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Value of incorporating geospatial information into the prediction of on-street parking occupancy - A case study

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Geo-Spatial Information Science 2021年第3期24卷 438-457页

作者： Michael Balmer Robert Weibel Haosheng Huang department of geography University of ZurichZurichSwitzerland department of geography Ghent UniversityGhentBelgium

In light of growing urban traffic,car parking becomes increasingly critical for cities to manage.As a result,the prediction of parking occupancy has sparked significant research interest in recent years.While many external data sources have been considered in the prediction models,the underlying geographic context has mostly been ignored.Thus,in order to study the contribution of geospatial information to parking occupancy prediction models,road network centrality,land use,and Point of Interest(POI)data were incorporated in Random Forest(RF)and Artificial Neural Network(ANN,specifically Feedforward Neural Network FFNN)prediction models in this work.Model performances were compared to a baseline,which only considers historical and temporal input data.Moreover,the influence of the amount of training data,the prediction horizon,and the spatial variation of the prediction were explored.The results show that the inclusion of geospatial information led to a performance improvement of up to 25%compared to the baseline.Besides,as the prediction horizon expanded,predictions became less reliable,while the relevance of geospatial data increased.In general,land use and POI data proved to be more beneficial than road network centrality.The amount of training data did not have a significant influence on the performance of the RF model.The ANN model,conversely,achieved optimal results on a training input of 5 days.Likely attributable to varying occupancy patterns,prediction performance disparities could be identified for different parking districts and street segments.Generally,the RF model outperformed the ANN model on all predictions.

关键词： Parking occupancy prediction on-street parking geospatial information machine learning

Analysis of Spatial Autocorrelation Patterns of Heavy and Super-Heavy Rainfall in Iran

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Advances in Atmospheric Sciences 2017年第9期34卷 1069-1081页

作者： Iman ROUSTA Mehdi DOOSTKAMIAN Esmaeil HAGHIGHI Hamid Reza GHAFARIAN MALAMIRI Parvane YARAHMADI department of geography Yazd University department of geography Zanjan University department of geography Tabriz University department of geography Khwarizmi University

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran＇s heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gi statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

关键词： Iran heavy rainfall super-heavy rainfall spatial autocorrelation Gi index

Spatially explicit estimation of soil organic carbon stock of an estuarine mangrove wetland of eastern India using elemental analysis and very-fine resolution satellite data

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Ecological Processes 2022年第1期11卷 411-426页

作者： Debajit Datta Madhumita Bairagi Mansa Dey Argha Pratim Pal Jibananda Gayen department of geography Jadavpur UniversityKolkata 700032India department of geography Sree Chaitanya CollegeHabra 743268India

Background:This study estimated the total soil organic C(SOC)stock of the wetland influence zone of Bichitrapur mangroves in eastern India in a spatially explicit manner.Both spatial and vertical distribution of SOC densities with respect to land use/land cover(LULC)pattern were assessed.Subsequently,some site-specific management strate-gies were forwarded towards enhancement of C sequestration potential.Methods:The changing patterns of LULC within the wetland influence zone of the site were analyzed using Landsat TM(30 m)and Pleiades-1A(2 m)imageries from 1988 to 2018.Point-specific SOC measurement was done using samples taken from four core-depth intervals(viz.D1:0–20 cm,D2:20–40 cm,D3:40–70 cm,D4:70–100 cm)at 89 locations belonging to different LULC categories.Spatial interpolation was applied on this point-based data to produce SOC density and stock models as a whole and at all core-depths.Relationships between SOC density,core-depth and present LULC were evaluated through multivariate statistical analyses.Results:The LULC transformations during last three decades suggested the gradual growth of mangrove plantations as well as agricultural and aquacultural activities.Most amount of SOC was concentrated in D1(37.17%)followed by D3(26.51%),while D4 had the lowest(10.87%).The highest mean SOC density was observed in the dense mangrove patches(248.92 Mg ha^(−1))and the lowest mean was in the Casuarina plantations(2.78 Mg ha^(−1)).Here,Spline method emerged as the best-fit interpolation technique to model SOC data(R^(2)=0.74)and estimated total SOC stock of the entire wetland influence zone as 169,569.40 Mg and the grand mean as 125.56 Mg ha^(−1).Overall,LULC was inferred as a major determinant of SOC dynamics with a statistically significant effect(p<0.001),whereas no such inference could be drawn for soil core-depth.Conclusions:The C sequestration potential of sites such as the present one could be increased with appropriate zone-wise plantation strategies,restriction on the land conversion to aquaculture and pr

关键词： Blue C density Core-depth Coastal wetland Dry combustion Land use conversion Wetland influence zone

Contribution of biophysical and climate variables to the spatial distribution of wildfires in Iran

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林业研究:英文版 2023年第6期34卷 1763-1775页

作者： Kobra Shojaeizadeh Mahmoud Ahmadi Abbasali Dadashi-Roudbari department of Physical geography Faculty of Earth SciencesShahid Beheshti UniversityTehranIran department of geography Ferdowsi University of MashhadMashhadIran

This study investigated the relationship between climate and biophysical variables in burned areas in Iran.The fire burned area(FBA)product(Fire CCI 5.1.1),land surface temperature(MOD11C3C),vegetation index(MOD13A1),and climate variables such as temperature,wind speed,relative humidity,and volumetric soil moisture from the ERA5 reanalysis dataset were used.Pearson correlation coefficient was used to determine the relationship between biophysical and climate variables and fire occurrence.The results show that FBA increased by 1.7 hectares/decade from 2001 to 2020.The high FBA in 2010(the black summer of Iran)was due to high temperatures and significant heatwaves that led to extensive wildfires.Although anthropogenic activities are considered a significant cause of wildfires,several variables,including increased temperatures,less precipitation,relative humidity,and wind speed and direction,contribute to the extent and occurrence of wildfires.The country’s FBA hotspot is in the Arasbaran region during the summer season.Temperature and relative humidity are the most significant variables influencing the occurrence of wildfires.The results show the vulnerability of Iran s forests and their high potential for fires.Considering the frequency of fire occurrences in Iran and the limited equipment,fire prevention plans should be carried out by applying proper management in high-risk regions.

关键词： Wildfire Burned areas Vegetation index(Ⅵ) Air temperature Iran

Seeing through a new lens: exploring the potential of city walking tour videos for urban analytics

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International Journal of Digital Earth 2023年第1期16卷 2555-2573页

作者： Maximilian C.Hartmann Ross S.Purves department of geography University of ZurichZurichSwitzerland

City Walking Tour Videos(CWTVs)are a novel source of Volunteered Geographic Information providing street-level imagery through video sharing platforms such as YouTube.We demonstrate that these videos contain rich information for urban analytical applications,by conducting a mobility study.We detect transport modes with a focus on active(pedestrians and cyclists)and motorised mobility(cars,motorcyclists and trucks).We chose the City of Paris as our area of interest given the rapid expansion of the bicycle network as a response to the Covid-19 pandemic and compiled a video corpus encompassing more than 66 hours of video footage.Through the detection of street names in the video and placename containing timestamps we extracted and georeferenced 1169 locations at which we summarise the detected transport modes.Our results show high potential of CWTVs for studying urban mobility applications.We detected significant shifts in the mobility mix before and during the pandemic as well as weather effects on the volumes of pedestrians and cyclists.Combined with the observed increase in data availability over the years we suggest that CWTVs have considerable potential for other applications in the field of urban analytics.

关键词： Street-level imagery city walking tour videos transport modes mobility object detection geolocation

Evaluation of hydro-chemistry in a phreatic aquifer in the Vindhyan Region, India, using entropy weighted approach and geochemical modelling

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Acta Geochimica 2023年第4期42卷 648-672页

作者： Ashutosh Mishra Aman Rai Prabuddh Kumar Mishra Suresh Chand Rai department of geography Delhi School of EconomicsUniversity of DelhiDelhi 110027India department of geography Shivaji CollegeUniversity of DelhiDelhi 110027India

Groundwater quality monitoring and geochemical characterization in the phreatic aquifer are critical for ensuring universal and equitable access to clean,reliable,and inexpensive drinking water for all.This research was intended to investigate the hydrogeochemical attributes and mechanisms regulating the chemistry of groundwater as well as to assess spatial variation in groundwater quality in Satna district,India.To accomplish this,the groundwater data comprising 13 physio-chemical parameters from thirty-eight phreatic aquifer locations were analysed for May 2020 by combining entropy-weighted water quality index(EWQI),multivariate statistics,geochemical modelling,and geographical information system.The findings revealed that the groundwater is fresh and slightly alkaline.Hardness was a significant concern as 57.89% of samples were beyond the permissible limit of the World Health Organisation.The dominance of ions were in the order of Ca^(2+)> Na^(+)> Mg^(2+)> K^(+) and HCO_(3)^(-)> SO_(4)^(2-)> Cl^-> NO_(3)^(-)> F^(-).Higher concentration of these ions is mainly concentrated in the northeast and eastern regions.Pearson correlation analysis and principal component analysis(PCA) demonstrated that both natural and human factors regulate groundwater chemistry in the region.The analysis of Q-mode agglomerative hierarchical clustering highlighted three significant water clusters.Ca-HCO_3 was the most prevalent hydro-chemical facies in all three clusters.Geochemical modelling through various conventional plots indicated that groundwater chemistry in the research region is influenced by the dissolution of calcite/dolomite,reverse ion exchange,and by silicate and halite weathering.EWQI data of the study area disclosed that 73.69% of the samples were appropriate for drinking.Due to high salinity,Magnesium(Mg^(2+)),Nitrate(NO_(3)^(-)),and Bicarbonate(HCO_(3)^(-)) concentrations,the north-central and north-eastern regions are particularly susceptible.The findings of the study may be accomplished by policymakers and groundwat

关键词： Groundwater quality assessment EWQI Multivariate statistical analysis Geochemical modelling Hydrogeochemical processes Saturation index

Expert perspectives on GIS use in Spanish geographic education

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International Journal of Digital Earth 2022年第1期15卷 1204-1218页

作者： I.J.Buzo-Sánchez C.Mínguez M.L.De Lázaro-Torres IES San Roque BadajozSpain Geography Department Universidad Complutense de MadridMadridSpain Geography Department UNEDMadridSpain

The emergence of new technological tools for territorial analysis,such as cloud-based GIS,or GIS viewers,compels us to closely examine its usefulness in geographic education. Specifically,it raises the professors and teachers’ questions: what to teach? how to teach? and what will students learn? This research responds to these three questions by interviewing Spanish experts who know how to use these tools to teach geography at university and secondary school levels. The Delphi technique was applied to achieve this,which established consensus and led to the following results from experts’ own experience: (1) that GIS help to understand territory in an experiential and non-memoristic way and (2) they enable the development of spatial thinking. This paper concludes that changes in methodologies and integrate technical knowledge into teacher training are needed.

关键词： geography Delphi GIS competencies spatial thinking

Comparing the terrain reversal effect in satellite images and in shaded relief maps:an examination of the effects of color and texture on 3D shape perception from shading

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International Journal of Digital Earth 2019年第4期12卷 442-459页

作者： Arzu Çöltekin Julien Biland department of geography University of ZurichZurichSwitzerland department of geography University of BernBernSwitzerland

Terrain reversal effect(TRE)causes reversed 3D shape perception in satellite images and shaded relief maps(SRMs),and introduces difficulties in identifying landforms such as valleys and ridges.With this paper,in a controlled laboratory experiment,we compare how well 27 participants could identify valleys and ridges over 33 locations using SRMs,color satellite images and grayscale satellite images.The main depth cue is shadow both in vertical-view images and SRMs.However,the presence of texture and color in images also affect 3D shape perception.All our participants experience the illusion strongly:with the SRMs,it is very severe(2%accuracy),with grayscale images low but considerably better than SRMs(17.6%accuracy),and slightly worse with color imagery(15.3%accuracy).These differences between SRMs and imagery suggest that the participants who are able to bypass the illusion consciously or subconsciously interpret the photographic information.We support this observation further with a cue-strength analysis.Furthermore,we provide exploratory analyses of the effects of expertise,global convexity bias,and bistable perception.Our original empirical observations serve towards a better understanding of this visual illusion,and contribute towards nuanced and appropriate solutions to correcting for TRE differently for satellite images and SRMs.

关键词： Terrain reversal relief inversion false topographic perception phenomenon photo interpretation visual illusion user study bistable perception global convexity bias

Local tips, global impact: community-driven measures as avenues of promoting inclusion in the control of neglected tropical diseases: a case study in Kenya

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Infectious Diseases of Poverty 2022年第4期11卷 81-90页

作者： Elizabeth A.Ochola Diana M.S.Karanja Susan J.Elliott department of geography and Environmental Management University ofWaterlooWaterlooONCanada

Background:Neglected tropical diseases(NTDs)affect poor populations with little or no’’political voice’to influence control activities.While most NTDs have interventions that work,the biggest challenge remains in delivering targeted interventions to affected populations residing in areas experiencing weak health systems.Despite the upward development trends in most countries of sub-Saharan Africa(SSA),the healthcare worker to population ratio remains exceptionally low,with some areas not served at all;thus,there is a need to involve other personnel for school and community-based healthcare approaches.Nonetheless,the current community-based programs suffer from inconsistent community participation due to a lack of coordinated response,and an expanded intervention agenda that lacks context-specific solutions applicable to rural,urban,and marginalized areas.Methods:This research investigated the capacity of local communities to address the burden of NTDs.Informed by the social theory of human capability,the research collected primary qualitative data by conducting key informant interviews and focus group discussions of people infected or affected by NTDs.The interview data were collected and transcribed verbatim for thematic analysis using Nvivo version 12.Results:Our findings reveal,first,a need for intersectoral collaboration between governments and affected populations for inclusive and sustainable NTD solutions.Second,a’’bottom-up’approach that enhances capacity building,sensitization,and behaviour change for improved uptake of NTD interventions.Third,the enforcement of Public Health Legislative Acts that mandates the reporting and treatment of NTDs such as leprosy.Fourth,the establishment of support groups and counseling services to assist persons suffering from debilitating and permanent effects of NTDs.Conclusions:Our research demonstrates the importance of human agency in encouraging new forms of participation leading to the co-production of inclusive and sustainable solutions against NTDs.

关键词： Neglected tropical diseases Control Community-driven measure Local solution Global impact Inclusion Kenya