沙漠化灾害遥感信息提取技术系统

论述了沙漠化灾害遥感信息增强、特征提取、信息分类等技术方法,建立了沙漠化灾害信息数据库,利用不同的数据接口可与地理信息系统(PC ARC/INFO)相连接,实现与各种专题要素的复合、匹配和更新,进行沙漠化灾害动态监测与评价。     

中国弱方沙漠化灾害危险度分区评价

沙漠化灾害是影响重大的全球性灾种之一，其危险度分区评价具有重要的理论与实践意义，本文从沙漠从沙漠化灾害危险分区评价的依据和原则出发，制定了其评价指标体系，建立了定量评，此对我国北方的沙漠化 灾害危险主进行了分区评价，共区分出１５个沙漠化灾害危险度区。     

中国北方沙漠化灾害危险度分区评价

沙漠化灾害是影响重大的全球性灾种之一，其危险度分区评价具有重要的理论与实践意义。本文从沙漠化灾害危险度分区评价的依据和原则出发，制定了其评价指标体系，建立了定量评价模型，以此对我国北方的沙漠化灾害危险度进行了分区评价，共区分出１５个沙漠化灾害危险度区，其中包括６个轻度危险度区、５个中度危险度区和４个重度危险度区，并对每个危险度区的基本概况进行了简要说明。     

沙漠化灾害监测评价信息系统空间数据分类编码研究

介绍本系统空间数据分类编码设计方案、原则及其特点，探索沙漠化灾害监测评价信息系统空间数据分类与编码规范化和标准化的途径，为沙漠化灾害信息的计算机存贮、管理、识别及提取奠定基础。     

甘肃省河西走廊干旱地区沙漠化灾害灾情分析及其减灾对策

甘肃省河西走廊是干旱沙漠化灾害有代表性的地区之一。土地沙化、旱化、次生盐渍化、风灾和干热风灾害的年直接经济损失达1-2亿元。据研究, 由于不乐观的自然因素及人口压力过大, 灾害有加剧趋势。但临泽试验站减灾试验表明: 灾害不仅可以防治, 而且有较大经济效益。为此, 建议:(1)大力开展全民减灾教育, 建立群防体系;(2)开展灾害评估研究, 建立减灾综合试验示范区;(3)建立灾害监测系统, 搞好预报;(4)预防沙漠化发生发展, 研究实用技术和提供必要的防治和研究经费。     

快速建立沙漠化灾害背景数据库技术——图形扫描输入TEKNICAD→ARC/INFO

利用TEK图形工作站扫描仪做为沙漠化灾害背景数据库图形扫描输入的设备,转换其制图软件Teknicad数据格式为ARC/INFO软件格式,用C语言编写该程序。     

我国沙漠化土地整治基本模式的探讨

我国是世界上沙漠戈壁、沙漠化土地较多的国家,也是受沙漠化灾害严重的国家之一,沙漠化是一种严重的、蚕食式、潜移式的灾害。经长期试验研究实践,形成具有我国特色的沙漠化土地整治的基本模式:1、采取防治与开发相结合的途径;2、形成试验站—试验示范区—幅射推广区的技术路线;3、当地政府官员、科技人员和人民群众相结合方式,把科研与生产,理论与实践密切相结合。     

青藏铁路错那湖段沙漠化土地变化及成因分析

青藏铁路格拉段铁路建设对沿线沙漠化土地变化的影响，是大家关注的焦点之一。通过利用地理信息系统和遥感监测技术，根据错那湖段Landsat影像、Google Earth影像和气象资料等数据，结合野外实地考察建立解译标志，采用人机交互的目视解译方法，提取青藏铁路错那湖段2001年、2008年和2015年沙漠化土地信息，并对沙漠化土地变化成因进行分析。同时对铁路沿线沙漠化土地的变化进行缓冲区分析。结果表明：（1） 2001—2008年沙漠化土地面积增加2.21 km²，土地沙漠化程度呈减轻趋势；2008—2015年沙漠化土地面积减少8.9 km²，土地沙漠化程度持续减轻。（2） 2001—2008年，沙漠化土地面积的增加主要与人为因素有关，土地沙漠化程度减轻主要与自然因素有关。2008—2015年，沙漠化土地面积的减少以及土地沙漠化程度的减轻主要与人为因素有关。（3） 青藏铁路错那湖段2 km范围内土地沙漠化程度变化最为明显，以沙漠化程度减轻为主要特征，青藏铁路对周边环境的影响范围为2 km。     

基于栅格累加法的塔里木盆地沙漠化分析

土地沙漠化是当今全球最严峻的环境问题之一,也是我国西北干旱区面临的主要生态环境问题。开展土地沙漠化动态研究有助于沙漠化灾害防治与国土资源空间开发。以2000-2018年MODIS-NDVI 1 km月数据为基础,运用栅格累加法与转移矩阵法对塔里木盆地土地沙漠化的变化速率、空间特征及其成因进行探索分析,结果表明:(1)土地沙漠化是一个具有年际波动和累积效应的动态变化过程;(2)栅格累加法具有较强的连续动态分析能力,能准确分析土地沙漠化变化速率、演变趋势、变化的空间特征,可以定量分析土地沙漠化原因;(3)塔里木盆地沙漠化退化主要是草地的退化,沙漠化改善则主要是林地和耕地的改善;(4)2000-2018年,塔里木盆地土地沙漠化整体呈极重度沙漠化逐级向非沙漠化变化的改善趋势,转移路径为:极重度沙漠化→重度沙漠化→中度沙漠化→轻度沙漠化→非沙漠化,改善区主要分布在绿洲区,恶化区主要在塔里木河中游与车尔臣河下游,土地沙漠化成因主要为人类活动。此文研究方法为土地沙漠化动态监测提供了一种新思路,其研究结果可为塔里木盆地国土资源开发和沙漠化治理提供理论依据。     

基于Logistic回归模型的内蒙古多伦县土地沙漠化驱动力分析

以内蒙古多伦县1960、1975、1987、1995、2000、2005年的土地沙漠化矢量数据及2010年2015年的遥感影像、地形图为主要数据来源，运用NEVI5.0和ArcGIS10.2软件提取8个时期土地沙漠化空间信息，划分为轻度沙漠化、中度沙漠化、重度沙漠化、严重沙漠化等不同类型进行时空分异特征分析。结合研究区实际情况，选取海拔高程、年均气温、降水量、平均风速、牲畜数量、第一产业、居民点距离等统计数据，运用Logistic回归模型定量分析了土地沙漠化动力机制，为京津风沙源区防治土地沙漠化，改善生态环境提供科学理论依据。结果表明：1960-2015年间多伦县土地沙漠化面积呈减少趋势，其中1960年到1995年间呈发展趋势，1995-2015年间呈减少趋势；1960-1995年间各类土地沙漠化增长的主导因子是第一产业和居民点距离；而在1995-2015年间影响各类土地沙漠化的主导因子是降水量、牲畜数量、第一产业和居民点距离。今后，继续控制牲畜数量、实施土地沙漠化治理政策来逆转土地沙漠化发展。     

A data model and algorithms for a spatial data marketplace

A data marketplace is a platform that facilitates online data trading. It gives sellers the capabilities of publishing data, defining the price function, the authorization rules and the data contract. It gives customers the capabilities to search for data services, to query for their price, to invoke them and to pay for the usage. As data are more and more emphasized as a payable asset, the need for data marketplaces rises. There is a lack of marketplace proposals for spatial data. This paper contributes to fill-in this gap. We propose a data model for representing the different types of data involved. The logical representation of data is a quadtree, and the physical representation fits into a key-value store. The model is thus logically simple and extensible, and physically scalable and highly available. We discuss price queries in detail and propose evaluation algorithms.     

多源空间数据无缝集成研究

随着地理信息系统的社会化发展 ,空间数据共享成为一种必然要求 ,然而要真正实现空间数据共享 ,多格式空间数据集成是一个亟待解决的问题。多源空间数据无缝集成( SIMS)技术实现了一种特殊的数据访问机制 ,不仅提供了直接存取多种数据格式的能力 ,而且使 GIS软件具有跨数据源复合分析功能 ,是实现空间数据共享的有效的技术基础。本文阐述了 SIMS技术体系结构 ,并探讨了 SIMS技术在 GIS软件开发中的应用。     

The GEO VIEW design A relational data base approach to geographical data handling

Abstract

Digital map data are currently available based on a variety of data structures, depending on the uses to which the data are to be put Within the major categories of vector and raster data, as well as other structures, there is a multiplicity of data formats. Further to this, data for digital map coordinates are frequently stored in a different way from attribute data pertaining to points, lines and polygons. Given these problems, this paper investigates the possibility of handling different kinds of data structures, as well as both coordinate and attribute information within a unified conceptual scheme. This scheme is expressed in terms of the design of an integrated geographical information system called GEO VIEW, which can be implemented in a relational data base environment. The structure of the tables in the data base is outlined, together with the methodology for coding different kinds of data structure into a standard form. Examples of queries are provided, using the SQL query language, to indicate how the system might be used and problems in optimizing spatial searching on a data base of this kind are addressed.     

极地科学数据关联方法及应用研究

为了从海量极地科学数据中准确、智能地发现用户所需要的数据,首先,系统研究分析极地科学数据特征,挖掘极地科学数据本身隐含的语义信息,建立极地科学数据关联指标体系;其次,研究极地科学数据关联方法,最后设计并实现极地科学数据关联查询应用原型系统。以极地科学数据共享平台的元数据作为语料库,自动抽取极地科学数据关联指标数据,实现极地科学数据集之间的自动关联。应用实践表明,利用极地科学数据关联方法不仅可直接检索出满足条件的数据,还可以检索出潜在的相关联的数据。该关联方法研究可促进极地科学数据的集成、融合与共享应用。     

Design of a spatial data structure using the relational normal forms

Abstract

In previous work, a relational data structure aimed at the exchange of spatial data between systems was developed. As this data structure was relational it was of first normal form, but compliance with the higher normal forms was not investigated. Recently, a new procedural method for composing fully normalized data structures from the basic data fields has been developed by H. C. Smith, as an alternative to the process of non-loss decomposition which is difficult to understand. Smith's method has been applied to data fields required to store points, lines and polygons in a chain-node spatial data model. When geographic domain, coverage layer and map are also considered, the procedure naturally leads to a catalogue model, needed for the exchange of spatial data. Although the method produces a fully normalized data structure, it is not as easy to identify which normal forms are responsible for the ultimate arrangement of the data fields into relations, but the benefits of these criteria for data base development also apply to spatial data structures and related ancillary data.     

基于对象关系数据库的时空数据模型研究

一体化时空数据建模是新一代GIS理论与技术研究的重要基础。基于对象关系数据库探讨时空数据库的数据建模方法,提出综合考虑矢量和栅格数据一体化的时空数据模型。首先基于基本类型派生定义矢量和栅格抽象数据类型,在此基础上定义时空数据类型为一系列空间类型的时间片序列。该抽象数据类型的定义包括其数据对象和相关操作,将其嵌入对象关系数据库中,扩展其时空数据的存储和查询能力。利用该数据模型,可以统一考虑矢量和栅格数据,建立基于对象关系的时空数据库,并支持矢量—栅格一体化时空数据访问和操作,进而对新一代GIS技术的研究与实现起到重要支撑作用。     

Wetland vegetation biomass estimation and mapping from Landsat ETM data:a case study of Poyang Lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18-28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.     

Wetland vegetation biomass estimation and mapping from Landsat ETM data: a case study of poyang lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18–28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.