GIS Ostrava 2022 Earth Observation for Smart City and Smart Region最新文献_第2页

3D Visualisation of Periodic Spatial Time Series from Radar Interferometry Measurements over Underground Gas Storage 基于地下储气库雷达干涉测量的周期性空间时间序列三维可视化

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-9

J. Struhár, P. Rapant

引用次数: 0

A Modified Deep Learning Approach for Reconstruction of MODIS LST Product 一种改进的深度学习方法用于MODIS LST产品的重建

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-6

A. Sekertekin, Serkal Kartan, Qi Liu, S. Bonafoni

引用次数: 1

Perception of the Impact of Heavy Vehicle Movement on Walkability in Krishnanagar Municipality, India 感知重型车辆运动对印度克里希那纳加尔市步行能力的影响

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-3

Sushmita Biswas, K. Roychowdhury

{"title":"Perception of the Impact of Heavy Vehicle Movement on Walkability in Krishnanagar Municipality, India","authors":"Sushmita Biswas, K. Roychowdhury","doi":"10.31490/9788024846026-3","DOIUrl":"https://doi.org/10.31490/9788024846026-3","url":null,"abstract":"Relatively narrow roads of small cities get adversely affected by heavy vehicular loads, reducing pedestrian movement. This study aims to use spatial analyses and statistical tools to provide an assessment of the impact of heavy vehicular movement on walkability in Krishnanagar municipality in India from the pedestrians’ perspectives. AHP-SWOT methods and walkability index were calculated over 10 road links. The results were verified using field observations and questionnaire surveys. It was observed that due to the absence of separate lanes and minimum scope for road expansion, walking on the roads is significantly impacted, reducing the walkability index on all the major road crossings to less than 0.3. The level of traffic and the externalities by the heavy vehicles’ operation has an effect on different population group of pedestrians. Pedestrians have highly rated the distress due to traffic congestion caused by heavy vehicle operation and reduction of walking space due to encroachment by vehicles as major demotivating factors for walking. The study proposes that, with an opportunity of sufficient road width to support medium/light vehicular flow, re-planning of traffic flow with the help of policy makers, planners and engineers will help towards developing a smart city with multiple sustainable benefits.","PeriodicalId":419801,"journal":{"name":"GIS Ostrava 2022 Earth Observation for Smart City and Smart Region","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132223774","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

Mapping Urban Green Space Dynamics: a Semantic Earth Observation Data Cube Approach 城市绿地动态映射:语义地球观测数据立方体方法

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-13

D. Tiede, M. Sudmanns, H. Augustin, Larisa Paulescu, A. Baraldi

{"title":"Mapping Urban Green Space Dynamics: a Semantic Earth Observation Data Cube Approach","authors":"D. Tiede, M. Sudmanns, H. Augustin, Larisa Paulescu, A. Baraldi","doi":"10.31490/9788024846026-13","DOIUrl":"https://doi.org/10.31490/9788024846026-13","url":null,"abstract":"Urban green space mapping based on satellite imagery is now possible more frequently and over shorter timespans thanks to dense time-series of open and free Earth observation (EO) images (e.g. the Copernicus Sentinel-2 mission). Despite this data availability, many approaches still focus on identifying the annual maximum extent of urban green spaces instead of utilising the entire dense image stack to characterise seasonal dynamics. We aim to temporally inform urban green space delineations, which could be relevant for applications like urban heat mitigation or citizens’ urban green perception. We present a semantic EO data cube approach that allows ad-hoc, browser-based vegetation mapping for custom areas and timespans using transferable semantic models. We demonstrate the approach using a Sentinel-2 semantic EO data cube covering Austria, which makes use of every available Sentinel-2 observation since 2015 and where non-valid observations (e.g. cloud) can be masked out on an individual pixel basis to increase the number of valid observations for shorter timespans rather than relying on image-wide metadata. While we show results for the city of Vienna, the approach is transferrable to anywhere in Austria using the same infrastructure, or any other similar semantic EO data cube worldwide.","PeriodicalId":419801,"journal":{"name":"GIS Ostrava 2022 Earth Observation for Smart City and Smart Region","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114618004","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

Effects of Transport Corridor Advancement on Agglomeration and Industrial Relocation – a Case Study of Disctrict 3 in Dallas 交通走廊推进对集聚和产业转移的影响——以达拉斯市3区为例

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-1

Subham Kharel, Parul Singh

{"title":"Effects of Transport Corridor Advancement on Agglomeration and Industrial Relocation – a Case Study of Disctrict 3 in Dallas","authors":"Subham Kharel, Parul Singh","doi":"10.31490/9788024846026-1","DOIUrl":"https://doi.org/10.31490/9788024846026-1","url":null,"abstract":"Cities serve as hubs for various activities that necessitate comprehensive transportation connectivity. This study examines the decadal urban agglomeration patterns from 2001- to 2020 and critically assesses the relationship between freeway developments, industrial relocation, and population density in the DFW (Dallas Fort Worth) metropolitan area. Landsat satellite imageries, US census, and open-source GIS datasets have been utilized in the study. Maximum Likelihood Classification (MLC) algorithm helped generate the vector database, using which Land Use/ Land Cover (LULC) variations were assessed. The calculated overall accuracies of the classified images for 2001, 2011, and 2020 were 93.12%, 91.87%, and 93.12%, and their corresponding kappa coefficients were 0.90, 0.89, and 0.90, respectively. Eventually, buffer generation techniques and summary statistics helped detect potential boom hotspots. Our results indicate that the highway advancement project lures industries, leading to population migration. The LULC variations suggest that the increase in highway infrastructure resulted in a surge in built-up and a decrease in open spaces in District-3 of DFW.","PeriodicalId":419801,"journal":{"name":"GIS Ostrava 2022 Earth Observation for Smart City and Smart Region","volume":"346 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122333582","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

Monitoring Landslide Displacements Through Maximum Cross-Correlation of Sentinel-2 Satellite Images 利用Sentinel-2卫星图像最大互相关监测滑坡位移

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-7

Lorenzo Amici, V. Yordanov, D. Oxoli, M. Brovelli

引用次数: 1

Using Multispectral Imagery from UAV to Derive Selected Forest Inventory Parameters 利用无人机多光谱图像提取选定森林清查参数

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region Pub Date : 1900-01-01 DOI: 10.31490/9788024846026-12

Jakub Seidl, Tereza Čenčíková, Ondřej Renner, Jan Bojko, Tomáš Vantuch

引用次数: 0