MapObjects在城市道路交通噪声管理中的应用

从Visual Basic控件技术出发，介绍了建立在对象链接与嵌入技术基础上由美国ESRI公司的采用GIS控件MapObjects的运行机制及特点。结合该控件在城市道路交通噪声信息管理系统开发中的应用，对系统的建设目标、结构及开发模式做了介绍；以对北京市道路交通噪声信息管理系统的开发为例，对系统的功能作了简要说明。     

Predicting the Impact of Sea-Level Rise on Caribbean Sea Turtle Nesting Habitat

Abstract:  The projected rise in sea level is likely to increase the vulnerability of coastal zones in the Caribbean, which are already under pressure from a combination of anthropogenic activities and natural processes. One of the major effects will be a loss of beach habitat, which provides nesting sites for endangered sea turtles. To assess the potential impacts of sea-level rise on sea turtle nesting habitat, we used beach profile measurements of turtle nesting beaches on Bonaire, Netherlands Antilles, to develop elevation models of individual beaches in a geographic information system. These models were then used to quantify areas of beach vulnerable to three different scenarios of a rise in sea level. Physical characteristics of the beaches were also recorded and related to beach vulnerability, flooding, and nesting frequency. Beaches varied in physical characteristics and therefore in their vulnerability to flooding. Up to 32% of the total current beach area could be lost with a 0.5-m rise in sea level, with lower, narrower beaches being the most vulnerable. Vulnerability varied with land use adjacent to the beach. These predictions about loss of nesting habitat have important implications for turtle populations in the region.     

GIS and geostatistics: Essential partners for spatial analysis

Initially, geographical information systems (GIS) concentrated on two issues: automated map making, and facilitating the comparison of data on thematic maps. The first required high quality graphics, vector data models and powerful data bases, the second is based on grid cells that can be manipulated by suites of mathematical operators collectively termed map algebra. Both kinds of GIS are widely available and are taught in many universities and technical colleges. After more than 20 years of development, most standard GIS provide both kinds of functionality and good quality graphic display, but until recently they have not included the methods of statistics and geostatistics as tools for spatial analysis. Recently, standard statistical packages have been linked to GIS for both exploratory data analysis and statistical analysis and hypothesis testing. Standard statistical packages include methods for the analysis of random samples of cases or objects that are not necessarily co-located in space—if the results of statistical analysis display a spatial pattern then that is because the underlying data also share that pattern. Geostatistics addresses the need to make predictions of sampled attributes (i.e., maps) at unsampled locations from sparse, often expensive data. To make up for lack of hard data geostatistics has concentrated on the development of powerful methods based on stochastic theory. Though there have been recent moves to incorporate ancillary data in geostatistical analyses, insufficient attention has been paid to using modern methods of data display for the visualization of results. GIS can serve geostatistics by aiding geo-registration of data, facilitating spatial exploratory data analysis, providing a spatial context for interpolation and conditional simulation, as well as providing easy-to-use and effective tools for data display and visualization. The value of geostatistics for GIS lies in the provision of reliable interpolation methods with known errors, methods of upscaling and generalization, and for supplying multiple realizations of spatial patterns that can be used in environmental modeling. These stochastic methods are improving understanding of how errors in models of spatial processes accrue from errors in data or incompleteness in the structure of the models. New developments in GIS, based on ideas taken from map algebra, cellular automata and image analysis are providing high level programming languages for modeling dynamic processes such as erosion or the development of alluvial fans and deltas. Research has demonstrated that these models need stochastic inputs to yield realistic results. Non-stochastic tools such as fuzzy subsets have been shown to be useful for spatial analysis when probabilistic approaches are inappropriate or impossible. The conclusion is that in spite of differences in history and approach, the linkage of GIS, statistics and geostatistics provides a powerful, and complementary suite of tools for spatial analysis in the agricultural, earth and environmental sciences.     

九龙江流域规模化养殖环境风险评价

在GIS支持下采用养分收支平衡法对九龙江流域规模化生猪养殖的环境风险进行评价。规模化养殖污染负荷在不同类型养殖场的分配、空间分布规律以及规模化养殖的环境风险评价结果表明：规模化养猪业年产粪尿量达107万t，以小型规模化养殖场产生的污染负荷最高；整体来看，规模化生猪养殖的环境风险不大，但由于养殖场的地理分布集中，造成近郊区域规模化养殖的环境风险极高；由于过多施用化肥，中远郊规模化养殖粪尿未得到合理利用而流失。位于水系附近的养殖场对水体影响较大，根据“福建省畜禽养殖污染防治管理办法”，为减少规模化生猪养殖对九龙江水质的直接威胁，需搬迁主要支流沿岸1km范围内的规模化养猪场250个。     

四川盆地臭氧浓度空间分异及驱动因子研究

为揭示四川盆地臭氧（O₃）的空间分布格局及其驱动因子,通过对2015~2017年四川盆地18城市82个国控环境监测站的O₃浓度观测数据,使用空间自相关,空间热点探测及地理探测器等地统计方法分析研究.结果表明：2015~2017年四川盆地O₃浓度总体呈现上升趋势（由2015年的（79.95±18.82） μg/m³上升到2017年的（88.64±11.67）μg/m³）,污染态势逐年加重.盆地中西部成都,资阳,雅安等城市O₃浓度最高,且高值区范围逐年扩大.O₃浓度的空间分布呈现出显著的聚集性规律（空间正相关,Moran's I指数大于0）,且年聚集区（H-H聚集区或L-L聚集区）主要呈现为H-H聚集区分布在盆地中西部,L-L聚集区分布在盆地东南部.此外,年聚集区的年际变化与浓度变化态势基本一致,即O₃浓度上升（降低）的区域转变为H-H聚集区（L-L聚集区）.基于地理探测器定量分析了二十个社会经济及自然驱动因子对O₃浓度空间分异的影响,结果显示社会经济因子占主导作用,其中城建用地占区面积比重（驱动值,q=0.5734）,人口密度（q=0.5479）的驱动作用最为突出,自然因子中年降水量（q=0.4592）具有最显著的驱动作用;地理探测器双因子交互对O₃浓度空间分异的影响有明显的交互增强作用（每个单因子q值平均增大了1.5~2.1倍）,且交互均值（即各因子交互q值的均值）与最大交互值逐年增大.在使得交互值达到最大驱动值的双因子中,出现频率最高的是人口密度（7次）和工业烟粉尘排放量（7次）.     

中国居民直接生活能源消费碳排放区域差异及影响因素分析

基于2003-2015年中国30个省份的居民直接生活能耗碳排放数据,利用空间自相关分析其空间格局变化,并利用地理加权回归模型分析了居民消费所产生的二氧化碳排放影响因素。结果表明,中国省域的碳排放空间依赖作用较为显著;居民消费水平、居民直接生活能耗碳排放强度、劳动年龄人口比重对居民人均直接生活能耗碳排放量的增加具有促进作用;家庭规模对人均碳排放的影响呈现较强的负向抑制作用。中国经济发展的区域不平衡在碳排放方面凸显为居民直接生活能源消费碳排放的差异,并在集聚格局上表现出多种类型。     

京津冀PM2.5时空分布特征及其污染风险因素

为分析京津冀及其周边区域2013年典型污染事件中PM_2.5的时空分布特征及污染风险因素,根据国家城市环境空气质量实时发布数据和京津冀地区地理国情信息监测成果,采用空间数据挖掘方法对PM_2.5污染的热点区域进行了划分;并采用地理探测器定量分析了PM_2.5污染风险因子及其影响程度. 结果表明:在选取的京津冀6个城市中,在PM_2.5污染事件统计上存在保定—廊坊—北京—天津—承德—张家口的污染顺序. PM_2.5污染在空间上呈河南省(山东省)—河北省—北京市(天津市)一线的带状分布特征,在单次污染事件中,城市间的PM_2.5污染存在空间运移关系. 空间热点探测表明,京津冀及其周边区域主要分为5个热点聚集区,其中3个高值区分布在北京市、天津市、河北省和山东省的中部,面积分别为5.31×104、10.26×104、5.04×104 km2. 在8个污染风险因子中,污染企业总数(影响力为0.97,下同)、降水量(0.93)、地形坡度(0.89)对PM_2.5污染的影响显著高于其他风险因子;其他风险因子影响力排序依次为人口数量(0.60)、降水量大于0.1 mm的降水日数(0.57)、地表覆盖类型(0.52)、年均相对湿度(0.51)、年均风速(0.33),但风险因子间相比没有显著性差异. 研究显示,京津冀地区PM_2.5污染的主要因素是污染物排放,其次,气象要素中的年降水量和自然地理环境中的地形坡度也是影响PM_2.5污染特征的重要风险因子.      

Evidence of Local Adaptation in the Demographic Response of American Ginseng to Interannual Temperature Variation

Abstract: Bioclimatic envelope models of species’ responses to climate change are used to predict how species will respond to increasing temperatures. These models are frequently based on the assumption that the northern and southern boundaries of a species’ range define its thermal niche. However, this assumption may be violated if populations are adapted to local temperature regimes and have evolved population‐specific thermal optima. Considering the prevalence of local adaptation, the assumption of a species‐wide thermal optimum may be violated for many species. We used spatially and temporally extensive demographic data for American ginseng (Panax quinquefolius L.) to examine range‐wide variation in response of population growth rate (λ) to climatic factors. Our results suggest adaptation to local temperature, but not precipitation. For each population, λ was maximized when annual temperatures were similar to site‐specific, long‐term mean temperatures. Populations from disparate climatic zones responded differently to temperature variation, and there was a linear relation between population‐level thermal optima and the 30‐year mean temperature at each site. For species that are locally adapted to temperature, bioclimatic envelope models may underestimate the extent to which increasing temperatures will decrease population growth rate. Because any directional change from long‐term mean temperatures will decrease population growth rates, all populations throughout a species’ range will be adversely affected by temperature increase, not just populations at southern and low‐elevation boundaries. Additionally, when a species’ local thermal niche is narrower than its range‐wide thermal niche, a smaller temperature increase than would be predicted by bioclimatic envelope approaches may be sufficient to decrease population growth.     

Evaluating conservation dogs in the search for rare species

Detecting rare species is important for both threatened species management and invasive species eradication programs. Conservation scent dogs provide an olfactory survey tool that has advantages over traditional visual and auditory survey techniques for some cryptic species. From the literature, we identified 5 measures important in evaluating the use of scent dogs: precision, sensitivity, effort, cost, and comparison with other techniques. We explored the scale at which performance is evaluated and examined when field testing under real working conditions is achievable. We also identified cost differences among studies. We examined 61 studies published in 1976–2018 that reported conservation dog performance, and considered the inconsistencies in the reporting of scent dog performance among these studies. The majority of studies reported some measure of performance; however, only 8 studies reported all 3 aspects necessary for performance evaluation: precision, sensitivity, and effort. Although effort was considered in 43 studies, inconsistent methods and incomplete reporting prevented meaningful evaluation of performance and comparison among studies. Differences in cost between similar studies were influenced by geographical location and how the dog and handler were sourced for the study. To develop consistent reporting for evaluation, we recommend adoption of sensitivity, precision, and effort as standard performance measures. We recommend reporting effort as the total area and total time spent searching and reporting sensitivity and precision as proportions of the sample size. Additionally, reporting of costs, survey objectives, dog training and experience, type of detection task, and human influences will provide better opportunities for comparison within and among studies.     

Assessing land-use/water-quality relationships across contrasting geologic areas in New Jersey

In all, 13 stream water-quality parameters, including specific conductance (SC), pH, dissolved oxygen (DO), dissolved organic carbon (DOC), three nutrients, and six major ions were compared between the northern bedrock and southern coastal plain regions of New Jersey, USA and related to watershed-disturbance gradients characterized by the percentage of urban land, impervious surface (IS), agriculture, and altered land (sum of urban land and agriculture) in the watersheds. SC, DO, calcium, magnesium, sodium, and chloride concentrations were greater in the north. DOC was higher and pH was lower in the south. Nutrient, potassium, and sulfate concentrations did not differ between regions. Regional water-quality differences are attributed to geologic setting and land use. Except for DO in southern streams, all water-quality parameters were related to urban land, agriculture, or both. Significant correlations between urban land and IS and water-quality variables were similar in both regions with differences in unitless correlation coefficients ranging from 0.00 to 0.06. Compared to urban land and agriculture, relationships between most water-quality variables and altered land were stronger in the south. The extent of urban and agricultural lands in the watersheds did not differ by region. Altered land was correlated with urban land in both regions and with agriculture only in the south. Although focused on New Jersey, this study has broader implications for watershed planning.