海绵城市建设下的生态效应分析——以常德市穿紫河流域为例     

王夏青  孙思远  杨萍  邹小燕  易巧梅  彭保发  许建伟 《地理学报》2019,74(10):2123-2135

海绵城市建设被认为是解决城市内涝、水污染和水资源短缺、热岛效应等问题的有效途径之一。中国自2015年起共确立30个海绵城市建设试点城区,为今后海绵城市建设在全国范围的推广提供示范。基于实地调研、查阅资料并对比分析穿紫河流域海绵城市建设前后的水文、植被和气候等自然要素变化。结果表明：常德市城市内涝有效缓解,但在暴雨发生时局部仍出现积水和内涝现象;穿紫河水质总体上由劣Ⅴ类转变为Ⅲ类,但在冬季周期性恶化及污染物富集;穿紫河流域生物多样性显著增加,同时也表现出植物种类单一、具有环境净化功能的植物种类较少、生态系统不完整和管理不善等问题;常德市夏季的热岛效应有一定程度缓解。常德市2004-2019年的海绵城市建设显著提升了穿紫河流域的生态效应,为该地区的社会经济发展和人居环境改善提供了重要的生态基础,也为合理评价其他试点城区海绵城市建设效果提供借鉴。  相似文献   

福州市地表温度热点及时空变化分析     

陈冰倩  张友水  程璟媛  赵雪 《地球信息科学学报》2019,21(5):710-719

中国作为世界第一大发展中国家,近年来城镇化发展迅速,大量自然地表转化为人工地表,从而引起了一系列环境问题,其中以城市热岛问题最为显著。因此如何缓解因城市化进程的加快引起的城市热岛效应已成为热门研究方向。为精确分析城市空间格局对热集聚的影响,本研究利用2000年5月4日的Landsat ETM+和2016年7月27日获取的Landsat OLI两期遥感影像,获取福州市的土地覆盖信息并进行精度验证。在地表温度（Land Surface Temperature, LST）反演基础上通过热点分析（Getis-Ord Gi*）,并结合不透水面（Impervious Surface Area, ISA）信息来研究城市化进程中福州市16 年来 LST的变化特性,空间集聚特性及其产生的尺度效应。热点分析结果显示：① 通过分析福州市内各地和热点中心的距离与LST的关系可较好地反映空间热聚集。2000 年在距热点中心0.97、1.03、0.95 km范围内热聚集明显;2016 年则增长到分别在距热点中心半径1.89、2.01、2.10、2.05、2.13 km范围内热集聚显著且热点区数量也从3 个增加至5 个。热集聚区（热点区和较热区）总面积在此期间从15.7%增至47.3%;② 由于热点图中的热点区和冷点区的形成不单取决于LST的高低,因此热点分析与空间自相关分析方法相比,能更直观地分析土地覆盖变化对LST的影响,了解城市内部热强度变化的细节。本研究采用的热点分析方法可用于城市环境保护与规划,将来还可作为城市土地规划与热环境影响的分析依据。同时可利用热点分析图模拟城市微气候,估算城市绿地降温程度等。此外,未来还可基于此进一步探讨更多时相以及不同城市的对比分析,特别是对不同城市类型如带状城市,多中心城市及中心城市等的研究。  相似文献   

Remote sensing of water depths in shallow waters via artificial neural networks     

Özçelik Ceyhun  Arısoy Yalçın 《Estuarine, Coastal and Shelf Science》2010

Determination of the water depths in coastal zones is a common requirement for the majority of coastal engineering and coastal science applications. However, production of high quality bathymetric maps requires expensive field survey, high technology equipment and expert personnel. Remotely sensed images can be conveniently used to reduce the cost and labor needed for bathymetric measurements and to overcome the difficulties in spatial and temporal depth provision. An Artificial Neural Network (ANN) methodology is introduced in this study to derive bathymetric maps in shallow waters via remote sensing images and sample depth measurements. This methodology provides fast and practical solution for depth estimation in shallow waters, coupling temporal and spatial capabilities of remote sensing imagery with modeling flexibility of ANN. Its main advantage in practice is that it enables to directly use image reflectance values in depth estimations, without refining depth-caused scatterings from other environmental factors (e.g. bottom material and vegetation). Its function-free structure allows evaluating nonlinear relationships between multi-band images and in-situ depth measurements, therefore leads more reliable depth estimations than classical regressive approaches. The west coast of the Foca, Izmir/Turkey was used as a test bed. Aster first three band images and Quickbird pan-sharpened images were used to derive ANN based bathymetric maps of this study area. In-situ depth measurements were supplied from the General Command of Mapping, Turkey (HGK). Two models were set, one for Aster and one for Quickbird image inputs. Bathymetric maps relying solely on in-situ depth measurements were used to evaluate resultant derived bathymetric maps. The efficiency of the methodology was discussed at the end of the paper. It is concluded that the proposed methodology could decrease spatial and repetitive depth measurement requirements in bathymetric mapping especially for preliminary engineering application.  相似文献   

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model   总被引：10，自引：0，他引：10  

Biswajeet Pradhan  Ahmed M. Youssef  Renuganth Varathrajoo 《地球空间信息科学学报》2010,13(2):93-102

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.  相似文献   

Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries     

Yongnian Zeng  Wei Huang  F. Benjamin Zhan  Honghui Zhang  Huimin Liu 《地球空间信息科学学报》2010,13(1):1-7

This study assesses surface urban heat island (UHI) and its associated surface physical characteristics using remote sensing approaches. TERRA/MODIS images acquired in 2005 in three different seasons were selected to generate land surface tem-perature and surface characteristics for the Changsha-Zhuzhou-Xiangtan metropolitan area in China. The intensity of urban heat is-land effects and its seasonal variations were examined. The result showed that UHI effects were significant both in the summer and the spri...  相似文献   

Impact of artificial subsurface drainage on groundwater travel times and baseflow discharge in an agricultural watershed,Iowa (USA)     

Keith E. Schilling  Priyanka Jindal  Nandita B. Basu  Matthew J. Helmers 《水文研究》2012,26(20):3092-3100

Pollutant delivery through artificial subsurface drainage networks to streams is an important transport mechanism, yet the impact of drainage tiles on groundwater hydrology at the watershed scale has not been well documented. In this study, we developed a two‐dimensional, steady‐state groundwater flow model for a representative Iowa agricultural watershed to simulate the impact of tile drainage density and incision depth on groundwater travel times and proportion of baseflow contributed by tile drains. Varying tile drainage density from 0 to 0.0038 m^?1, while maintaining a constant tile incision depth at 1.2 m, resulted in the mean groundwater travel time to decrease exponentially from 40 years to 19 years and increased the tile contribution to baseflow from 0% to an upper bound of 37%. In contrast, varying tile depths from 0.3 to 2.7 m, while maintaining a constant tile drainage density of 0.0038 m^?1, caused mean travel times to decrease linearly from 22 to 18 years and increased the tile contribution to baseflow from 30% to 54% in a near‐linear manner. The decrease in the mean travel time was attributed to decrease in the saturated thickness of the aquifer with increasing drainage density and incision depth. Study results indicate that tile drainage affects fundamental watershed characteristics and should be taken into consideration when evaluating water and nitrate export from agricultural regions. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

厦门同安湾鳄鱼屿海岸侵蚀与防护对策     

林河山  廖连招  庄孔造  朱嘉  蔡晓琼  蔡鹭春 《台湾海峡》2010,29(4):566-570

在2009年3月对鳄鱼海岸线测量的基础上,利用ArcGIS软件分析比较了现有海岸线与厦门市集美区地形图（1988年版,图号：7-50-129甲-）中鳄鱼屿海岸线位置的变化.结果表明21a来,鳄鱼屿海岸最大侵蚀率为2.0 m/a,东南侧最大侵蚀宽度达42 m,侵蚀总面积达14 000 m2;其东北侧海岸侵蚀后退约35 m,侵蚀总面积达4 100 m2;其西北侧海岸最大侵蚀宽度达30 m,侵蚀面积达12 000 m2.文中就厦门市鳄鱼屿海岸侵蚀的成因进行了分析,提出了工程防护、人工补沙、红树林修复以及加强海岛及其周边海域资源综合管理等方面的防护对策.这可为我国其他无居民海岛的海岸侵蚀防护提供经验借鉴.  相似文献   

A collective approach to Pacific islands fisheries management: Moving beyond regional agreements     

Quentin Hanich  Feleti Teo  Martin Tsamenyi 《Marine Policy》2010

The sustainable management and profitable development of the Pacific island tuna fisheries is the key ocean governance challenge for the Pacific islands region in the short and medium term. Resolving these challenges is fundamental to the long term future of the region and its ability to implement oceans governance across all resource and conservation concerns.  相似文献   

Modelling combined open channel flow by artificial neural networks     

Han‐Chung Yang  Fi‐John Chang 《水文研究》2005,19(18):3747-3762

Combined open channel flow is encountered in many hydraulic engineering structures and processes, such as irrigation ditches and wastewater treatment facilities. Extensive experimental studies have conducted to investigate combined flow characteristics. Nevertheless, there is no simple relationship that can fully describe the velocity profiles in a turbulent flow. The artificial neural network (ANN) has great computational capability for solving various complex problems, such as function approximation. The main objective of this study is to evaluate the applicability of the ANN for simulating velocity profiles, velocity contours and estimating the discharges accordingly. The velocity profiles measured by an acoustic doppler velocimeter in the open channel of the Chihtan purification plant, Taipei, with different discharges at fixed measuring section and different depths are presented. The total number of data sets is 640 and the data sets are split into two subsets, i.e. training and validation sets. The backpropagation algorithm is used to construct the neural network. The results demonstrate that the velocity profiles can be modelled by the ANN, and the ANN constructed can nicely fit the velocity profiles and can precisely predict the discharges for the conditions investigated. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?     

《水文科学杂志》2013,58(1)

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.  相似文献