巴马县地形因子与土地利用空间分布关系研究

选取广西喀斯特地区代表之一巴马县,利用土地利用现状图和DEM,从中提取出研究区的高程、坡度、坡向数据。利用ArcGIS的空间分析功能,分别对高程、坡度、坡向和土地利用数据进行叠加处理,得到在不同高程、坡度、坡向下的土地利用分布情况,并利用SPSS软件对土地利用类型与地形因子进行相关分析。     

基于DEM的广东省山区土地利用变化分析

土地利用/覆盖变化研究是全球环境变化与可持续发展研究的热点和前沿领域。近年来,随着广东省经济发展迅速,土地利用在受珠江三角洲地区辐射影响的广东山区也发生了较大的变化。在DEM的基础上,分析1993~2003年来广东省山区韶关市的土地利用变化与高程、坡度和坡向的关系。研究结果表明,1993~2003年来广东省山区韶关市的土地利用变化在高程、坡度和坡向有很大差异,这些因素对该地区的土地利用有着重要的影响。为促进该地区的土地可持续利用,需进一步因地制宜,结合高程、坡度和坡向等影响因素优化土地利用类型和改善地表覆盖。     

基于DEM的地形高度与土地利用空间格局的关系——以韶关市大塘镇为例

地形高度是影响土地利用空间格局分布的影响因素之一,本文以韶关市大塘镇为研究区,基于研究区的DEM和土地利用现状图,利用GIS提取研究区的地形高程及土地利用信息,并将各地形高度与土地利用图进行叠加分析,研究地形高度与土地利用空间格局的关系。研究结果表明:1随着高程增加,各土地利用类型的面积及占土地总面积的比例都呈下降趋势;2土地利用类型占该该类土地利用的比重均在第一级高程或第二级高程达到最大值,随高程增加,分布比重逐渐下降;3低高程区域土地利用较为破碎,高高程区域土地利用较为集中,以林地为主。     

水电站库区土地利用景观空间分异特征

利用高空间分辨率Quick Bird影像解译了玛尔挡水电站库区的土地利用类型,并分析了土地利用景观随高程、坡度、坡向的空间分异特征。结果表明：土地利用景观格局的空间分异特征符合当地自然规律和社会经济规律。分析区域土地利用景观格局的空间分异特征,有利于掌握水电开发的区域生态环境背景,有助于项目的科学论证和工程建设的顺利实施。     

基于DEM的龙口市土地利用空间格局与时空变化研究

本文以龙口市为例,在ARCG IS软件的支持下,分别从高程、坡度与坡向三个方面,对研究区内的耕地、园地、林地和建设用地四种土地利用类型,进行了空间格局与时空变化研究。研究结果表明:从1989年到2005年的17年间,耕地总数在减少,但其分布仍主要集中于低地形等级上。园地的面积增加较多,空间分布上,有向地形高等级发展的趋势,说明园地对各地形因子的适应性较强。林地主要分布于高海拔,大坡度的区域,这有利于防止水土流失。建设用地基本上不受地形的限制,其分布主要是人类活动的结果,因此它在各地形等级的变化表现不明显。通过对土地利用空间格局指标及参数特征的定量分析,将有助于优化该区土地利用结构,实现不同地形上土地利用类型的合理布局,促进区域持续发展。     

南昌市城区土地利用变化时空特征分析

在遥感技术与GIS挂术的支持下,对南昌市城区15年来土地利用的时间动态特征和空间动态特征进行了定量分析。具体表现为通过数学建模,利用土地利用动态度模型、土地利用开发度模型、土地利用耗减度模型等对土地利用时空特征进行了分析。研究结果表明:南昌市城区的土地利用格局分布越来越均匀,斑块间的面积差异在逐渐缩小,某一土地利用类型占优势的状况逐渐减小,土地利用受人类影响程度越来越大。而且还揭示出土地利用类型中除耕地面积大量减少、建设用地面积大量增加外,其他土地利用类型均有不同程度的变化。     

广西喀斯特山区土地利用景观格局特征分析

利用GIS技术方法对广西都安县2006年的土地利用数据进行了景观格局指数研究,包括景观多样性指数、形状指数、边界密度等。结合土地利用现状图分析喀斯特地区的景观格局分布特点。总体看来该区域土地利用类型多样复杂,景观破碎度较高,连通性差,抵抗外界干扰能力弱。研究土地利用景观空间格局可以为喀斯特岩溶山区土地利用结构的调整、土地管理政策的制定及生态环境的恢复重建提供决策依据。     

基于地形梯度的山地流域土地利用格局及时空演变研究——以云南小江流域为例

地形差异是山区土地利用结构和空间格局分异的重要影响因素,云南小江流域作为典型山地流域的代表,针对其土地利用结构不合理导致生态环境恶化的问题,文中提出利用小江流域1990、2000、2010年三期土地利用数据,采用GIS空间分析技术,在简要分析土地利用宏观总体格局及变化的基础上,分析流域4大垂直带谱的土地利用格局,并分析驱动因素。重点从高程和坡度两个因子分析流域土地利用格局及演变的地形梯度特征,得出土地利用变化所在的各地形梯度位置范围,可为小江流域土地利用结构优化、土地资源合理利用和生态环境治理及改善提供重要参考。     

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。     

一种统计坡面上土地表面积的方法研究

本文主要介绍和研究一种统计坡面上土地表面积的方法。建立在G IS的基础上,利用江浦县1∶25万、1∶5万地形图、六合县1∶5万地形图的数字化等高线生成的DEM数据,自动提取坡度信息、计算坡度的正割值信息,并分别与江浦县和六和县的同空间分辨率的土地利用栅格数据进行叠合分析,得出两县不同土地利用类型在不同坡度级上的表面积和投影面积数值。并经不同比例尺、不同空间分辨率、不同区域内各类土地的表面积与投影面积之比作比较。研究结果表明,利用此方法提取的表面积在一定研究范围内,对于那些坡度较大而且面积亦大的土地利用类型面积的准确统计有重要意义。     

Tourism land use simulation for regional tourism planning using POIs and cellular automata

Previous studies on tourism land use primarily focus on the spatial distribution, and its related impacts on the environment. Here, we propose a future tourism land use simulation model for mountain vacations based on the cellular automata and Markov chain methods, having verified and simulated tourism land use in Emeishan city at a spatial resolution of 30 × 30 m using remote sensing and GIS. In addition, we introduced a tourism land use intensity index to study the spatial expansion mode of tourism land use. The results have confirmed the validity of the model and demonstrated its ability to simulate future tourism land use. The average growth rate of tourism land use from 2010 to 2015 is 33.36%, and tourism land use will rise from 1.26% of Emeishan city’s land area in 2015 to 2.95% in 2030. Tourism land use shows a spatial expansion pattern along channels from scenic spots to the urban area. The growth of tourism land use in the protected area has an increasing trend when there is no restriction on development, especially in the Eshan region. The simulation results can provide useful implications and guides for regional tourism planning and management.     

Predicting the distribution of C3 (Festuca spp.) grass species using topographic variables and binary logistic regression model

The spatial distribution of different C3 and C4 grass species in tropical montane areas is commonly influenced by a number of factors that include site-specific topography. Hence, the distribution of these grasses across topographic gradients can vary significantly. In this study, we investigate the influence of topographic factors (elevation, slope and aspect) on the spatial distribution of Festuca grass species in a commonage area, comprising agro-biodiversity conservation land use. Integration of the topographic variables using GIS and binary logistic regression (LR) modelling showed that C3, Festuca grass species distribution can be predicted or mapped with an accuracy of 80% in the landscape under study. The study contributes to understanding the spatial distribution of C3 grass species and provides valuable information for designing and optimizing rangeland conservation in the subtropical montane landscapes.     

基于DEM的桂西北土地利用与地形关系特征分析

以都安瑶族自治县为例,利用DEM数据、土地利用现状图,以及野外实际调查资料,通过建立基于高程的地貌分区、叠加分析,分析了研究区土地利用空间分布特征及与地形因子的关系.结果表明,土地利用类型空间分布具有强烈的区域差异性,各地貌分区区域的土地利用组合不同,同一土地利用类型在不同高程区域的分布存在差异;随海拔高程增加,居民地...     

Examining the Effect of Ancillary and Derived Geographical Data on Improvement of Per-Pixel Classification Accuracy of Different Landscapes

Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. Multi-resolution remote sensing (RS) data coupled with additional ancillary topographical layers (both remotely acquired or derived from ground measurements) with appropriate classification strategies would be more effective in capturing LC dynamics and changes associated with the natural resources. Ancillary information would make the decision boundaries between the LC classes more widely separable, enabling classification with higher accuracy compared to conventional methods of RS data classification. In this work, we ascertain the possibility of improvement in classification accuracy of RS data with the addition of ancillary and derived geographical layers such as vegetation indices, temperature, digital elevation model, aspect, slope and texture, implemented in three different terrains of varying topography—urbanised landscape (Greater Bangalore), forested landscape (Western Ghats) and rugged terrain (Western Himalaya). The study showed that use of additional spatial ancillary and derived information significantly improved the classification accuracy compared to the classification of only original spectral bands. The analysis revealed that in a highly urbanised area with less vegetation cover and contrasting features, inclusion of elevation and texture increased the overall accuracy of IKONOS data classification to 88.72% (3.5% improvement), and inclusion of temperature, NDVI, EVI, elevation, slope, aspect, Panchromatic band along with texture measures, significantly increased the overall accuracy of Landsat ETM+ data classification to 83.15% (7.6% improvement). In a forested landscape with moderate elevation, temperature was useful in improving the overall accuracy by 6.7 to 88.26%, and in a rugged terrain with temperate climate, temperature, EVI, elevation, slope, aspect and Panchromatic band significantly improved the classification accuracy to 89.97% (10.84% improvement) compared to the classification of only original spectral bands, suggesting selection of appropriate ancillary data depending on the terrain.     

Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed

Human-induced land use/cover change has been considered to be one of the most important parts of global environmental changes. In loess hilly and gully regions, to prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades. The main objective of this study is to quantify the spatio-temporal variability of land use/cover change spatial patterns and make preliminary estimation of the role of human activity in the environmental change in Xihe watershed, Gansu Province, China. To achieve this objective, the methodology was developed in two different aspects, that is, (1) analysis of change patterns by binary image of change trajectories overlaid with different natural geographic factors, in which Relative Change Intensity (RCI) metric was established and used to make comparisons, and (2) analysis based on pattern metrics of main trajectories in the study area. Multi-source and multi-temporal Remote Sensing (RS) images (including Landsat ETM+ (30 June 2001), SPOT imagery (21 November 2003 and 5 May 2008) and CBERS02 CCD (5 June 2006)) were used due to the constraints of the availability of remotely sensed data. First, they were used to extract land use/cover types of each time node by object-oriented classification method. Classification results were then utilized in the trajectory analysis of land use/cover changes through the given four time nodes. Trajectories at every pixel were acquired to trace the history of land use/cover change for every location in the study area. Landscape metrics of trajectories were then analyzed to detect the change characteristics in time and space through the given time series. Analysis showed that most land use/cover changes were caused by human activities, most of which, under the direction of local government, had mainly led to virtuous change on the ecological environments. While, on the contrary, about one quarter of human-induced changes were vicious ones. Analysis through overlaying binary image of change trajectories with natural factors can efficiently show the spatio-temporal distribution characteristics of land use/cover change patterns. It is found that in the study area RCI of land use/cover changes is related to the distance to the river line. And there is a certain correlation between RCI and slope grades. However, no obvious correlation exists between RCI and aspect grades.     

基于遥感影像的土地动态变化监测

土地利用/覆盖变化是目前研究全球及区域环境的一个重要领域,在城镇化加速的今天,城镇的土地利用格局也发生了飞速的变化。本文通过其一研究区内的Landsat TM遥感影像进行处理,获取了2007~2016年10个时相土地利用/覆盖信息,通过不同的预测模型对监测到的数据进行处理及比较,根据相应的最优预测方法预测了2017~2019年南昌市各土地类型的数据,由此研究并探讨了南昌市土地利用/覆盖的时空格局变化。     

Analyzing the effects of scale and land use pattern metrics on land use database generalization indices

The generalization index system is one of the critical issues for computer-aided land use database generalization. This paper studies the scale and land use pattern effects on land use database generalization indices and estimates the thresholds of these indices based on a typical land use database sample. The index system of land use database generalization is discussed and constructed from macro and micro perspectives. Six land use pattern metrics, namely, land use diversity index, land use dominance index, land use homogeneity index, land use fragmentation index, the index of land use type dominance, and the index of land use type fragmentation, are designed to characterize land use patterns and are introduced into the analysis of land use pattern effect on land use database indices. The analysis framework of the scale and land use pattern effects on the land use database indices are proposed by employing statistical techniques. Based on the land use database samples at multiple spatial scales collected in various land use regions across China, the study generates rules for both scale and land use pattern effects on the indices, including map area proportion of land use types, total map load, parcel map load, and minimum parcel area. The thresholds of these indices in land use database generalization are produced at the scales of 1:50,000, 1:100,000, 1:250,000, and 1:500,000. An experimental generalization at county level demonstrates how to determine the generalization index values considering scale and land use pattern, and how to evaluate the generalization results using our macro indices.