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。     

Modeling Habitat Suitability for Complex Species Distributions by Environmental-Distance Geometric Mean

This paper presents a new habitat suitability modeling method whose main properties are as follows: (1) It is based on the density of observation points in the environmental space, which enables it to fit complex distributions (e.g. nongaussian, bimodal, asymmetrical, etc.). (2) This density is modeled by computing the geometric mean to all observation points, which we show to be a good trade-off between goodness of fit and prediction power. (3) It does not need any absence information, which is generally difficult to collect and of dubious reliability. (4) The environmental space is represented either by an expert-selection of standardized variables or the axes of a factor analysis [in this paper we used the Ecological Niche Factor Analysis (ENFA)].We first explain the details of the geometric mean algorithm and then we apply it to the bearded vulture (Gypaetus barbatus) habitat in the Swiss Alps. The results are compared to those obtained by the median algorithm and tested by jack-knife cross-validation. We also discuss other related algorithms (BIOCLIM, HABITAT, and DOMAIN). All these analyses were implemented into and performed with the ecology-oriented GIS software BIOMAPPER 2.0.The results show the geometric mean to perform better than the median algorithm, as it produces a tighter fit to the bimodal distribution of the bearded vulture in the environmental space. However, the median algorithm being quicker, it could be preferred when modeling more usual distribution.     

Managing Radioactively Contaminated Land: Implications for Habitat Diversity

Radioactive contamination of agricultural land may necessitate long-term changes in food production systems, through application of selected countermeasures, in order to reduce the accumulation of radionuclides in food. We quantified the impact of selected countermeasures on habitat diversity, using the hypothetical case of two agricultural areas in Finland. The management scenarios studied were conversions from grassland to cereal production and from grassland and crop production to afforestation. The two study sites differed with respect to present agricultural production: one being predominantly cereal production and seminatural grasslands, while the other was dominated by intensive grass and dairy production. Some of the management scenarios are expected to affect landscape structures and habitat diversity. These potential changes were assessed using a spatial pattern analysis program in connection with geographic information systems. The studied landscape changes resulted in a more monotonous landscape structure compared to the present management, by increasing the mean habitat patch size, reducing the total habitat edge length and reducing the overall habitat diversity calculated by the Shannon diversity index. The degree of change was dependent on the present agricultural management practice in the case study sites. Where dairy production was predominant, the landscape structure changes were mostly due to conversion of intensive pastures and grasslands to cereal production. In the area dominated by cereal production and seminatural grasslands, the greatest predicted impacts resulted from afforestation of meadows and pastures. The studied management changes are predicted to reduce biodiversity at the species level as well as diminishing species-rich habitats. This study has predicted prominent side effects in habitat diversity resulting from application of management scenarios. These potential long-term impacts should be considered by decision-makers when planning future strategies in the event of radionuclide deposition.     

Evaluation of Land Condition Trend Analysis for Birds on a Kansas Military Training Site

/ Land condition trend analysis (LCTA) is a long-term monitoring program used on military training lands to identify ecological changes that result from training and management activities. We initiated LCTA at the Kansas Army National Guard Training Facility (KANGTF) in Saline County, Kansas, in March 1998. This paper evaluates the LCTA methodology for birds by comparing LCTA results with a modified methodology designed to place sampling transects in field-identified rather than satellite-identified land-cover types. In the satellite-identified land-cover types developed at the site, grassland habitats included a large component of woody vegetation, which resulted in poor resolution of bird assemblages associated with the different land-cover types. Using these cover classes, mixed grass prairie included five grass/forb (g/f) and 10 woody-dependent species; old-field included four g/f and four woody-dependent species; and riparian included one g/f and six woody-dependent species. LCTA sampling was too limited in the ecologically important riparian woodland habitat with the result that bird species were not adequately sampled there. In the alternate sampling strategy, we identified three land-cover classes (grassland, hedgerow, and riparian woodland) by field reconnaissance and increased sampling in the riparian woodland. Grassland included six g/f and three woody-dependent species; hedgerow included six g/f and 20 woody-dependent species, and riparian included two g/f and 19 woody-dependent species. The modifications greatly improved the resolution of bird assemblages associated with land-cover classes at the KANGTF. Use of the alternative sampling method should improve the ability to detect long-term trends in the bird communities.     

Testing the Use of a Land Cover Map for Habitat Ranking in Boreal Forests

Habitat loss and modification is one of the major threats to biodiversity and the preservation of conservation values. We use the term conservation value to mean the benefit of nature or habitats for species. The importance of identifying and preserving conservation values has increased with the decline in biodiversity and the adoption of more stringent environmental legislation. In this study, conservation values were considered in the context of land-use planning and the rapidly increasing demand for more accurate methods of predicting and identifying these values. We used a k-nearest neighbor interpreted satellite (Landsat TM) image classified in 61 classes to assess sites with potential conservation values at the regional and landscape planning scale. Classification was made at the National Land Survey of Finland for main tree species, timber volume, land-use type, and soil on the basis of spectral reflectance in satellite image together with broad numerical reference data. We used the number and rarity of vascular plant species observed in the field as indicators for potential conservation values. We assumed that significant differences in the species richness, rarity, or composition of flora among the classes interpreted in the satellite image would also mean a difference in conservation values among these classes. We found significant differences in species richness among the original satellite image classes. Many of the classes examined could be distinguished by the number of plant species. Species composition also differed correspondingly. Rare species were most abundant in old spruce forests (>200 m³/ha), raising the position of such forests in the ranking of categories according to conservation values. The original satellite image classification was correct for 70% of the sites studied. We concluded that interpreted satellite data can serve as a useful source for evaluating habitat categories on the basis of plant species richness and rarity. Recategorization of original satellite image classification into such new conservation value categories is challenging because of the variation in species composition among the new categories. However, it does not represent a major problem for the purposes of early-stage land-use planning. Benefits of interpreted satellite image recategorization as a rapid conservation value assessment tool for land-use planners would be great.     

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.     

Tijuana Childhood Lead Risk Assessment Revisited: Validating a GIS Model with Environmental Data

The objective of this research was to determine the spatial distributions of childhood lead poisoning and soil lead contamination in urban Tijuana. The Bocco–Sanchez model of point-source emissions was evaluated in terms of validity and reliability. We compared the model's predicted vulnerable populations with observed cases of childhood lead poisoning in Tijuana, identified fixed point sources in the field, and analyzed 76 soil samples from 14 sites. The soil lead results were compared to the blood lead analyses performed on Tijuana children whose blood lead levels were ≥10 μg/dL, who reported that they did not use lead-glazed ceramics for cooking or storing food (n = 63). Using GIS, predicted vs observed risk areas were assessed by examining spatial patterns, including the distribution of cases per designated risk area. Chi-square analysis of expected vs observed values did not differ significantly at the p = 0.02 level, showing that the model was strikingly accurate in predicting the distribution of subjects with elevated blood lead. Results reveal that while point sources are significant, other sources of lead exposure are also important. The relative public health risk from exposure to lead in an urban setting may be assessed by distinguishing among sources of exposure and associating concentrations to blood lead levels. The results represent an iterative approach in environmental health research by linking environmental and human biomarker lead concentrations and using these results to validate an environmental model of risk to lead exposure.     

Selecting suitable sites for animal waste application using a raster GIS

Rapid growth of intensive animal industries in southeast Queensland, Australia, has led to large volumes of animal waste production, which posses serious environmental problems in the Murray Darling Basin (MDB). This study presents a method of selecting sites for the safe application of animal waste as fertiliser to agricultural land. A site suitability map for the Westbrook subcatchment within the MDB was created using a geographic information system (GIS)-based weighted linear combination (WLC) model. The factors affecting the suitability of a site for animal waste application were selected, and digital data sets derived from up to 1:50,000 scale maps were acquired. After initial preprocessing, digital data sets were clipped to the size of the delineated subcatchment boundary producing input factors. These input factors were weighted using the analytical hierarchy process (AHP) that employed an objectives-oriented comparison (OOC) technique to formulate the pairwise comparison matrix. The OOC technique, which is capable of deriving factor weight independently, formulated the weight derivation process by making it more logical and systematic. The factor attributes were classified into multiple classes and weighted using the AHP. The effects of the number of input factors and factor weighting on the areal extent and the degree of site suitability were examined. Due to the presence of large nonagricultural and residential areas in the subcatchment, only 16% of the area was found suitable for animal waste application. The areal extent resulting from this site suitability assessment was found to be dependent on the areal constraints imposed on each input factor, while the degree of suitability was principally a function of the weight distribution between the factors.     

Ecosystem Manipulation Experimentation as a Means of Testing a Biogeochemical Model

2 concentration, and global or regional temperature change. Such model projections are frequently used as the basis or justification for public policy decisions and legislation. A substantial need has therefore arisen to test and substantiate the veracity of mathematical model projections. Unfortunately, environmental models can never be truly validated because natural systems are never closed and model solutions are always nonunique. Partial model confirmation is possible, however, and entails demonstration of agreement between prediction and observation. Experimental ecosystem manipulation provides one of the best, and in many cases only, available basis for model confirmation. The use and potential misuse of data from experimental ecosystem manipulations for model testing is explored using examples drawn from the application of an acid–base chemistry model, MAGIC. As model projections provide an increasingly important basis for public policy decisions, and as both the scientific questions and the models become increasingly complex, it will become critical to provide data from a suite of well-designed ecosystem manipulation experiments in order to evaluate the quality and uncertainty of those model projections and the models upon which they are based.     

Demonstration of GIS Capabilities for Fisheries Management Decisions: Analysis of Acquisition Potential Within the Meramec River Basin

/ Geographic information systems (GIS) allow users to explore possible spatial relations that may exist within their data. At the Missouri Department of Conservation (MDC), GIS data is being used to help make management decisions. Thirteen geographic data layers of the Meramec River Basin, Missouri, were used to help demonstrate the usefulness of GIS for making fisheries management decisions. The data were used to help identify potential acquisition areas within the Meramec River Basin. The basin was separated into 22 strata based on ecoregion boundaries, watershed boundaries, and stream order. Suitability for acquisition was determined for each stratum based on species richness, habitat characteristics, percent of public land, and number of human impacts, such as gravel and ore mining. Eleven strata scored high enough to be recommended as potential acquisition areas. After further evaluation of the 11 strata, three were chosen as areas where available land and willing sellers should be considered. Four strata needed more sampling before land within them should be considered for acquisition. The final four were considered low priority because there was already a considerable amount of public land present in the strata. The analysis was helpful in allowing managers to focus in on a smaller area for acquisition consideration; 91% of the area was eliminated from the analysis. Instead of having to survey every parcel of land that becomes available, parcels that don't fall within the recommended strata can be eliminated without further investigation.     

Degradation Model: A Quantitative EIA Instrument,Acting as a Decision Support System (DSS) for Environmental Management

Environmental assessment of alternative development plans, programs, and policies may bring conflict among decision-makers, particularly when some quantitative measures for decision-making are needed and where cumulative impacts are neglected. Environmental impact assessment (EIA) and environmental economics theories, despite their usefulness, are not capable of addressing those issues and problems alone. In recent years, the decision support system (DSS) has provided some solutions, but mathematical analysis of the system to show the internal structure of the problem is not always possible. To addres the above shortcomings and ongoing problems of decision-making in Iran, a degradation model (DM) was introduced as an instrument of EIA, to act as a DSS for managers. The model is a compromise between knowledge-based decision support systems, detailed models, digested information models, and the basic theorem of environmental economics. In the present study (1996–2000), the model was applied in three provinces of Iran, representing three of four biogeographical regions of Iran. The study area was divided into a set of grids (100 km²). The degradation coefficient (H) was computed for all grids (1333), representing the degree of degradation in the grid. It is obvious that the higher the coefficient the more area is degraded and less prone to further development, and vice versa. In order to provide decision-makers with a set of quantitative measures to observe impacted areas (critical and noncritical) for resource allocation and further development, the degradation coefficients of all grids were classified into categories and criteria, using a fuzzy set theoretic approach. Accordingly, only 24% of study areas are prone to further development. The degradation model as a knowledge-based decision support system has its strengths and weaknesses, but it has solved managers' ongoing problems in Iran and it could be used elsewhere.     

A GIS Model of Subsurface Water Potential for Aquatic Resource Inventory,Assessment, and Environmental Management

Biological, chemical, and physical attributes of aquatic ecosystems are often strongly influenced by groundwater sources. Nonetheless, widespread access to predictions of subsurface contributions to rivers, lakes, and wetlands at a scale useful to environmental managers is generally lacking. In this paper, we describe a neighborhood analysis approach for estimating topographic constraints on spatial patterns of recharge and discharge and discuss how this index has proven useful in research, management, and conservation contexts. The Michigan Rivers Inventory subsurface flux model (MRI-DARCY) used digital elevation and hydraulic conductivity inferred from mapped surficial geology to estimate spatial patterns of hydraulic potential. Model predictions were calculated in units of specific discharge (meters per day) for a 30-m²-cell raster map and interpreted as an index of potential subsurface water flux (shallow groundwater and event through-flow). The model was evaluated by comparison with measurements of groundwater-related attributes at watershed, stream segment, and local spatial scales throughout Lower Michigan (USA). Map-based predictions using MRI-DARCY accounted for 85% of the observed variation in base flow from 128 USGS gauges, 69% of the observed variation in discharge accrual from 48 river segments, and 29% of the residual variation in local groundwater flux from 33 locations as measured by hyporheic temperature profiles after factoring out the effects of climate. Although it does not incorporate any information about the actual water table surface, by quantifying spatial variation of key constraints on groundwater-related attributes, the model provides strata for more intensive study, as well as a useful spatial tool for regional and local conservation planning, fisheries management, wetland characterization, and stream assessment.     

An Aquifer Vulnerability Assessment of the Paluxy Aquifer, Central Texas, USA, Using GIS and a Modified DRASTIC Approach

D epth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and Conductivity of the aquifer). Using such an approach allows one to investigate the potential for groundwater contamination on a regional, rather than site-specific, scale. Based upon data from variables such as soil permeability, depth to water, aquifer hydraulic conductivity, and topography, subjective numerical weightings have been assigned according to the variable's relative importance in regional groundwater quality. The weights for each variable comprise a GIS map layer. These map layers are combined to formulate the final groundwater pollution potential map. Using this method of investigation, the pollution potential map for the study area classifies 47% of the area as having low pollution potential, 26% as having moderate pollution potential, 22% as having high pollution potential, and 5% as having very high pollution potential.     

Development of a GIS tool for qualitative assessment of the Egyptian’s quality of life

A frame work was presented for the assessment of the quality of life through the development of different indicators applied for Egypt. This paper focuses on the assessment of the quality of life using previously developed indicators in the first part of the study. A GIS user-friendly interface was developed to enhance the presentation of the study. This enables non technical users to directly use the developed GIS application to explore different concerns. Three cases were demonstrated in this paper, where an assessment of the quality of life of farmers, civilians, and agricultural investors was attained under specific scenario in each case. Assessment for other cases can still be made by browsing through the dropdown menu for each interest group under the selected scenario. Based on the demonstrated results for the three groups of people, it was found that the quality of life for a certain group of people under the strict scenario is in general less than the quality of life for the same group under the relax scenario.     

Combined use of GIS and environmental indicators for assessment of chemical, physical and biological soil degradation in a Spanish Mediterranean region

Soil is one of the main non-renewable natural resources in the world. In the Valencian Community (Mediterranean coast of Spain), it is especially important because agriculture and forest biomass exploitation are two of the main economic activities in the region. More than 44% of the total area is under agriculture and 52% is forested. The frequently arid or semi-arid climate with rainfall concentrated in few events, usually in the autumn and spring, scarcity of vegetation cover, and eroded and shallow soils in several areas lead to soil degradation processes. These processes, mainly water erosion and salinization, can be intense in many locations within the Valencian Community. Evaluation of soil degradation on a regional scale is important because degradation is incompatible with sustainable development. Policy makers involved in land use planning require tools to evaluate soil degradation so they can go on to develop measures aimed at protecting and conserving soils. In this study, a methodology to evaluate physical, chemical and biological soil degradation in a GIS-based approach was developed for the Valencian Community on a 1/200,000 scale. The information used in this study was obtained from two different sources: (i) a soil survey with more than 850 soil profiles sampled within the Valencian Community, and (ii) the environmental information implemented in the Geo-scientific map of the Valencian Community digitised on an Arc/Info GIS. Maps of physical, chemical and biological soil degradation in the Valencian Community on a 1/200,000 scale were obtained using the methodology devised. These maps can be used to make a cost-effective evaluation of soil degradation on a regional scale. Around 29% of the area corresponding to the Valencian Community is affected by high to very high physical soil degradation, 36% by high to very high biological degradation, and 6% by high to very high chemical degradation. It is, therefore, necessary to draw up legislation and to establish the policy framework for actions focused on preventing soil degradation and conserving its productive potential.     

TUGAI: An Integrated Simulation Tool for Ecological Assessment of Alternative Water Management Strategies in a Degraded River Delta

The development of ecologically sound water allocation strategies that account for the needs of riverine ecosystems is a pressing issue, especially in semiarid river basins. In the Aral Sea Basin, a search for strategies to mitigate ecological and socioeconomic deterioration has been in process since the early 1990s. The Geographic Information System–based simulation tool TUGAI has been developed to support the policy determination process by providing a simple, problem-oriented method to assess ecological effects of alternative water management strategies for the Amudarya River. It combines a multiobjective water allocation model with simple, spatially explicit statistical and rule-based models of landscape dynamics. Changes in environmental conditions are evaluated by a fuzzy habitat suitability index for Populus euphratica, which is the dominant species of the characteristic riverine Tugai forests. Water management scenarios can be developed by altering spatiotemporal water distribution in the delta area or the amount of water inflow into the delta. Outcomes of scenario analysis are qualitative comparisons of the ecological effects of different options for a time period of up to 28 years. The given approach utilizes different types of knowledge, from quantitative hydrological data to qualitative local expert knowledge. The main purpose of the tool is to integrate the knowledge in a comprehensive way to make it available for discussions on alternative policies in moderated workshops with stakeholders. In this article, the modules of the tool, their integration, and three hypothetical scenarios are presented. Based on the experience gained when developing the TUGAI tool, we propose that the general framework can be transferred to other areas where tradeoffs in water allocation between the environment and other water users are of major concern. The potential for a simulation tool to structure and inform a complex resource management situation by involving local experts and stakeholders in the development of possible future scenarios will become increasingly valuable for transparent and participatory resource management.     

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.     

Development and Testing of a Physically Based Model of Streambank Erosion for Coupling with a Basin‐Scale Hydrologic Model SWAT

A comprehensive streambank erosion model based on excess shear stress has been developed and incorporated in the hydrological model Soil and Water Assessment Tool (SWAT). It takes into account processes such as weathering, vegetative cover, and channel meanders to adjust critical and effective stresses while estimating bank erosion. The streambank erosion model was tested for performance in the Cedar Creek watershed in north‐central Texas where streambank erosion rates are high. A Rapid Geomorphic field assessment (RAP‐M) of the Cedar Creek watershed was done adopting techniques developed by the Natural Resources Conservation Service (NRCS), and the stream segments were categorized into various severity classes. Based on the RAP‐M field assessment, erosion pin sites were established at seven locations within the severely eroding streambanks of the watershed. A Monte Carlo simulation was carried out to assess the sensitivity of different parameters that control streambank erosion such as critical shear stress, erodibility, weathering depth, and weathering duration. The sensitive parameters were adjusted and the model was calibrated based on the bank erosion severity category identified by the RAP‐M field assessment. The average observed erosion rates were in the range 25‐367 mm year^?1. The SWAT model was able to reasonably predict the bank erosion rates within the range of variability observed in the field (R² = 0.90; E = 0.78). Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.