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Power outage and environmental justice in Winter Storm Uri: an analytical workflow based on nighttime light remote sensing

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International Journal of Digital Earth 2023年第1期16卷 2259-2278页

作者： Jinwen Xu Yi Qiang Heng Cai Lei Zou gis Center Florida International UniversityMiamiFLUSA School of Geosciences University of South FloridaTampaFLUSA department of Geography Texas A&M UniversityCollege StationTXUSA

The intensity of extreme weather events has been increasing,posing a unique threat to society and highlighting the importance of our electrical power system,a key component in our *** severe weather events,quickly identifying power outage impact zones and affected communities is crucial for informed disaster ***,a lack of household-level power outage data impedes timely and precise *** address these challenges,we introduced an analytical workflow using NASA’s Black Marble daily nighttime light(NTL)images to detect power outages from the 2021 Winter Storm *** workflow includes adjustments to mitigate viewing angle and snow reflection *** outage is detected by comparing storm-time and baseline(normal condition)NTL images using an empirical adjusted *** outcomes of the workflow are 500-meter resolution power outage maps,which have the optimal correlation with real outage tracking data when NTL intensity is reduced by 26%.With the resultant power outage maps,we analyzed the relations between power outages and disadvantaged populations in 126 Texas counties and 4182 census tracts to evaluate environmental justice in the *** results show that Latino/Hispanic communities tend to suffer more from power outages at both the county and census tract levels.

关键词： Nighttime light disaster resilience natural disaster spatial analysis environmental justice power outage

Magnetic fabric and geomorphic characteristic of Neotectonic activity along strike direction of North Almora Thrust,Kumaun Lesser Himalaya,India

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Geodesy and Geodynamics 2022年第3期13卷 261-274页

作者： Ritu Chauhan Girish Ch Kothyari Surendra S.Bhakuni Pitamber Dutt Pant Ajay Kumar Taloor CAS in Geology Kumaun UniversityNainitalIndia Institute of Seismological Research RaisanGandhinagar382009India Wadia Institute of Himalayan Geology DehradunIndia department of Remote Sensing and gis University of JammuJammuIndia

Structurally,the North Almora Thrust(NAT),is placed in the northern proximity of the Almora Nappe(AN)in the Kumaun Lesser *** NAT is characterized by the presence of a zone of mylonitic rocks of basal Saryu Formation(1800±100 Ma)in the hanging wall and the metasedimentaries of Inner Lesser Himalayan rocks as the footwall *** NAT has been dextrally offset by two estabilished maj or faults *** River Fault(SRF)in Saryu Valley and Dwarahat-Chaukhutia Fault(DCF)in Ramganga *** present study,we identified four new faults,based on field study,geomorphic landform and magnetic fabric *** faults are N-S trending Pancheshwar Fault,NE-SW Rameshwer Fault,NNE-SSW trending Kosi Fault,and NNE-SSW trending Gagas Fault(GF).Our results show that the zone is bound by cross cutting relation with NAT and these fault zones are comparatively more active than other ***,we suggest that the steep and NW-SE orientation of magnetic foliation within the NAT zone is a result of NE-SW oriented progressive regional *** magnetic foliations represent the unseen internal foliations in the rocks developed due to preferred alignment of magnetic minerals and can be found through the Anisotropy of magnetic susceptibility(AMS)*** in the alignment of the field and magnetic foliations are developed due to superimposed brittle deformation along the faults over the pre-existing field *** foliations represent the impact of last stage deformation and significant to find brittle deformation and finite strain in the rocks of the study *** lowering of anisotropy(Pj)away from the fault zone represents distribution of strain across the NAT *** fabric confirms the presence of faults developed across the NAT zone and also explains the deformation pattern along these *** geomorphic anomalies and steepness changes across the NAT zone are correlated with active deformation along the NAT and associated transverse

关键词： North Almora Thrust(NAT) Geomorphology Anisotropy of magnetic susceptibility Neotectonics Kumaun Lesser Himalaya

A novel semantic segmentation approach based on U-Net,WU-Net,and U-Net++deep learning for predicting areas sensitive to pluvial flood at tropical area

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International Journal of Digital Earth 2023年第1期16卷 3661-3679页

作者： Laura Melgar-García Francisco Martínez-álvarez Dieu Tien Bui Alicia Troncoso Data Science&Big Data Lab Pablo de Olavide UniversitySevilleSpain gis Group Department of Business and ITUniversity of South-Eastern NorwayGullbringvegen 36B?i Telemark3800Norway

Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the ***, the ability to predict flood-prone areas in advance is crucialfor effective risk management. The objective of this research is to assessand compare three convolutional neural networks, U-Net, WU-Net, andU-Net++, for spatial prediction of pluvial flood with a case study at atropical area in the north of Vietnam. They are relative new convolutionalgorithms developed based on U-shaped architectures. For this task, ageospatial database with 796 historical flood locations and 12 floodindicators was prepared. For training the models, the binary crossentropywas employed as the loss function, while the Adaptive momentestimation (ADAM) algorithm was used for the optimization of themodel parameters, whereas, F1-score and classification accuracy (Acc)were used to assess the performance of the models. The results unequivocally highlight the high performance of the three models,achieving an impressive accuracy rate of 96.01%. The flood susceptibility maps derived from this research possess considerable utility for local authorities, providing valuable insights and informationto enhance decision-making processes and facilitate the implementation of effective risk management strategies.

关键词： Flash-flood assessment convolutional networks climate change gis

Seismic vulnerability assessment of urban buildings and traffic networks using fuzzy ordered weighted average

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Journal of Mountain Science 2019年第3期16卷 677-688页

作者： Yasaman ASADI Najmeh Neysani SAMANY Keyvan EZIMAND department of Remote Sensing and gis Faculty of GeographyUniversity of Tehran Remote Sensing and gis Center Faculty of Earth ScienceUniversity of Shahid Beheshti

Urban buildings and urban traffic network are considered as the vital arteries of cities which have particular effects especially after the crisis in the search and rescue operations. The aim of this study is to determine the vulnerability of urban areas especially, buildings and traffic networks using multicriteria geographic information systems and decisionmaking methods. As there are many effective criteria on the seismic vulnerability that they have uncertain and vague properties, the method of this paper is applying fuzzy ordered weighted average(OWA) to model the seismic vulnerability of urban buildings and traffic networks in the most optimistic and pessimistic states. The study area is district 6 of Tehran that is affected by the four major faults, and thus will be threatened by the earthquakes. The achieved results illustrated the vulnerability with different degrees of risk levels including very high, high, medium, low and very low. The results show that in the most optimistic case 14% and in the pessimistic case 1% of buildings tolerate in very low vulnerability. The vulnerability of urban street network also indicates that in the optimistic case 12% and in the pessimistic case at most 9% of the area are in appropriate condition and the North and NorthEast of the study area are more vulnerable than South of it.

关键词： Earthquake Vulnerability Assessment Urban buildings Traffic network Multi-Criteria Decision Analysis(MCDA) Fuzzy-OWA

The application of ResU-net and OBIA for landslide detection from multi-temporal Sentinel-2 images

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Big Earth Data 2023年第4期7卷 961-985页

作者： Omid Ghorbanzadeh Khalil Gholamnia Pedram Ghamisi alnstitute of Advanced Research in Artificial Intelligence(IARAl) ViennaAustria department of Remote Sensing and gis University of TabrizTabrizIran Machine Learning Group Helmholtz-Zentrum Dresden-RossendorfHelmholtz Institute Freiberg for Resource TechnologyFreibergGermany

Landslide detection is a hot topic in the remote sensing community,particularly with the current rapid growth in volume(and variety)of Earth observation data and the substantial progress of computer *** learning algorithms,especially fully convolutional networks(FCNs),and variations like the ResU-Net have been used recently as rapid and automatic landslide detection *** FCNs have shown cutting-edge results in automatic landslide detection,accuracy can be improved by adding prior knowledge through possible *** study evaluates a rulebased object-based image analysis(OBIA)approach built on probabilities resulting from the ResU-Net model for landslide *** train the ResU-Net model using a landslide dataset comprising landslide inventories from various geographic regions,including our study area and test the testing area not used for *** the OBIA stage,we frst calculate land cover and image difference indices for pre-and post-landslide multi-temporal ***,we use the generated indices and the resulting ResU-Net probabilities for image segmentation;the extracted landslide object candidates are then optimized using rule-based *** the result validation section,the landslide detection of the proposed integration of the ResU-Net with a rule-based classification of OBIA is compared with that of the ResU-Net *** proposed approach improves the mean intersection-over-union of the resulting map from the ResU-Net by more than 22%.

关键词： Deep learning(DL) Eastern Iburi Japan European Space Agency(ESA) Fully Convolutional Networks(FCNs) object-based image analysis(OBIA) rapid landslide mapping ResUnet Sentinel-2

Uses of online geoprocessing technology in analyses and case studies:a systematic analysis of literature

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International Journal of Digital Earth 2015年第11期8卷 901-917页

作者： Barbara Hofer Interfaculty department of Geoinformatics–Z_gis University of SalzburgSalzburgAustria

Interpreting spatial data to derive information is a core task in the field of Geographic Information Science and Technology.A logical step following the collection of data in online repositories is to provide geoprocessing technology for analysing data *** geoprocessing technology can be employed for providing a specified set of tools in a theme-specific platform,documenting a model or workflow and making it widely available,automating recurring tasks or offering simple tools to a large user *** systematic analysis of literature evaluates how much available online geoprocessing tools are being used for answering questions in specific application *** initial set of articles is derived from a keyword-based search in the database *** set of articles is manually filtered to identify applications of online geoprocessing *** analysis of application-related articles shows that virtually all applications require further development of *** outside the spatial information science field are still underrepresented regarding the use of this *** required adaptation of technology for user tasks is identified as major barrier for the wide use of online *** research needs to assess user tasks and how online geoprocessing can provide the required functions in a useroriented manner.

关键词： e-science online geoprocessing Web service service-oriented architecture

Geo-Hazard Susceptibility Assessment and Its Impacts on Livelihoods in Kerio Valley, Kenya

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International Journal of Geosciences 2022年第3期13卷 199-243页

作者： Mark Boitt John Gathoni Institute of Geomatics GIS and Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya department of Research and Development GIS and Remote Sensing Section-Mapinfotek Nairobi Kenya

Geohazards are a recurrent issue in the Kerio River catchment of Kenya, which usually results in life and property loss. This research focuses on mapping geo-hazard risk zones of the region. The risk zones were developed from a combination of land use land cover maps, agroecological zones maps and soil erosion maps using the Analytical Hierarchy Process method of multi-criteria analysis. The final results depict the geohazard risk maps which show the susceptibility of different areas in the catchment (classified as risk zones) to hazards. The zones range from no risk zones to very high-risk zones. The results showed that the lowlands are most susceptible to hazards as they were classified as high-risk zones. These risk zone areas have impacts on the socio-economic development hence negatively impacting livelihoods in the area.

关键词： Kerio Valley Basin Land Use Land Cover Moisture Zones Agroecological Zones Soil Erosion RUSLE Model Geohazard Risk Zones Multivariate Clustering Analytical Hierarchy Process

GeoAI Technologies and Their Application Areas in Urban Planning and Development: Concepts, Opportunities and Challenges in Smart City (Kuwait, Study Case)

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Journal of Data Analysis and Information Processing 2022年第2期10卷 110-126页

作者： Abdelkhalek I. Alastal Ashraf Hassan Shaqfa Geography and gis department Arts College Islamic University of Gaza Gaza Palestine

Artificial intelligence has significantly altered many job workflows, hence expanding earlier notions of limitations, outcomes, size, and prices. GeoAI is a multidisciplinary field that encompasses computer science, engineering, statistics, and spatial science. Because this subject focuses on real-world issues, it has a significant impact on society and the economy. A broad context incorporating fundamental questions of theory, epistemology, and the scientific method is used to bring artificial intelligence (Al) and geography together. This connection has the potential to have far-reaching implications for the geographic study. GeoAI, or the combination of geography with artificial intelligence, offers unique solutions to a variety of smart city issues. This paper provides an overview of GeoAI technology, including the definition of GeoAI and the differences between GeoAI and traditional AI. Key steps to successful geographic data analysis include integrating AI with gis and using GeoAI tools and technologies. Also shown are key areas of applications and models in GeoAI, likewise challenges to adopt GeoAI methods and technology as well as benefits. This article also included a case study on the use of GeoAI in Kuwait, as well as a number of recommendations.

关键词： Smart City Geospatial Artificial Intelligence Machine Learning Deep Learn-ing Convolutional Neural Network Geographic Information Systems

Assessment of the fused image of multispectral and panchromatic images of SPOT5 in the investigation of geological hazards

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Science China(Technological Sciences) 2008年第S2期51卷 144-153页

作者： KANG TingJun,ZHANG XinChang & WANG HaiYing department of Remote Sensing and gis Engineering,Sun Yat-sen University,Guangzhou 510275,China department of Remote Sensing and gis Engineering Sun Yat-sen University Guangzhou China

The investigated area in this paper is located on the northern mountain in Guangzhou *** is characterized by high relief and *** and pan Images of SPOT5 were used as the remote sensing data source,and high-pass filtering(HPF),Brovery transform(BT),intensity-hue-saturation(IHS),principal component analysis(PCA) and the modified IHS(MIHS) methods were adopted for image ***,a comparison has been made between the entire fused images and the original multispectral *** evaluation and objective evaluation(entropy,average gradient,correlation coefficient,distribution of gray) have been adopted to assess the quality of the fused *** regional geological survey has been taken to find the interpretation *** show that the MIHS is the best image fusion method for geological hazards interpretation,and the fused image can provide abundant textural and spectral information for easy interpretation of such geological hazards as collapse,landslip,and debris flow.

关键词： geological hazard remote sensing image fusion SPOT5