城市热力景观格局季节变化特征分析及其应用

热岛效应是城市发展过程中所产生的特有的环境问题,已经成为一种城市环境公害,对其形成和演变规律的研究有助于人们提出有效的应对措施。热力景观是分析城市热岛空间格局的一种新方法。以厦门为研究对象,利用2002年1、2、3、8、12月的Landsat ETM＋影像数据进行地表温度反演,在此基础上使用景观格局指数分析厦门城市热力景观格局的季节变化特征。结果表明：厦门城市热岛在夏季（8月）最强,春秋次之,冬季（1月）最弱。该变化特征是城市地表吸收太阳辐射和人为废热排放随季节变化的共同结果。应用该方法对2002年厦门热污染源进行调查,发现当年共有热污染源26个,其中工业热污染源18个。该研究可为环保、能源等部门乃至于整个城市的规划管理提供有力的决策依据。     

广东省城市体系生态环境类型

城市生态环境类型是随城市和区域不断发展而分化的产物，根据广东省城市体系格局，选取主要的十九个城市，确定适当的生态环境参数，对广东省城市生态环境的区域差异和主要类型进行多元统计复合分析，根据生态环境的相似性和相异性将广东省城市体系划分为四个类型，为区域规划和城市管理决策提供依据。     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用。以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特征。结果表明,（1）研究区2000—2018年植被覆盖趋向改善,NDVI呈现增加趋势,增速为0.11/10a,2008年以后植被增长较为明显;NDVI在2018年中高等级（0.6—0.8）面积比2000年中高等级面积明显增加;中高等级集中于榆林市东部黄土丘陵区,中低等级（0.2—0.4）集中于榆林市西北部的风沙区,植被覆盖呈现东部高西北低的空间分布特征。（2）人口密度和气温因子较好地解释植被NDVI空间分异性,是影响NDVI空间分异性的主要因子,GDP、土地利用类型和坡度是次级影响因子,其他因子对NDVI空间分异存在间接影响;坡向、降水和土壤类型因子与其他自然、人文因素对植被空间分布影响存在显著性差异。（3）自然、人文因子对榆林市NDVI的影响存在交互作用,因子之间的交互...     

利用微拟球藻去除污水中氮磷及生产富油生物质

为探讨污水深度处理和同步获取产油微藻的可行性,建立光生物反应器,应用微拟球藻去除污水和中水中的氮磷,并分析不同浓度的Fe3+和Zn2+离子对微藻的生长和油脂积累的影响,从而在净化污水的同时培养微藻获得富油生物质。结果表明,该藻对污水氮磷具有较强的去除能力,可在13 d内,去除水体中96%的氨氮和94%的磷,同时化学需要氧量(COD)的去除率可达72.9%。在生活污水中培养至第16天,微藻的细胞密度可达4.55×106 cell/mL。Fe3+浓度对微拟球藻的生长具有显著影响(P6 cell/mL。该研究以中水和生活污水为基质培养微拟球藻,同时获取微藻油脂,为污水中氮磷的去除和能源的同步获取提供了新途径。     

贵州草海湿地农田渠系水质空间分异特征及影响分析

为了解草海湿地农田渠系水质现状、空间分异特征及影响因素,于2011年秋季对草海湿地进行大空间尺度的采样,分析了氮磷等理化指标,采用单因子污染指数法和营养状态指数法分别对农田渠系水质和湖泊营养状态进行评价.结果表明,草海湿地农田渠系水质污染严重,多数水质为V类或劣V类,总氮和溶解氧是水体中的主要污染因子;上游水质劣于下游,尤其是上游靠近县城区域的水质最差;多等级排水渠系对氮磷具有一定的截留作用,干渠V级水质好于低级渠系水质;不同的土地利用方式对水质的影响不同,城镇用地>集中式村落>农田;草海湿地水体上、中、下游营养水平分别为中度富营养、轻度富营养和中营养,外源污染物的累积和湖泊营养水平的提高导致其沼泽化,而流域不合理的土地利用结构加剧了沼泽化的进程.     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

PARTITIONING SMALL SCALE SPATIAL VARIABILITY OF RUNOFF AND EROSION ON SAGEBRUSH RANGELAND1

ABSTRACT: Most hydrologic models require input parameters which represent the variability found across an entire landscape. The estimation of such parameters is very difficult, particularly on rangeland. Improved model parameter estimation procedures are needed which incorporate the small-scale and temporal variability found on rangeland. This study investigates the use of a surface soil classification scheme to partition the spatial variability in hydrologic and interrill erosion processes in a sagebrush plant community. Four distinct microsites were found to exist within the sagebrush coppice-dune dune-interspace complex. The microsites explained the majority of variation in hydrologic and interrill erosion response found on the site and were discernable based on readily available soil and vegetation information. The variability within each microsite was quite low and was not well correlated with soil and vegetation properties. The surface soil classification scheme defined in this study can be quite useful for defining sampling procedures, for understanding hydrologic and erosion processes, and for parameterizing hydrologic models for use on sagebrush range-land.     

PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES1

ABSTRACT: The usefulness of stochastic models in describing the spatial variability of hydrogeologic quantities, such as permeability, storativity, piezometric head, seepage velocity, and solute concentrations is now widely recognized. In practice, these quantities are represented as the sum of a well-structured component, or drift, and a more erratic fluctuation component which is described statistically through its covariance function. This paper reviews some of the most recent and most promising methods for the estimation of parameters of these covariances from existing data. They are maximum likelihood, restricted maximum likelihood, minimum-variance unbiased quadratic estimation, and minimum-norm (weighted least squares) estimation. The applicability of such methods to conditional and unconditional probability problems is discussed.     

Riera de Caldes new town: the restriction of growth

The historical and regional context to the development of a planning strategy for Barcelona is examined, providing an explanation of the obstacles to development of new towns in the region, and that of Riera de Caldes in particular. The paper analyses the reasons for the failure to develop the new town, and its subsequent reversion to rural uses and a place of pilgrimage for environmentalists.     

ASSESSMENT OF POSSIBLE IMPACTS OF CLIMATE CHANGE IN AN URBAN CATCHMENT1

ABSTRACT: Stationarity of rainfall statistical parameters is a fundamental assumption in hydraulic infrastructure design that may not be valid in an era of changing climate. This study develops a framework for examining the potential impacts of future increases in short duration rainfall intensity on urban infrastructure and natural ecosystems of small watersheds and demonstrates this approach for the Mission/Wagg Creek watershed in British Columbia, Canada. Nonstationarities in rainfall records are first analyzed with linear regression analysis, and the detected trends are extrapolated to build potential future rainfall scenarios. The Storm Water Management Model (SWMM) is used to analyze the effects of increased rainfall intensity on design peak flows and to assess future drainage infrastructure capacity according to the derived scenarios. While the framework provided herein may be modified for cases in which more complex distributions for rainfall intensity are needed and more sophisticated stormwater management models are available, linear regressions and SWMM are commonly used in practice and are applicable for the Mission/Wagg Creek watershed. Potential future impacts on stream health are assessed using methods based on equivalent total impervious area. In terms of impacts on the drainage infrastructure, the results of this study indicate that increases in short duration rainfall intensity may be expected in the future but that they would not create severe impacts in the Mission/Wagg Creek system. The equivalent levels of imperviousness, however, suggest that the impacts on stream health could be far more damaging.