无人机编队指多无人机协作执行任务的过程中,无人机群保持几何形状排列,如V字形、环形等。采用马尔科夫链节点状态模型,对基于载波侦听多路访问/冲突避免(Carrier Sense Multiple Access with Collision Avoid,CSMA/CA)协议的多接口无...无人机编队指多无人机协作执行任务的过程中,无人机群保持几何形状排列,如V字形、环形等。采用马尔科夫链节点状态模型,对基于载波侦听多路访问/冲突避免(Carrier Sense Multiple Access with Collision Avoid,CSMA/CA)协议的多接口无人机环形编队自组网容量进行分析,推导出节点包碰撞概率、发包概率和网络吞吐量参数的关系模型,提出了网络容量分析方法。通过仿真验证了网络容量分析方法的合理性,并给出了吞吐量随网络节点数、接口数变化的性能结果以及包碰撞概率、发包概率随接口数、竞争节点数变化的理论特性。展开更多
Increased anthropogenic activities in the Little Ruaha River Catchment have modulated the catchment condition, nevertheless, the future changes as a result of increased anthropogenic activities are unknown. Understand...Increased anthropogenic activities in the Little Ruaha River Catchment have modulated the catchment condition, nevertheless, the future changes as a result of increased anthropogenic activities are unknown. Understanding the future changes is vitally important for the design of appropriate strategies towards sustainable management of the catchment resources. This study applied Remote Sensing and GIS techniques (Jensen & Lulla, 1987) to assess the historical long-term changes in land use and land cover using Landsat satellite images of 1990, 2005 and 2015, and modelled the future change in land use and land cover up to 2040 using the stochastic CA-Markov chain (Almeida et al., 2005). The historical land use and land cover change detection results indicate that between 1990 and 2005 the area under forest changed from 39,872 ha to 22,957 ha, woodland changed from 109,692 ha to 72,809 ha, wetland decreased from 19,157 ha to 11,785 ha, the cultivated land increased from 106,782 ha to 109,047 ha, likewise, the built-up area increased from 9408 ha to 11,674 ha. Results between 2005 and 2015 show the substantial changes where the forest decline from 22,957 ha to 15,950 ha, woodland decreased from 72,809 ha to 58,554 ha and the wetland changed from 11,785 ha to 5622 ha. Cultivated land and built up area increased from 109,047 ha and 11,674 ha to 143,468 ha and 13,765 ha respectively. Generally, the study has revealed the substantial decline in forest, woodland and wetland by 23,922 ha, 51,138 ha and 13,535 ha respectively, and an increase of cultivated land and built up area by 36,668 ha and 4357 ha respectively in 15 years, between 1990 and 2015. The predicted future land use and cover for the next 15 years (2040) showed an overall increase in cultivated land, built up area, grassland and bushland to 24.82%, 2.24%, 25.18% and 20.41% respectively, and a decrease in forest, woodland and wetland in the order of 1.87%, 7.87% and 0.03% respectively. The study concludes that, there have been significant changes in land use and cover in the catchment which likely to impend the sustainability of the catchment productivity, hence recommends the holistic system thinking and analysis approach in management and utilization of catchment resources.展开更多
For thousands of years, cities have been the center of civilization. According to that, detecting, monitoring and controlling urban growth became the most urgent need in urban planning and urban development process to...For thousands of years, cities have been the center of civilization. According to that, detecting, monitoring and controlling urban growth became the most urgent need in urban planning and urban development process to get the expected results that can build a concrete base for decision makers to drive the polices toward best track. The issue of this paper is about urban growth and planning models and techniques such as geographic information system (GIS), cellular automata (CA), genetic algorithm (GA), regression model (R model) and etc. The main objective of this paper is to summarize the 70 scientific papers concern about urban growth to make a review and find out the most important objective, factors, techniques and results for best approach to studying urban growth. The criteria of choosing the papers are that each paper should focus mainly on urban growth modeling and techniques, also, using wide variety of data and factors. This paper aims to fill the gap of absence of the best methods for studying urban growth, as there is a diversity in the methods used, and there is also an absence of exemplary methods or optimal methods for using analytical tools to study urban growth. So, this paper tries to make it easy for researcher to mix the suitable techniques to get acceptable result for their hypothesis. The results assert combining two or more than two techniques and model to assure that the simulation or prediction models can give real and right approaches. However, most researches focused on combining specific techniques with models such as Cellular Automata CA-Markov Chain MC Model-Logistic regression or Cellular Automata CA-Markov Chain MC model or GIS-MCDM or GIS Based AHP etc. Although, in many references some of these techniques were combined together to extract best result. However, the rule that defines the best combination relies on project criteria, the infinite factors, analysis tools, the nature and quality of these models. On the other hand, whether the project needs a simulation or prediction models, all these models can achieve better result when integrated with quantitative models such as analytic hierarchy process (AHP), the Markov chain analysis or multi-criteria decision making (MCDM) techniques. Also, using remote sensing, satellite images and land use and land cover maps as basic data for analysis were the most common factors according to this review.展开更多
文摘无人机编队指多无人机协作执行任务的过程中,无人机群保持几何形状排列,如V字形、环形等。采用马尔科夫链节点状态模型,对基于载波侦听多路访问/冲突避免(Carrier Sense Multiple Access with Collision Avoid,CSMA/CA)协议的多接口无人机环形编队自组网容量进行分析,推导出节点包碰撞概率、发包概率和网络吞吐量参数的关系模型,提出了网络容量分析方法。通过仿真验证了网络容量分析方法的合理性,并给出了吞吐量随网络节点数、接口数变化的性能结果以及包碰撞概率、发包概率随接口数、竞争节点数变化的理论特性。
文摘Increased anthropogenic activities in the Little Ruaha River Catchment have modulated the catchment condition, nevertheless, the future changes as a result of increased anthropogenic activities are unknown. Understanding the future changes is vitally important for the design of appropriate strategies towards sustainable management of the catchment resources. This study applied Remote Sensing and GIS techniques (Jensen & Lulla, 1987) to assess the historical long-term changes in land use and land cover using Landsat satellite images of 1990, 2005 and 2015, and modelled the future change in land use and land cover up to 2040 using the stochastic CA-Markov chain (Almeida et al., 2005). The historical land use and land cover change detection results indicate that between 1990 and 2005 the area under forest changed from 39,872 ha to 22,957 ha, woodland changed from 109,692 ha to 72,809 ha, wetland decreased from 19,157 ha to 11,785 ha, the cultivated land increased from 106,782 ha to 109,047 ha, likewise, the built-up area increased from 9408 ha to 11,674 ha. Results between 2005 and 2015 show the substantial changes where the forest decline from 22,957 ha to 15,950 ha, woodland decreased from 72,809 ha to 58,554 ha and the wetland changed from 11,785 ha to 5622 ha. Cultivated land and built up area increased from 109,047 ha and 11,674 ha to 143,468 ha and 13,765 ha respectively. Generally, the study has revealed the substantial decline in forest, woodland and wetland by 23,922 ha, 51,138 ha and 13,535 ha respectively, and an increase of cultivated land and built up area by 36,668 ha and 4357 ha respectively in 15 years, between 1990 and 2015. The predicted future land use and cover for the next 15 years (2040) showed an overall increase in cultivated land, built up area, grassland and bushland to 24.82%, 2.24%, 25.18% and 20.41% respectively, and a decrease in forest, woodland and wetland in the order of 1.87%, 7.87% and 0.03% respectively. The study concludes that, there have been significant changes in land use and cover in the catchment which likely to impend the sustainability of the catchment productivity, hence recommends the holistic system thinking and analysis approach in management and utilization of catchment resources.
文摘For thousands of years, cities have been the center of civilization. According to that, detecting, monitoring and controlling urban growth became the most urgent need in urban planning and urban development process to get the expected results that can build a concrete base for decision makers to drive the polices toward best track. The issue of this paper is about urban growth and planning models and techniques such as geographic information system (GIS), cellular automata (CA), genetic algorithm (GA), regression model (R model) and etc. The main objective of this paper is to summarize the 70 scientific papers concern about urban growth to make a review and find out the most important objective, factors, techniques and results for best approach to studying urban growth. The criteria of choosing the papers are that each paper should focus mainly on urban growth modeling and techniques, also, using wide variety of data and factors. This paper aims to fill the gap of absence of the best methods for studying urban growth, as there is a diversity in the methods used, and there is also an absence of exemplary methods or optimal methods for using analytical tools to study urban growth. So, this paper tries to make it easy for researcher to mix the suitable techniques to get acceptable result for their hypothesis. The results assert combining two or more than two techniques and model to assure that the simulation or prediction models can give real and right approaches. However, most researches focused on combining specific techniques with models such as Cellular Automata CA-Markov Chain MC Model-Logistic regression or Cellular Automata CA-Markov Chain MC model or GIS-MCDM or GIS Based AHP etc. Although, in many references some of these techniques were combined together to extract best result. However, the rule that defines the best combination relies on project criteria, the infinite factors, analysis tools, the nature and quality of these models. On the other hand, whether the project needs a simulation or prediction models, all these models can achieve better result when integrated with quantitative models such as analytic hierarchy process (AHP), the Markov chain analysis or multi-criteria decision making (MCDM) techniques. Also, using remote sensing, satellite images and land use and land cover maps as basic data for analysis were the most common factors according to this review.
