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.     

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.     

Conservation strategies for effective land management of protected areas using an erosion prediction information system (EPIS)

This research demonstrates the predictive modeling capabilities of a geographic information system (GIS)-based soil erosion potential model to assess the effects of implementing land use change within a tropical watershed. The Revised Universal Soil Loss Equation (RUSLE) was integrated with a GIS to produce an Erosion Prediction Information System (EPIS) and modified to reflect conditions found in the mountainous tropics. Research was conducted in the Zenzontia subcatchment of the Río Ayuquíla, located within the Sierra de Manantlán Biosphere Reserve (SMBR), México. Expanding agricultural activities within this area will accentuate the already high rate of soil erosion and resultant sediment loading occurring in the Río Ayuquíla. Two land-use change scenarios are modeled with the EPIS: (1) implementation of soil conservation practices in erosion prone locations; and (2) selection of sites for agricultural expansion which minimize potential soil loss. Confronted with limited financial resources and the necessity for expedient action, managers of the SMBR can draw upon the predictive capacity of the EPIS to facilitate rapid and informed land-use planning decisions.     

Testing a GIS Model of Habitat Suitability for a Declining Grassland Bird

Demand for information that can be used to manage loggerhead shrikes has recently increased because of concern over declining populations and loss of open, non-forested habitat. A previously-developed habitat model was modified to predict shrike habitat quality on Fort Riley Military Reservation (FRMR) in Kansas. Shrike habitat suitability indices were calculated based on the amount of potential and usable foraging habitat, and the number of potential nesting sites within a specified area. Interpretation of high quality digital photographs was used to delineate land cover classes, hedgerows and tree counts. These data were entered into a geographic information system (GIS) as individual data sets. The shrike habitat model was then employed to produce a GIS database predicting low, moderate, and high quality shrike habitat throughout the Reservation. Model results indicated that 67% of the Reservation was suitable habitat for loggerhead shrikes. Although over 80% of FRMR was mapped as grassland, the presence of few to several isolated trees or hedgerows was identified as a key factor in modeling habitat suitability. The accuracy of the GIS model was 82% in predicting suitable (moderate and high quality) loggerhead shrike habitat using an independent set of 66 recent shrike observations. The number of potential nesting sites and percent cover of usable foraging habitat were significantly related to habitat suitability of the sites occupied by shrikes.     

Measurement of the scarcity of soil in agriculture

The paper defines the concept of land degradation and costs and effects of soil erosion. Through the concept of optimal levels of soil erosion, a conceptual model of the social costs of soil degradation is elaborated. The discussion focuses on the measurement aspects of the economic scarcity of soil in the agriculture sector. Reliable estimates of the true impacts of soil degradation can only be made if data on marginal damage costs and marginal conservation costs are available. The different scarcity indicators are evaluated and competitive land rental prices are considered as appropriate in indicating soil scarcity in agriculture.     

Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing

Sediment transport from steep slopes and agricultural lands into the Uluabat Lake (a RAMSAR site) by the Mustafakemalpasa (MKP) River is a serious problem within the river basin. Predictive erosion models are useful tools for evaluating soil erosion and establishing soil erosion management plans. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Turkey and the rest of the world. This research integrates the RUSLE within a geographic information system environment to investigate the spatial distribution of annual soil loss potential in the MKP River Basin. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index: The topographic factor was developed from a digital elevation model; the K factor was determined from a combination of the soil map and the geological map; and the land cover factor was generated from Landsat-7 Enhanced Thematic Mapper (ETM) images. According to the model, the total soil loss potential of the MKP River Basin from erosion by water was 11,296,063?Mg?year(-1) with an average soil loss of 11.2?Mg?year(-1). The RUSLE produces only local erosion values and cannot be used to estimate the sediment yield for a watershed. To estimate the sediment yield, sediment-delivery ratio equations were used and compared with the sediment-monitoring reports of the Dolluk stream gauging station on the MKP River, which collected data for >41?years (1964-2005). This station observes the overall efficiency of the sediment yield coming from the Orhaneli and Emet Rivers. The measured sediment in the Emet and Orhaneli sub-basins is 1,082,010?Mg?year(-1) and was estimated to be 1,640,947?Mg?year(-1) for the same two sub-basins. The measured sediment yield of the gauge station is 127.6?Mg?km(-2)?year(-1) but was estimated to be 170.2?Mg?km(-2) year(-1). The close match between the sediment amounts estimated using the RUSLE-geographic information system (GIS) combination and the measured values from the Dolluk sediment gauge station shows that the potential soil erosion risk of the MKP River Basin can be estimated correctly and reliably using the RUSLE function generated in a GIS environment.     

Optimal Land Use Management for Soil Erosion Control by Using an Interval-Parameter Fuzzy Two-Stage Stochastic Programming Approach

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China’s Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10⁹ $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.     

Land Use Change and Land Degradation in Southeastern Mediterranean Spain

The magnitude of the environmental and social consequences of soil erosion and land degradation in semiarid areas of the Mediterranean region has long been recognized and studied. This paper investigates the interrelationship between land use/cover (LULC) changes and land degradation using remotely sensed and ancillary data for southeastern Spain. The area of study, the Xaló River catchment situated in the north of the Alicante Province, has been subjected to a number of LULC changes during the second half of the 20th century such as agricultural abandonment, forest fires, and tourist development. Aerial photographs dating back to 1956 were used for the delineation of historic LULC types; Landsat ETM+ data were used for the analysis and mapping of current conditions. Two important indicators of land degradation, namely, susceptibility to surface runoff and soil erosion, were estimated for the two dates using easily parametrizable models. The comparison of 1956 to 2000 conditions shows an overall “recuperating” trend over the catchment and increased susceptibility to soil erosion only in 3% of the catchment area. The results also identify potential degradation hot-spots where mitigation measures should be taken to prevent further degradation. The readily implemented methodology, based on modest data requirements demonstrated by this study, is a useful tool for catchment to regional scale land use change and land degradation studies and strategic planning for environmental management.     

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.     

Effects of climate and land use changes on groundwater resources in coastal aquifers

To estimate the freshwater loss in coastal aquifers due to salinisation, a numerical model based on the sharp interface assumption has been introduced. The developed methodology will be useful in areas where limited hydrological data are available. This model will elaborate on the changes in fresh groundwater loss with respect to climate change, land use pattern and hydrologic soil condition. The aridity index has been introduced to represent the variations in precipitation and temperature. The interesting finding is that the deforestation leads to increase groundwater recharge in arid areas, because deforestation leads to reduce evapotranspiration even though it favors runoff. The combined climate and land use scenarios show that when the aridity index is less than 60, the agricultural lands give higher groundwater recharge than other land use patterns for all hydrologic soil conditions. The calculated recharge was then used to estimate the freshwater-saltwater interface and percentage of freshwater loss due to salinity intrusion. We found that in arid areas, the fresh groundwater loss increases as the percentage of forest cover increases. The combined effects of deforestation and aridity index on fresh groundwater loss show that deforestation causes an increase in the recharge and existing fresh groundwater resource in areas having low precipitation and high temperature (arid climates).     

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.     

COMPARATIVE EVALUATION OF LAND COVER DATA SOURCES FOR EROSION PREDICTION1

ABSTRACT: A fundamental problem in protecting surface drinking water supplies is the identification of sites highly susceptible to soil erosion and other forms of nonpoint source (NPS) pollution. The New York City Department of Environmental Protection is trying to identify erodible sites as part of a program aimed at avoiding costly filtration. New York City's 2,000 square mile watershed system is well suited for analysis with geographic information systems (GIS); an increasingly important tool to determine the spatial distribution of sensitive NPS pollution areas. This study used a GIS to compare three land cover sources for input into the Modified Universal Soil Loss Equation (MUSLE), a model estimating soil loss from rangeland and forests, for a tributary watershed within New York City's water supply system. Sources included both conventional data (aerial photography) and Landsat data (MSS and TM images). Although land cover classifications varied significantly across these sources, location-specific and aggregate watershed predictions of the MUSLE were very similar. We conclude that using Landsat TM imagery with a hybrid classification algorithm provides a rapid, objective means of developing large area land cover databases for use in the MUSLE, thus presenting an attractive alternative to photo interpretation.     

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.     

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.     

Assessing Land-Use Impacts on Natural Resources

/ Much information is available on changes that occur in natural resources from both spatially-explicit data on environmental conditions and models of the interactions of these conditions and resources with human activities. The strategy for assessing land-use impacts on natural resources developed in this paper provides a framework for using relevant data and models to address questions of how management practices can promote both use and protection of resources. This assessment strategy integrates spatially explicit environmental data using geographic information systems (GIS) with computer models that simulate changes in land cover in response to land-use impacts. The computer models also simulate susceptibility of species to changes in habitat suitability and landscape patterns. The approach is applied to management of limestone barrens on the Oak Ridge Reservation in East Tennessee. Potential limestone barrens habitats are identified by overlaying appropriate soils, geology, slope, and land-use/land-cover conditions. Their validity is tested against known sites containing rare species that occur in these habitats. The location of habitats at risk in the aftermath of human activities is determined by using an available area model that identifies the size and proximity of sites that particular types of species can no longer use as habitat. The resulting risk map can be used in land management planning. The approach uses readily available in situ and remotely sensed data and is applicable to a wide range of locations and land-use scenarios. This approach can be refined based on needs identified by land managers and on the sensitivity of the results to the resolution of available resource information.KEY WORDS: Land management; Assessment; Habitat characterization; Limestone barrens; Ecological modeling; Geographic information systems     

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.     

Land Evaluation for Maize Based on Fuzzy Set and Interpolation

The objective of this article is to apply fuzzy set and interpolation techniques for land suitability evaluation for maize in Northern Ghana. Land suitability indices were computed at point observations using the Semantic Import (SI) model, whereas spatial interpolation was carried out by block kriging. Interpolated land suitability shows a high correlation (R2 = 0.87) with observed maize yield at the village level. This indicates that land suitability is closely related to maize yield in the study area. Membership functions were further used to assess the degree of limitation of land characteristics to maize. Sixty percent of the data has membership functions ranging from 0.23 for ECEC to 1.00 for drainage. ECEC, organic C, and clay are the major constraints to maize yield. The use of the fuzzy technique is helpful for land suitability evaluation, especially in applications in which subtle differences in soil quality are of a major interest. Furthermore, the use of kriging that exploits spatial variability of data is useful in producing continuous land suitability maps and in estimating uncertainties associated with predicted land suitability indices.     

Integrated Use of GLEAMS and GIS to Prevent Groundwater Pollution Caused by Agricultural Disposal of Animal Waste

/ In modern intensive animal farming the disposal of a large amount of waste is of great concern, as, if not properly performed, it can cause the pollution of water, mainly because of the high content of nitrate and phosphate. This paper presents the results of a study intended to assess the environmental sustainability of animal waste disposal on agricultural soils in the alluvial plain of the River Chiana (Tuscany, Italy), a particularly sensitive area because of the high vulnerability of the shallow aquifer and of the intensive agricultural and breeding activities. With this aim, a strategy has been employed, that consists of the integrated use of a management model and GISs. The consequences on groundwater of applying animal waste to different kind of soils and crop arrangements have been simulated by means of the management model GLEAMS (Groundwater Loading Effects of Agricultural Management Systems, ver 2.01). As the huge amount of data required by such a sophisticated model does not allow applications at a scale larger than the field size, IDRISI and GRASS GIS packages have been used to divide the study area into land units, with homogeneous environmental characteristics, and then to generalize on these units the outputs of the model. The main conclusions can be synthesized as follows: The amount of animal waste produced in some of the investigated areas (i.e., municipal territory) is greater than that disposable on their own agricultural soil with no risks to the groundwater; consequently a cooperative approach among municipalities is necessary in order to plan waste disposal in a comprehensive and centralized way.KEY WORDS: Land use; Animal waste disposal; Groundwater protection; GIS, Management models     

Land Evaluation in a Salt-Affected Irrigated District Using an Index of Productive Potential

2 semiarid irrigated area with salt-affected soils. The available soil map is at 1:100,000 scale and its mapping units are used for the land evaluation with the FAO framework. These data are then elaborated using the index value method. This procedure gives a map of land evaluation units and a table that rates the productive potential of these units for six crops: alfalfa, barley, maize, rice, sunflower, and wheat.     

Land Suitability Assessment in the Catchment Area of Four Southwestern Atlantic Coastal Lagoons: Multicriteria and Optimization Modeling

In the present study, a land suitability assessment was conducted in the basin of four Uruguayan coastal lagoons (Southwestern Atlantic) to analyze the productive development while minimizing eutrophication, biodiversity loss and conflicts among different land uses. Suitable land for agriculture, forest, livestock ranching, tourism and conservation sectors were initially established based on a multi-attribute model developed using a geographic information system. Experts were consulted to determine the requirements for each land use sector and the incompatibilities among land use types. The current and potential conflicts among incompatible land use sectors were analyzed by overlapping land suitability maps. We subsequently applied a multi-objective model where land (pixels) with similar suitability was clustered into "land suitability groups", using a two-phase cluster analysis and the Akaike Information Criterion. Finally, a linear programming optimization procedure was applied to allocate land use sectors into land suitable groups, maximizing total suitability and minimizing interference among sectors. Results indicated that current land use overlapped by 4.7?% with suitable land of other incompatible sectors. However, the suitable land of incompatible sectors overlapped in 20.3?% of the study area, indicating a high potential for the occurrence of future conflict. The highest competition was between agriculture and conservation, followed by forest and agriculture. We explored scenarios where livestock ranching and tourism intensified, and found that interference with conservation and agriculture notably increased. This methodology allowed us to analyze current and potential land use conflicts and to contribute to the strategic planning of the study area.