GI_Forum最新文献_第5页

Suggestions on the Selection of Satellite Imagery for Future Remote Sensing-Based Humanitarian Applications 关于未来基于遥感的人道主义应用卫星图像选择的建议

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_01_s228

Yunya Gao, S. Lang, D. Tiede, L. Wendt, Getachew Workineh Gella

{"title":"Suggestions on the Selection of Satellite Imagery for Future Remote Sensing-Based Humanitarian Applications","authors":"Yunya Gao, S. Lang, D. Tiede, L. Wendt, Getachew Workineh Gella","doi":"10.1553/giscience2021_01_s228","DOIUrl":"https://doi.org/10.1553/giscience2021_01_s228","url":null,"abstract":"Satellite imagery is an important information source for research on remote sensing (RS)based humanitarian applications. The selection of satellite imagery is one of the most important steps for such research. This paper firstly shows the selection of satellite imagery in past research from 2015 to 2021. It can be found that most research on land cover and land use (LCLU) change caused by conflicts or refugees/internally displaced persons (IDPs) chose medium spatial resolution (MSR) imagery. Most research on dwelling detection of refugee/IDP camps applied high or very high spatial resolution (HSR/VHSR) imagery. There is much research that applied multiple types of satellite imagery for humanitarian applications. Then, the paper presents general characteristics of commonly available optical satellite imagery. Next, with the development of sensors, this paper suggests that data fusion of SPOT5 and Sentinel-2 may be helpful in LCLU change detection caused by refugees/IDPs or conflicts. Smallsat imagery may be promising for research on humanitarian applications that require a high temporal frequency of imagery.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87054552","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: 0

Innovation for Sustainable Cities: The Effects of Nudging and Gamification Methods on Urban Mobility and Sustainability Behaviour 可持续城市的创新:推动和游戏化方法对城市交通和可持续行为的影响

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_02_s251

Claudia Luger-Bazinger, Veronika Hornung-Prähauser

引用次数: 4

Testing Transferability of Deep-Learning-Based Dwelling Extraction in Refugee Camps 在难民营中测试基于深度学习的住所提取的可转移性

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_01_s220

Getachew Workineh Gella, L. Wendt, S. Lang, Andreas Braun, D. Tiede, Barbara Hofer, Yunya Gao, B. Riedler, Ahmad Alobaidi, Gina Schwendemann

引用次数: 5

Monitoring Land Degradation from Space 从空间监测土地退化

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_01_s143

Filippo Iodice, Federica D’Acunto, L. Bigagli

引用次数: 0

Towards Sustainable Urban Car–Parking Solutions: Exploring Effects of Parking Policies Using Spatial Regression Analysis 面向可持续城市停车解决方案:利用空间回归分析探索停车政策的效果

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_02_s228

Meng-Chin Tsai, S. van Gasselt, Tzu–Chin Lin

引用次数: 0

Application of Land Surface Temperature Analysis in Urban Green Spaces: Case Studies from South Asia 地表温度分析在城市绿地中的应用:以南亚为例

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_02_s202

G. Mohiuddin, J. Mund

引用次数: 0

A Comparison of Convolutional Neural Network Architectures for Automated Detection and Identification of Waterfowl in Complex Environments 复杂环境中水禽自动检测与识别的卷积神经网络体系结构比较

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_02_s152

Mohammad Mustafa Sa'doun, C. Lippitt, Gernot Paulus, Karl-Heinrich Anders

{"title":"A Comparison of Convolutional Neural Network Architectures for Automated Detection and Identification of Waterfowl in Complex Environments","authors":"Mohammad Mustafa Sa'doun, C. Lippitt, Gernot Paulus, Karl-Heinrich Anders","doi":"10.1553/giscience2021_02_s152","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s152","url":null,"abstract":"Waterfowl monitoring is an important task for understanding waterfowl distribution and habitats. Surveying approaches using hyper-spatial airborne imagery, collected by small unoccupied aerial systems (sUAS), hold potential to overcome the limitations of traditional methods while improving count efficiency and reliability. Difficulties obtaining waterfowl counts, particularly in complex image scenes, from the high quantity of imagery required hinders deployment of large-scale surveys. In this paper, we test Convolutional Neural Networks (CNNs) to understand their potential and how they behave across different versions of our waterfowl dataset. Three CNN architectures (YOLO, Retinanet and Faster RCNN) were trained on 3 hierarchical levels: waterfowl detection (True / False), waterfowl type (3 classes), and waterfowl species (8 classes). The architectures generally performed well, and results indicate that automated waterfowl detection in complex environments, and therefore enumeration, is feasible using current technology. Waterfowl identification in complex environments was not successful using the available training data, but we propose steps that might enhance the results.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90515111","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: 1

Putting Pedestrians First: Sidewalk Infrastructures, Width Patterns and COVID–19 以行人为先:人行道基础设施、宽度模式和COVID-19

GI_Forum Pub Date : 2021-01-01 DOI: 10.1553/giscience2021_02_s242

Victoria Fast, Jiaao Guo

{"title":"Putting Pedestrians First: Sidewalk Infrastructures, Width Patterns and COVID–19","authors":"Victoria Fast, Jiaao Guo","doi":"10.1553/giscience2021_02_s242","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s242","url":null,"abstract":"As the COVID-19 crisis has forced people to adhere to social distancing, the proximity to each other of pedestrians on the sidewalk suddenly becomes meaningful: do pedestrians have enough space to safely move within cities? With decades of urban planning prioritizing roads and automobiles, the answer is ‘no’. Cities all over the world have been forced to make urgent changes to pedestrian infrastructure in order to make it safe for people to move about public spaces during the pandemic. In this study, using the sidewalk infrastructure from the Canadian city of Calgary as an example, we model sidewalk widths and then analyse the spatial patterns across the city. Our results reveal that Calgary's sidewalk widths vary substantially and form clusters of narrow sidewalks among residential zones, while wide sidewalks are typically found in downtown, and in some parks and recreational areas. We recommend that the City of Calgary, and all cities, re-evaluate their sidewalk and pathway development patterns, and upgrade sidewalk infrastructures in those narrowsidewalk communities. By developing more robust methods for modelling and analysing sidewalk width, paired with adequate sidewalk data, cities can make informed decisions that lead to more inclusive, pedestrian-safe, cities.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89185263","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: 1

Uncertain Spaces, Uncertain Places. Dealing with Geographic Information in Digital Humanities: The Example of a Language Legacy Dataset 未知的空间，未知的地方。处理数字人文学科中的地理信息:一个语言遗留数据集的例子

GI_Forum Pub Date : 2020-06-25 DOI: 10.1553/giscience2020_01_s32

A. Dorn, R. R. Souza, B. Piringer, E. Wandl-Vogt

引用次数: 0

Implementing Geo Citizen Science Solutions: Experiences from the citizenMorph Project 实施地球公民科学解决方案:来自citizenMorph项目的经验

GI_Forum Pub Date : 2020-01-01 DOI: 10.1553/giscience2020_01_s3

S. Hennig, L. Abad, D. Hölbling, D. Tiede

引用次数: 2