The use of digital map data in the segmentation and classification of remotely-sensed images

Abstract

Remotely-sensed data constitute a major potential source of input to geographical information systems (GIS)However, these data often have a relatively poor classification accuracy compared with that of the cartographic data from maps with which they may be combined in the course of GIS analysis. The possibility exists of using data sets (in the form of digital maps) resident within a GIS in order to improve this accuracy, before the classified image is incorporated into the GIS. Results are discussed from a British Alvey Information Technology project to develop a system for the knowledge-based segmentation and classification of remotely-sensed terrain images, in which the knowledge contained in digital map     

近25 年三北防护林工程区土地退化及驱动力分析

以长时间序列的遥感数据NOAA/AVHRR NDVI 为基础, 利用Sen 趋势度与Mann-Kendall 分析法相结合的方式分析了三北防护林工程区1982 年到2006 年土地退化趋势,结合气候因子降雨,运用残差法模型评价了人类活动在工程区内土地退化中所起的作用。结果表明:区域内土地退化程度整体趋于减轻,即植被上升的区域大于下降的区域,13.00%的地区退化程度显著减轻,6.20%的地区退化程度显著加重。其中绝大多数省份的土地退化程度趋于减轻,尤以内蒙古、青海和新疆最为明显,只有甘肃省土地退化程度明显趋于加重。而人类活动对植被变化起显著正作用的占11.93%,显著负作用的为6.19%。这说明在干旱、半干旱区,由于降雨随时间的变化不显著,对植被变化的影响相对较为微弱,植被显著变化主要受人类活动的影响。     

基于DEM的北京市大流域界线重新勘定研究

大流域区划数据是反映水资源分布的重要数据,也是土地利用总体规划和农业结构总体规划所必需的重要基础数据。针对当前没有与北京市土地利用现状数据一致的大流域区划数据,参照北京市已有的流域划分数据与方案,以DEM和SPOT5遥感影像为基础数据源,通过GIS数据处理、水文特征分析与流域划分等生成北京市五大流域区划数据;通过三维景观图等对大流域界线进行调整,重新勘定北京市大流域界线。     

遥感影像智能图解及其地学认知问题探索

本文提出遥感地学智能图解模型 (RSIGIM)概念 ,主要内容是如何模拟地学专家对遥感影像的综合解译和分析过程 ,对遥感影像中包含的地物目标进行描述、识别、分类和解释 ,提取遥感影像中地物目标所属的类别 ,判别其大小、结构、相互关系等地学属性及遥感成像机理、内部特征 ,进一步融合地学分析模型 ,预测地理现象和地理过程的发展趋势 ,作出决策性规划。 RSIGIM的核心问题——遥感地学智能图解中的认知模型 ,具有层次结构 ,从低到高包括基于数理统计的影像基本处理和分析模型、基于神经计算模型影像视觉生理认知模型和基于符号知识逻辑心理认知模型等三个层次的分析认知模型。     

Tsunami exposure estimation with land-cover data: Oregon and the Cascadia subduction zone

A Cascadia subduction-zone earthquake has the potential to generate tsunami waves which would impact more than 1000 km of coastline on the west coast of the United States and Canada. Although the predictable extent of tsunami inundation is similar for low-lying land throughout the region, human use of tsunami-prone land varies, creating variations in community exposure and potential impacts. To better understand such variations, land-cover information derived from midresolution remotely-sensed imagery (e.g., 30-m-resolution Landsat Thematic Mapper imagery) was coupled with tsunami-hazard information to describe tsunami-prone land along the Oregon coast. Land-cover data suggest that 95% of the tsunami-prone land in Oregon is undeveloped and is primarily wetlands and unconsolidated shores. Based on Spearman rank correlation coefficients (r_s), correlative relationships are strong and statistically significant (p < 0.05) between city-level estimates of the amount of land-cover pixels classified as developed (impervious cover greater than 20%) and the amount of various societal assets, including residential and employee populations, homes, businesses, and tax-parcel values. Community exposure to tsunami hazards, described here by the amount and relative percentage of developed land in tsunami-prone areas, varies considerably among the 26 communities of the study area, and these variations relate to city size. Correlative relationships are strong and significant (p < 0.05) for community exposure rankings based on land-cover data and those based on aggregated socioeconomic data. In the absence of socioeconomic data or community-based knowledge, the integration of hazards information and land-cover information derived from midresolution remotely-sensed imagery to estimate community exposure may be a useful first step in understanding variations in community vulnerability to regional hazards.     

基于Landsat 8 OLI数据与面向对象分类的昆嵛山地区土地覆盖信息提取

利用2015年Landsat 8 OLI遥感影像和DEM作为分类数据源,结合野外调查数据,采用面向对象的分类方法对昆嵛山地区土地覆盖信息进行提取,并对分类结果进行精度评价与比较分析。研究表明：面向对象分类方法提取的各地类连续且边界清晰,分类效果与实际情况基本吻合。昆嵛山地区占主导地位的土地覆盖类型是针叶林,面积为1 546.81 km²。研究区土地覆盖分类的总体精度和Kappa系数分别为91.5%和0.88,其中针叶林、草地、水体和建设用地的生产者精度均达到87%以上。相对于监督分类方法,本研究提出的土地覆盖信息提取方法的总体分类精度和Kappa系数分别提高14.7%和0.17。基于面向对象的中分辨率遥感影像,能够获取较高精度的土地覆盖信息,为大范围土地覆盖分类研究提供方法参考。     

Combining spatial data with survey data improves predictions of boundaries between settlements

Studies of land-use change often require the combination of socioeconomic survey data with spatially continuous maps of land-cover change. One approach is to define maps of land ownership, assuming that all land-use change can be attributed to the owners or managers of each parcel of land. Unfortunately, records of administrative boundaries between towns and villages are commonly unavailable in developing countries and prohibitively costly or time consuming to map for individual projects. However, point locations of the settlements themselves can be obtained easily from existing maps or remotely-sensed imagery. In this paper we compare three methods – circular buffers, unweighted Voronoi polygons (sometimes referred to as Thiessen polygons) and multiplicatively weighted Voronoi polygons – for estimating boundaries between villages in an agricultural landscape in West Africa. The benefits and limitations of each approach are discussed, and their accuracy assessed using 98 independently collected GPS coordinates of village boundaries. We present a novel method for generating and optimising weights for multiplicatively weighted Voronoi polygons using survey data of village sizes from a subset of villages. By using both spatial information and survey data from villages, we show that multiplicatively weighted Voronoi polygons outperform other methods of predicting village boundaries, and increase the correlation coefficient between surveyed village area and mapped areas from 0.18 to 0.68 compared with more commonly used unweighted Voronoi polygons. Our method of weighting Voronoi polygons can be implemented with data and software commonly available to researchers and non-governmental organisations.     

土地利用/土地覆被时空分布100年数字重建——以大庆市杜尔伯特蒙古族自治县为例

长时间序列的土地利用/ 土地覆被数据是开展全球变化、可持续发展及生态安全等各项研究的重要基础。然而,早期的土地利用/ 土地覆被数据,特别是卫星遥感数据出现之前 的土地利用/ 土地覆被信息通常很难获取。利用TM、MSS 遥感影像数据和地形图、气候、地质、地貌、土壤、植被、水文等自然环境背景图件以及数据,社会经济统计数据等多源数 据,选择大庆市杜尔伯特蒙古族自治县作为典型案例区,在GIS 技术支持下建立了土地利用/ 土地覆被数字重建模型,再现了典型研究区20 世纪30 年代和50 年代土地利用/ 土地覆被空间分布状况。通过野外调查和历史文献资料对土地利用数字重建结果进行精度评价并初步得到以下结论：① 采用逐个图斑跟踪记录的方法对研究区各个时期土地利用/ 覆被变化的敏感 性进行分析,有利于揭示区域土地利用/ 土地覆被变化的规律;② 在定量、定位分析环境背景对土地利用/ 土地覆被分布及其变化的影响基础上,综合判断各种土地利用/ 土地覆被分布概率,其结果可为土地利用数字重建提供依据;③ 对1:10 万地形图提取土地利用信息的可行性与可信度分析表明,地形图中土地利用信息完全能够达到一级土地利用分类精度,同时疏林地、灌木林、沼泽地、盐碱地、沙地等二级分类信息也能获取。     

利用遥感信息决策树方法分层提取荒漠化土地类型的研究探讨

选择甘肃省民勤县绿洲作为典型荒漠化区域,根据荒漠化土地分类体系确定决策树的结构及各类地物在树形中的位置。基于各类地物的光谱反射特性和图象数据反映的综合特征,采取相应的识别和提取方法,以最大限度地利用遥感数据源。对于非荒漠化土地分类,利用土壤调节植被指数、阈值数字信号统计可以分离成一类树枝;而重点讨论的3种荒漠化土地类型的分层分类,则相继采用光谱特征提取、几何特征提取、纹理特征提取、监督分类以及植被指数等复合识别指标进行分枝。结果表明:利用决策树分层提取法可以有效地排除和避免提取地物时所有多余信息的干扰及影响,目标明确。同时,为提高分类的精度,开展野外遥感调查和特征分析是极其重要的。     

A Euler number-based topological computation model for land parcel database updating

Intersection relations are important topological considerations in database update processes. The differentiation and identification of non-empty intersection relations between new updates and existing objects is one of the first steps in the automatic incremental update process for a land parcel database. The basic non-empty intersection relations are meet, overlap, cover, equal and inside, but these basic relationships cannot reflect the complex and detailed non-empty relations between a new update and the existing objects. It is therefore necessary to refine the basic non-empty topological relations to support and trigger the relevant update operations. Such relations have been refined by several researchers using topological invariants (e.g., dimension, type and sequence) to represent the intersection components. However, the intersection components often include only points and lines, and the refined types of 2-dimensional intersection components that occur between land parcels have not been defined. This study examines the refinement of non-empty relations among 2-dimensional land parcels and proposes a computation model. In this model, an entire spatial object is directly used as the operand, and two set operations (i.e., intersection (∩) and difference (\)) are applied to form the basic topological computation model. The Euler number is introduced to refine the relations with a single 2-dimensional intersection (i.e., cover, inside and overlap) and to distinguish the refined types of 2-dimensional intersection components for the relations with multiple intersections. In this study, the cover and overlap relations with single intersections between regions are refined into seven cases, and nine basic types of 2-dimensional intersection components are distinguished. A composite computation model is formed with both Euler number values and dimensional differences. In this model, the topological relations with single intersections are differentiated by the value of the dimension and the Euler number of the resulting set of the whole-object intersection and differences, whereas the relations with multiple intersections are discriminated by the value of the resulting set at a coarse level and are further differentiated by the type and sequence of the whole-object intersection component in a hierarchical manner. Based on the refined topological relations, an improved method for automatic and incremental updating of the land parcel database is presented. The effectiveness of the models and algorithms was verified by the incremental update of a land cover database. The results of this study represent a new avenue for automatic spatial data handling in incremental update processes.     

近几年国内数字地价模型研究综述

数字地价模型在城市地价的研究应用越来越广泛。本文采用文献资料法,阐述了数字地价模型研究的内容体系,数字地价模型中插值方法的选取,数字地价模型在地价时空分析、地价动态监测以及土地定级与基准地价更新应用现状研究,并提出数字地价模型下一步的研究展望：应该把自然地理条件、社会经济、城市规划等因素进行融合,建立数字地价模型在时间序列上演变模型,加强软件开发等。     

Albedo-NDVI特征空间及沙漠化遥感监测指数研究

利用遥感数据和野外调查数据分析了沙漠化与地表定量参数之间的关系,提出了Albedo-NDVI特征空间的概念以及基于Albedo-NDVI特征空间的沙漠化遥感监测模型,即沙漠化遥感监测差值指数模型(DDI)。这个模型充分利用了多维遥感信息,指标反映了沙漠化土地地表覆盖、水热组合及其变化,具有明确的生物物理意义。而且指标简单、易于获取,有利于沙漠化的定量分析与监测。     

Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed: (1) the interactions between climate change and land surface phenology dynamic; (2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums; (3) the contributions of crop physiology characteristic changes to land surface biophysical process; (4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.     

基于人工免疫克隆选择算法的遥感图像识别

遥感图像分类受自然环境的复杂性和实际样本数据的分布情况约束,其结果将直接影响对土地利用、覆盖情况的认知。人工免疫系统具有自学习、自组织、记忆的能力,可解决非线性分类问题中的局部极值、鲁棒性等难点。该文将人工免疫系统引入遥感图像分类领域,设计了基于克隆选择算法的遥感图像监督分类方法,并将其应用于广州市遥感影像分类。实验结果表明:与最大似然法相比,该方法具有更高的精度;同时该方法对公路、桥梁等线状城市用地较敏感,适用于快速发展的中心城市的遥感影像分类。     

农业物候动态对地表生物物理过程及气候的反馈研究进展（英文）

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed:(1) the interactions between climate change and land surface phenology dynamic;(2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums;(3) the contributions of crop physiology characteristic changes to land surface biophysical process;(4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.     

AutoLogistic 方法在土地利用格局模拟中的应用 —— 以张家界市永定区为例

土地利用/ 土地覆被变化(LUCC) 是当前研究全球变化的重要内容, 而区域土地利用 格局模拟是LUCC 研究的核心内容之一。以张家界市永定区为研究单元, 根据由2005 年土地 利用现状图和数字高程模型数据源得到的土地利用、地形、河流以及道路等空间数据, 对区 域土地利用类型空间格局的空间自相关性特征进行了建模研究, 并通过在传统Logistic 模型 中引入描述空间自相关性的成份, 实现了能够考虑自相关性因素的回归分析模型 (AutoLogistic 模型), 同时应用该模型对区域土地利用格局进行了模拟和分析。结果显示, 通 过与没有考虑空间自相关性的回归模型(传统Logistic 模型) 相比较, 该模型显示了更好的拟 合优度和更高的拟合准确率(耕地、林地、建设用地及未利用地的ROC 值分别从0.851、 0.913、0.877 和0.852 提高到0.893、0.940、0.907 和0.863)。研究结果说明了基于 AutoLogistic 方法的土地利用格局的相关性建模在一定意义上是合理的。同时研究结果也可以 为永定区及其相似地区的土地利用规划决策提供更为科学的依据。     

A spatial data model design for feature-based geographical information systems

Abstract

In state-of-the-art GIS, geographical features are represented as geometric objects with associated topological relations and classification attributes. Semantic relations and intrinsic interrelations of the features themselves are generally neglected. In this paper, a feature-based model that enhances the representation of geographical features is described. Features, as the fundamental depiction of geographical phenomena, encompass both real world entities and digital representation. A feature-based object incorporates both topological relations among geometric elements and non-topological (semantic) relations among features. The development of an object-oriented prototype feature-based GIS that supports relations between feature attributes and feature classes is described. Object-oriented concepts such as class inheritance and polymorphism facilitate the development of feature-based GTS.     

分布式水文模型结合遥感研究地表蒸散发

地表蒸散发是研究土壤-植被-大气系统水热平衡的关键因子。用改进的DHSVM分布式水文模型对汉江上游子午河流域蒸散发进行模拟。根据流域特点,主要进行TM遥感数据的大气校正和几何校正,在此基础上得到叶面积指数和土地覆盖等地表参数;再利用GIS技术基于DEM求出坡度、坡向和地形指数等因子。分析了蒸散发时空分布特征,表明日尺度蒸散发空间分布差异较大。初步验证了结果,表明模型在中国典型湿润区小流域取得较好效果。     

土地管理市级数据中心建设研究

分析市级土地管理业务处理体系结构、数据框架及土地管理各业务间数据逻辑关联,建立了土地管理领域模型,利用功能分析法,从数据协同的角度对土地管理数据中心的数据类型、数据存储及数据应用进行分析,提出以数据为中心构建土地管理市级数据中心的思路,给出土地管理市级数据中心模型,并结合徐州市金土工程项目应用研究的需要,构建了以数据中心为核心的土地管理信息化体系架构.     

Road network detection from SPOT imagery for updating geographical information systems in the rural–urban fringe

Abstract

Visual interpretation of high-resolution satellite data has been useful for mapping linear features, such as roads and updating land-use changes. However, it would be beneficial to map new road networks digitally from satellite data to update digital databases using semi-automated techniques. In this paper, an algorithm called Gradient Direction Profile Analysis (GDPA) is used to extract road networks digitally from SPOT High Resolution Visible (HRV) panchromatic data. The roads generated are compared with a visual interpretation of the SPOT HRV multispectral and panchromatic data. The technique is most effective in areas where road development is relatively recent. This is due to the spectral consistency of new road networks. As new road networks are those of most interest to the land manager, this is a useful technique for updating digital road network files within a geographical information system of urban areas.