漯河市近40年土地利用及景观格局变化特征研究

本文以河南省漯河市为例,以遥感解译的漯河市近40年来土地利用数据为基础,运用GIS叠置分析、土地利用转移矩阵等空间分析方法,结合景观格局指标,研究其改革开放以来土地利用及景观格局变化特征,为优化土地资源配置及科学的城市规划提供依据。结果表明:(1)1980年至2015年间漯河城镇用地面积呈显著增加趋势,扩张主要占用耕地;(2)林地和农村居民点用地总体呈增加趋势,2000年来其他建设用地面积迅速增加;(3)漯河市各景观类型总体呈平衡发展态势,耕地优势度有所下降,建设用地优势度不断上升;(4)人口增长与经济发展、交通条件改善及政府政策变动是影响漯河市土地利用变化和景观格局演变的主要因素。     

半城市化的土地利用/覆盖变化分析——以吴江为例

以长江三角洲半城市化(Desakota)典型区——吴江市为研究区,利用研究区1978~2010年六期Landsat MSS/TM序列卫星影像,获取土地利用/覆被变化信息,计算分析吴江市土地利用/覆被变化在不同历史时期的变化量、变化率及空间变化格局。结果表明:1从土地利用结构上看,吴江市土地结构以耕地和水域为主,但城镇建设用地占比逐步增加,农村建设用地相对维持不变。2从变化速率看,2000~2004年城镇建设用地的变化速率最大,达到49.14%。3从空间变化格局来看,呈现一种非集聚性的半城市化发展态势,在沿上海、浙江、苏州、太湖的乡镇发展极为速度。     

遥感技术支持下的下龙湾西岸养殖塘变化监测及其对“三生用地”影响分析

下龙湾西岸是越南北部沿海的养殖大区，随着水产养殖用地规模的逐渐扩大，周边三生用地（生产用地、生活用地、生态用地）空间格局受到影响。本文以下龙湾西岸的5个沿海地区为研究区，利用1990、2000、2010、2015年4期无云Landsat TM/OLI遥感数据，采用分类回归树方法，对1990—2015年的土地利用变化进行监测。通过土地利用净变化量、土地利用动态度模型、相关性分析等方法，定量分析养殖塘时空格局演变特征及对三生用地的影响。结果表明：①25年间，养殖塘面积呈“单峰”式先增后减变化，净增加66.65 km²，2000年面积为156.65 km²，较1990年面积增长113%，2015年较2000年面积减少11%。总体呈现数量上“北增南减”、速率上“东快西慢”的面积变化特征。②养殖塘转入面积中，生产用地对养殖塘转移面积占31%，生活用地占4%，生态用地占65%。空间格局整体以白藤江及陆地中轴为界线，呈南北分区、东西分界的转入转出规律。③养殖塘占用生活用地7.24 km²，二者呈正相关关系，R²为0.46；养殖塘分别占用生产用地和生态用地55.14、115.14 km²，并与两者成负相关关系，R²分别为-0.96和-0.81。由此可知，利用遥感技术监测养殖塘时空变迁对土地资源的规划配置与可持续发展具有重意义。     

湖北省生态系统服务价值演变及影响因素分析

针对区域生态系统服务价值(ESV)多在单一尺度下进行分析以及影响因素存在空间异质性的问题，该文利用ESV评估模型、空间自相关分析和地理探测器等方法，基于1980—2020年土地利用等数据，分析了湖北省土地利用变化下的ESV时空变化、多尺度时空格局特征，探讨了ESV空间分异的影响因素。结果表明：(1)湖北省1980—2020年耕地、未利用地呈减少趋势，建设用地、水域呈增加趋势，林地、草地维持相对稳定；(2)近40年间湖北省ESV增加了459.83亿元，水域是ESV增加的贡献者；(3)湖北省多尺度全局自相关分析表明7 km格网尺度下的ESV空间集聚性最为显著，局部自相关分析显示以襄州区—宜都市为界，湖北省东部ESV表现出明显的局部聚集效应，而西部则不显著；(4)湖北省整体ESV空间分异的主导因子为归一化植被指数和气温，西部地区主要受人为影响综合指数的影响，而东部地区受高程的主导。     

北京五六环区域绿化控制带发展潜力评估

以TM遥感图像为数据源，分析了北京五、六环之间土地格局的空间分布特征，评价了绿带发展的潜力。结果表明，穿越规划 区的几条重要交通干线构建了绿化控制带基本的楔形结构；各类非建设土地资源占60％左右，为绿地的发展提供了可直接利用潜力。 但现有土地资源布局零乱，缺乏科学有效的规划管理，各种大型城镇建设用地的空间格局已大大超过绿带的规划构想。提高建设用地 的空间利用率，缩小建设用地的空间规模，科学配置各类绿色景观是绿带建设中的重点和难点。     

四川省江油市2004～2020年土地利用动态分析及预测

基于2004、2010、2015年Landsat-5 TM、Landset-80LI遥感影像土地利用现状解译数据,分析了江油市近11年土地利用动态变化;同时,利用元胞自动机-马尔科夫(CA-Markov)模型,模拟预测了2020年江油市土地利用空间分布格局.结果表明,2004 ～ 2015年期间,江油市耕地、草地、水域面积总体减少,建设用地和林地面积总体呈增加趋势.2015 ～2020年期间,江油市土地利用变化较快,与上一个五年相比,建设用地、耕地和草地面积将有所增加,林地面积有所减少,水域面积基本不变;建设用地从原有基础往外围耕地扩张,耕地面积则主要由林地转入.     

基于RS与GIS的南京市土地利用及景观格局变化分析

人类社会经济的发展对土地利用和景观格局会产生重要的影响。本文以2010、2015、2020年3期TM遥感影像数据为基础,借助RS与GIS技术对南京市土地利用与景观格局的变化进行分析。研究结果表明,南京市土地类型主要以耕地、林地、建设用地和水域为主,而草地和未利用地面积相对较小,占比不足1%。在研究期间变化过程主要是建设用地在增加,十年间增加了168.86 km²。景观格局分析表明,南京市景观的斑块密度、形状指数、香农多样性指数和均匀度指数不断增加,景观的破碎化程度提高,异质性增强。南京市土地利用和景观格局有明显的变化趋势,城市化和退耕还林是南京市土地利用和景观格局变化的主要因素。     

赣江新区建设用地空间格局监测

通过对新区城乡建设用地和城市建设用地空间格局变化监测，分析其变化特征，对新区未来建设和发展以及推动生态文明建设有重要指导意义。本文以赣江新区为例，从建设用地空间形态模式、空间重心指数、空间紧凑度、空间形状分形维数等方面，分析了赣江新区2017—2018年建设用地空间格局变化特征，研究结果表明：(1)城乡建设用地和城市建设用地总量均呈现逐步增长的态势，并符合规划；(2)新区属于组团型发展模式，建设空间重心整体向东北方向扩张；(3)为有关政府部门继续推进新区建设和规划调整提供参考依据。     

基于RS与GIS的宁波市鄞州区土地利用变化分析

利用1990年土地详查变更调查数据和2006年SPOT遥感影像数据,借助GIS空间分析能力,通过计算土地利用类型动态度、转移矩阵、扩展强度指数分析了鄞州区的城镇土地利用变化的时空特征。研究结果表明:1)鄞州区城市、建制镇、交通运输用地、工矿用地扩展的大部分来源于耕地;2)区各街道城镇建设用地扩展强度指数大于建制镇;3)建设用地扩展以新城区及宁波城区周边的街道镇为主。     

近20年苏州土地利用动态变化时空特征分析

针对快速发展的城镇化地区土地利用矛盾突出的问题,该文以苏州市为例,对其近20年来的土地利用状况进行分析。以遥感影像为基础数据,采用了土地利用转移矩阵、标准差椭圆、点密度分析和热点分析等多个方法,讨论苏州市20年来土地利用数量结构的变化,并挖掘其在空间分布上的特征。结果表明:1995—2015年间苏州土地利用发生了剧烈变化,城镇建设用地快速扩张、大量农田急剧消减;扩张的城建用地在空间上具有明显的连片分布趋势;并且土地利用变化位置在空间上具有明显的方向性和集中性特征。     

西安城市扩展时空特征与驱动因素分析

针对西安城市扩展研究当中研究时段跨度大、政府政策对城市扩张影响分析较少等问题,该文基于1988—2015年10期Landsat影像及统计数据,利用线性趋势、多元回归分析等方法,分析了西安1988—2015年城市扩展特征及驱动因素。结果表明:西安主城区建设用地增量大、非主城区增速快,城市扩展主要发生在先后建立的经济新区当中,而第一、第二产业,城镇固定资产投资,非农业人口增加是驱动西安城市扩展的主要社会经济因素。     

Step-wise Land-class Elimination Approach for extracting mixed-type built-up areas of Kolkata megacity

The extraction of urban built-up areas is an important aspect of urban planning and understanding the complex drivers and biophysical mechanism of urban climate processes. However, built-up area extraction using Landsat data is a challenging task due to spatio-temporal dynamics and spatially intermixed nature of Land Use and Land Cover (LULC) in the cities of the developing countries, particularly in tropics. In the light of advantages and drawbacks of the Normalized Difference Built-up Index (NDBI) and Built-up Area Extraction Method (BAEM), a new and simple method i.e. Step-wise Land-class Elimination Approach (SLEA) is proposed for rapid and accurate mapping of urban built-up areas without depending exclusively on the band specific normalized indices, in order to pursue a more generalized approach. It combines the use of a single band layer, Normalized Difference Vegetation Index (NDVI) image and another binary image obtained through Logit model. Based on the spectral designation of the satellite image in use, a particular band is chosen for identification of water pixels. The Double-window Flexible Pace Search (DFPS) approach is employed for finding the optimum threshold value that segments the selected band image into water and non-water categories. The water pixels are then eliminated from the original image. The vegetation pixels are similarly identified using the NDVI image and eliminated. The residual pixels left after elimination of water and vegetation categories belong either to the built-up areas or to bare land categories. Logit model is used for separation of the built-up areas from bare lands. The effectiveness of this method was tested through the mapping of built-up areas of the Kolkata Metropolitan Area (KMA), India from Thematic Mapper (TM) images of 2000, 2005 and 2010, and Operational Land Imager (OLI) image of 2015. Results of the proposed SLEA were 95.33% accurate on the whole, while those derived by the NDBI and BAEM approaches returned an overall accuracy of 83.67% and 89.33%, respectively. Comparisons of the results obtained using this method with those obtained from NDBI and BAEM approaches demonstrate that the proposed approach is quite reliable. The SLEA generates new patterns of evidence and hypotheses for built-up areas extraction research, providing an integral link with statistical science and encouraging trans-disciplinary collaborations to build robust knowledge and problem solving capacity in urban areas. It also brings landscape architecture, urban and regional planning, landscape and ecological engineering, and other practice-oriented fields to bear together in processes for identifying problems and analyzing, synthesizng, and evaluating desirable alternatives for urban change. This method produced very accurate results in a more efficient manner compared to the earlier built-up area extraction approaches for the landscape and urban planning.     

An analysis of changes in the urban landscape composition and configuration in the Sancaktepe District of Istanbul Metropolitan City,Turkey using landscape metrics and satellite data

Changes in landscape composition and configuration patterns of Sancaktepe Municipal District in the Asian side of Istanbul Metropolitan City of Turkey were analysed using landscape metrics. Class-level and landscape-level metrics were calculated from the land cover/land use data using Patch Analyst, an extension in the Arc View GIS. The land cover/land use data were derived from classified satellite images of Landsat Thematic Mapper of 2002 and 2009 for Sancaktepe District. There was evidence of increase in agglomeration process of built-up patches as indicated by the increases in mean patch size, decrease in total edge and number of patches between 2002 and 2009. The urban expansion pattern experienced overall was not fragmented but concentrated due to infilling around existing patches. Changes in Area-Weighted Mean Shape Index and Area-Weighted Patch Fractal Dimension Index indicated that the physical shapes within built-up, forest and bareland areas were relatively complex and irregular. A conclusion is made in this study that spatial metrics are useful tools to describe the urban landscape composition and configuration in its various aspects and certain decisions whether to approve a specific development in urban planning could, for example, be based on some measures of urban growth form or pattern in terms of uniformity and irregularity, attributable to the dynamic processes of agglomeration and fragmentation of land cover/land use patches caused by urban expansion.     

典型海岸带城市扩张的多源遥感监测与预测——以青岛市为例

本文利用自1995年以来的4期DMSP-OLS、NPP-VIIRS夜光遥感影像与Landsat多光谱遥感影像,分析了青岛市近25年的城市建成区范围、各市区边界形态与扩展趋势,并结合土地利用分类、路网、POI、DEM等多源驱动因子及元胞自动机-马尔可夫（CA-Markov）模型,模拟并预测了2027年青岛市土地利用分类。结果表明,近25年青岛建成区扩展主要以外延式为主,其他城区总体上沿胶州湾方向扩展,四周向青岛主城区汇集,主城区建设用地向西北侧发展。本文验证了夜光遥感在监测与预测典型海岸带城市扩张方面的适用性,为城市化发展进程管理与决策提供了重要依据。     

Time series evaluation of landscape dynamics using annual Landsat imagery and spatial statistical modeling: Evidence from the Phoenix metropolitan region

Urbanization is a natural and social process involving simultaneous changes to the Earth’s land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective.     

Optimization of spatial statistical approaches to identify land use/land cover change hot spots of Pune region of Maharashtra using remote sensing and GIS techniques

This study investigated land use/land cover change (LULCC) dynamics using temporal satellite images and spatial statistical cluster analysis approaches in order to identify potential LULCC hot spots in the Pune region. LULCC hot spot classes defined as new, progressive and non-progressive were derived from Gi* scores. Results indicate that progressive hot spots have experienced high growth in terms of urban built-up areas (20.67% in 1972–1992 and 19.44% in 1992–2012), industrial areas (0.73% in 1972–1992 and 3.46% in 1992–2012) and fallow lands (4.35% in 1972–1992 and ?6.38% in 1992–2012). It was also noticed that about 28.26% of areas near the city were identified as new hot spots after 1992. Hence, non-significant change areas were identified as non-progressive after 1992. The study demonstrated that LULCC hot spot mapping through the integrated spatial statistical approach was an effective approach for analysing the direction, rate, spatial pattern and spatial relationship of LULCC.     

Satellite monitoring of urbanization and environmental impacts—A comparison of Stockholm and Shanghai

This study investigates urbanization and its potential environmental consequences in Shanghai and Stockholm metropolitan areas over two decades. Changes in land use/land cover are estimated from support vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix features. Landscape metrics are used to investigate changes in landscape composition and configuration and to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbanization is calculated by urbanization indices and the resulting impacts on the environment are quantified by ecosystem services. Growth of urban areas and urban green spaces occurred at the expense of cropland in both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120% in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover change was a 12% urban expansion that mostly replaced agricultural areas. From the landscape metrics results, it appears that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural/agricultural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted in ecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to the decrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very little. Total urban growth in Shanghai was 1768 km² and 100 km² in Stockholm. The developed methodology is considered a straight-forward low-cost globally applicable approach to quantitatively and qualitatively evaluate urban growth patterns that could help to address spatial, economic and ecological questions in urban and regional planning.     

Evaluating the compatibility of multi-functional and intensive urban land uses

This research is aimed at developing a model for assessing land use compatibility in densely built-up urban areas. In this process, a new model was developed through the combination of a suite of existing methods and tools: geographical information system, Delphi methods and spatial decision support tools: namely multi-criteria evaluation analysis, analytical hierarchy process and ordered weighted average method. The developed model has the potential to calculate land use compatibility in both horizontal and vertical directions. Furthermore, the compatibility between the use of each floor in a building and its neighboring land uses can be evaluated. The method was tested in a built-up urban area located in Tehran, the capital city of Iran. The results show that the model is robust in clarifying different levels of physical compatibility between neighboring land uses. This paper describes the various steps and processes of developing the proposed land use compatibility evaluation model (CEM).