Statistical evaluation of an agricultural land suitability model

The land evaluation and site assessment (LESA) method has been used extensively in the United States to assess agricultural land suitability for different localities. Despite widespread use, LESA models rarely have been evaluated in a systematic, comprehensive manner. This article discusses development of a LESA system for Hawaii, the first statewide application of the LESA methodology. The empirical model was implemented with a computerized geographic information system (GIS). The system's efficiency, ability to discriminate among land parcels, and robustness to subjective model parameter values are evaluated with statistical analyses and map overlays of GIS data. Results show great potential to simplify the original model specification, primarily through deletion of marginal site assessment factors. System output was generally insensitive to the numeric values selected for model parameters, with exception of the ratio used to combine the land evaluation (LE) and site assessment (SA) component scores. Relative supplies of the differing land attributes measured by the two components must be considered in determining an appropriate LE:SA ratio for a given area.     

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.     

Using a computerized land-use planning package with the FAO framework for land evaluation

The Food and Agriculture Organization's (FAO) land evaluation methodology provides a procedure for assessing the suitability of land units within a study area for different land uses. This article describes the use of theLuplan computerized land-use planning package to provide an explicit means to select the land use for each land unit which best satisfies defined policies. The use of the package is demonstrated in a study that allocated multiple use activities within a native forest.     

How good is GLASOD?

The Global Assessment of Soil Degradation (GLASOD) has been the most influential global appraisal of land quality in terms of environmental policy. However, its expert judgments were never tested for their consistency and could not be reproduced at unvisited sites, while the relationship between the GLASOD assessments of land degradation and the social and economic impact of that degradation remains unclear. Yet, other methodologies that could respond to urgent calls for an updated assessment of the global environmental quality are not operational or, at best, in progress. Therefore, we evaluate the reliability and social relevance of the GLASOD approach and assess its candidacy for new global environmental assessments. The study concentrates on the African continent, capitalizing on new GIS data to delineate and define the characteristics of GLASOD map units. Consistency is tested by comparing expert judgments on soil degradation hazard for similar combinations of biophysical conditions and land use. Reproducibility is evaluated by estimating an ordered logit model that relates the qualitative land degradation classes to easily available information on explanatory variables, the results of which can be used to assess the land degradation at unvisited sites. Finally, a cross-sectional analysis investigates the relation between GLASOD assessments and crop production data at sub-national scale and its association with the prevalence of malnutrition. The GLASOD assessments prove to be only moderately consistent and hardly reproducible, while the counter-intuitive trend with crop production reveals the complexity of the production-degradation relationship. It appears that increasing prevalence of malnutrition coincides with poor agro-productive conditions and highly degraded land. The GLASOD approach can be improved by resolving the differences in conceptualization among experts and by defining the boundaries of the ordered classes in the same units as independent, quantitative land degradation data.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

Comparing Environmental Conditions Using Indicators of Pollution Hazard

/ Land use/land cover classifications for 1973 and 1991, derived from the interpretation of satellite imagery, are quantified on the basis of biophysical land units in a study area in southeastern Australia. Nutrient export potentials are estimated for each land unit based on their composition of land use/land cover classes. Spatial and temporal comparisons are made of the land units based on the calculated pollution hazard indicators to provide an insight into changes in the state of the environment and the regional significance of land use changes. For example, one ecosystem, unique to the study, showed a large increase in pollution hazard over the study period as a manifestation of an 11-fold rise in cleared area and an expansion of cropping activities. The benefits to environmental management in general are discussed.KEY WORDS: Land cover change; Nutrient export; Environmental condition; Pollution hazard; Agricultural pollution; Nonpoint source pollution; Diffuse pollution; Environmental degradation     

From land cover change to land function dynamics: a major challenge to improve land characterization

Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.     

The Influence of Land Use Change on Landslide Susceptibility Zonation: The Briga Catchment Test Site (Messina,Italy)

The spatial distribution of landslides is influenced by different climatic conditions and environmental settings including topography, morphology, hydrology, lithology, and land use. In this work, we have attempted to evaluate the influence of land use change on landslide susceptibility (LS) for a small study area located in the southern part of the Briga catchment, along the Ionian coast of Sicily (Italy). On October 1, 2009, the area was hit by an intense rainfall event that triggered abundant slope failures and resulted in widespread erosion. After the storm, an inventory map showing the distribution of pre-event and event landslides was prepared for the area. Moreover, two different land use maps were developed: the first was obtained through a semi-automatic classification of digitized aerial photographs acquired in 1954, the second through the combination of supervised classifications of two recent QuickBird images. Exploiting the two land use maps and different land use scenarios, LS zonations were prepared through multivariate statistical analyses. Differences in the susceptibility models were analyzed and quantified to evaluate the effects of land use change on the susceptibility zonation. Susceptibility maps show an increase in the areal percentage and number of slope units classified as unstable related to the increase in bare soils to the detriment of forested areas.     

Ecological land classification: A survey approach

A landscape approach to ecological land mapping, as illustrated in this article, proceeds by pattern recognition based on ecological theory. The unit areas delineated are hypotheses that arise from a knowledge of what is ecologically important in the land. Units formed by the mapper are likely to be inefficient or irrelevant for ecological purposes unless he possesses a sound rationale as to the interactions and controlling influences of the structural components of ecosystems. Here is the central problem with what have been called objective multivariate approaches to mapping based on grid units and the sometimes arbitrary attributes thereof; they tend to conceal the importance of ecological theory and the necessity for theory-based supervision of pattern recognition. Multivariate techniques are best used iteratively to verify and refine map units initially recognized and delineated by theoretical considerations. These ideas are illustrated by an example of a reconnaissance survey in the Northwest Territories of Canada.     

生态适宜度评价在开发区环评和环境规划中的应用——以江苏常熟东南开发区为例

本文以江苏省常熟东南开发区为研究对象，在开发区的环境影响评价和环境保护规划中引入土地利用生态适宜度评价的方法，建立开发区生态适宜度评价指标体系，并借助GIS技术将数值计算和图形叠置有机结合，实现了对经济开发区土地利用进行生态适宜度评价的定量化研究方法，为经济开发区的合理规划提供决策依据。     

梁子湖自然保护区土地利用/土地覆盖动态变化研究

基于梁子湖自然保护区1987年和2004年Landsat-TM影像遥感数据，在Erdas Imagine 8．5图像处理软件的支持下，结合野外实地考察，获得了土地利用现状图，通过对数据的统计分析，研究了保护区近20年来土地利用／土地覆盖的动态变化。研究表明：耕地和水域是保护区内的主要土地利用类型；近20年来，耕地、园地、林地、草地的面积都有减少，其中耕地面积减少了2320．816hm^2，减少比例达到11．78％，是面积减少最多的土地利用类型；居民点、交通、水域用地有所增加，其中池塘面积变化最大，增幅达到213．4％，是面积增加最多的土地利用类型，居民点用地增加了551．18hm^2，增幅达到59．07％，是增长幅度较大的土地利用类型。变化的原因主要是经济的发展、人口数量的增长和旅游业的发展。     

Land-Use Planning in the Chaco Plain (Burruyacú, Argentina): Part 2: Generating a Consensus Plan to Mitigate Land-Use Conflicts and Minimize Land Degradation

The Burruyacú district (Tucumán province, Northwest Argentina) has been traditionally an area with rural activities based on the exploitation of the Chaco forest for timber and livestock browsing. Since the 1960s, local institutions started promoting soybean due to favorable land conditions and good market prices. Soybean extension, as from the 1970s, has resulted in important reduction of the Chaco forest and also caused physical soil degradation, especially soil compaction and erosion. A land-use-planning exercise was carried out using the Land-Use Planning and Information System (LUPIS) as a spatial decision support system. LUPIS facilitates the generation of alternative land-use plans by adjusting the relative importance attributed by multiple stakeholders to preference and avoidance policies. The system leads to the allocation of competing land uses to land map units in accordance with their preferred resource requirements, conditional upon the resource base of the area and the stakeholders' demands. After generating a land use plan for each stakeholder category identified in the study area, including commercial farmers, conservative/conventional farmers, and conservationists, a consensus plan was established to address the land-use conflicts between mechanized agriculture, traditional agriculture and forest conservation, and to mitigate soil degradation caused by extensive dry-farming. Although the planning exercise did not directly involve the stakeholders, the results are sufficiently practical and realistic to suggest that the approach could be extended to the entire Chaco plain region.     

Effect of land cover data on nitrous oxide inventory in fen meadows

Landscape representations based on land cover databases differ significantly from the real landscape. Using a land cover database with high uncertainty as input for emission inventory analyses can cause propagation of systematic and random errors. The objective of this study was to analyze how different land cover representations introduce systematic errors into the results of regional N2O emission inventories. Surface areas of grassland, ditches, and ditch banks were estimated for two polders in the Dutch fen meadow landscape using five land cover representations: four commonly used databases and a detailed field map, which most closely resembles the real landscape. These estimated surface areas were scaled up to the Dutch western fen meadow landscape. Based on the estimated surface areas agricultural N2O emissions were estimated using different inventory techniques. All four common databases overestimated the grassland area when compared to the field map. This caused a considerable overestimation of agricultural N2O emissions, ranging from 9% for more detailed databases to 11% for the coarsest database. The effect of poor land cover representation was larger for an inventory method based on a process model than for inventory methods based on simple emission factors. Although the effect of errors in land cover representations may be small compared to the effect of uncertainties in emission factors, these effects are systematic (i.e., cause bias) and do not cancel out by spatial upscaling. Moreover, bias in land cover representations can be quantified or reduced by careful selection of the land cover database.     

Gaining forests but losing ground: A GIS evaluation in a Himalayan watershed

GIS overlay techniques were used to provide a quantitative historic documentation of deforestation and land-use dynamics in the Middle Mountains of Nepal between 1947 and 1990. Deforestation was most critical in the 1960s, but active afforestation programs in the 1980s have reversed the process. In spite of these trends, the degradation problem is more complex. The GIS evaluation showed that 86% of the recently afforested land is now under pine plantations located primarily at lower elevations and moderately steep slopes. In contrast, rainfed agricultural expansion is most pronounced on acidic soils and steeper, upper elevation sites, suggesting marginalization of agriculture. Agricultural expansion coupled with major losses of grazing land to pine forests are the key processes pointing towards major animal feed deficits. An alternative animal feed source is suggested through GIS using a topographically based microclimatic classification to generate a tree-planting map where the optimum ecological conditions for selective native fodder tree species are identified.     

First application of automated land evaluation in iran

A computerized land evaluation was employed for a speedy land evaluation to locate a new industrial-urban development site in Iran under a multiple-land-use setting. A special-purpose programming language of modeling was generated to facilitate computer application. In doing so, some types of models were initially tested. Finally, an optimization model was decided on for this purpose, because it provided the best result. Four optimization models using linear programming were developed for evaluating the study area (south of Isfahan) involving agriculture, soil conservation, outdoor recreation, and industrial-urban development. Then, the models were combined to produce a multiple-use optimization model (MOM) for land-use classification and planning of the area. In applying the MOM model, a computerized map was produced to indicate the optimum capability of the area for industrial-urban development, agriculture, soil conservation, and outdoor recreation. The employed methodology provided a quick and meaningful result for the study area, which has a low biological productivity.     

Spatial extrapolation of soil characteristics using whole-soil particle size distributions

Soils support ecosystem functions such as plant growth and water quality because of certain physical, chemical, and biological properties. These properties have been studied at different spatial scales, including point scales to satisfy basic research needs, and regional scales to satisfy monitoring needs. Recently, soil property data for the entire USA have become available in the State Soil Geographic Data Base (STATSGO), which is appropriate for regional-scale research. We analyzed and created models of STATSGO data in this study to serve as a research tool, for example, for linking the soil to regional water quality monitoring data in our companion paper. Map units in STATSGO define geographic land areas by soil characteristics (SCs) of similar soil series. We selected 27 SCs that influenced water properties (in varying degrees), aggregated the layer and component SCs to map unit SCs, and used SCs to calculate relationships among map units. The relationships were defined by equations of conditional mean for the qth SC (SCq), while using the remaining 26 SCs as predictors. The relative standard errors for 22 of the 27 SCs were less than 10%, and less than 22% for the remaining five. We conclude that spatial extrapolation of SCs is feasible and the procedures are a first step toward extrapolating information across a region using SC-water property relationships. Although our procedure is for regional scale monitoring, it is also applicable to finer spatial scales commensurate with available soil data.     

THE CONCEPT OF HYDROLOGIC LANDSCAPES1

ABSTRACT: Hydrologic landscapes are multiples or variations of fundamental hydrologic landscape units. A fundamental hydrologic landscape unit is defined on the basis of land‐surface form, geology, and climate. The basic land‐surface form of a fundamental hydrologic landscape unit is an upland separated from a lowland by an intervening steeper slope. Fundamental hydrologic landscape units have a complete hydrologic system consisting of surface runoff, ground‐water flow, and interaction with atmospheric water. By describing actual landscapes in terms of land‐surface slope, hydraulic properties of soils and geologic framework, and the difference between precipitation and evapotranspiration, the hydrologic system of actual landscapes can be conceptualized in a uniform way. This conceptual framework can then be the foundation for design of studies and data networks, syntheses of information on local to national scales, and comparison of process research across small study units in a variety of settings. The Crow Wing River watershed in central Minnesota is used as an example of evaluating stream discharge in the context of hydrologic landscapes. Lake‐research watersheds in Wisconsin, Minnesota, North Dakota, and Nebraska are used as an example of using the hydrologic‐land‐scapes concept to evaluate the effect of ground water on the degree of mineralization and major‐ion chemistry of lakes that lie within ground‐water flow systems.     

Spatial analysis of land use impact on ground water nitrate concentrations

In spatial analyses of causes or health effects of environmental pollutants, small units of analyses are usually preferred for internal environmental homogeneity reasons but can only be done when fine resolution data are available for most units. Objectives of this study were to determine which land use practices were spatially associated with ground water nitrate concentrations across Prince Edward Island (PEI), Canada, and which spatial aggregation is the preferred unit of analyses. Nitrate concentrations were determined for 4855 samples from private wells. Validated field-by-field land use data were available. Average nitrate concentration and percentage of area for the 14 major land use categories in PEI were determined for each of three spatial aggregations: watersheds based on topography and hydrology; freeform polygon boundaries based on similar neighboring nitrate concentrations; and 500-m buffer zones around each well. Results showed that the percentages of potato, grain, and hay coverage were positive predictors of ground water nitrate concentrations. Percentage of blueberry was a marginally significant negative predictor in the watershed and freeform polygon models, and percentage of residential coverage was a positive predictor in the freeform polygon and buffer zone models. Spatial autocorrelation was present in the freeform polygon and buffer zone models even after land use was taken into account. In conclusion, analyses based on watersheds produced the best predictive model with the percentages of land cover of potato, hay, and grain being significantly associated with ground water nitrate concentrations, and the percentages of blueberry, clear-cut woodland, and other agriculture being marginally significant.