Agricultural land evaluation and site assessment in the United States: An introduction

The US Soil Conservation Service has developed an agricultural land evaluation and site assessment (LESA) system. The LESA system is being used by the US Department of Agriculture and other federal agencies to implement the Farmland Protection Policy Act of 1981. The LESA system and three case studies from the Pacific North-west are introduced in this article.Scientific Paper no. 7166, College of Agriculture and Home Economics Research Paper. Washington State University, Pullman, Washington. Project no. 0010.     

Use of agricultural land evaluation and site assessment in Linn County,Oregon, USA

Oregon state law requires each county in the state to identify agricultural land and enact policies and regulations to protect agricultural land use. State guidelines encourage the preservation of large parcels of agricultural land and discourage partitioning of agricultural land and construction of nonfarm dwellings in agricultural areas. A land evaluation and site assessment (LESA) system was developed in Linn County to aid in the identification of agricultural land and provide assistance to decision makers concerning the relative merits of requests to partition existing parcels of ricultural land and introduce nonagricultural uses.Land evaluation was determined by calculating soil potential ratings for each agricultural soil in the county based on the soil potentials for winter wheat, annual ryegrass, permanent pasture, and irrigated sweet corn. Soil potential ratings were expressed on a scale of 0 to 150 points. The land evaluation score for a parcel consists of the weighted average soil potential rating for all of the soils in the parcel, weighted by the percentage of each soil present in the parcel.Site assessment was based on the size of a parcel and on the amount of existing conflict between agricultural and nonagricultural uses, particularly rural residential uses, both adjacent to and in the vicinity of a parcel. Parcel size refers to both size in relation to a typical field and size in relation to a typical farm unit. Conflict takes into account the number of nonfarm dwellings within 1/4 mile (0.4 km) of a parcel, the amount of the perimeter that adjoins conflicting land uses, and the residential density adjacent to the parcel. Empirical scales were derived for assigning points to each of the site assessment factors. Both parcel size and conflict were worth 75 points in the model. For parcel size, 45 points were allocated to field size and 30 points to farm-unit size. For conflict, 30 points were allocated to nonfarm dwellings within 1/4 mile and 45 points to perimeter conflicts.The LESA model was validated by testing on 23 parcels in Linn County for which requests to partition and/or convert to nonagricultural uses had been received by the County Planning Department. This testing was an essential part of the development process, as it pointed out inconsistencies and errors in the model and allowed continuous adjustment of factors and point scales. The results of application of the final model to three of the case studies are presented to illustrate the concepts.Three possible uses of the information generated by the LESA system include determining the relative agricultural value of a parcel, determining grades of agricultural land suitability, and determining the impacts of changing land use on other parcels in the vicinity. Relative agricultural value is a direct outcome of application of the evaluation criteria in the LESA model. Good, marginal, and nonagricultural grades of agricultural suitability were determined by examining the data from all 23 test cases and establishing threshold point values for soil quality, conflict, parcel size, and total LESA score. Impact analyses were not done in this study, but could be achieved by calculating LESA scores for all parcels possibly affected by a land-use change both before and after a proposed change. All three applications fall short of making a specific land-use decision, but they do provide information that should be of value to the local jurisdiction charged with making such decisions.     

基于GIS的泗县开发区土地集约利用评价研究

以安徽省泗县开发区为例,从土地利用状况、用地效益、管理绩效和可持续发展状况4个方面构建开发区土地集约利用评价指标体系,运用GIS技术、特尔斐法,选择评价模型确定权重后对泗县开发区进行土地集约利用评价,研究泗县开发区土地集约利用状况.结果显示,泗县开发区土地集约利用总体水平为中等集约利用,土地利用状况和用地效益度方面存在着一定问题.基于反映的问题,提出相应的措施.     

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.     

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.     

Land Resource Sustainability for Urban Development: Spatial Decision Support System Prototype

Land resource sustainability for urban development characterizes the problem of decision-making with multiplicity and uncertainty. A decision support system prototype aids in the assessment of incremental land development plan proposals put forth within the long-term community priority of a sustainable growth. Facilitating this assessment is the analytic hierarchy process (AHP), a multicriteria evaluation and decision support system. The decision support system incorporates multiple sustainability criteria, weighted strategically responsive to local public policy priorities and community–specific situations and values, while gauging and directing desirable future courses of development. Furthermore, the decision support system uses a GIS, which facilitates an assessment of urban form with multiple indicators of sustainability as spatial criteria thematically. The resultant land-use sustainability scores indicate, on the ratio-scale of AHP, whether or not a desirable urban form is likely in the long run, and if so, to what degree. The two alternative modes of synthesis in AHP—ideal and distributive—provide assessments of a land development plan incrementally (short-term) and city-wide pattern comprehensively (long-term), respectively. Thus, the spatial decision support system facilitates proactive and collective public policy determination of land resource for future sustainable urban development.     

TIM: Assessing the sustainability of agricultural land management

TIM (Threat Identification Model) is a framework for the ex ante assessment of agricultural land management sustainability at the land unit scale that identifies sources of unsustainability within agricultural land management systems. The model explicitly links defined hazards to land productivity and environmental integrity, land resource data and information, and land management practice options using expert and local knowledge on land management and its potential effects. The model was tested in the Crystal Creek Subcatchment, a narrow coastal strip of land situated in north Queensland, Australia. This area was chosen due to the expansion of the sugar industry onto increasingly marginal land in the area, which represents a threat to sustainable land use and a requirement for careful land-use planning and land management.TIM may be used in a relational database as a stand alone decision support system for land-management planning. Its usefulness in land-use planning is greatest when it is linked to a Geographic Information System (GIS) as shown in this paper. GIS allows TIM outputs, such as constraints to agriculture and site-specific best-management practices, to be identified in a spatially explicit manner.The main advantages of TIM are that it can be done ex ante, it removes the need to define sustainability assessment criteria and indicators, it utilises current understanding of the causes and effects of land degradation and how different land-management practices influence these, and links this knowledge to definite land-management options.     

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.     

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。     

Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region

Landfill siting is a difficult, complex, tedious, and protracted process requiring evaluation of many different criteria. This paper presents a fuzzy multicriteria decision analysis alongside with a geospatial analysis for the selection of landfill sites. It employs a two-stage analysis synergistically to form a spatial decision support system (SDSS) for waste management in a fast-growing urban region, south Texas. The first-stage analysis makes use of the thematic maps in Geographical information system (GIS) in conjunction with environmental, biophysical, ecological, and socioeconomic variables leading to support the second-stage analysis using the fuzzy multicriteria decision-making (FMCDM) as a tool. It differs from the conventional methods of integrating GIS with MCDM for landfill selection because the approach follows two sequential steps rather than a full-integrated scheme. The case study was made for the city of Harlingen in south Texas, which is rapidly evolving into a large urban area due to its vantage position near the US-Mexico borderlands. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of FMCDM method to identify the most suitable site using the information provided by the regional experts with reference to five chosen criteria. Research findings show that the proposed SDSS may aid in recognizing the pros and cons of potential areas for the localization of landfill sites in any study region. Based on initial GIS screening and final FMCDM assessment, "site 1" was selected as the most suitable site for the new landfill in the suburban area of the City of Harlingen. Sensitivity analysis was performed using Monte Carlo simulation where the decision weights associated with all criteria were varied to investigate their relative impacts on the rank ordering of the potential sites in the second stage. Despite variations of the decision weights within a range of 20%, it shows that "site 1" remains its comparative advantage in the final site selection process.     

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.     

URBAN IMPACTS ON PHYSICAL STREAM CONDITION: EFFECTS OF SPATIAL SCALE,CONNECTIVITY, AND LONGITUDINAL TRENDS1

ABSTRACT: An assessment of physical conditions in urban streams of the Puget Sound region, coupled with spatially explicit watershed characterizations, demonstrates the importance of spatial scale, drainage network connectivity, and longitudinal downstream trends when considering the effects of urbanization on streams. A rapid stream assessment technique and a multimetric index were used to describe the physical conditions of multiple reaches in four watersheds. Watersheds were characterized using geographic information system (GIS) derived landscape metrics that represent the magnitude of urbanization at three spatial scales and the connectivity of urban land. Physical conditions, as measured by the physical stream conditions index (PSCI), were best explained for the watersheds by two landscape metrics: quantity of intense and grassy urban land in the subwatershed and quantity of intense and grassy urban land within 500 m of the site (R²= 0.52, p > 0.0005). A multiple regression of PSCI with these metrics and an additional connectivity metric (proximity of a road crossing) provided the best model for the three urban watersheds (R²= 0.41, p > 0.0005). Analyses of longitudinal trends in PSCI within the three urban watersheds showed that conditions improved when a stream flowed through an intact riparian buffer with forest or wetland vegetation and without road crossings. Results demonstrate that information on spatial scale and patterns of urbanization is essential to understanding and successfully managing urban streams.     

Pimp Your Landscape: A Tool for Qualitative Evaluation of the Effects of Regional Planning Measures on Ecosystem Services

The article presents the platform “Pimp your landscape” (PYL), which aims firstly at the support of planners by simulating alternative land-use scenarios and by an evaluation of benefits or risks for regionally important ecosystem services. Second, PYL supports an integration of information on environmental and landscape conditions into impact assessment. Third, PYL supports the integration of impacts of planning measures on ecosystem services. PYL is a modified 2-D cellular automaton with GIS features. The cells have the major attribute “land-use type” and can be supplemented with additional information, such as specifics regarding geology, topography and climate. The GIS features support the delineation of non-cellular infrastructural elements, such as roads or water bodies. An evaluation matrix represents the core element of the system. In this matrix, values in a relative scale from 0 (lowest value) to 100 (highest value) are assigned to the land-use types and infrastructural elements depending on their effect on ecosystem services. The option to configure rules for describing the impact of environmental attributes and proximity effects on cell values and land-use transition probabilities is of particular importance. User interface and usage of the platform are demonstrated by an application case. Constraints and limits of the recent version are discussed, including the need to consider in the evaluation, landscape-structure aspects such as patch size, fragmentation and spatial connectivity. Regarding the further development, it is planned to include the impact of land management practices to support climate change adaptation and mitigation strategies in regional planning.     

Modelling of light pollution in suburban areas using remotely sensed imagery and GIS

This paper describes a methodology for modelling light pollution using geographical information systems (GIS) and remote sensing (RS) technology. The proposed approach attempts to address the issue of environmental assessment in sensitive suburban areas. The modern way of life in developing countries is conductive to environmental degradation in urban and suburban areas. One specific parameter for this degradation is light pollution due to intense artificial night lighting. This paper aims to assess this parameter for the Athens metropolitan area, using modern analytical and data capturing technologies. For this purpose, night-time satellite images and analogue maps have been used in order to create the spatial database of the GIS for the study area. Using GIS advanced analytical functionality, visibility analysis was implemented. The outputs for this analysis are a series of maps reflecting direct and indirect light pollution around the city of Athens. Direct light pollution corresponds to optical contact with artificial night light sources, while indirect light pollution corresponds to optical contact with the sky glow above the city. Additionally, the assessment of light pollution in different periods allows for dynamic evaluation of the phenomenon. The case study demonstrates high levels of light pollution in Athens suburban areas and its increase over the last decade.     

INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS1

ABSTRACT: Significant land cover changes have occurred in the watersheds that contribute runoff to the upper San Pedro River in Sonora, Mexico, and southeast Arizona. These changes, observed using a series of remotely sensed images taken in the 1970s, 1980s, and 1990s, have been implicated in the alteration of the basin hydrologic response. The Cannonsville subwatershed, located in the Catskill/Delaware watershed complex that delivers water to New York City, provides a contrast in land cover change. In this region, the Cannonsville watershed condition has improved over a comparable time period. A landscape assessment tool using a geographic information system (GIS) has been developed that automates the parameterization of the Soil and Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS) hydrologic models. The Automated Geospatial Watershed Assessment (AGWA) tool was used to prepare parameter input files for the Upper San Pedro Basin, a subwatershed within the San Pedro undergoing significant changes, and the Cannonsville watershed using historical land cover data. Runoff and sediment yield were simulated using these models. In the Cannonsville watershed, land cover change had a beneficial impact on modeled watershed response due to the transition from agriculture to forest land cover. Simulation results for the San Pedro indicate that increasing urban and agricultural areas and the simultaneous invasion of woody plants and decline of grasslands resulted in increased annual and event runoff volumes, flashier flood response, and decreased water quality due to sediment loading. These results demonstrate the usefulness of integrating remote sensing and distributed hydrologic models through the use of GIS for assessing watershed condition and the relative impacts of land cover transitions on hydrologic response.     

A Biological Assessment of Streams in the Eastern United States Using a Predictive Model for Macroinvertebrate Assemblages1

Abstract: A predictive model (RIVPACS‐type) for benthic macroinvertebrates was constructed to assess the biological condition of 1,087 streams sampled throughout the eastern United States from 1993‐2003 as part of the U.S. Geological Survey’s National Water‐Quality Assessment Program. A subset of 338 sites was designated as reference quality, 28 of which were withheld from model calibration and used to independently evaluate model precision and accuracy. The ratio of observed (O) to expected (E) taxa richness was used as a continuous measure of biological condition, and sites with O/E values <0.8 were classified as biologically degraded. Spatiotemporal variability of O/E values was evaluated with repeated annual and within‐site samples at reference sites. Values of O/E were regressed on a measure of urbanization in three regions and compared among streams in different land‐use settings. The model accurately predicted the expected taxa at validation sites with high precision (SD = 0.11). Within‐site spatial variability in O/E values was much larger than annual and among‐site variation at reference sites and was likely caused by environmental differences among sampled reaches. Values of O/E were significantly correlated with basin road density in the Boston, Massachusetts (p < 0.001), Birmingham, Alabama (p = 0.002), and Green Bay, Wisconsin (p = 0.034) metropolitan areas, but the strength of the relations varied among regions. Urban streams were more depleted of taxa than streams in other land‐use settings, but larger networks of riparian forest appeared to mediate biological degradation. Taxa that occurred less frequently than predicted by the model were those known to be generally intolerant of a variety of anthropogenic stressors.     

Application of the DPSIR framework to environmental degradation assessment in northern Ghana

In many communities in northern Ghana, the environment has been altered by complex natural and human driven forces with significant impact on the lives of their inhabitants. The need to formulate an improved, holistic and consistent methodological approach to assess the problem is critical for sustainable natural resource management. This paper examines the potential of the DPSIR environmental assessment framework utilizing GIS‐based participatory methodology in the assessment of environmental degradation in northern Ghana. Community truthing tools such as key informant interviews, focus group discussions, participant observation and participatory Geographical Information Systems (GIS) were employed as a means of soliciting societal responses integrated to conventional GIS spatial analysis to measure the indicators of the Driving force–Pressure–State–Impacts–Response (DPSIR) assessment framework. Post classification GIS imagery results show a marked natural vegetation decrease of 634 km2 (42%) of the study area with a corresponding increase of 600 km² (39%) of grasses and built‐up and barren environment in the period of 14 years from 1990 to 2004. This is attributed to extreme climatic conditions and human driven causes such as poverty, population growth, migration and land tenure system. Poverty reduction strategies, amendment of the Mining and Mineral Law (PNDC law 153), improvement of the existing land tenure system and the control of migrants and Fulani herdsmen from neighbouring Burkina Faso were some of the solutions selected by the research participants, to be emphasized in the National Environmental Action Plan (EPA Act 490). This paper concludes that the DPSIR environmental assessment framework is an effective means of organizing complex environmental information to facilitate policy decision making.     

Soil erosion and non-point source pollution impacts assessment with the aid of multi-temporal remote sensing images

Soil erosion associated with non-point source pollution is viewed as a process of land degradation in many terrestrial environments. Careful monitoring and assessment of land use variations with different temporal and spatial scales would reveal a fluctuating interface, punctuated by changes in rainfall and runoff, movement of people, perturbation from environmental disasters, and shifts in agricultural activities and cropping patterns. The use of multi-temporal remote sensing images in support of environmental modeling analysis in a geographic information system (GIS) environment leading to identification of a variety of long-term interactions between land, resources, and the built environment has been a highly promising approach in recent years. This paper started with a series of supervised land use classifications, using SPOT satellite imagery as a means, in the Kao-Ping River Basin, South Taiwan. Then, it was designed to differentiate the variations of eight land use patterns in the past decade, including orchard, farmland, sugarcane field, forest, grassland, barren, community, and water body. Final accuracy was confirmed based on interpretation of available aerial photographs and global positioning system (GPS) measurements. Finally, a numerical simulation model (General Watershed Loading Function, GWLF) was used to relate soil erosion to non-point source pollution impacts in the coupled land and river water systems. Research findings indicate that while the decadal increase in orchards poses a significant threat to water quality, the continual decrease in forested land exhibits a potential impact on water quality management. Non-point source pollution, contributing to part of the downstream water quality deterioration of the Kao-Ping River system in the last decade, has resulted in an irreversible impact on land integrity from a long-term perspective.