Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Regional impervious surface estimation: an urban heat island application

This paper describes a GIS-based estimation method that can be used to forecast future amounts of impervious surface as a mitigation measure for urban heat island effect in a metropolitan region. The method is unique because it employs a regression model that links the existing amount of impervious surface to population and employment at the census tract level. This approach provides a means to forecast future amounts of impervious surface based on projected population and employment. The method also includes a detailed analysis of high-resolution aerial photography to divide impervious surfaces into different categories. Subdividing impervious surfaces is necessary to evaluate potential urban heat island mitigation policies for different types of impervious surface. The analysis here shows that the impervious surface in the metropolitan Atlanta region will increase to 2638 km2 2. “The Albedo is defined as the hemispherical reflectivity averaged over the solar spectrum. A perfect reflector has a = 1, and a perfect absorber has a = 0” (Pomerantz et al. 1999 Pomerantz, M. 1999. Reflective surfaces for cooler buildings and cities. Philosophical magazine B, 79: 1457–1476. [Taylor & Francis Online], [Web of Science ®] [Google Scholar], p. 1458). View all notes in 2030, an increase of 45% from 2000. The most common type of impervious surface is dark-coloured pavement. Within this study area, the analyses showed that two-thirds of impervious surfaces are dark. Replacing dark pavement with light pavement materials, therefore, represents an important opportunity to mitigate the urban heat island effect in the Atlanta region.     

基于GIS的陇南灾区建设用地适宜性评价

以甘肃省陇南市地震灾区为例,运用AHP法和GIS空间分析方法,综合考虑了地区气候地形、人口分布、交通区位、经济基础和地震易发程度等影响因子,并通过用地适宜性分区,对地区自然生态和社会经济格局进行重新审视,从协调资源、环境、人口、经济的相互关系出发,空间开发强调因地制宜,即让开发成本低、资源环境容量大的地区承担高强度的开发建设活动;而让生态和地质环境脆弱、开发难度大的区域承担生态维护和生态产业功能。结果表明：陇南市用地适宜性呈现出极大的地缘差异性,适宜发展用地主要分布于东北部丘陵盆地地区,南部地区以限制发展用地为主,西北部地区由适度发展用地和限制发展用地构成。其中适宜发展用地占地区总面积1727%,适度发展用地占4441%,限制发展用地占3831%。     

Gas/particle partitioning of atmospheric PCDD/Fs in a satellite town in Eastern China

Gas/particle partitioning of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in ambient air was investigated in a satellite town in Eastern China from April 2007 to January 2008 comprehending large temperature variations (from 3 to 34 °C, daily average). Molecular weight, molecular structure and ambient temperatures are the three major factors that govern the gas/particle partitioning of atmospheric PCDD/Fs throughout the year. Generally, good agreements were obtained (except for winter) between measured particulate fractions and theoretical estimates of both the Junge–Pankow adsorption model and Harner Bidleman absorption model using different sets of subcooled liquid vapor pressure and octanol–air partition coefficient (K_oa), respectively. Models utilizing estimates, derived from gas chromatographic retention indices (GC-RIs), are more accurate than that of entropy-based. Moreover, during winter, the K_oa-based model using the GC-RIs approach performs better on lower chlorinated PCDD/Fs than that of -based. Furthermore, possible sources of mismatch between measured and predicted values in winter (3–7 °C) were discussed. Gas adsorption artifact was demonstrated to be of minor importance for the phenomena observed. On the other hand, large deviations of slopes (m_r) and intercepts (b_r) in logK_p vs. plots from theoretical values are observed in the literature data and these are found to be linearly correlated with ambient temperatures (P<0.001) in this study. This indicates that the non-equilibrium partitioning of PCDD/Fs in winter may be significantly influenced by the colder temperatures that may have slowed down the exchange between gaseous and particulate fractions.     

Comprehensive Assessment on Tourism Eco-environment of Gansu Province Based on Spatial Data

The article studies tourism eco-environment of 14 cities of Gangsu Province, China, based on GIS with many kinds of multi-subject spatial database, such as remote sensing data, observation data and literature data. The research results were as follows. First, spatial features of 14 cities＇ tourism eco-environment are displayed with five levels of vulnerability respectively. The vulnerability in Gansu becomes worse from Gannan City, located in southern Gansu to Hexi Corridor which lies in northwestern Gansu. Second, the areas of above the middle vulnerability level make up 75% of the total areas of Gansu Province. Third, more than 70% of high-level human and natural tourism resources are in the areas with high vulnerability eco-environment. Fourth, it is crucial to develop comprehensive tourism industry in order to improve the harmonious development between tourism industry and eco-environment in Gansu Province.     

Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach

The perils of unplanned urbanization and increasing pressure of human activities on hydro-geomorphologic system often result in modification of the existing recharge mechanism, which leads to many environmental consequences. In the present research, an attempt has been made to investigate the applicability of remote sensing and geographical information system (GIS) in dealing with spatial and temporal variability of dynamic phenomena, like urbanization and its impact on groundwater. This paper covers primarily, quantitative and qualitative impacts of urban growth on the behavior of aquifer in Ajmer city (India). Urban growth of the Ajmer city in last 17 years has been estimated from the satellite images. Database related to urbanization and groundwater has been created in GIS. Groundwater recharge has been computed using a water balance approach known as Water Level Fluctuation Methodology. Recharge estimation methodology has been implemented in GIS to introduce the spatial variability of hydro-geological characteristics. Further, temporal and spatial variations in groundwater quality and quantity have been correlated with urban growth using overlay analysis in GIS. The study reveals a general decline in water table and quality with urbanization. Further, remote sensing and GIS technologies have been found useful in assessment of spatial and temporal phenomena of urbanization and its impact on groundwater system.     

基于GIS的耕地土壤重金属污染与农业功能定位研究——以山东省聊城市为例

按8km×8km的网格将聊城市耕地分为137个采样点,调查砷、镉、铬、铜、汞、镍、铅、锌等重金属的污染状况。采用国家土壤环境质量标准、农产品安全质量标准和绿色食品产地环境条件作为评价标准,采用单因子指数和综合指数为评价方法进行污染评价。研究表明,聊城市土壤污染强度依次为铜〉镍〉锌〉砷〉铬〉镉〉铅〉汞,但均未超标。以GIS为操作平台显示聊城市重金属空间分布状况,并对区域耕地进行了功能的定位。聊城市西南部土壤质量最优,适宜种植绿色食品;无公害蔬菜和安全粮食种植区在各县市均有不同程度的分布。     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

基于GIS的重庆市城区环境质量评价

城区环境质量评价是环境评价的重要研究内容,但是目前关于城区环境质量评价指标体系与模型还不够完善,为此提出了城区环境质量评价的方法。该方法通过系统分析,建立城区环境质量评价指标体系,在此基础上,建立城区环境质量评价方法,并通过实例详细分析了城区环境质量评价方法的应用。     

Estimating pesticide runoff in small streams

Surface runoff is one of the most important pathways for pesticides to enter surface waters. Mathematical models are employed to characterize its spatio-temporal variability within landscapes, but they must be simple owing to the limited availability and low resolution of data at this scale. This study aimed to validate a simplified spatially-explicit model that is developed for the regional scale to calculate the runoff potential (RP). The RP is a generic indicator of the magnitude of pesticide inputs into streams via runoff. The underlying runoff model considers key environmental factors affecting runoff (precipitation, topography, land use, and soil characteristics), but predicts losses of a generic substance instead of any one pesticide. We predicted and evaluated RP for 20 small streams. RP input data were extracted from governmental databases. Pesticide measurements from a triennial study were used for validation. Measured pesticide concentrations were standardized by the applied mass per catchment and the water solubility of the relevant compounds. The maximum standardized concentration per site and year (runoff loss, R_Loss) provided a generalized measure of observed pesticide inputs into the streams. Average RP explained 75% (p < 0.001) of the variance in R_Loss. Our results imply that the generic indicator can give an adequate estimate of runoff inputs into small streams, wherever data of similar resolution are available. Therefore, we suggest RP for a first quick and cost-effective location of potential runoff hot spots at the landscape level.