Monitoring land changes in an urban area using satellite imagery,GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

资源环境系列制图研究的现实基础与发展

本文侧重于全国性资源环境及有关自然条件等专题制图工作的现实基础和成就,作简要总结和回顾。针对提高和重新认识制图效益和重点进行讨论,提出科学效益是基础,社会效益是目的,经济效益是根本,为资源环境的合理开发利用提供依据,并提出今后发展设想。     

针对MODIS数据的大气水汽含量反演及31和32波段透过率计算

 针对MODIS的波段特征,首先,用近红外波段反演大气水汽含量; 然后,通过LOWTRAN模拟大气水汽含量与MODIS 31和32热红 外波段透过率的统计关系; 最后,计算31和32波段的透过率。该方法克服了以往一景图像只用1个透过率的局限性,使得透过率的求 算精确到每1个像元,同时保证参数获取的实时性。     

ArcGIS环境下地图符号库的实现

地图符号作为地图语言在地图的制作和输出中起着非常重要的作用。但是,由于ArcGIS中的数据输入、编辑、查询与制图模块Arc Map中自带的符号库不能满足我国基本比例尺地图输出的要求,因此,必须为它建立符合地图图式要求的符号库。对于在Arc GIS中不能实现的符号,如电力线,将由Arc Object来制作完成。应用VB程序设计将电力线做出并且加入到Arc GIS环境中去。本文重点论述了Arc GIS环境下地图符号库的设计方法,并分别讨论了点状符号、线状符号和面状符号的实现方式。     

驻村帮扶“一张图”设计与实现——以明溪县为例

结合明溪县驻村帮扶工作的开展情况,探索基于地理信息技术下开展驻村帮扶工作的关键技术,依托"数字明溪地理空间框架"的建设成果,设计并实现了明溪县驻村帮扶"一张图",实现了明溪县驻村帮扶信息可视化、透明化和精准化的管理,增强了明溪县驻村帮扶项目管理的科学性。     

基于“天地图·永定”的永定旅游地图服务网设计与实现

"天地图·永定"是永定区统一、权威、标准的地理信息公共平台,本文利用"天地图·永定"提供的丰富的数据服务和二次开发接口,开发了永定旅游地图服务网,实现了永定旅游服务和"天地图"的融合,为游客提供便捷、丰富的旅游服务,对永定区的旅游发展起到了一定的推动作用。     

Point grid map: a new type of thematic map for statistical data associated with geographic points

ABSTRACT

Social, economic, and environmental statistical data associated with geographic points are currently globally available in large amounts. When conventional thematic maps, such as proportional symbol maps or point diagram maps, are used to represent these data, the maps appear cluttered if the point data volumes are relatively large or cover a relatively dense region. To overcome these limitations, we propose a new type of thematic map for statistical data associated with geographic points: the point grid map. In a point grid map, an input point data set is transformed into a grid in which each point is represented by a square grid cell of equal size while preserving the relative position of each point, which leads to a clear and uncluttered appearance, and the grid cells can be shaded or patterned with symbols or diagrams according to the attributes of the points. We present an algorithm to construct a point grid map and test it with several simulated and real data sets. Furthermore, we present some variants of the point grid map.     

中国地图藏南地名的表示

该文针对1958年之后,中国地图上西藏南部有一片地区只标志寥寥无几地名的历史状况,以中国地图上藏南地区编制方法的历史状况为纽带,搜索相关历史事实,重现1958年针对藏南地区地图问题引发的两国交流,认清地图对于国家领土主权确认的重要性,推动标注藏南地区地名标注工作的进行。     

Synchronising geometric representations for map mashups using relative positioning and Linked Data

Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying.