基于缓冲区分析的城市化与地表水质关系研究——以烟台沿海区县为例

将城市化过程中的人为土地定义为建设用地,利用2004年TM影像得到烟台沿海区县建设用地数据。用缓冲区分析提取乡镇水平上建设用地比率和人口密度数据,缓冲半径从100m到2000m,利用ArcView空间分析功能对建设用地比率、人口密度、河网等级和水质进行叠置分析,并结合逐步回归分析方法揭示烟台沿海区县28个水质监测站各水质参量的空间变化情况。结果显示,通过建设用地比率和人口密度共同作用可以解释85%以上的水质参量模型,反映城市化的建设用地比率比人口密度能更好地解释水质参量的空间变化,大多数水质参量的最佳模型出现在2000m的缓冲半径上,表明建设用地比率和人口密度是影响研究区域水质的首要因素。同时,运用缓冲区分析等GIS空间分析方法为区域城市化进程与水环境质量的研究提供了新的途径。     

Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh,Indonesia

Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited.     

Predicting the Impact of Coastal Development on Water Quality Using Remote Sensing and GIS‐assisted Hydrologic Modeling Techniques

Abstract

A decline in water quality in the Okatie River, a coastal estuary located in Beaufort County, SC, has resulted in the closure of several shellfish beds. Continuing urban development within the watershed has altered land cover conditions and may be contributing to the recent decline in water quality. Remote sensing and geographic information system (GIS) technology, coupled with a water quality model were used to spatially model stormwater runoff to understand the relationship between recent changes in land cover and watershed runoff characteristics. High spatial resolution imagery acquired in 1994 and 1996 spatially documented pre‐ and post‐development land cover conditions within the watershed. The water quality model Agricultural Nonpoint Source Pollution (AGNPS) evaluated land characteristics such as soil type, topography, and land cover to simulate surface water flow and sediment transport over past and current land cover conditions. Results of the model were used to locate net increases of fresh water discharge and to suggest best management practices (BMP).     

苏州运河水质的TM分析

本文利用苏州地区陆地卫星TM数据和同期的地面水质监测资料建立了TM图像遥感水质模型,并将该模型应用于TM可见光彩色合成图像的分割处理,得到苏州地区水质空间分布图像。结合苏州运河水网的水文及水污染特征对遥感水质空间分布图像作了分析。结果表明TM数据真实地反映了苏州地区水质的空间分布规律,并得到当地环境监测部门的验证。     

土地利用空间数据尺度转换中的精度损失分析

在地理信息系统的支持下,利用两种矢栅转换原则对土地利用空间数据进行尺度转换,并对不同栅格大小下,各种土地利用类型的精度损失特征进行了分析.研究结果表明: (1)面积最大值原则(RMA)下,栅格大小< 80 m时,其精度损失均< 2%; 中心值原则(RCC)下,栅格大小< 160 m时,其精度损失均< 2%.(2)在栅格大小为800 m时,水域在面积最大值原则下的精度损失超过50%,在中心值原则下的精度损失超过20%.(3)在空间粒度逐渐增大过程中,面积最大值原则下生成的栅格数据相对误差较大,各地类精度损失的绝对值与栅格大小之间成正相关; 中心值原则下,各地类的相对误差较小且复相关系数均很小,表现出很强的随机性.     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

Oasis dynamics change and its influence on landscape pattern on Jinta oasis in arid China from 1963a to 2010a: Integration of multi-source satellite images

As one of the vital research highlights of global land use and cover change, oasis change and its interaction with landscape pattern have been regarded as an important content of regional environmental change research in arid areas. Jinta oasis, a typical agricultural oasis characterized by its dramatic exploitation and use of water and land resources in Hexi corridor, northwest arid region in China, was selected as a case to study the spatiotemporal oasis change and its effects on oasis landscape pattern. Based on integration of Keyhole satellite photographs, KATE-200 photographs, Landsat MSS, TM and ETM+ images, we evaluated and analyzed the status, trend and spatial pattern change of Jinta oasis and the characteristics of landscape pattern change by a set of mathematical models and combined this information with landscape metrics and community surveys. During the period of 1963a–2010a, Jinta oasis expanded gradually with an area increase of 219.15 km², and the conversion between oasis and desert was frequent with a state of “imbalance–balance–extreme imbalance conditions”. Moreover, most of the changes took place in the ecotone between oasis and desert and the interior of oasis due to the reclamation of abandoned land, such as Yangjingziwan and Xiba townships. Furthermore, the area, size and spatial distribution of oasis were influenced by human activities and resulted in fundamental changes of oasis landscape pattern. The fractal characteristics, dispersion degree and fragmentation of Jinta oasis decreased and the oasis landscape tended to be simple and uniform. Oasis change trajectories and its landscape pattern were mainly influenced by water resource utilization, policies (especially land policies), demographic factors, technological advancements, as well as regional economic development. We found that time series analysis of multi-source remote sensing images and the application of an oasis change model provided a useful approach to monitor oasis change over a long-term period in arid area. It is recommended that the government and farmers should pay more attention to the fragility of the natural system and the government should enhance the leading role of environmental considerations in the development process of oasis change, particularly with respect to the utilization of the limited water and land resources in arid China.     

基于土地利用类型提高人口格网数据空间精度的方法

高空间精度的人口格网数据具有空间分辨率高、人口空间分布特征准确的特点,在受灾人群估计、城市规划建设等领域有广泛的应用。针对已有的公开人口格网数据集(如WorldPop世界人口格网数据集)存在人口空间分布特征在小尺度上刻画不准确、空间分辨率较低的问题,本文使用东营市土地利用类型数据,结合地类权重和面积权重对WorldPop数据进行空间精度优化,获得东营市东营区黄河路街道25 m人口格网数据。相较于WorldPop数据,经过本文方法处理后的数据集空间分辨率更优,在可视化对比中,能够更准确地刻画人口分布特征,并在各地类人口占比统计中人口空间分布与用地单元分布一致性更高。该方法为获取小区域高空间精度人口格网数据提供了一种新思路。     

耕地自然质量空间分布及其影响因子分析——以北京市大兴区为例

定量分析耕地质量的空间分布特征,是制定与实施耕地保护措施的重要依据。本文以耕地质量等级补充完善成果为基础,以自然等指数为空间变量,采用空间自相关分析方法对北京市大兴区耕地自然质量的空间分布特征进行了研究,并采用变异系数、二元相关分析和偏相关分析方法对其影响机制进行分析,揭示了耕地自然质量空间差异的主导影响因子。研究结果表明:大兴区耕地自然质量在200~900m尺度范围内呈显著的空间正相关性,正相关HH型高等地明显聚集分布,LL型低等地面积较大且聚集性较低,负相关类型(HL和LH型)耕地无明显集中区域,零星分布。土壤有机质、表土质地和土壤剖面构型是影响耕地自然质量空间分布格局的主导因子,但影响程度有所差异。     

黑龙江省耕地非农化的空间格局与重心曲线分析

为了揭示耕地非农化的空间格局与重心曲线,为耕地资源保护和利用政策制定提供决策支撑,该文以黑龙江省1980、1990、2000、2010、2015年土地利用数据为基础,运用GIS空间分析方法,引入重心模型分析黑龙江省耕地非农化的空间格局及重心曲线。研究结果表明:1980—2015年黑龙江省耕地非农化发展不平衡,4个时期耕地非农化面积呈波动增长的趋势;耕地非农化等级空间分布特征明显,等级较高的城市集中分布在西部地区;耕地非农化速度等级的重心曲线在空间分布上,具有从中心向边缘延伸的特点;耕地非农化围绕中心地区进行,其空间扩散路径在图形上呈现出一个回旋状。     

利用地理省情监测数据分析土地利用变化——以济南市东部老工业区为例

传统的土地利用变化分析方法无法进行大规模、长周期的土地动态变化监测,也无法适应城市日新月异的发展需求。本文利用山东省地理省情监测数据,采用多种土地利用指数模型对济南市东部老工业区的土地利用变化情况进行了研究。这些指数模型包括动态度、转移矩阵、多度、重要度等。本文通过定量分析2017-2019年老工业区各土地类型的空间格局演变过程,揭示其土地利用空间格局演化机理,并结合社会经济发展的相关资料,对发生变化的原因和内在驱动力作了合理的解释和说明,为新型城镇化政策制定提供了切实的数据支撑和决策依据。     

Predictive fire occurrence modelling to improve burned area estimation at a regional scale: A case study in East Caprivi,Namibia

Fires threaten human lives, property and natural resources in Southern African savannas. Due to warming climate, fire occurrence may increase and fires become more intense. It is crucial, therefore, to understand the complexity of spatiotemporal and probabilistic characteristics of fires. This study scrutinizes spatiotemporal characteristics of fires and the role played by abiotic, biotic and anthropogenic factors for fire probability modelling in a semiarid Southern African savanna environment. The MODIS fire products: fire hot spots (MOD14A2 and MYD14A2) and burned area product MODIS (MCD45A1), and GIS derived data were used in analysis. Fire hot spots occurrence was first analysed, and spatial autocorrelation for fires investigated, using Moran's I correlograms. Fire probability models were created using generalized linear models (GLMs). Separate models were produced for abiotic, biotic, anthropogenic and combined factors and an autocovariate variable was tested for model improvement. The hierarchical partitioning method was used to determine independent effects of explanatory variables. The discriminating ability of models was evaluated using area under the curve (AUC) from the receiver operating characteristic (ROC) plot. The results showed that 19.2–24.4% of East Caprivi burned when detected using MODIS hot spots fire data and these fires were strongly spatially autocorrelated. Therefore, the autocovariate variable significantly improved fire probability models when added to them. For autologistic models, i.e. models accounting for spatial autocorrelation, discrimination was good to excellent (AUC 0.858–0.942). For models not counting spatial autocorrelation, prediction success was poor to moderate (AUC 0.542–0.745). The results of this study clearly showed that spatial autocorrelation has to be taken in to account in the fire probability model building process when using remotely sensed and GIS derived data. This study also showed that fire probability models accounting for spatial autocorrelation proved to be superior in regional scale burned area estimation when compared with MODIS burned area product (MCD45A1).     

时序InSAR监测京雄城际铁路河北段地面沉降

本文以京雄城际铁路河北段固安站至雄安站沿线作为研究区,利用2018—2020年共34景Sentinel-1B影像,基于小基线集雷达干涉测量技术(SBAS-InSAR)获取京雄城际铁路河北段沿线的地面沉降时空分布信息,结合空间自相关分析方法,揭示研究区地面沉降的空间分布格局,并对沉降原因进行初步分析。研究结果表明,京雄城际铁路河北段沿线地面沉降发展由北向南存在一定的差异。北部年均沉降速率小于10 mm/a,南部沉降较为严重,最大年均沉降速率达-105.6 mm/a,且沿线西部年均沉降速率高于东部区域。通过分析影响因素得知,地面沉降量与地下水埋深值存在相关性,地下水埋深高的地区地面沉降量较高。同时结合研究区土地利用变化结果发现,城市化建设所产生的静载荷对京雄城际铁路沿线的地面沉降产生一定的影响。     

Spatial analysis of high-resolution urban thermal patterns in Vojvodina,Serbia

Main objective of this study was to establish a relationship between land cover and land surface temperature (LST) in urban and rural areas. The research was conducted using Landsat, WorldView-2 (WV-2) and Digital Mapping Camera. Normalised difference vegetation index and normalised difference built-up index were used for establishing the relation between built-up area, vegetation cover and LST for spatial resolution of 30 m. Impervious surface and vegetation area generated from Digital Mapping Camera from Intergraph and WV-2 were used to establish the relation between built-up area, vegetation cover and LST for spatial resolutions of 0.1, 0.5 and 30 m. Linear regression models were used to determine the relationship between LST and indicators. Main contribution of this research is to establish the use of combining remote sensing sensors with different spectral and spatial resolution for two typical settlements in Vojvodina. Correlation coefficients between LST and LST indicators ranged from 0.602 to 0.768.     

3D Geographic Reconstruction and Visualization Techniques Applied to Land Resource Management

Optimized land resource management depends on reliable and detailed information describing the spatial distribution of soils, geology, topography, and land use. Soil–landscapes are three–dimensional (3D) systems commonly represented using 2D maps utilizing geographic information systems. Addressing 3D soil–landscape reality is crucial for land resource management in terms of crop growth and transport processes (e.g. nitrate leaching) that are driving soil and water quality. Our objective was to investigate the usefulness of 3D geographic information technology (GIT) applied to land resource management. Our approach is based on 2D and 3D ordinary kriging interpolating surface and subsurface attributes to reconstruct soil–landscapes. We used Virtual Reality Modeling Language, which is a web–based 3D graphics language, to visualize objects (e.g. voxels, polyhedrons) representing soil and landscape attributes. We produced a 3D block model showing the spatial distribution of bulk densities and relief for a site in southern Wisconsin and a 3D stratigraphic model showing the spatial distribution of soil horizons and relief for a site in northern Florida. Emerging GIT was used to develop 3D soil–landscape models describing continuous changes of soil and landscape attributes. Combining multimedia elements (e.g. WWW, 3D visualization, and interactivity) can produce insight that would not arise from use of the elements alone. Three–dimensional scientific visualization is a powerful tool to help us see what is invisible from above the ground.     

基于北京二号与地理国情数据的林地提取

由于地理国情林地数据不包含实地面积小于400 m²的树木或四旁单排林,若仅利用地理国情的林地数据统计区域森林覆盖率,将对四旁树面积较大地区的林地统计结果产生较大误差。为提取区域内准确的林地覆盖与空间分布状况,本文借助地理国情地表覆盖数据,提出了一种基于北京二号高分辨率遥感影像的林地提取方法。首先,根据遥感影像光谱特征,将研究区按植被、道路、铁路、建筑用地进行地类划分,并基于遥感影像进行各地类的样本提取,通过可分离检验的样本利用最大似然分类提取研究区内植被覆盖范围;然后,借助地理国情地表覆盖数据,使用叠置分析剔除误分、错分地类,得到区域林地的空间分布。试验结果表明：(1)研究区内林地覆盖率为20.3%,尚未满足北京新一轮林地规划需求;(2)地理国情地表覆盖数据内林地面积占提取林地总面积的54.03%,说明在部分地区使用本文方法对地理国情林地数据进行补充是有必要的。通过将试验结果与遥感影像进行目视比对并结合外业调查结果发现,提取的林地空间分布情况与实际分布基本相符。本文为地理国情的应用提供了一种新方法,研究结果可辅助区域的绿色发展规划,有助于构建科学的生态空间格局。     

深圳市土地利用结构时空分析

基于2009年与2014年深圳市土地利用变更数据,分析其土地利用结构特征及其空间布局,有利于实现区域土地合理开发和可持续利用。运用多种指标及模型从土地利用的综合程度、组合类型和各地类区位意义3个方面来分析深圳市10区土地利用结构的时空变化特征。结果表明:研究区交通用地、城镇工矿用地、耕地面积有所增加,但总体变化不大,趋势放缓,各区之间存在一定差异;组合类型上表现为整体功能较弱、类型数少,各区组合多包含城镇及工矿用地与林地,分布集中连片,主导着深圳市土地利用变化趋势;程度变化上,整体综合指数较高并有所增加,表明利用程度高且处于持续发展中,但各区之间程度高低不一;区位意义在各区域地类上表现也不尽相同且变化不大。结论:研究区域土地供需矛盾仍十分突出,人多地少态势明显,区域间土地利用结构存在明显分异规律,区域发展协调性不够,利用布局有待优化。     

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.     

基于土地利用变化模拟的生态风险动态评价

以松滋市2000年和2010年Landsat TM影像为基础,利用CA-Markov模型并引入土地利用总体规划限制因素,预测松滋市2020年土地利用情况。构建土地利用生态风险指数,运用4 km×4 km的网格模型采样,采用普通克里金插值法进行插值,引入密度分割法进行归一化等级划分,利用GIS工具进行空间叠加分析并制作土地利用生态风险分级图,实现土地利用变化生态风险动态评价,揭示生态风险变化趋势。模拟预测及评价结果显示:1松滋市2000~2020年土地利用结构发生较大变化,耕地、水域和未利用地面积减少,林地和建设用地面积增加。2土地利用生态风险呈逐步升高趋势,由2000年的21.95升高到2020年的88.53,分布以中部及南部较高,西部及东北部较低。32000~2020年分级结果主要以低风险、较低风险及次中风险为主,特高风险区域逐渐增多,生态风险等级以中心城区为中心呈圈层分布,且距离越远生态风险等级越低。     

用基于知识的决策树方法分层提取矿区土地类型——以湖北大冶为例

以湖北大冶为研究区,采用多时相陆地卫星遥感图像,通过不同波段组合,以及ironoxide指数和归一化差异植被指数(NDVI)等,详细分析了各地表地物光谱特征和空间特征,建立了研究区分类知识库表,采用决策二叉树法进行分类,得到了高精度分类结果图。基于不同时相分类结果的变化检测,通过对研究区水体污染、矿区复垦、耕地变化等分析,认为从1986～2002年,研究区水质虽有一定改善,但矿区植被退化严重,耕地大量减少,停产矿区复垦仅为20%,为合理保护矿区生态环境和科学管理采矿企业提供了有用资料。