GI_Forum最新文献_第9页

Augmented Reality and Mobile GIS as Tools for Teaching Data-collection in the Context of Forest Inventories 增强现实和移动GIS作为森林清查背景下教学数据收集的工具

GI_Forum Pub Date : 2019-01-01 DOI: 10.1553/giscience2019_02_s129

J. Mund, Susanne Müller

引用次数: 3

Trends in the Alaskan Bottom-Trawl Fishery from 1993 to 2015: A GIS-based Spatiotemporal Analysis 1993 - 2015年阿拉斯加底拖网渔业趋势:基于gis的时空分析

GI_Forum Pub Date : 2019-01-01 DOI: 10.1553/GISCIENCE_2019_01_S87

C. Steves

引用次数: 4

Describe! Analyse! Act! Geomedia and Sustainability: Results from a European School Project 描述!分析!行动!几何学和可持续性:来自欧洲学校项目的结果

GI_Forum Pub Date : 2019-01-01 DOI: 10.1553/2019_02_s144

Friedrich Barnikel, Floris Willems, Robert Plötz

引用次数: 0

Spatial Climate Justice and Green Infrastructure Assessment: A case study for the Huron River watershed, Michigan, USA 空间气候正义与绿色基础设施评估:以美国密歇根州休伦河流域为例

GI_Forum Pub Date : 2016-06-29 DOI: 10.1553/GISCIENCE2016_01_S176

C. Cheng

{"title":"Spatial Climate Justice and Green Infrastructure Assessment: A case study for the Huron River watershed, Michigan, USA","authors":"C. Cheng","doi":"10.1553/GISCIENCE2016_01_S176","DOIUrl":"https://doi.org/10.1553/GISCIENCE2016_01_S176","url":null,"abstract":"Green infrastructure serves as a critical no-regret strategy to address climate change mitigation and adaptation in climate action plans. Climate justice refers to the distribution of climate change-induced environmental hazards (e.g., increased frequency and intensity of floods) among socially vulnerable groups. Yet no index has addressed both climate justice and green infrastructure planning jointly in the USA. This paper proposes a spatial climate justice and green infrastructure assessment framework to understand social-ecological vulnerability under the impacts of climate change. The Climate Justice Index ranks places based on their exposure to climate change-induced flooding, and water contamination aggravated by floods, through hydrological modelling, GIS spatial analysis and statistical methodologies. The Green Infrastructure Index ranks access to biophysical adaptive capacity for climate change. A case study for the Huron River watershed in Michigan, USA, illustrates that climate justice hotspots are concentrated in large cities; yet these communities have the least access to green infrastructure. This study demonstrates the value of using GIS to assess the spatial distribution of climate justice in green infrastructure planning and thereby to prioritize infrastructure investment while addressing equity in climate change adaptation.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"176 1","pages":"176-190"},"PeriodicalIF":0.0,"publicationDate":"2016-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76851078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Spatio-temporal Visualization of Interpolated Particulate Matter (PM2.5) in Beijing 北京插值颗粒物(PM2.5)时空可视化

GI_Forum Pub Date : 2015-01-01 DOI: 10.1553/GISCIENCE2015S464

A. Keler, J. Krisp

{"title":"Spatio-temporal Visualization of Interpolated Particulate Matter (PM2.5) in Beijing","authors":"A. Keler, J. Krisp","doi":"10.1553/GISCIENCE2015S464","DOIUrl":"https://doi.org/10.1553/GISCIENCE2015S464","url":null,"abstract":"People in growing urban areas are more and more influenced by emissions coming from numerous vehicles and factories. In this paper we inspect the concentration of particulate matter (PM2.5) visually over time. This information stems from a data set of air quality measurements from 36 static sensors in Beijing over one year (from 8.02.2013 till 8.02.2014). One possibility for creating an overview for 36 positions with varying PM2.5 measurements in time is the use of interpolation techniques. In our approach, we generate surfaces of PM2.5 concentration using inverse distance weighting (IDW). The resulting surfaces represent interpolated PM2.5 values, based on averaged PM2.5 information (e.g. average of one day). We create simple interactive visualizations using points as surface representations. Each surface point within the 3D visual analysis display exhibits its PM2.5 value by differing coloration and z-value (height component). The interactivity consists of using selection circles for stacked 3D displays of interpolated PM2.5 surfaces for different times (time series). The aim of this visual information analysis is the possible detection of periodical hotspots of high PM2.5 concentrations, which might be useful for people with respiratory diseases. For the detection of dynamic PM2.5 hotspot variations, we introduce thresholds for querying only the highest PM2.5 values of the surfaces. Afterwards, these points are aggregated into convex hulls (polygons), with the idea of comparing the size and shape of the PM2.5 hotspots in each created surface. The change of position and size of these polygons over time may be an indicator for air quality changes within an urban environment. Considering the above, this may be a starting point for the conception of a personalized routing solution for pedestrians or vehicle drivers with respiratory diseases, who want to avoid these hotspots of high PM2.5 concentrations.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"17 1","pages":"464-474"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90997389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Automatic Detection of Driving–Lane Geometry Based on Aerial Images and Existing Spatial Data 基于航拍图像和现有空间数据的车道几何形状自动检测

GI_Forum Pub Date : 1900-01-01 DOI: 10.1553/giscience2021_02_s122

J. Růžička, Lukás Bruha

引用次数: 0