A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

基于RS与GIS的规划用地生态适宜性评价

利用遥感影像获取研究区土地利用类型,并运用GIS空间分析功能,分析了影响开发区规划用地生态适宜性的7个因子,并以此对生态适宜性进行综合评价,得到了定量化的评价结果,为区域规划奠定了基础。     

Sensitivity Analysis of Land Unit Suitability for Conservation Using a Knowledge-Based System

The availability of spatially continuous data layers can have a strong impact on selection of land units for conservation purposes. The suitability of ecological conditions for sustaining the targets of conservation is an important consideration in evaluating candidate conservation sites. We constructed two fuzzy logic-based knowledge bases to determine the conservation suitability of land units in the interior Columbia River basin using NetWeaver software in the Ecosystem Management Decision Support application framework. Our objective was to assess the sensitivity of suitability ratings, derived from evaluating the knowledge bases, to fuzzy logic function parameters and to the removal of data layers (land use condition, road density, disturbance regime change index, vegetation change index, land unit size, cover type size, and cover type change index). The amount and geographic distribution of suitable land polygons was most strongly altered by the removal of land use condition, road density, and land polygon size. Removal of land use condition changed suitability primarily on private or intensively-used public land. Removal of either road density or land polygon size most strongly affected suitability on higher-elevation US Forest Service land containing small-area biophysical environments. Data layers with the greatest influence differed in rank between the two knowledge bases. Our results reinforce the importance of including both biophysical and socio-economic attributes to determine the suitability of land units for conservation. The sensitivity tests provided information about knowledge base structuring and parameterization as well as prioritization for future data needs.     

人海和谐视角下沿海城市国土空间开发建设适宜性评价研究——以江苏省沿海地区为例

国土空间开发适宜性评价对合理开发国土空间、优化国土空间利用格局具有重要的科学指导价值。遵循陆海统筹原则,采用短板原理、线性加权求和法、空间叠加分析法,从自然环境适宜性、资源环境承载力两个方面构建适宜性评价指标体系,通过对经济社会统计数据、空间数据的处理叠加,对江苏省沿海城市南通、盐城、连云港国土空间开发适宜性进行评价与分析。研究结果表明,国土空间开发适宜性空间分异明显,江苏沿海地区不适宜、基本不适宜、基本适宜、适宜区域面积分别为14 710.37 km²、3376.18 km²、6776.30 km²、5695.64km²,分别占陆域国土总面积的46.76%、10.73%、21.54%、18.10%,各地级市外围区域保护与发展之间的矛盾较为突出。     

Fuzzy assessment of land suitability for scientific research reserves

Evaluating the characteristics of a set of sites as potential scientific research reserves is an example of land suitability assessment. Suitability in this case is based upon multiple criteria, many of which can be linguistically imprecise and often incompatible. Fuzzy logic is a useful method for characterizing imprecise suitability criteria and for combining criteria into an overall suitability rating. The Ecosystem Management Decision Support software combined a fuzzy logic knowledge base we developed to represent the assessment problem with a GIS database providing site-specific data for the assessment. Assessment of sites as a potential natural reserve for the new University of California campus at Merced demonstrates the benefits of fuzzy suitability assessment. The study was conducted in three stages of successively smaller assessment regions with increasingly fine spatial resolution and specificity of criteria. Several sites were identified that best satisfy the suitability criteria for a reserve to represent vernal pool habitat.     

A quantitative evaluation of monitoring networks for region-specific nitrate reduction policies

Modern environmental policy implementation in many developed countries is increasingly regionally oriented. Regional governments have undertaken measures designed for the specific needs of the region but, so far, the resulting change in environmental quality has hardly been monitored. This study develops a method for the quantitative evaluation of region-specific environmental policy. Two forms of monitoring are distinguished: monitoring of performance of policy measures and monitoring of environmental quality. This study investigates two regions in the Netherlands where region-specific policy has been implemented. Performance monitoring focused on reduction of nitrate leaching to groundwater. Leaching reductions were calculated with simple models or rules of thumb. Quality monitoring focused on nitrate concentrations under grassland and other land use. An analysis of variance showed significant differences between different soil units. Stratified kriging was applied for spatial interpolation, showing within-unit variability. The current monitoring network could be improved by using a more regular type of grid.     

Definition of Management Zones for Enhancing Cultivated Land Conservation Using Combined Spatial Data

The loss of cultivated land has increasingly become an issue of regional and national concern in China. Definition of management zones is an important measure to protect limited cultivated land resource. In this study, combined spatial data were applied to define management zones in Fuyang city, China. The yield of cultivated land was first calculated and evaluated and the spatial distribution pattern mapped; the limiting factors affecting the yield were then explored; and their maps of the spatial variability were presented using geostatistics analysis. Data were jointly analyzed for management zone definition using a combination of principal component analysis with a fuzzy clustering method, two cluster validity functions were used to determine the optimal number of cluster. Finally one-way variance analysis was performed on 3,620 soil sampling points to assess how well the defined management zones reflected the soil properties and productivity level. It was shown that there existed great potential for increasing grain production, and the amount of cultivated land played a key role in maintaining security in grain production. Organic matter, total nitrogen, available phosphorus, elevation, thickness of the plow layer, and probability of irrigation guarantee were the main limiting factors affecting the yield. The optimal number of management zones was three, and there existed significantly statistical differences between the crop yield and field parameters in each defined management zone. Management zone I presented the highest potential crop yield, fertility level, and best agricultural production condition, whereas management zone III lowest. The study showed that the procedures used may be effective in automatically defining management zones; by the development of different management zones, different strategies of cultivated land management and practice in each zone could be determined, which is of great importance to enhance cultivated land conservation, stabilize agricultural production, promote sustainable use of cultivated land and guarantee food security.     

Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.     

Determination of Frequency for Remeasuring Ground and Vegetation Cover Factor Needed for Soil Erosion Modeling

Determining a remeasurement frequency of variables over time is required in monitoring environmental systems. This article demonstrates methods based on regression modeling and spatio-temporal variability to determine the time interval to remeasure the ground and vegetation cover factor on permanent plots for monitoring a soil erosion system. The spatio-temporal variability methods include use of historical data to predict semivariograms, modeling average temporal variability, and temporal interpolation by two-step kriging. The results show that for the cover factor, the relative errors of the prediction increase with an increased length of time interval between remeasurements when using the regression and semivariogram models. Given precision or accuracy requirements, appropriate time intervals can be determined. However, the remeasurement frequency also varies depending on the prediction interval time. As an alternative method, the range parameter of a semivariogram model can be used to quantify average temporal variability that approximates the maximum time interval between remeasurements. This method is simpler than regression and semivariogram modeling, but it requires a long-term dataset based on permanent plots. In addition, the temporal interpolation by two-step kriging is also used to determine the time interval. This method is applicable when remeasurements in time are not sufficient. If spatial and temporal remeasurements are sufficient, it can be expanded and applied to design spatial and temporal sampling simultaneously.     

Modeling the Suitability of Potential Wetland Mitigation Sites with a Geographic Information System

Wetland mitigation is frequently required to compensate for unavoidable impacts to wetlands. Site conditions and landscape context are critical factors influencing the functions that created wetlands perform. We developed a spatial model and used a geographic information system (GIS) to identify suitable locations for wetland mitigation sites. The model used six variables to characterize site conditions: hydrology, soils, historic condition, vegetation cover, adjacent vegetation, and land use. For each variable, a set of suitability scores was developed that indicated the wetland establishment potential for different variable states. Composite suitability scores for individual points on the landscape were determined from the weighted geometric mean of suitability scores for each variable at each point. These composite scores were grouped into five classes and mapped as a wetland mitigation suitability surface with a GIS. Sites with high suitability scores were further evaluated using information on the feasibility of site modification and project cost. This modeling approach could be adapted by planners for use in identifying the suitability of locations as wetland mitigation sites at any site or region.     

A land suitability model for the evaluation of land-use change

A land suitability model was developed to provide the planner with a quantitative tool for assessing the environmental limitations on proposed land-use changes in the area surrounding Lake Monroe in southern Indiana. The model incorporates a weighting procedure that allows the environmental evaluation of a decision to convert the present land use to another category. The data base for the model was assembled by a multidisciplinary team. A case study is included, which illustrates the advantages and limitations of the land suitability model as it is applied to the evaluation of a site for the Alumni Family Camp.     

土地适宜性评价研究

本文以土地生态学和经济学为理论基础,首次用系统评价方式研究山区土地质量与用途之间的匹配关系。评价特点是以定量评价为主,土地质量为基础,土地生产率为综合评价指标,土地类型为评价单元,当前和潜在适宜性同步评价。当前适宜性由适宜纲、不适宜纲和不相关三部分组成。适宜纲分高度适宜、中度适宜和勉强适宜3个级。每一单元都作水田、旱地、园地、林地、牧地的多宜性评价。由评价表可得11幅土地适宜性评价系列图。研究成果具有直观性和实用性特点,全面适应我国南方山区土地资源的开发利用和整治保护的需要。     

Modeling Change-Pattern-Value Dynamics on Land Use: An Integrated GIS and Artificial Neural Networks Approach

The use of spatial methods to detect and characterize changes in land use has been attracting increasing attention from researchers. The objectives of this article were to formulate the dynamics of land use on the temporal and spatial dimensions from the perspectives of the Change-Pattern-Value (CPV) and driving mechanism, based on multitemporal remote sensing data and socioeconomic data. The Artificial Neural Networks were used to identify the factors driving changes in land use. The Pearl River Delta Region of southeast China, which was experiencing rapid economic growth and widespread land conversion, has been selected as the study region. The results show that from 1985 to 2000 in the study region (1) the most prominent characteristics of change in land use were the expansion of the urban land at the expense of farmland, forests, and grasslands, (2) the land-use pattern was being optimized during this period, (3) in an analysis of value, built-up land can yield a return of more than 30 times that of farmland, water area, and forests lands, and (4) rapid economic development, growth in population, and the development of an infrastructure were major driving factors behind ecological land loss and the nonecological land expansion.     

Site-specific phosphorus application based on the kriging fertilizer-phosphorus availability index of soils

Site-specific phosphorus management is done to optimize crop production and minimize P loss from soils. The spatial variability of the available P prior to fertilizer application and the P-fixation tendency of soil both need to be taken into account for variable-rate P application. The objectives of this research were to document the spatial variability of the fertilizer-P availability index, which shows the P-fixation tendency, and to develop a strategy that takes the spatial distribution of this index into account for site-specific phosphorus application. In this study, the spatial patterns of the fertilizer-P availability index were characterized by using geostatistics. The ordinary kriging was used for spatial interpolation of the fertilizer-P availability index. Because the fertilizer-P availability index of soil is related to oxalate-extractable Fe and Al and because measuring oxalate-extractable Fe and Al is much easier than directly determining the fertilizer-P availability index, the spatial distribution of the fertilizer-P availability index can be obtained using the oxalate-extractable Fe and Al data. The spatial distribution of Olsen-extractable P, which was used to measure the available-P status prior to fertilizer-P application, was also estimated by using ordinary kriging. The required fertilizer-P amounts were then determined using the kriging estimates of the fertilizer-P availability index and Olsen-extractable P. A fertilizer-P recommendation map for the 430-ha study site in Changhua county, Taiwan was generated by using this approach for illustration. The proposed method for generating fertilizer-P recommendation maps can be used for variable-rate application to maintain an adequate P status for crop production and to potentially reduce the P loss from soils.     

The role of population in understanding Honduran land use patterns

Land use patterns are usually influenced by large variety of factors that act over a broad range of scales. Biophysical, climatic, and socioeconomic factors are important and need to be considered, when distribution of land use is to be understood. The main objective of this study is to test this hypothesis using a statistical analysis at 'supra-local' level. Regression analysis is used to describe land use patterns in Honduras, selected because of its rare combination in Latin America of high population growth and poor biophysical conditions. Furthermore, the aim of the analysis is to specifically highlight two aspects, the effect of spatial and temporal scale and the influence of population density: to determine the influence of spatial and temporal scale, six spatial resolutions at two points in time (1974 and 1993) were included. To determine the role of population density and population growth, this factor was singled out; an analysis of migration patterns was performed; and a measure for technological development was calculated. Multiple regression equations indicate the importance of soil-related, climatic and demographic factors for most of the land uses. Relations appear to be stable in space and time. Rural population density dominates as driver over the whole range of resolutions and for both years, especially for maize where it explains up to 80% of the variation. The strong constant relationship between population and agricultural area could be caused by a lack of technological development. An analysis of yield development confirms that for most annual crops yield increases lag behind area growth. Besides, the strong correlation could be explained by assuming rural population density to be a proxy for a range of other factors, like labour costs, or accessibility that are the direct drivers of land use change. In any case, this study suggests that for a specific--relatively coarse--window of temporal and spatial scale, land use patterns can be described with very simple relationships, with a strong contribution of population density. More local studies are needed to test the hypothesis that rural population density is a proxy for other variables.     

Integrating social preference in GIS-aided planning for forestry and conservation activities: a case study from rural SE Asia

Land-use planning using geographic information systems (GIS) commonly emphasizes biophysical spatial data; however planning can be improved by integrating spatial sets of socioeconomic data into the GIS. As an example, we compared a traditional GIS-aided forestry planning protocol that considered only biophysical suitability, with an integrated GIS-aided approach that incorporated both biophysical and socioeconomic suitability. The analyses were conducted for the planning of plantation investments in the Kyaukpadaung Township in the dry zone of central Myanmar. The traditional approach used three biophysical layers for suitability: land use, slope, and accessibility. In contrast, the integrated GIS approach included biophysical suitability data, perceptions and preferences of local villagers towards forestry (social suitability), and quantitative socioeconomic data. The results indicated that the integrated approach provided two principal benefits over the traditional method. First, the integrated method resulted in a more precise idea of suitable sites for plantation investment that could benefit more rural people and also lead to greater investment efficiency. Second, incorporating social preference into the GIS takes into account the crucial element of social capital (viz., social preference), which should lead to higher levels of community acceptance of plantation projects because those plantations would be established on socially suitable land. A second GIS exercise showed how conservation investment decisions could be informed using the integrated method. The results of this study support the idea that GIS-aided planning activities can be enhanced through the incorporation of social data into the analysis. When applicable, spatial data collection efforts for GIS-based planning exercises should incorporate spatial socioeconomic data.     

Constructing Interpretable Environments from Multidimensional Data: GIS Suitability Overlays and Principal Component Analysis

In landscape planning applications, practitioners and governmental agencies are often faced with a broad array of clientele and constituents having particular land use requirements and needs, ranging from biological conservation to urban development, generating complex multidimensional regional planning goals and objectives. Under this often complex situation, investigators are searching for methods to intelligently simplify complicated spatial environments and render them into interpretable and practical settings. While numerous investigators have studied the generation of a single suitability map, we were interested in addressing the problem of coping with a set of many suitability maps. We applied a data reduction method, principal component analysis, across 15 suitability overlays representing diverse landscape requirements to search for simplified explanations indicating the latent structure of the landscape. The study area was located in a moraine landscape of southern Michigan. We discovered that the 15 suitability overlays could be reduced to seven dimensions, containing 65% of the original data structure and that the seven dimensions reflect a structure where a variety of land uses each have their own optimal spatial locations, indicating low to moderate competition between potentially conflicting land uses and rendering a more easily understood environment. This approach did not render a simple elegant solution but it did reduce the complexity associated with combining many suitability maps.     

Use of agricultural land evaluation and site assessment in Whitman County,Washington, USA

Whitman County, Washington, USA, one of the largest wheat producing counties in the country, developed a land evaluation and site assessment system for evaluating proposed conversions of agricultural land to heavy commercial uses. The system uses soil potential indices to determine a land evaluation score and a nine-factor site assessment system to weigh suitability for development. Details on each of these are provided along with results for four sample sites.Scientific Paper no. 7165, College of Argiculture and Home Economics Research Paper, Washington State University, Pullman, Washington, project no. 0010.     

基于层次模糊综合评判法的土地集约利用研究——以河北省永清县为例

土地集约节约利用越来越成为人们关注的问题，对其进行科学评价也成为焦点。通过对永清县乡镇土地集约利用状况的调查，构建了适合乡镇土地集约度评价的指标体系，采用AHP和模糊综合评判相结合的方法对乡镇土地集约度进行了评价。从而得出永清县土地利用集约度状况，为以后的发展提供借鉴依据。     

建设用地集约利用空间差异研究

土地的集约利用对社会发展具有重要的意义，研究土地集约利用空间差异可以更有效地提高土地利用水平。根据新一轮土地利用规划大纲要求和各区域土地利用实际，建立土地集约利用评价指标体系，确定土地集约利用评价的计算方法，包括数据的量化、标准化及综合计算模型，最后得出各地区土地集约利用程度。运用上述方法对孝感市建设用地集约利用空间差异进行分析，找出了其土地利用方面的问题和优势，为下一步改造提供依据和方向。