Comparison of existing methods for building triangular irregular network,models of terrain from grid digital elevation models

Abstract

Triangulated irregular networks (TINs) are increasingly popular for their efficiency in data storage and their ability to accommodate irregularly spaced elevation points for many applications of geographical information systems. This paper reviews and evaluates various methods for extracting TINs from dense digital elevation models (DEMs) on a sample DEM. Both structural and statistical comparisons show that the methods perform with different rates of success in different settings. Users of DEM to TIN conversion methods should be aware of the strengths and weaknesses of the methods in addition to their own purposes before conducting the conversion.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.     

Monitoring Mongolia Gobi dust transport using OMI data

The characteristics of long-distance dust transport from Asia to the United States over the Pacific Ocean are statistically analyzed using OMI AI (Ozone Monitoring Instrument Aerosol Index) data during 2005–2007. The results show that there is a high correlation of AI (the correlation coefficients are as high as 0.83 in March, 0.62 in April and 0.54 in May) between the Mongolia Gobi Desert and the west coast region of the United States (40°–50°N, 120°–130°W), indicating a strong source-receptor area relationship. Through calculating the lag correlation coefficient of the dust propagation time, we determined that the dust propagation time from the Mongolia Gobi Desert to the west coast of the United States is about 6–7 days at the 99% confidence level.     

Predicting demand for 311 non-emergency municipal services: An adaptive space-time kernel approach

Many cities in the United States and Canada offer a 311 helpline to their residents for submitting requests for non-emergency municipal services. By dialing 311, urban residents can report a range of public issues that require governmental attention, including potholes, graffito, sanitation complaints, and tree debris. The demand for these municipal services fluctuates greatly with time and location, which poses multiple challenges to effective deployment of limited resources. To address these challenges, this study uses a locally adaptive space-time kernel approach to model 311 requests as an inhomogeneous Poisson process and presents an analytical framework to generate predictions of 311 demand in space and time. The predictions can be used to optimally allocate resources and staff, reduce response time, and allow long-term dynamic planning. We use a bivariate spatial kernel to identify the spatial structure and weigh each kernel by corresponding past observations to capture the temporal dynamics. Short-term serial dependency and weekly temporality are modeled through the temporal weights, which are adaptive to local community areas. We also transform the computation-intensive parameter estimation procedure to a low dimensional optimization problem by fitting to the autocorrelation function of historical requests. The presented method is demonstrated and validated with sanitation service requests in Chicago. The results indicate that it performs better than common industry practice and conventional spatial models with a comparable computational cost.     

Grassland degradation in the “Three-River Headwaters&rdquo|region, Qinghai Province

Supported by MSS images in the mid and late 1970s, TM images in the early 1990s and TM/ETM images in 2004, grassland degradation in the “Three-River Headwaters” region (TRH region) was interpreted through analysis on RS images in two time series, then the spatial and temporal characteristics of grassland degradation in the TRH region were ana-lyzed since the 1970s. The results showed that grassland degradation in the TRH region was a continuous change process which had large affected area and long time scale, and rapidly strengthen phenomenon did not exist in the 1990s as a whole. Grassland degradation pattern in the TRH region took shape initially in the mid and late 1970s. Since the 1970s, this deg-radation process has taken place continuously, obviously characterizing different rules in different regions. In humid and semi-humid meadow region, grassland firstly fragmentized, then vegetation coverage decreased continuously, and finally “black-soil-patch” degraded grassland was formed. But in semi-arid and arid steppe region, the vegetation coverage de-creased continuously, and finally desertification was formed. Because grassland degradation had obviously regional differences in the TRH region, it could be regionalized into 7 zones, and each zone had different characteristics in type, grade, scale and time process of grass-land degradation.     

Characteristics and progress of land use/cover change research during 1990–2018

Journal of Geographical Sciences - Land use/cover change (LUCC) is the foundation and frontier for integrating multiple land surface processes. This paper aims to systematically review LUCC...     

内蒙古和林格尔新区核心区地下空间适宜性评价

本文以内蒙古和林格尔新区核心区为研究范围,利用已有调查数据,基于MapGIS平台,从水文地质、工程地质、不良地质及地貌4个方面选取9个因子组成了地下空间适宜性评价指标体系,采用层次分析法对研究区地下空间适宜性进行了评价。评价结果显示：研究区浅层地下空间较适宜区占总面积99.71%;中层地下空间较适宜区占总面积95.03%;深层地下空间较适宜区分布于研究区东南部,占总面积26.95%,次适宜区大面积分布于研究区中西部区域,占总面积72.27%。研究结果表明：研究区地下空间资源综合适宜性等级基本以较适宜、次适宜为主,区内不同竖向层次与不同区位地下空间资源的适宜性存在差异,资源条件总体上呈现\     

基于GIS的四射珊瑚分类信息系统

古生物学是一门古老的学科,在长期的研究中积累了大量的资料,如何充分利用这些宝贵 的资料,是人们关注的热点。计算机技术的发展,特别是近年来ＧＩＳ在各学科的应用,为古生物学研究提供了新的方法,为长期以来所积累的大量数据的分析与再利用提供了有效的研究手段。     

基于多源数据的夜间经济时空分布格局研究方法

夜间经济是一个城市经济发展和消费水平的重要表征。目前国内外研究者对夜间经济的研究多停留在理论层面,或基于市场调研和问卷调查的小范围精细化研究。本文融合多源数据为夜间经济提供了新的视角,相较于传统的调查数据,具有更加快速、高效、广泛的特点,适合于夜间经济大范围研究。本文基于夜间灯光、POI、OD流等多源数据,采用DBSCAN、K-Means++等空间聚类算法和研究供需关系的盈亏法,分别从消费者角度和商户角度识别厦门市夜间活动热点区域和夜间服务设施分布区域,分析厦门市夜间经济时空分布格局及相关性。研究表明:① 厦门市夜间活动在空间上呈多环状分布并向四周递减,夜间活动热点区域分布受假期的影响因地而异;② 厦门市部分区域已有服务设施未能很好地服务于夜间经济,现有的照明、夜景等夜间灯光基础设施存在供给不足之处;③ 居住人口密度与夜间活动密度呈中度正相关,研究结果具有有效性,夜间服务设施盈亏值及数量、夜间灯光与夜间活动密度呈中、弱度相关,并且餐饮设施更加依赖于夜间灯光。最后,为厦门市未来夜间经济建设提出了根据不同的消费人群和心理提供不同的夜间服务、加强夜间灯光基础设施建设以及市场扶持的举措。研究结论对促进社会就业、增强基础设施使用率有积极意义,同时也能够为城市夜间经济发展和政策制定提供参考。     

地理信息公共服务平台地理实体数据建模研究

围绕国家地理信息公共服务平台在线地理信息服务的需求,在分析国内外相关成果的基础上,提出了面向实体的数据建模思路,设计了地理实体数据模型,能够方便地实现地理信息与社会、经济、自然资源等专题信息的挂接,并有效解决多比例尺实体目标的一致性维护问题.