GeoScape最新文献_第2页

Geospatial and Analytical Hierarchical Process approach for potential sites of water harvesting in lower Kulsi basin, India 印度库尔西盆地下游潜在集水地点的地理空间和分析层次过程方法

IF 1.3

GeoScape Pub Date : 2023-06-01 DOI: 10.2478/geosc-2023-0005

G. Thakuriah

引用次数: 0

Problem-solving procedures in spatially explicit tasks: comparing procedures with printed and digital cartographic documents 空间显式任务中的问题解决程序：将程序与印刷和数字制图文件进行比较

IF 1.3

GeoScape Pub Date : 2023-06-01 DOI: 10.2478/geosc-2023-0003

Petr Trahorsch, Jakub Reich

引用次数: 0

Using electronic record of sales to support fair budgetary allocations across Czech municipalities 使用电子销售记录支持捷克各城市的公平预算分配

IF 1.3

GeoScape Pub Date : 2023-06-01 DOI: 10.2478/geosc-2023-0004

Pavel Semerád, V. Rogalewicz, M. Barták

引用次数: 1

Vehicle detection using panchromatic high-resolution satellite images as a support for urban planning. Case study of Prague’s centre 车辆检测使用全色高分辨率卫星图像作为城市规划的支持。布拉格中心案例研究

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0009

Peter Golej, J. Horák, Pavel Kukuliac, Lucie Orlikova

{"title":"Vehicle detection using panchromatic high-resolution satellite images as a support for urban planning. Case study of Prague’s centre","authors":"Peter Golej, J. Horák, Pavel Kukuliac, Lucie Orlikova","doi":"10.2478/geosc-2022-0009","DOIUrl":"https://doi.org/10.2478/geosc-2022-0009","url":null,"abstract":"Abstract The optical sensors on satellites nowadays provide images covering large areas with a resolution better than 1 meter and with a frequency of more than once a week. This opens up new opportunities to utilize satellite-based information such as periodic monitoring of transport flows and parked vehicles for better transport, urban planning and decision making. Current vehicle detection methods face issues in selection of training data, utilization of augmented data, multivariate classification or complexity of the hardware. The pilot area is located in Prague in the surroundings of the Old Town Square. The WorldView3 panchromatic image with the best available spatial resolution was processed in ENVI, CATALYST Pro and ArcGIS Pro using SVM, KNN, PCA, RT and Faster R-CNN methods. Vehicle detection was relatively successful, above all in open public places with neither shade nor vegetation. The best overall performance was provided by SVM in ENVI, for which the achieved F1 score was 74%. The PCA method provided the worst results with an F1 score of 33%. The other methods achieved F1 scores ranging from 61 to 68%. Although vehicle detection using artificial intelligence on panchromatic images is more challenging than on multispectral images, it shows promising results. The following findings contribute to better design of object-based detection of vehicles in an urban environment and applications of data augmentation.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"108 - 119"},"PeriodicalIF":1.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49560965","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

Spatial distribution of military bases and power of interest groups in an emergent democracy 新兴民主国家军事基地的空间分布与利益集团的权力

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0013

Bohuslav Pernica, J. Ženka

引用次数: 0

Development of Academic Patenting in European Regions – A Large Scale Analysis 欧洲地区学术专利的发展——大规模分析

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0012

Miroslav Špurek, Š. Rehák

{"title":"Development of Academic Patenting in European Regions – A Large Scale Analysis","authors":"Miroslav Špurek, Š. Rehák","doi":"10.2478/geosc-2022-0012","DOIUrl":"https://doi.org/10.2478/geosc-2022-0012","url":null,"abstract":"Abstract In this article, we analyze academic patenting on an unprecedented scale - for 29 European countries. The comprehensive identification phase captures both groups of academic patents, in and outside of the ownership of universities. With stronger patent rights of universities, the share of university-owned patents is increasing faster. Nevertheless, even today, universities own only one third of their patents while the other two thirds remain in the property of individuals and companies. Universities have recently accounted for 13% of regional patent production and compared to firms their contribution to region’s innovation performance remains small. The share of academic patents is higher in Eastern Europe and in regions where innovative companies are lacking, in capital regions, and in regions with a strong tradition in academic patenting. The contribution of universities to the innovation performance of the most innovative regions is relatively small, although there are large differences, and the size of the contribution can vary significantly for similar levels of patent intensity. Given the effects of university research, it has been known since the 1990s that increasing university spending on research is driving innovation on the part of companies and within the region. However, such an effect is limited to high quality research and is most effective in terms of regional policy in poor regions where innovative companies are lacking. In this paper, instead of research expenditure, university patents filed with the EPO represent university research, as other patents are assumed to be a product of companies. We have found that the latter can be predicted by the volume of academic patents.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"148 - 157"},"PeriodicalIF":1.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47748232","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

Effects of Transport Corridor Advancement on Agglomeration and Industrial Relocation – Dallas Fort Worth (US) case study 交通走廊推进对集聚和产业转移的影响——以美国达拉斯沃斯堡为例

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0010

Subham Kharel, Parul Singh

{"title":"Effects of Transport Corridor Advancement on Agglomeration and Industrial Relocation – Dallas Fort Worth (US) case study","authors":"Subham Kharel, Parul Singh","doi":"10.2478/geosc-2022-0010","DOIUrl":"https://doi.org/10.2478/geosc-2022-0010","url":null,"abstract":"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. The 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%, 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. From our study, we find that 79.16% of old industries are located near old freeways, while 78.84% of new industries are located near new freeways. Further, our industrial area to road area comparison clearly shows that industrial relocation was driven by transportation advancements over time. Our results also confirm that this relocation of industries fostered a massive population influx during the following decades.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"120 - 313"},"PeriodicalIF":1.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69208403","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

Using open data to reveal factors of urban susceptibility to natural hazards and man-made hazards: case of Milan and Sofia 利用开放数据揭示城市对自然灾害和人为灾害的易感性因素:以米兰和索非亚为例

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0008

A. Vavassori, Angelly De Jesús Pugliese Viloria, M. Brovelli

{"title":"Using open data to reveal factors of urban susceptibility to natural hazards and man-made hazards: case of Milan and Sofia","authors":"A. Vavassori, Angelly De Jesús Pugliese Viloria, M. Brovelli","doi":"10.2478/geosc-2022-0008","DOIUrl":"https://doi.org/10.2478/geosc-2022-0008","url":null,"abstract":"Abstract Multi-hazard mapping in urban areas is relevant for preventing and mitigating the impact of nature- and human-induced disasters while being a challenging task as different competencies have to be put together. Artificial intelligence models are being increasingly exploited for single-hazard susceptibility mapping, from which multi-hazard maps are ultimately derived. Despite the remarkable performance of these models, their application requires the identification of a list of conditioning factors as well as the collection of relevant data and historical inventories, which may be non-trivial tasks. The objective of this study is twofold. First, based on a review of recent publications, it identifies conditioning factors to be used as an input to machine and deep learning techniques for singlehazard susceptibility mapping. Second, it investigates open datasets describing those factors for two European cities, namely Milan (Italy) and Sofia (Bulgaria) by exploiting local authorities’ databases. Identification of the conditioning factors was carried out through the review of recent publications aiming at hazard mapping with artificial intelligence models. Two indicators were conceived to define the relevance of each factor. A first research result consists of a relevance-sorted list of conditioning factors per hazard as well as a set of open and free access data describing several factors for Milan and Sofia. Based on data availability, a feasibility analysis was carried out to investigate the possibility to model hazard susceptibility for the two case studies as well as for the limit case of a city with no local data available. Results show major differences between Milan and Sofia while pointing out Copernicus services’ datasets as a valuable resource for susceptibility mapping in case of limited local data availability. Achieved outcomes have to be intended as preliminary results, as further details shall be disclosed after the discussion with domain experts.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"93 - 107"},"PeriodicalIF":1.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48288506","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

The Neighborhood Impact of Industrial Blight: A Path Analysis 工业衰败的邻里影响:路径分析

IF 1.3

GeoScape Pub Date : 2022-12-01 DOI: 10.2478/geosc-2022-0011

R. Banai, E. Momeni

{"title":"The Neighborhood Impact of Industrial Blight: A Path Analysis","authors":"R. Banai, E. Momeni","doi":"10.2478/geosc-2022-0011","DOIUrl":"https://doi.org/10.2478/geosc-2022-0011","url":null,"abstract":"Abstract Historically, industry shaped the space-economy of the American city, a major source of employment opportunity for residents that selected housing nearby or within a convenient or affordable commuting distance. However, the contemporary American city is structurally characterized by abandoned, blighted, vacant industrial properties due to urban expansion, deindustrialization and the suburbanization of both jobs and population. The urban studies literature rarely documents the neighborhood impact of industrial blight akin to studies of residential blight. We determine the proximity-effect of industrial blight on the neighborhood thought of not as an isolated and closed entity, but as a connected and open entity within the city and the region. Unlike studies confined to the property value impact, we determine Pearson correlations of industrial blight and vacancy expansively with the socio-economic and physical characteristics of neighborhoods. We use path analysis to determine direct, indirect, and total neighborhood impact of industrial blight and vacancy. The census block group and parcel-level geographic information system (GIS) provide our principal sources of data. The block group geography contains the neighborhood as a fundamental spatial unit. We determine how the neighborhood impact varies with distance from the blighted, vacant industrial property.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"132 - 147"},"PeriodicalIF":1.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45553141","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

Assessment of neighborhood sustainability in terms of urban mobility: A case study in Dhaka City, Bangladesh 从城市流动性角度评估社区可持续性：以孟加拉国达卡市为例

IF 1.3

GeoScape Pub Date : 2022-06-01 DOI: 10.2478/geosc-2022-0001

Md. Hamidur Rahman, Mamata Jafrin Mouli, Fajle Rabbi Ashik

{"title":"Assessment of neighborhood sustainability in terms of urban mobility: A case study in Dhaka City, Bangladesh","authors":"Md. Hamidur Rahman, Mamata Jafrin Mouli, Fajle Rabbi Ashik","doi":"10.2478/geosc-2022-0001","DOIUrl":"https://doi.org/10.2478/geosc-2022-0001","url":null,"abstract":"Abstract For achieving sustainable cities, sustainable mobility is one of the key elements. Policymakers around the world are taking different strategies to ensure sustainable urban mobility at the local level. However, sustainable urban mobility assessment at neighborhoods of a developing country received a significant research gap. This study attempts to close this research gap by deriving and comparing neighborhood sustainability based on three indicators: modal share, travel time, and travel cost, in Dhaka city, Bangladesh. Using a two-step cluster model, neighborhoods were grouped into three clusters. Study results classified 41 (44.6%) neighborhoods as sustainable, 30 (32.6%) as potentially sustainable, and 21 (22.8%) as unsustainable neighborhoods due to less positive outcomes of sustainable mobility policies. Later, median income and jobs-housing ratio value for different neighborhood types validated the classification result. Findings from this study reveal insights for transport planners, development agencies, policymakers to identify areas where mobility of the residents needs to be improved on a priority basis; advocate further research on comprehensive sustainability assessment at the neighborhood level. Highlights for public administration, management and planning: • There is a significant difference in modal share, travel time, and travel cost in neighborhoods. • A traditional neighborhood of the city is comparatively more sustainable than newly developed ones. • Neighborhoods with similar sustainability status tend to be clustered on the city scale. • Median income and jobs-housing ratio can effectively capture the difference in sustainability level in terms of urban mobility. • Sustainable urban mobility assessment can contribute city planning and development process.","PeriodicalId":42291,"journal":{"name":"GeoScape","volume":"16 1","pages":"1 - 14"},"PeriodicalIF":1.3,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47103093","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: 2