Modelling,encoding and transforming of open geographic data to examine interoperability between GIS applications

The interoperability of geographic data sets is required between geo-information system applications to use geographic data sets effectively. Thus, international standardisation organisation/technical committee 211 standards supporting model-driven architecture were examined to test the ability of producing interoperable geographic data sets. With Turkey case, unified modelling language application schemas were designed for base geographic data themes and encoded to data interchange model based on geography markup language. To test the applicability of the open data models, extract-transform-load (ETL) tools were developed and applied for case applications such as topographic map and web urban atlas. This study gives a methodology and indicates that ETL tools should be created to enable multiple uses of geo-data sets without spending time and labour. However, data model design should be refined and kept as simple as possible because data transformation is laborious to use the models in the applications.     

Creating a Population of 12‐Digit Headwater Basins within the Albemarle‐Pamlico Estuary System

Ecological research within the US Environmental Protection Agency's Office of Research and Development has recently changed its focus to quantifying and mapping ecosystem services provided to humans. Our local research group has been charged to develop a regional assessment of several ecosystem services in the Albemarle‐Pamlico Estuary System (APES). Time, data, and funding constraints precluded explicit modeling of the entire APES, so in Phase 1 of our research plan we chose to model ecosystem services in a random sample of headwater catchments. After observing numerous inconsistencies between the National Hydrography Dataset‐Plus (NHDPlus) stream network and the Virginia/North Carolina Watershed Boundary Dataset 12‐digit HUC coverage, we began by creating modified 12‐digit hydrologic units (HUCs) by aggregating smaller catchments delineated within the NHDPlus. In defining our population of interest (headwater 12‐digit HUCs with perennial, natural, wadeable pour points), we generally excluded HUCs that had multiple pour points, no pour points, or whose pour points were intermittent streams, artificial segments, ditches/canals, or lentic systems (lakes and reservoirs). After taking these actions, 318 HUCs remained and a stratified random sample (Omnerik ecoregions as strata) of 50 HUCs was chosen from this population.     

四川省测绘地理信息行业监管系统架构设计

行业监管是行业健康快速发展的重要动力和必要措施。通过充分的调研,针对四川省测绘地理信息行业监管的现状和存在的问题,从系统数据库架构、系统技术架构和系统功能架构等方面对系统的构建做了详细的分析,对系统实现和改善行业监管的现状具有重要意义。     

Using control data to determine the reliability of volunteered geographic information about land cover

There is much interest in using volunteered geographic information (VGI) in formal scientific analyses. This analysis uses VGI describing land cover that was captured using a web-based interface, linked to Google Earth. A number of control points, for which the land cover had been determined by experts allowed measures of the reliability of each volunteer in relation to each land cover class to be calculated. Geographically weighted kernels were used to estimate surfaces of volunteered land cover information accuracy and then to develop spatially distributed correspondences between the volunteer land cover class and land cover from 3 contemporary global datasets (GLC-2000, GlobCover and MODIS v.5). Specifically, a geographically weighted approach calculated local confusion matrices (correspondences) at each location in a central African study area and generated spatial distributions of user's, producer's, portmanteau, and partial portmanteau accuracies. These were used to evaluate the global datasets and to infer which of them was 'best’ at describing Tree cover at each location in the study area. The resulting maps show where specific global datasets are recommended for analyses requiring Tree cover information. The methods presented in this research suggest that some of the concerns about the quality of VGI can be addressed through careful data collection, the use of control points to evaluate volunteer performance and spatially explicit analyses. A research agenda for the use and analysis of VGI about land cover is outlined.     

Quantifying local fire regimes using the Landsat data-archive: a conceptual framework to derive detailed fire pattern metrics from pixel-level information

Free and open access to the Landsat archive has enabled the detection and delineation of an unprecedented number of fire events across the globe. Despite the availability and potential of these data, few studies have analysed residual vegetation patterns and/or partial mortality of fire across the Canadian boreal forest, and those available, are either incomplete or inaccurate. Further, they all differ in the methods and spatial language, which makes it difficult for managers to interpret fire patterns over large areas. There is an urgent need for methods to help unify fire pattern observations across the Canadian boreal forest. This study explores the capacity of the Landsat data archive when coupled with a recently developed fire mapping approach and a robust spatial language to characterize and compare tree mortality patterns across the boreal plains ecozone, Canada. With 507 fires 2.5?Mha mapped, this study represents the most comprehensive analysis of mortality patterns for study area. Summaries from this demonstration generated an accurate characterization of the fire patterns the various ecoregions based on seven key fire metrics. The comparison between ecoregions revealed differences in the amount of residual vegetation, which in turn suggested various climate, topography and/or vegetation ecosystem drivers.     

Crowdsourcing the character of a place: Character‐level convolutional networks for multilingual geographic text classification

This article presents a new character‐level convolutional neural network model that can classify multilingual text written using any character set that can be encoded with UTF‐8, a standard and widely used 8‐bit character encoding. For geographic classification of text, we demonstrate that this approach is competitive with state‐of‐the‐art word‐based text classification methods. The model was tested on four crowdsourced data sets made up of Wikipedia articles, online travel blogs, Geonames toponyms, and Twitter posts. Unlike word‐based methods, which require data cleaning and pre‐processing, the proposed model works for any language without modification and with classification accuracy comparable to existing methods. Using a synthetic data set with introduced character‐level errors, we show it is more robust to noise than word‐level classification algorithms. The results indicate that UTF‐8 character‐level convolutional neural networks are a promising technique for georeferencing noisy text, such as found in colloquial social media posts and texts scanned with optical character recognition. However, word‐based methods currently require less computation time to train, so currently are preferable for classifying well‐formatted and cleaned texts in single languages.     

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.     

The influence of sampling design on spatial data quality in a geographic citizen science project

Geographic citizen science has much potential to assist in wildlife research and conservation, but the quality of observation data is a key concern. We examined the effects of sampling design on the quality of spatial data collected for a koala citizen science project in Australia. Data were collected from three samples—volunteers (n = 454), an Internet panel (n = 103), and landowners (n = 35)—to assess spatial data quality, a dimension of citizen science projects rarely considered. The locational accuracy of koala observations among the samples was similar when benchmarked against authoritative data (i.e., an expert‐derived koala distribution model), but there were differences in the quantity of data generated. Fewer koala location data were generated per participant by the Internet panel sample than the volunteer or landowner samples. Spatial preferences for land uses affecting koala conservation were also mapped, with landowners more likely to map locations for residential and tourism development and volunteers less likely. These spatial preferences have the potential to influence the social acceptability of future koala conservation proposals. With careful sampling design, both citizen observations and land use preferences can be included within the same project to augment scientific assessments and identify conservation opportunities and constraints.     

Tile‐based polygon overlay of vector data in a virtual globe

The demand for analysis of large‐scale data has increased with increased access to spatial vector data. Polygon overlay of vector data in a virtual globe requires proprietary data structures and proprietary analysis algorithms. A vector data structure is designed for rapid polygon overlay in a virtual globe by recording the metadata of the triangles (TriMeta) that constitute polygons. A polygon overlay algorithm is proposed based on this data structure. The overlay of two complex GIS polygons is transformed into the intersection computation of their 3D triangular presentations. The intersection computation of two sets of triangles is reduced considerably by utilizing TriMeta to filter out the disjoint triangle pairs and rapidly identify the contained triangle. The new method improves the overlay efficiency in a virtual globe because the amount of computation required to calculate the intersections of two large polygons and drape the intersections onto a terrain surface is reduced.     

Mapping areas of asynchronous‐temporal interaction in animal‐telemetry data

Animal interactions are a crucial aspect of behavioral ecology that affect mating, territorial behavior, resource use, and disease spread. Commonly, animals will interact because of shared resources. Recent methods have used time geography to map landscape areas where interactions were possible. However, such methods do not identify areas of less direct interaction, like through smell or sight. These indirect or asynchronous interactions are also a crucial aspect of animal behavioral ecology and affect group behaviors such as leading/following hierarchies and joint resource use. Asynchronous interactions are difficult to map because they can occur in a synchronous space at asynchronous times, as well as in asynchronous spaces at a synchronous time. Here, we present a method termed the temporally asynchronous‐joint potential path area (ta‐jPPA) that maps areas of potential temporally asynchronous–spatially synchronous interactions. We used simulated data to statistically test ta‐jPPA and empirical data to demonstrate how ta‐jPPA can find patterns in habitat use.     

Examining the influences of air quality in China's cities using multi‐scale geographically weighted regression

This study evaluates the influences of air pollution in China using a recently proposed model—multi‐scale geographically weighted regression (MGWR). First, we review previous research on the determinants of air quality. Then, we explain the MGWR model, together with two global models: ordinary least squares (OLS) and OLS containing a spatial lag variable (OLSL) and a commonly used local model: geographically weighted regression (GWR). To detect and account for any variation of the spatial autocorrelation of air pollution over space, we construct two extra local models which we call GWR with lagged dependent variable (GWRL) and MGWR with lagged dependent variable (MGWRL) by including the lagged form of the dependent variable in the GWR model and the MGWR model, respectively. The performances of these six models are comprehensively examined and the MGWR and MGWRL models outperform the two global models as well as the GWR and GWRL models. MGWRL is the most accurate model in terms of replicating the observed air quality index (AQI) values and removing residual dependency. The superiority of the MGWR framework over the GWR framework is demonstrated—GWR can only produce a single optimized bandwidth, while MGWR provides covariate‐specific optimized bandwidths which indicate the different spatial scales that different processes operate.     

Assessment with satellite data of the urban heat island effects in Asian mega cities

This study focuses on using remote sensing for comparative assessment of surface urban heat island (UHI) in 18 mega cities in both temperate and tropical climate regions. Least-clouded day- and night-scenes of TERRA/MODIS acquired between 2001 and 2003 were selected to generate land-surface temperature (LST) maps. Spatial patterns of UHIs for each city were examined over its diurnal cycle and seasonal variations. A Gaussian approximation was applied in order to quantify spatial extents and magnitude of individual UHIs for inter-city comparison. To reveal relationship of UHIs with surface properties, UHI patterns were analyzed in association with urban vegetation covers and surface energy fluxes derived from high-resolution Landsat ETM+ data. This study provides a generalized picture on the UHI phenomena in the Asian region and the findings can be used to guide further study integrating satellite high-resolution thermal data with land-surface modeling and meso-scale climatic modeling in order to understand impacts of urbanization on local climate in Asia.     

基于土地利用类型提高人口格网数据空间精度的方法

高空间精度的人口格网数据具有空间分辨率高、人口空间分布特征准确的特点,在受灾人群估计、城市规划建设等领域有广泛的应用。针对已有的公开人口格网数据集(如WorldPop世界人口格网数据集)存在人口空间分布特征在小尺度上刻画不准确、空间分辨率较低的问题,本文使用东营市土地利用类型数据,结合地类权重和面积权重对WorldPop数据进行空间精度优化,获得东营市东营区黄河路街道25 m人口格网数据。相较于WorldPop数据,经过本文方法处理后的数据集空间分辨率更优,在可视化对比中,能够更准确地刻画人口分布特征,并在各地类人口占比统计中人口空间分布与用地单元分布一致性更高。该方法为获取小区域高空间精度人口格网数据提供了一种新思路。     

大数据时代下测绘地理信息检验检测面临的问题与思考

大数据时代下,测绘地理信息数据作为承载各类自然资源信息、社会信息、经济信息、人文信息等重要基础数据,其质量作用举足轻重.然而,当前测绘地理信息的质量检验检测从理论基础、方式方法、服务模式等各个方面都不能完全满足时代的需求.本文分析了大数据时代的一些典型特征和思维方式,从质量度量方式、抽样检查评价、检验与检测等方面分析了...     

遥感数据时空尺度对地理要素时空变化分析的影响

地理要素的时空变化分析对于了解和掌握地表的规律性有着重要的作用。利用地面站点观测、实地调查等传统方式获取数据,对地理要素进行时空变化分析是最常用的方法。但该类方法往往表现的是"点尺度"观测,不能在大尺度情况下准确地反映地表的时空变化信息。遥感卫星能以一定的时间间隔获得空间连续的对地"面尺度"观测数据,然而其特定的空间和时间分辨率使其获取的地表信息仍十分有限。同时地表的空间异质性和个别地表短时间内的快速变化,使得利用遥感数据对地理要素进行时空变化分析时,时空变化分析结果会随观测尺度而发生改变。本文从空间尺度和时间尺度两方面综述遥感数据时空尺度对地理要素的时空变化分析产生的影响和原因,并针对这些问题总结了减小时空尺度对结果不确定性影响的现行方法。可以通过多源遥感协同观测和反演、尺度转换、空间建模等方法减小空间尺度引起的不确定性;通过联合多时相遥感数据的方法减小时间尺度引起的不确定性。在实际应用中,应根据所观测地理要素的实际情况,综合分析选择合适的方法。     

Possibilities of using raster data in client‐side web maps

Companies and individual developers have recently put serious effort into improving web mapping libraries. A significant front in this development is hardware‐accelerated vector graphics. Owing to those efforts, and the continuously evolving World Wide Web, users can visualize large vector layers, and even animate them. On the other hand, this rapid development cannot be observed with raster data. There are some data abstraction libraries for reading raster files, although web mapping libraries do not use them to offer raster capabilities. Since there are no mature raster management pipelines on the web, this study explores two inherently different techniques for handling raster data. One of them uses the traditional, texture‐based method. The other is a hybrid technique rendering raster layers as vectors, overcoming some limitations of the raster model. While the traditional technique gives a smooth user experience, the hybrid method shows promising results for rendering hexagonal coverages.     

An open source GIS‐based Planning Support System: Application to the land use plan of La Troncal,Ecuador

Planning Support Systems (PSS) comprise a wide variety of geo‐technological tools related to GIS and spatial modeling aimed at addressing land planning processes. This article describes the OpenRules system, a PSS based on a previous system called RULES. Among OpenRules new features are its architecture, based exclusively on free and open source software, and its applicability to all land use types, including rural and urban uses. In addition, OpenRules incorporates an unlimited number of land evaluation factors and a new objective in land use spatial allocation. OpenRules has been programmed in Java and implemented as a module of the free GIS software gvSIG, with full integration between the GIS and the decision support tools. Decision support tools include multicriteria evaluation, multiobjective linear programming and heuristic techniques, which support three basic stages of land use planning processes, namely land suitability evaluation, land use area optimization and land use spatial allocation. The application of OpenRules to the region of La Troncal, Ecuador, demonstrates its capability to generate alternative and coherent solutions through a scientific and justified procedure at low cost in terms of time and resources.     

A heuristic‐based approach to mitigating positional errors in patrol data for species distribution modeling

Species distribution modeling (SDM) at fine spatial resolutions requires species occurrence data of high positional accuracy to achieve good model performance. However, wildlife occurrences recorded by patrols in ranger‐based monitoring programs suffer from positional errors, because recorded locations represent the positions of the ranger and differ from the actual occurrence locations of wildlife (hereinafter referred to as positional errors in patrol data). This study presented an evaluation of the impact of such positional errors in patrol data on SDM and developed a heuristic‐based approach to mitigating the positional errors. The approach derives probable wildlife occurrence locations from ranger positions, utilizing heuristics based on species preferred habitat and the observer's field of view. The evaluations were conducted through a case study of SDM using patrol records of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) in Yunnan, China. The performance of the approach was also compared against alternative sampling methods. The results showed that the positional errors in R. bieti patrol data had an adverse effect on SDM performance, and that the proposed approach can effectively mitigate the impact of the positional errors to greatly improve SDM performance.