Ho</span><span style="font-family:Verdana;">w</span><span style="font-family:Verdana;">ever, when we include the condition that a wind farm must have at least 4</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">km<sup></sup></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;"> of surface area, is goes from 2.56% to 2.22% (11</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">602.494414 km<sup></sup></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;"> to</span><span style="font-family:Verdana;"> 10</span><span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;">344.424539 km</span><span style="font-family:Verdana;"><sup></sup></span></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;">);thus a surface reduction of approximately 1258</span><span style="font-family:Verdana;">.</span><span style="font-family:;" "=""><span style="font-family:Verdana;">069875 km</span><span style="font-family:Verdana;"><sup></sup></span></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;">. We can conclude that despite the fact that Cameroon does not have a huge potential for wind energy because of the low wind speed observed in the country, it is still possible to have some favorable sites for the installation of the parks wind. In addition, a study of hybrid solar-wind systems could improve the efficiency of the power plants in Cameroon.</span>展开更多
In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance ...In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.展开更多
专题地图是一种重要的空间数据展示形式,广泛用于地理、环境和城市规划等领域。为实现专题制作的准确性和可行性目标,本文基于专题地图制作中地理信息系统(Geographic Information System,GIS)的基本原理介绍,详细论述了基于GIS的专题...专题地图是一种重要的空间数据展示形式,广泛用于地理、环境和城市规划等领域。为实现专题制作的准确性和可行性目标,本文基于专题地图制作中地理信息系统(Geographic Information System,GIS)的基本原理介绍,详细论述了基于GIS的专题地图设计原则和制作流程,并结合具体案例,论述了应用GIS进行专题地图制作实践。结果表明,该技术在专题地图制作中的科学应用,不仅使地图信息丰富且用户友好,还易于公众和规划者理解。展开更多
This study treats the determination of routes for evacuation on foot in earthquake disasters as a multi-objective optimization problem, and aims to propose a method for quantitatively searching for evacuation routes u...This study treats the determination of routes for evacuation on foot in earthquake disasters as a multi-objective optimization problem, and aims to propose a method for quantitatively searching for evacuation routes using a multi-objective genetic algorithm (multi-objective GA) and GIS. The conclusions can be summarized in the following three points. 1) A GA was used to design and create an evacuation route search algorithm which solves the problem of the optimization of earthquake disaster evacuation routes by treating it as an optimization problem with multiple objectives, such as evacuation distance and evacuation time. 2) In this method, goodness of fit is set by using a Pareto ranking method to determine the ranking of individuals based on their relative superiorities and inferiorities. 3) In this method, searching for evacuation routes based on the information on present conditions allows evacuation routes to be derived based on present building and road locations.?Further, this method is based on publicly available information;therefore, obtaining geographic information similar to that of this study enables this method to be effective regardless of what region it is applied to, or whether the data regards the past or the future. Therefore, this method has high degree of spatial and temporal reproducibility.展开更多
基金supported by the GLOWA-JR Project of the German Federal Ministry of Education and Research (BMBF)
文摘Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number （CN） is a key factor in determining runoff in the SCS （Soil Conservation Service） based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems （G/S） are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.
文摘The negative effects of traditional methods of electricity generation on the<span style="font-family:;" "=""><span style="font-family:Verdana;"> environment have created the need for strategic planning and development of renewable and sustainable energy systems. This paper presents the analysis of the suitability of wind farm sites using a Boolean decision-making approach </span><span style="font-family:Verdana;">based on geographic information system (GIS) modeling. This analysis is </span><span style="font-family:Verdana;">based on different climatic, geographical, economic and environmental criteria such </span><span style="font-family:Verdana;">as wind resource, slope, accessibility by road, proximity to the electricity</span><span style="font-family:Verdana;"> network and optimal distance from airports. The results of the study show that the most favorable sites are mainly located in the northern part of the country, particularly in the Far North and North regions. There are also favorable </span><span style="font-family:Verdana;">sites in the North-West, South-West, West, Littoral and very little in the</span><span style="font-family:Verdana;"> South while the central and eastern regions are not suitable. This is mainly due to the tropical forest that covers the entire region of East Cameroon and the low wind speed in these regions which is the determining factor for the installation of wind farms. The appropriate land for the installation of wind </span><span style="font-family:Verdana;">farms is </span><span style="font-family:Verdana;">approximately 2.56% corresponding to an area of </span></span><span style="font-family:Verdana;">11</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">602</span><span style="font-family:Verdana;">.494414</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">km<span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span><span style="font-family:Verdana;">. Ho</span><span style="font-family:Verdana;">w</span><span style="font-family:Verdana;">ever, when we include the condition that a wind farm must have at least 4</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">km<sup></sup></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;"> of surface area, is goes from 2.56% to 2.22% (11</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;">602.494414 km<sup></sup></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;"> to</span><span style="font-family:Verdana;"> 10</span><span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;">344.424539 km</span><span style="font-family:Verdana;"><sup></sup></span></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;">);thus a surface reduction of approximately 1258</span><span style="font-family:Verdana;">.</span><span style="font-family:;" "=""><span style="font-family:Verdana;">069875 km</span><span style="font-family:Verdana;"><sup></sup></span></span><span style="font-family:Verdana;"><span style="white-space:normal;font-family:Verdana;"><span style="white-space:nowrap;"><sup></sup></span><sup></sup></span><span style="white-space:normal;font-family:Verdana;"><sup>2</sup><span style="white-space:nowrap;"></span></span></span><span style="font-family:Verdana;">. We can conclude that despite the fact that Cameroon does not have a huge potential for wind energy because of the low wind speed observed in the country, it is still possible to have some favorable sites for the installation of the parks wind. In addition, a study of hybrid solar-wind systems could improve the efficiency of the power plants in Cameroon.</span>
文摘In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.
文摘专题地图是一种重要的空间数据展示形式,广泛用于地理、环境和城市规划等领域。为实现专题制作的准确性和可行性目标,本文基于专题地图制作中地理信息系统(Geographic Information System,GIS)的基本原理介绍,详细论述了基于GIS的专题地图设计原则和制作流程,并结合具体案例,论述了应用GIS进行专题地图制作实践。结果表明,该技术在专题地图制作中的科学应用,不仅使地图信息丰富且用户友好,还易于公众和规划者理解。
文摘This study treats the determination of routes for evacuation on foot in earthquake disasters as a multi-objective optimization problem, and aims to propose a method for quantitatively searching for evacuation routes using a multi-objective genetic algorithm (multi-objective GA) and GIS. The conclusions can be summarized in the following three points. 1) A GA was used to design and create an evacuation route search algorithm which solves the problem of the optimization of earthquake disaster evacuation routes by treating it as an optimization problem with multiple objectives, such as evacuation distance and evacuation time. 2) In this method, goodness of fit is set by using a Pareto ranking method to determine the ranking of individuals based on their relative superiorities and inferiorities. 3) In this method, searching for evacuation routes based on the information on present conditions allows evacuation routes to be derived based on present building and road locations.?Further, this method is based on publicly available information;therefore, obtaining geographic information similar to that of this study enables this method to be effective regardless of what region it is applied to, or whether the data regards the past or the future. Therefore, this method has high degree of spatial and temporal reproducibility.
