Urban land use mapping and zoning of Bombay Metropolitan Region using remote sensing data

Bombay Metropolitan Region covering an area of about 4,360 sq. km. was selected for urban land use studies and for urban land use zoning. Urban land use mapping was carried out using SPOT multispectral linear array imagery on 1∶25,000 scale employing visual analysis tehcniques. Fifteen maps were prepared depicting the spatial distribution of various urban classes in the Greater Bombay and New Bombay regions. Sixteen urban land use maps were also prepared using Landsat TM data showing the distribution of land use pattern on 1∶50,000 scale for the entire metropolitan region. Urban land use zoning was carried out based upon suitability index on 1∶250,000 scale. This map provides information on the areas to be used for construction and areas to be kept under green belt in the metropolitan region. This study is a joint venture of Space Applications Centre with Bombay Metropolitan Development authority.     

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree,Markov chain and cellular automata models in GIS

Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved.     

Urban growth monitoring and projection using remote sensing and geographic information systems: a case study in the Twin Cities Metropolitan Area,Minnesota

This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary.     

Exploring land use policy scenarios with the use of a cellular automata-based model: urban sprawl containment and sustainable development in Thessaloniki

This study addresses the issue of urban sprawl through the application of a cellular automata (CA)-based model in the area of Thessaloniki, Greece. The model integrates a multiple regression model at the regional level with a CA model at the local level. New urban land is allocated in a disaggregated field of land units (cells) taking into account a wide range of data. Particular emphasis is placed on the way zoning regulations and land availability data are inserted into the model, so that alternative land use policy scenarios could be examined. Thessaloniki, a typical Mediterranean city, is used as a case study. The model is used to compare two scenarios of urban growth up to year 2030; the first one assuming a continuation of existing trends, whereas the second one assuming the enactment of various land use zoning regulations in order to contain urban sprawl.     

Incorporating GIS data into an agent-based model to support planning policy making for the development of creative industries

This paper presents an extension to the agent-based model “Creative Industries Development–Urban Spatial Structure Transformation” by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries’ development process.     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

Urban land-use suitability analysis — A case study of Calcutta Metropolitan Area

Urban land-use zoning analysis has been carried out to evaluate the suitability of land for urbanisation i.e. a process of assessing the fitness of different land characteristics (soils, physiography, slope, land use etc.) for urban development in Calcutta Metropolitan Development Authority (CMDA) area (1350 sq. km). Remote sensing data in conjunction with Survey of India maps and ancillary data have been employed for the analysis. A GIS-based methodology has been developed for the integration of different physical parameters and generation of urban land development units. In all 82 Urban Land Development Units (ULDUs) were delineated and evaluated with respect to physical constraints and the degree to which each class could limit the development for urban purpose. These ULDUs are categorised into five suitability classes for urban use. The relationships between ULDU classes, suitabilities and urban land development considerations in a generalised form have also been assessed. It has been observed that the physical constraints have become progressively greater from class-I to class-V meaning thereby that the cost for the developing the area for urban purpose increases from class-I and becomes uneconomic for class-V. The suitability map prepared using this methodology would also serve as a sub-set for the preparation of a Master plan of the city.     

Analyzing Urban Sprawl in Rethymno,Greece

Analysis of urban sprawl is an issue that has been continuously attracting attention in the planning and research community. Τhis paper presents the results of an analysis of the growth of the city of Rethymno during the 1997–2010 time period. Rethymno is a city in the island of Crete in Greece with population of about 35,000 people, in which developed land has expanded at a rate that is double the growth of the population during the study period. A qualitative analysis was first performed to identify growth patterns in the different parts of the city, how these are related to planning regulations and the extent of cohesiveness of the development. A logistic regression model was estimated using various variables influencing the expansion of the built up area. Variables such as slope, distance from main roads, distance from the University, distance from coastline, as well as variables describing the proximity to other developed areas were used as independent variables in the logistic regressions. Planning constraints with respect zoning were also considered. The accuracy/goodness of fit of the simulation results were also tested using Receiver Operating Characteristic (ROC) curve. The results revealed high (performance) accuracy, which can support the applicability of the proposed method in urban sprawl modeling. Once the equations were estimated they were applied using data from 2010 to identify future trends of urbanization. The methodology adopted in this study can result in a tool that can be of use to urban planning authorities in identifying areas of future urban growth and therefore, adopt zoning policies encouraging or discouraging growth in these areas according to the sustainability objectives of the local community.     

基于人工蜂群CA模型的南京市土地利用变化模拟与预测

以南京市为例,构建人工蜂群元胞自动机（CA_ABC）模型,对2000—2007年的土地利用变化进行模拟以实现CA_ABC模型的校正,并以2007—2015年的土地利用变化为案例,验证该模型的有效性。模拟结果总体精度（OA）2007年为87.79%,2015年为80.61%;模拟结果的品质因数（FOM）2007年为21.23%,2015年为19.25%。基于CA_ABC模型和马尔可夫链预测未来城市土地总量,对南京市2025和2035年的土地利用格局进行了预测,对城市扩张和生态用地被侵占现象进行分析。模型预测结果表明,未来20年的城市扩张主要以牺牲耕地和林地为代价,2025和2035年80%的城市扩张面积来源于对耕地面积的侵占,17%的城市面积扩张是由2015年的林地转换得到的。研究表明,准确模拟、预测未来城市格局及评估城市扩张能够对生态用地侵占,以及为决策者合理规划城市、推动城市可持续发展提供帮助。     

基于FLUS模型的土地利用变化模拟与预测方法研究

模拟和预测土地利用演变过程是规划者把握城市扩张趋势,从而确定更合理的城市用地布局的重要途径之一,对指导国土空间规划具有重要意义.研究基于CA原理改进的FLUS模型,通过耦合GeoSOS-FLUS及ArcGIS软件,从2011年土地利用数据中获取元胞转换概率,模拟了2018年土地利用变化情况.模拟精度较高,证明选取的模拟...     

大城市工业用地调整的决策支持及技术、方法研究——以广州为例

针对广州市工业用地调整的时序问题,提出一套包括调整潜力评价、发展政策约束及调整时序安排等完整的决策支持研究思路,调整潜力评价是基于对工业用地不适宜性与非工业用地的适宜性综合评价,以优化城市空间结构为导向;政策约束是梳理未来影响广州工业用地调整的政策,以落实政策空间影响为目标;调整分配是综合潜力评价与政策影响,提出未来广州市工业用地调整的时序安排。就实践层面而言,本研究为广州市土地储备部门制定年度实施计划提供依据,而在理论层面,本研究初步形成一个完整的用地优化决策技术框架,为今后类似大城市的用地空间优化提供一种借鉴与探索。     

Analysis and simulation of land use spatial pattern in Harbin prefecture based on trajectories and cellular automata—Markov modelling

There have been rapid population and accelerating urban growth with associated changes in land use and soil degradation in northeast China, an important grain-producing region. The development of integrated use of remote sensing, geographic information systems, and combined cellular automata– Markov models has provided new means of assessing changes in land use and land cover, and has enabled projection of trajectories into the future. We applied such techniques to the prefecture-level city of Harbin, the tenth largest city in China. We found that there had been significant losses of the land uses termed “cropland”, “grassland”, “wetland”, and “floodplain” in favour of “built-up land” and lesser transformations from “floodplain” to “forestland” and “water body” over the 18-year period. However, the transition was not a simple process but a complex network of changes, interchanges, and multiple transitions. In the absence of effective land use policies, projection of past trajectories into a balance state in the future would result in the decline of cropland from 65.6% to 46.9% and the increase of built-up area from 7.7% to 23.0% relative to the total area of the prefecture in 1989. It also led to the virtual elimination of land use types such as unused wetland and floodplain.     

Socioeconomic Factors and Urban Tree Cover Policies in a Subtropical Urban Forest

Cities are increasingly promoting policies that increase and conserve urban forests based largely on biophysical and land use-cover metrics. This study demonstrates how socioeconomic factors need to be considered in geospatial analyses when formulating urban greening policies. Using remote sensing, geographical information systems, spatial field and census data, and policy analyses, we analyzed the effectiveness of urban forest cover policies that included socioeconomic factors when quantifying urban forest cover. We found that urban forest cover was heterogeneous across the study area and non-white residents younger than 19 and greater than 45 years old living in rentals were more likely to reside in areas with less urban forest cover than any other age cohort. Our analyses also indicated that urban forest cover was temporally variable and demographic factors unique to Miami-Dade County bring to light the complexity of establishing homogenous, county-wide "tree canopy" and urban greening policy goals. We present a localized socioeconomic and ecologically based geospatial approach for formulating urban forest cover goals.     

城市局部气候分区对地表温度的影响 ——以大连市区为例

以大连市区建筑数据、SPOT 5和Landsat 8遥感数据为基础,运用局部气候带分类、地表温度反演方法,研究大连市局部气候带分区类型和特征,进而分析不同局部气候带对城市地表温度的影响。研究结果表明：①大连市建筑类型高度主要为低层建筑、多层建筑和中高层建筑,建筑密度为中密度和较高密度,甘井子区分布大量森林绿地,中山区具有丰富的公园绿地;②地表温度整体偏高,空间上呈现东高西低的趋势,其中半数以上地区地表温度达到28℃~31℃,并且有超过1%的地区地表温度大于38℃,该区域出现极端高温;③同一建筑高度上,密度越大的建筑区域,地表温度越高;同一建筑密度,多层建筑高度覆盖区地表温度较高。森林绿地地表温度最低,公园绿地和社区绿地地表温度几乎一致,附属绿地地表温度最高。     

基于可达性测度的公园绿地服务公平性时空分析

由于城区土地资源的稀缺性,公园绿地的供给与人口对绿地的需求往往难以匹配,出现了公园绿地空间分布不均衡和服务不公平性的现象。本文以两步移动搜索法的可达性测度为基础,开展武汉市主城区公园绿地社会公平性的时空分析研究。研究表明:新一轮规划实施后,从服务的整体效益来看,武汉市主城区公园绿地资源分配向着更趋于公平的方向发展;从公园绿地服务的空间格局来看,绿地可达性提高较为显著,可达性极低区域面积减少。     

Land Use/Cover Change Detection of Tiruchirapalli City, India, Using Integrated Remote Sensing and GIS Tools

The rapid growth of urban population in India is a cause of concern among country??s urban and town planners for efficient urban planning. The drastic growth of urban areas has resulted in sharp land use and land cover changes. In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information systems (GIS) has been widely used. The present study investigates the urban growth of Tiruchirapalli city, Tamilnadu using IRS satellite data for the years 1989, 1992, 1995, 1998, 2001, 2004, 2007, and 2010. The eight satellite images are enhanced using convolution spatial enhancement method with Kernel (7?×?7) edge enhance function. Supervised classification method is used to classify the urban land use and land cover. The GIS is used to prepare the different layers belonging to various land uses identified from remotely sensed data. The analysis of the results show the drastic increase of built up area and reduced green cover within the city boundary limit.     

运用RS和GIS技术进行城市绿地覆盖调查

较详细地介绍了运用遥感和地理信息系统技术进行城市绿地覆盖调查的方法、技术流程以及其优点。由该方法获取的城市绿地覆盖数字信息,可以方便地进行各种分析、评价,辅助绿化部门的规划管理.     

Quantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region

We estimated urbanization rates (2001–2006) in the Gulf of Mexico region using the National Land Cover Database (NLCD) 2001 and 2006 impervious surface products. An improved method was used to update the NLCD impervious surface product in 2006 and associated land cover transition between 2001 and 2006. Our estimation reveals that impervious surface increased 416 km² with a growth rate of 5.8% between 2001 and 2006. Approximately 1110.1 km² of non-urban lands were converted into urban land, resulting in a 3.2% increase in the region. Hay/pasture, woody wetland, and evergreen forest represented the three most common land cover classes that transitioned to urban. Among these land cover transitions, more than 50% of the urbanization occurred within 50 km of the coast. Our analysis shows that the close-to-coast land cover transition trend, especially within 10 km off the coast, potentially imposes substantial long-term impacts on regional landscape and ecological conditions.     

1973年—2013年经济特区城市空间扩展遥感监测

选取1973年—2013年多源遥感影像为数据源,以深圳、厦门、海口为例,开展中国经济特区城市建城区的长时序、高频数空间扩展遥感监测。选取城市扩展速度、城市扩展对土地利用的影响、城市形态紧凑度和城市重心迁移作为指标,剖析经济特区城市扩展的时空特征,耦合自然要素与人为要素,对比分析深圳、厦门和海口在城市扩展过程中表现出来的异同,并探讨其原因。结果表明:(1)近40年来,经济特区城市扩展先后经历了一个缓慢平稳扩展阶段、两个加速扩展阶段和两个减速扩展阶段。深圳的扩展速度最快,其次是厦门,海口的扩展速度最慢;(2)耕地对经济特区城市扩展贡献最大,林地、水域、城乡工矿和居民用地、海域也是经济特区城市扩展的重要土地来源,草地和未利用土地的贡献最小;(3)经济特区城市的空间形态总体趋于松散,1973年—2004年城市紧凑度剧烈降低,2004年之后趋于平稳;(4)在政策与填海造地工程的共同影响下,经济特区城市重心有向海岸线方向迁移的趋势,深圳的迁移量最大,海口最小。     

长江经济带城市土地利用效率的影响因素及其空间溢出效应研究

在人多地少的基本国情下,提高城市土地利用效率是促进区域可持续发展和建设生态文明的内在要求。本文在对2009-2016年长江经济带108个地级及以上城市土地利用效率的研究基础上,采用空间相关性研究方法分析了时空分布格局,通过构建空间杜宾模型(SDM)对其空间溢出效应进行分析。研究结果表明:1)2009-2016年长江经济带城市土地利用效率整体呈现稳定上升趋势;基本呈现以上海、南京、武汉等不同城市群中心城市向外逐步降低的“中心-外围”的分布格局。2)通过构建空间杜宾模型分析发现,经济发展水平、产业结构有显著为正的直接效应和溢出效应;土地市场化水平有显著为正的溢出效应;城市固定资产投资对城市土地利用效率具有正的直接效应和负的溢出效应;政府财政支出水平则对城市土地利用效率的直接效应和溢出效应均不明显。3)不同影响因素对经济带上中下游城市土地利用效率的空间效应存在一定差异性。