基于小波神经网络的区域景观生态评价研究
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摘要
景观是处于生态系统之上、地理区域之下的一种尺度,许多土地利用问题只有在景观尺度上才能得到合理的解释。然而,随着现代工业的发展,人类生活生产与自然环境之间的物质交换仍在以惊人的速度发展。一方面,是过度消耗土地、森林、能源、淡水及其它自然资源的现象,尤其是对动植物可再生资源的开发利用,已使之难以恢复再生,导致生物多样性遭到破坏,珍稀动植物濒临灭绝;另一方面,是向环境排泄的废弃物不断增加,不断恶化生态环境,严重威胁着人类和其它生物的生存。如此种种导致了各种生态问题的出现,主要表现为:自然资源面临枯竭,水土流失严重,土地沙漠化迅速发展,草原退化,森林面积锐减,乱挖滥采、乱捕野生动物,生态环境被严重破坏,生物多样性下降等,这些问题已经成为制约社会经济稳步发展和人类生存的瓶颈,因此随着生态问题的严重性不断加剧,保护景观生态环境逐渐被提上日程。
文章在总结已有的景观生态和神经网络的研究基础上,将小波神经网络(WNN)引入景观生态评价领域,开展了基于WNN景观生态评价原理、程序和方法等方面的研究,形成了比较完整、系统的景观生态评价WNN模型的理论与方法体系。具体来讲,本文主要进行了以下几方面的研究:
(1)通过对景观生态评价的概念和内容分析,将景观生态评价分为景观生态质量评价、景观脆弱性评价与景观生态风险评价3各方面,并总结了景观生态评价的方法可包括:现场调查专家判断、统计分析法、RS和GIS制图、数学模型方法等。
(2)提出了基于WNN景观生态评价的综合指数评价模型,然后提出了该模型的原理和程序。基于WNN景观生态评价可按以下流程进行:①研究区现状调查,②构建评价区域的评价指标体系,③单项分析与评价,④采用WNN模型开展综合评价等4个步骤。
(3)根据景观生态状况的内涵,构建了基于WNN景观生态评价指标体系,即包括景观生产力、景观受胁度和景观稳定性,用以描述景观生态系统的生产力、弹性和面临的压力。
(4)还提出景观生态评价的小波神经网络(WNN)模型,主要包括构建指标评价体系、应用WNN计算综合风险指数、与评判标准比较等步骤.为研究WNN的准确性和适用性,还可以将其结果与ANN模型模拟结果相对照。然而景观生态系统属于复杂系统,其影响因素也较为复杂,因此,综合风险指数计算除了采用定量模型外,还需要定性分析推理。
(5)本文以姜堰市为研究对象,通过景观生态评价的WNN模型,开展了土地可持续利用景观生态评价实证研究。结果表明研究区域可分为5个等级:高持续区,面积占研究区总面积的12.64%;较高持续区,占6.70%;中等持续区,占35.04%;一般持续区,占39.17%;弱持续区,占6.45%,并针对不同的等级提出了管理措施。研究结果也显示,本文提出的一种计算评价土地利用可持续性小波神经元网络拟合模型,并具有快速、准确的优点,其适用性较强。
(6)本文还以泰州市辖区为研究对象,应用WNN模型,开展了城市边缘区景观生态评价。研究表明:该模型在很大程度上消除了人为因素的影响,能把影响景观生态的各种因素进行综合考虑,并能够充分利用有关景观生态特征参数的统计数据信息,通过高度的非线性映射,寻求景观生态的综合评价与其影响特征因素之间的隐含的内在机理,增强了所得数据的客观性,从而给出具体的综合评价结果,可为进一步的景观生态管理和建设提供重要的科学依据。
(7)本文不仅针对不同等级的提出了保护景观生态环境的对策,还针对研究中发现的主要景观生态问题,提出了相应的政策建议,包括:①合理布局景观;②加强景现多样性保护;③系统建设区域景观廊道;④发挥好农田等绿地系统的作用。
Landscape is a scale which contains geographical region and is included in ecosystem, many land use problems couldn't get reasonable explanation without being based on landscape scale. However, with the development of the modern industry, the material exchange between human activities and living environment is developing with astonishing speed. On the one hand, existing over-consumption of land, forest, energy, freshwater and other natural resources, especially to the development and utilization of renewable resources as animals and plants, which have been difficult to restorative regeneration, and also lead to the destruction of biodiversity and the extinct of valuable animals and plants. On the other hand, the increasing waste excreted to the environment causes the worsening of the eco-environment continuously, threats the survival of human and other livings seriously. Based on the above aspects, many ecological problems produced, mainly presented exhaustion of natural resources, severe water and soil erosion, spread of land desertification, degeneration of grassland, reduction of the forests ,disordered exploitation and excavation, indiscriminate killing of wildlife, serious destruction of its ecological environment and biological diversity decline. These problems have been become the restriction of the development of social economy and the survival of human beings, therefore, the protection of landscape eco-environment was on the agenda gradually as the constant increasing of the severity of ecological problems.
The paper based on the summary the foundation of landscape ecology and neural network introduces wavelet neural network (WNN) to the field of landscape ecology assessment, an analysis of landscape assessment principle, process and methods based on WNN is presented. Forms relatively complete theory and method system for WNN model of landscape ecology. Concretely speaking, the paper makes a study on the following aspects:
(1) Based on the concept and contents analysis of landscape ecology assessment, the landscape ecology assessment is deposed into quality assessment of landscape ecology part, vulnerability assessment of landscape ecology part and landscape ecological risk assessment part. And summarizes the methods of landscape ecology assessment, which are following: field survey, expert judgment, statistical analysis, RS and GIS mapping, mathematical model methods and so on.
(2) The paper supports a comprehensive assessment index model based on WNN landscape ecology assessment, and then, proposes the principle and process of the model. The landscape ecology assessment based on WNN is as following in process:①he present condition investigation of study area,②constructing assess index system of assessment region,③single analysis and assessment,④evaluate comprehensively with WNN model.
(3) According to the connotation of landscape ecological status, constructing the landscape ecology assessment index system based on WNN, which include landscape productivity, degree of landscape threatened and landscape stability to describe the productivity, elasticity and pressure facing of landscape ecological system.
(4) The paper also proposes WNN model of landscape ecology assessment, main process includes constructing assess index system, calculating comprehensive risk index, comparing with assessment standard, etc. For the good accuracy and precision, the model result and that ANN model simulated could be analytically compared. However, the landscape ecological system is a system with complex influencing factors, during the calculating of comprehensive risk index, besides quantitative model, also needs qualitative analysis reasoning.
(5)This paper will take Jiangyan City as an example, and study sustainable land-use landscape ecology assessment by using landscape ecology assessment WNN model. The results show that study region can be compartmentalized into five grades, high sustainable region, the area of which accounts the whole area 12.64%, less-high sustainable region, accounting 6.70%, medium sustainable region, accounting 35.04%, ordinary sustainable region, accounting 39.17%, inferior sustainable region, accounting 6.45%,and propose management measures against different grades. The study results also show, calculating assessment sustainable land-use wavelet neural network elaboration model which is proposed in this paper has fast, accurate and better-suitable such advantages.
(6)This paper takes Taizhou domination area as study object. Through application of WNN model, start landscape ecology assessment of city edge region. The study shows, this model will most eliminate the effects of human factors, consider various factors of affecting landscape ecology, and make full use of statistical data information about characteristic parameters of landscape ecology. Through high nonlinear mapping, seek the implied intrinsic mechanisms between landscape ecology synthetic assessment and characteristic factors. So objectivity of obtained data can be strengthened and give concrete synthetic assessment results, which can provide important scientific basis of further landscape assessment management and construction.
(7)This paper not only proposes measures of protecting landscape ecology environment against different grades, but also proposes corresponding policy and suggestions against main landscape ecology problems found during study. That include,①putting rational distribution of landscape;②strengthening landscape diversity protection;③accelerating the construction of regional landscape corridor;④Maximizing the role of green space system such as farmland.
文章在总结已有的景观生态和神经网络的研究基础上,将小波神经网络(WNN)引入景观生态评价领域,开展了基于WNN景观生态评价原理、程序和方法等方面的研究,形成了比较完整、系统的景观生态评价WNN模型的理论与方法体系。具体来讲,本文主要进行了以下几方面的研究:
(1)通过对景观生态评价的概念和内容分析,将景观生态评价分为景观生态质量评价、景观脆弱性评价与景观生态风险评价3各方面,并总结了景观生态评价的方法可包括:现场调查专家判断、统计分析法、RS和GIS制图、数学模型方法等。
(2)提出了基于WNN景观生态评价的综合指数评价模型,然后提出了该模型的原理和程序。基于WNN景观生态评价可按以下流程进行:①研究区现状调查,②构建评价区域的评价指标体系,③单项分析与评价,④采用WNN模型开展综合评价等4个步骤。
(3)根据景观生态状况的内涵,构建了基于WNN景观生态评价指标体系,即包括景观生产力、景观受胁度和景观稳定性,用以描述景观生态系统的生产力、弹性和面临的压力。
(4)还提出景观生态评价的小波神经网络(WNN)模型,主要包括构建指标评价体系、应用WNN计算综合风险指数、与评判标准比较等步骤.为研究WNN的准确性和适用性,还可以将其结果与ANN模型模拟结果相对照。然而景观生态系统属于复杂系统,其影响因素也较为复杂,因此,综合风险指数计算除了采用定量模型外,还需要定性分析推理。
(5)本文以姜堰市为研究对象,通过景观生态评价的WNN模型,开展了土地可持续利用景观生态评价实证研究。结果表明研究区域可分为5个等级:高持续区,面积占研究区总面积的12.64%;较高持续区,占6.70%;中等持续区,占35.04%;一般持续区,占39.17%;弱持续区,占6.45%,并针对不同的等级提出了管理措施。研究结果也显示,本文提出的一种计算评价土地利用可持续性小波神经元网络拟合模型,并具有快速、准确的优点,其适用性较强。
(6)本文还以泰州市辖区为研究对象,应用WNN模型,开展了城市边缘区景观生态评价。研究表明:该模型在很大程度上消除了人为因素的影响,能把影响景观生态的各种因素进行综合考虑,并能够充分利用有关景观生态特征参数的统计数据信息,通过高度的非线性映射,寻求景观生态的综合评价与其影响特征因素之间的隐含的内在机理,增强了所得数据的客观性,从而给出具体的综合评价结果,可为进一步的景观生态管理和建设提供重要的科学依据。
(7)本文不仅针对不同等级的提出了保护景观生态环境的对策,还针对研究中发现的主要景观生态问题,提出了相应的政策建议,包括:①合理布局景观;②加强景现多样性保护;③系统建设区域景观廊道;④发挥好农田等绿地系统的作用。
Landscape is a scale which contains geographical region and is included in ecosystem, many land use problems couldn't get reasonable explanation without being based on landscape scale. However, with the development of the modern industry, the material exchange between human activities and living environment is developing with astonishing speed. On the one hand, existing over-consumption of land, forest, energy, freshwater and other natural resources, especially to the development and utilization of renewable resources as animals and plants, which have been difficult to restorative regeneration, and also lead to the destruction of biodiversity and the extinct of valuable animals and plants. On the other hand, the increasing waste excreted to the environment causes the worsening of the eco-environment continuously, threats the survival of human and other livings seriously. Based on the above aspects, many ecological problems produced, mainly presented exhaustion of natural resources, severe water and soil erosion, spread of land desertification, degeneration of grassland, reduction of the forests ,disordered exploitation and excavation, indiscriminate killing of wildlife, serious destruction of its ecological environment and biological diversity decline. These problems have been become the restriction of the development of social economy and the survival of human beings, therefore, the protection of landscape eco-environment was on the agenda gradually as the constant increasing of the severity of ecological problems.
The paper based on the summary the foundation of landscape ecology and neural network introduces wavelet neural network (WNN) to the field of landscape ecology assessment, an analysis of landscape assessment principle, process and methods based on WNN is presented. Forms relatively complete theory and method system for WNN model of landscape ecology. Concretely speaking, the paper makes a study on the following aspects:
(1) Based on the concept and contents analysis of landscape ecology assessment, the landscape ecology assessment is deposed into quality assessment of landscape ecology part, vulnerability assessment of landscape ecology part and landscape ecological risk assessment part. And summarizes the methods of landscape ecology assessment, which are following: field survey, expert judgment, statistical analysis, RS and GIS mapping, mathematical model methods and so on.
(2) The paper supports a comprehensive assessment index model based on WNN landscape ecology assessment, and then, proposes the principle and process of the model. The landscape ecology assessment based on WNN is as following in process:①he present condition investigation of study area,②constructing assess index system of assessment region,③single analysis and assessment,④evaluate comprehensively with WNN model.
(3) According to the connotation of landscape ecological status, constructing the landscape ecology assessment index system based on WNN, which include landscape productivity, degree of landscape threatened and landscape stability to describe the productivity, elasticity and pressure facing of landscape ecological system.
(4) The paper also proposes WNN model of landscape ecology assessment, main process includes constructing assess index system, calculating comprehensive risk index, comparing with assessment standard, etc. For the good accuracy and precision, the model result and that ANN model simulated could be analytically compared. However, the landscape ecological system is a system with complex influencing factors, during the calculating of comprehensive risk index, besides quantitative model, also needs qualitative analysis reasoning.
(5)This paper will take Jiangyan City as an example, and study sustainable land-use landscape ecology assessment by using landscape ecology assessment WNN model. The results show that study region can be compartmentalized into five grades, high sustainable region, the area of which accounts the whole area 12.64%, less-high sustainable region, accounting 6.70%, medium sustainable region, accounting 35.04%, ordinary sustainable region, accounting 39.17%, inferior sustainable region, accounting 6.45%,and propose management measures against different grades. The study results also show, calculating assessment sustainable land-use wavelet neural network elaboration model which is proposed in this paper has fast, accurate and better-suitable such advantages.
(6)This paper takes Taizhou domination area as study object. Through application of WNN model, start landscape ecology assessment of city edge region. The study shows, this model will most eliminate the effects of human factors, consider various factors of affecting landscape ecology, and make full use of statistical data information about characteristic parameters of landscape ecology. Through high nonlinear mapping, seek the implied intrinsic mechanisms between landscape ecology synthetic assessment and characteristic factors. So objectivity of obtained data can be strengthened and give concrete synthetic assessment results, which can provide important scientific basis of further landscape assessment management and construction.
(7)This paper not only proposes measures of protecting landscape ecology environment against different grades, but also proposes corresponding policy and suggestions against main landscape ecology problems found during study. That include,①putting rational distribution of landscape;②strengthening landscape diversity protection;③accelerating the construction of regional landscape corridor;④Maximizing the role of green space system such as farmland.
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