榆林东北部地区新石器时代环境宜居性分析

针对榆林东北部地区新石器时代的环境宜居性分布规律进行研究,通过SOFM神经网络模型对研究区聚落等级进行划分,结合地形高程、坡度、坡向、距水系距离、植被覆盖度等因子,利用指数变异法客观确定各因子的相对重要性并构建指数模型。研究结果表明,研究区遗址大都分布在海拔1 000~1 200 m、坡度3~9°、距水系距离为0~800 m、坡向为阳坡以及植被覆盖度较好的区域,一级聚落均分布在古代环境宜居性较高的区域。与仅使用地形因子建立的指数模型相比,加入植被覆盖度和聚落等级因子的模型对不宜居的沙漠和遗址分布空白区域划分的宜居性等级低,对遗址分布密集的宜居区域划分的宜居性等级高,宜居性等级划分结果与各等级遗址密度分布的客观事实更为吻合,综合因子模型对区域宜居性等级划分更为精确。     

基于RS与GIS技术的泸定县植被空间分布分析

以四川省泸定县为分析研究区域,综合运用遥感图像处理技术与GIS空间分析技术,用ETM+遥感影像获取归一化植被指数(NDVI)信息并反演植被覆盖度,用地形图等高线生成数字高程模型(DEM)并提取地形因子。借助叠合分析法,讨论植被覆盖度与海拔高度、坡度、坡度变率、坡向、坡向变率5种地形因子的空间关系,得到泸定县关于地形因子的各等级植被空间分布特征。分析对地植物学中高山峡谷地区植被的地形格局分布规律研究与生态环境的评价与改良都具有重要的参考价值。     

借助GIS研究史前聚落遗址的空间分布特征

对史前聚落遗址的分布特征研究,有助于了解史前人类对环境的选择策略以及聚落系统的演变规律。利用地理信息系统空间分析方法,对河南省史前聚落遗址的分布特征进行研究,分析聚落选址与区域海拔高度、地形坡度、水系等地理环境之间的相互关系。研究结果表明：四个时期的史前聚落大部分分布在海拔50-400m、坡度小于3°、距离河流在3km以内的地带。     

采用逻辑回归的汾河流域遗址分布研究

为了更好地指导考古挖掘和理解古人类活动,该文从汾河流域DEM数据中提取高程、坡度、坡向、地形起伏度、地表曲率、距河流距离及距大遗址距离等作为自变量,利用二元逻辑回归建立流域内仰韶时期至夏商时期各时期遗址分布模型,对模型结果进行了定量分析并生成了汾河流域各时期遗址分布概率图,在此基础上对汾河流域人类文化遗址的分布特征进行研究。遗址分布模型总体分类精度较好。遗址分布模型对考古工作及古环境研究具有重要价值,可以为考古工作提供决策支持。     

郑洛地区史前聚落遗址坡向坡度分析

基于前人的研究成果,本文利用GIS软件对郑洛地区三个连续文化时期的史前聚落遗址的坡向、坡度分布情况进行了分析。研究结果表明,研究区中大部分聚落遗址分布在坡向朝南、坡度小于3°的地点,但是仍然有少部分遗址处于光照差、坡度较大的地点。     

叶尔羌河流域植被指数与地貌状况耦合度研究

针对叶尔羌河流域这一生态脆弱区,基于像元二分法利用MODIS NDVI数据计算该研究区典型正常年份2016年6—9月生长季植被指数(植被覆盖度),分析探讨了该流域植被覆盖度与土地利用/覆盖状况及高程、坡度、坡向等地貌状况主要要素之间的耦合关联关系。结果表明:叶尔羌河下游地区地形起伏较小,植被覆盖状况和土地利用/覆盖类型均具有明显的地带状与分层分布特征,植被覆盖度仅与距离水源地的远近相关性显著,与高程、坡度等其他地貌因子无明显相关性;而叶尔羌河中上游地区植被覆盖状况复杂,植被覆盖度与高程、坡度和坡向三因子总体耦合度较高。高程对植被覆盖状况的影响尤为显著,具有明显的垂直地带性;同时,随着高程增加,坡度对植被覆盖度的影响则表现出一定的垂直周期地带变化特性,以及随着坡向的变化植被覆盖度呈现出由阴坡、半阴坡较高(4 000m以下地区)按"顺时针"向阳坡、半阳坡较高(4 000m以上地区)逐渐转移。     

泰山地区近三十年植被覆盖变化与地形因子分析

针对在人类活动影响下,泰山地区植被覆盖面积变化情况,以陆地卫星(Landsat TM/OLI)遥感影像为研究基础影像,采用遥感图像处理平台(ENVI)和ArcGIS软件,对泰山地区1985、1995、2003、2008、2013、2018年的6期遥感影像,通过归一化指数(NDVI)对遥感影像植被信息进行反演,通过地形因子提取实现对高程、坡度、坡向信息的提取与绿色植物覆盖的综合分析.研究发现:泰山地区植被面积由西北向中南递减,周边农村区域植被覆盖大于中心城区;伴随海拔增高,植被面积呈倒"U"变化,多在100～500 m高程范围内;植被多分布在坡度较缓,向阳区域.     

典型绿洲城市不透水面提取及时空变化分析

选取库尔勒市城区为研究区,以2009、2012、2014年Rapid Eye影像为数据源,利用混合像元分解方法提取了库尔勒市的不透水面信息,分析了不透水面的时空变化特征。选取高程、坡度、坡向、距水系距离、距道路距离、距2009年城区距离、距规划区距离7个因子,利用Logistic回归进一步分析了2009—2014年库尔市不透水面扩张的主要影响因素。结果表明:2009年库尔勒市不透水面所占比例为27.04%,2012年为32.89%,2014年为35.69%;各因素的贡献率依次为坡度、坡向、距规划区距离、距道路距离、距2009年城区距离、距水系距离、高程;整体来看,在交通线密集的地方,城市不透水面分布较多,相对而言交通线稀疏的地方不透水面分布较少,并且具有沿道路轴线发展的趋势。     

绿色空间生态服务与地形因子的相关性分析

绿色空间生态服务(green space ecosystem services,GSES)与地形因子(坡度、海拔、坡向)有密切的关系,研究其关系对区域生态服务功能的修复、完善和可持续发展具有重要意义。通过奉化市绿色空间地类的划分和生态服务的计算模型获得GSES的价值。利用GIS技术提取坡度、海拔、坡向3个地形因子,同时分别获得每个因子对应的GSES值,最后选择Spearman相关分析模型对GSES价值与地形因子值进行检验。结果显示,奉化市GSES价值在空间上呈现出东北部、东南部GSES价值最低,西部、南部GSES价值较高的格局;GSES价值与地形因子的相关性强度表现为:坡度海拔坡向。同时由于海拔、坡度和坡向的变化导致温度、水分和太阳辐射在地表发生变化,并致使生态服务空间格局随海拔、坡度和坡向的变化呈现一定的规律性。     

中国地区3"SRTM高程误差特征

系统评估了中国地区航天飞机雷达地形测绘任务（Shuttle Radar Topography Mision,SRTM）3″高程误差的分布及其与地形和地表覆盖因素的关系。通过单因子分析法,使用从50多万个样本点中提取的地表特征属性确定误差的变化规律。结果显示:SRTM高程误差与不同地形和地表覆盖类型关系密切;坡度增大误差由正变负,误差绝对值增大;正误差集中在偏北坡向,负误差集中在西南坡向;误差随植被覆盖增加而增大;冰川、沙漠、湿地区域误差整体为负,城镇建筑区的误差整体为正;坡度作为主导因素,同时影响其他因素对高程误差的作用。数据在某些区域存在明显高程异常,在平坦地区存在条带现象。整体上SRTM高程误差在中国地区呈现复杂的变化规律。     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

基于GIS技术的武夷山市农村居民点空间分布特征

农村居民点形成和发展与区域的自然环境有着密切的关系。利用GIS空间分析功能,定量分析农村居民点与海拔高度、坡度、坡向、交通、河流等自然环境因子的关系,结果表明:①武夷山市农村居民点的分布格局受海拔、坡度、坡向、道路、河流的影响比较明显。②农村居民点呈数量多、质量低、大散居、小聚居的空间分布特征,部分居民点分布在不适宜人们居住的区域,有待调整。因此本研究能为武夷山市农村居民点整理、农村居民点规划提供一定的决策支持。     

澜沧江流域居民点空间分布格局及影响因素研究

居民点空间分布是区域自然、社会、经济以及历史发展的综合反映,影响着区域经济发展的规模、方向以及发展的可能性。区域自然环境是居民点形成和发展的基础,社会经济因素也对居民点的分布产生重要影响。基于澜沧江流域数字高程模型(DEM)提取坡度、坡向和地形起伏度,结合1∶5万地名数据库的居民点及国家1∶25万基础地理信息数据库的河流、道路信息,研究了澜沧江流域居民点的空间分布格局,并对澜沧江流域居民点分布的影响因素进行定量了分析。研究结果显示,海拔、坡度、坡向、地形起伏度对居民点的分布有显著影响,居民点倾向于分布在海拔较低、坡度和起伏度较小、东南坡向的地区,各级居民点沿河流、道路分布明显。另外,较高级别的居民点更趋向于分布在自然条件较好的区域。研究结果可为澜沧江流域综合开发和生态环境保护提供科学依据。     

Vulnerability Assessment and Earthquake Risk Mapping in Part of North Iran Using Geospatial Techniques

Earthquakes cause huge loss of lives and infrastructure every year in Iran. Many settlement areas (urban & rural) as well as Tehran, the capital city of Iran are located in the hazardous area. This research deals with the earthquake risk assessment and mapping based on recent remote sensing information on a GIS platform. The study area is part of Central Alborz in southern Caspian Sea and north of capital city of Tehran called Marzanabad area. It is a potentially high-risk zone as several earthquakes have occurred in the past. The study’s main objective is to develop an Earthquake Risk Map at the scale of 1:25,000 to identify high-risk zone and vulnerability areas to the settlements and infrastructure of area. Digital lineaments wear extraction and analysis for identification the faults using several RADAR and optical images with spatial analysis techniques. The probable faults were detected by superimposition of the lithological and geomorphologic features and their variance over the lineaments in a GIS environment. This research work involved fault identification on the remote sensed dataset as well as field studies and the risky areas were classified in the vicinity of the faults by applying different buffer with specifying distance of the source/site of risk to fault location. Statistical analysis of Earthquake Risk Map (ERM) by GIS indicated that 32% of the total area with about 66% of settlements and 52% of population is located in strongly high-risk and high-risk zone. Moderately low risk and low risk zones cover 38.67% of total area, which is free of settlements as well as population. The Earthquake map elaborated in this research work will be a useful tool for disaster management as well as urban and regional planning of future activities in the area.     

独龙江流域居民点的空间分布

利用ArcGIS软件提取了研究区DEM的高程、坡度、坡向、起伏度等信息与国家1:250000基础地理地理信息数据提供的居民点、水源信息进行空间叠加分析,得出云南省独龙江流域特有民族之一独龙族居民点的空间分布与高程、坡度、坡向、起伏度、水源的定量关系,揭示了自然因素对本区居民的影响程度,为人们更好地了解独龙族所处的独特地理环境提供了依据,也为政府做好本区的民族工作提供了依据。     

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.     

Landscape drainage modelling to enhance Landsat classification accuracies

Studies integrating digital elevation models (DEMs) with multispectral digital satellite data have typically concentrated on geographic areas characterized by moderate to high topographic relief. Variables such as elevation, slope gradient and aspect contribute most significantly to the zonation of vegetation in these environments. In areas where relief is low, vegetation zonation is based not on individual form elements but rather on physical processes. The purpose of this research was to investigate the potential of integrating multispectral and ancillary process data in such a low relief environment. For this a study area was chosen in the Boreal forest of west central Alberta where the zonation of vegetation is based, to a large extent, on landscape drainage. An initial classification of forest cover based on Landsat multispectral data yielded overall classification accuracies of 58%. A DEM was developed from a digitized 1:50,000 topographic map sheet. The differential geometry of the DEM was mapped as a series of coverages: slope, aspect, and directional curvatures (down ‐ and across slope). Two additional coverages, relief and flow paths, were also developed and mapped. A data set was extracted from the DEM through which landscape drainage could be evaluated. A univariate analysis of drainage using the form variables resulted in a 45% to 47% explanation of the observed variation. Multivariate analysis combining slope gradient, across and down slope curvatures, relief, and flow paths increased the explanation to 68%. The MSS data were reinterpreted integrating the DEM ‐ based landscape drainage model. The resulting classification accuracy was increased to 73%.