Pub Date : 2020-06-01DOI: 10.1139/geomat-2019-0022
R. Ahola, R. Chénier, Mesha Sagram, Bradley Horner
Canada’s coastline presents challenges for charting. Within Arctic regions, in situ surveying presents risks to surveyors, is time consuming and costly. To better meet its mandate, the Canadian Hydrographic Service (CHS) has been investigating the potential of remote sensing to complement traditional charting techniques. Much of this work has focused on evaluating the effectiveness of empirical satellite derived bathymetry (SDB) techniques within the Canadian context. With greater knowledge of applying SDB techniques within Canadian waters, CHS is now interested in understanding how characteristics of optical sensors can impact SDB results. For example, how does the availability of different optical bands improve or hinder SDB estimates? What is the impact of spatial resolution on SDB accuracy? Do commercial satellites offer advantages over freely available data? Through application of a multiple band modelling technique to WorldView-2, Pléiades, PlanetScope, SPOT, Sentinel-2, and Landsat-8 imagery obtained over Cambridge Bay, Nunavut, this paper provides insight into these questions via comparisons with in situ survey data. Result highlights in the context of these questions include the following: Similarities between sensors: Overall linear error at 90% (LE90) results for each sensor ranged from 0.88 to 1.91 m relative to in situ depths, indicating consistency in the accuracy of SDB estimates from the examined satellites. Most estimates achieved Category of Zone of Confidence level C accuracy, the suggested minimum survey accuracy level for incorporating SDB information into navigational charts. SDB coverage: Between sensors, differences in the area of the sea floor that could be measured by SDB were apparent, as were differences in the ability of each sensor to properly represent spatial bathymetry characteristics. Sensor importance: Though relationships between SDB accuracy and sensor resolution were found, significant advantages or disadvantages for particular sensors were not identified, suggesting that other factors may play a more important role for SDB image selection (e.g., sea floor visibility, sediments, waves). Findings from this work will help inform SBD planning activities for hydrographic offices and SDB researchers alike.
{"title":"The impact of sensors for satellite derived bathymetry within the Canadian Arctic","authors":"R. Ahola, R. Chénier, Mesha Sagram, Bradley Horner","doi":"10.1139/geomat-2019-0022","DOIUrl":"https://doi.org/10.1139/geomat-2019-0022","url":null,"abstract":"Canada’s coastline presents challenges for charting. Within Arctic regions, in situ surveying presents risks to surveyors, is time consuming and costly. To better meet its mandate, the Canadian Hydrographic Service (CHS) has been investigating the potential of remote sensing to complement traditional charting techniques. Much of this work has focused on evaluating the effectiveness of empirical satellite derived bathymetry (SDB) techniques within the Canadian context. With greater knowledge of applying SDB techniques within Canadian waters, CHS is now interested in understanding how characteristics of optical sensors can impact SDB results. For example, how does the availability of different optical bands improve or hinder SDB estimates? What is the impact of spatial resolution on SDB accuracy? Do commercial satellites offer advantages over freely available data? Through application of a multiple band modelling technique to WorldView-2, Pléiades, PlanetScope, SPOT, Sentinel-2, and Landsat-8 imagery obtained over Cambridge Bay, Nunavut, this paper provides insight into these questions via comparisons with in situ survey data. Result highlights in the context of these questions include the following: Similarities between sensors: Overall linear error at 90% (LE90) results for each sensor ranged from 0.88 to 1.91 m relative to in situ depths, indicating consistency in the accuracy of SDB estimates from the examined satellites. Most estimates achieved Category of Zone of Confidence level C accuracy, the suggested minimum survey accuracy level for incorporating SDB information into navigational charts. SDB coverage: Between sensors, differences in the area of the sea floor that could be measured by SDB were apparent, as were differences in the ability of each sensor to properly represent spatial bathymetry characteristics. Sensor importance: Though relationships between SDB accuracy and sensor resolution were found, significant advantages or disadvantages for particular sensors were not identified, suggesting that other factors may play a more important role for SDB image selection (e.g., sea floor visibility, sediments, waves). Findings from this work will help inform SBD planning activities for hydrographic offices and SDB researchers alike.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2019-0022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46935943","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}
Pub Date : 2019-12-18DOI: 10.1139/geomat-2019-0021
Caroline Erickson, G. Banham, R. Berg, Joey Chessie, M. Craymer, B. Donahue, Renée Tardif, Y. Thériault, M. Véronneau
In 2022, the U.S., as part of its reference system modernization, will replace its North American Datum of 1983 (NAD83) with a new North American Terrestrial Reference Frame (NATRF2022), creating 1.3 to 1.5 m horizontal coordinate differences at the Canada–U.S. border with respect to Canada’s NAD83(CSRS). Never before have such significant differences existed between our two countries’ reference frames. This paper reviews why the U.S. is making this change and then looks at Canada’s situation with respect to reference frames. There are compelling reasons for Canada to follow suit and move to NATRF2022 within a decade, but there are also major challenges. Whether or not Canada follows the same path, there is much work to be done to prepare Canada for the U.S.’ move to NATRF2022. This paper is intended as a first step to inform the Canadian geospatial community of the U.S.’ move to NATRF2022 and what it means for Canada.
{"title":"The U.S. is replacing NAD83 with NATRF2022: what this means for Canada","authors":"Caroline Erickson, G. Banham, R. Berg, Joey Chessie, M. Craymer, B. Donahue, Renée Tardif, Y. Thériault, M. Véronneau","doi":"10.1139/geomat-2019-0021","DOIUrl":"https://doi.org/10.1139/geomat-2019-0021","url":null,"abstract":"In 2022, the U.S., as part of its reference system modernization, will replace its North American Datum of 1983 (NAD83) with a new North American Terrestrial Reference Frame (NATRF2022), creating 1.3 to 1.5 m horizontal coordinate differences at the Canada–U.S. border with respect to Canada’s NAD83(CSRS). Never before have such significant differences existed between our two countries’ reference frames. This paper reviews why the U.S. is making this change and then looks at Canada’s situation with respect to reference frames. There are compelling reasons for Canada to follow suit and move to NATRF2022 within a decade, but there are also major challenges. Whether or not Canada follows the same path, there is much work to be done to prepare Canada for the U.S.’ move to NATRF2022. This paper is intended as a first step to inform the Canadian geospatial community of the U.S.’ move to NATRF2022 and what it means for Canada.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2019-0021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45050375","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}
Pub Date : 2019-12-01DOI: 10.1139/geomat-2019-0014
C. Minielly, O. Adebooye, P. Akponikpè, D. Oyedele, D. Boer, Yanping Li, D. Peak
Climate change and food security are complex global issues that require multidisciplinary approaches to resolve. A nexus exists between both issues, especially in developing countries, but little prior research has successfully bridged the divide. Existing resolutions to climate change and food security are expensive and resource demanding. Climate modelling is at the forefront of climate change literature and development planning, whereas agronomy research is leading food security plans. The Benin Republic and Nigeria have grown and developed in recent years but may not have all the tools required to implement and sustain long-term food security in the face of climate change. The objective of this paper is to describe the development and outputs of a new model that bridges climate change and food security. Data from the Intergovernmental Panel on Climate Change’s 5th Regional Assessment (IPCC AR5) were combined with a biodiversity database to develop the model to derive these outputs. The model was used to demonstrate what potential impacts climate change will have on the regional food security by incorporating agronomic data from four local underutilized indigenous vegetables (Amaranthus cruentus L., Solanum macrocarpon L., Telfairia occidentalis Hook f., and Ocimum gratissimum L.). The model shows that, by 2099, there is significant uncertainty within the optimal recommendations that originated from the MicroVeg project. This suggests that MicroVeg will not have long-term success for food security unless additional options (e.g., new field trials, shifts in vegetable grown) are considered, creating the need for need for more dissemination tools.
{"title":"Application of a 1 km2 resolution model for climate change effects upon Benin and Nigeria vegetable agriculture","authors":"C. Minielly, O. Adebooye, P. Akponikpè, D. Oyedele, D. Boer, Yanping Li, D. Peak","doi":"10.1139/geomat-2019-0014","DOIUrl":"https://doi.org/10.1139/geomat-2019-0014","url":null,"abstract":"Climate change and food security are complex global issues that require multidisciplinary approaches to resolve. A nexus exists between both issues, especially in developing countries, but little prior research has successfully bridged the divide. Existing resolutions to climate change and food security are expensive and resource demanding. Climate modelling is at the forefront of climate change literature and development planning, whereas agronomy research is leading food security plans. The Benin Republic and Nigeria have grown and developed in recent years but may not have all the tools required to implement and sustain long-term food security in the face of climate change. The objective of this paper is to describe the development and outputs of a new model that bridges climate change and food security. Data from the Intergovernmental Panel on Climate Change’s 5th Regional Assessment (IPCC AR5) were combined with a biodiversity database to develop the model to derive these outputs. The model was used to demonstrate what potential impacts climate change will have on the regional food security by incorporating agronomic data from four local underutilized indigenous vegetables (Amaranthus cruentus L., Solanum macrocarpon L., Telfairia occidentalis Hook f., and Ocimum gratissimum L.). The model shows that, by 2099, there is significant uncertainty within the optimal recommendations that originated from the MicroVeg project. This suggests that MicroVeg will not have long-term success for food security unless additional options (e.g., new field trials, shifts in vegetable grown) are considered, creating the need for need for more dissemination tools.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2019-0014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47839082","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}
Pub Date : 2019-11-13DOI: 10.1139/geomat-2020-0005
Matthieu Viry, Marlène Villanova-Oliver
Lorsqu’une intervention de secours est nécessaire, localiser précisément et rapidement le site sur lequel envoyer les équipes est primordial. La littérature montre que des outils de géovisualisation constituent des solutions pertinentes pour supporter des processus d’analyse d’informations dans des contextes variés. Nous nous intéressons ici au raisonnement du secouriste réceptionnant un appel à l’aide et visons des solutions conceptuelles et logicielles dédiées à la tâche de détermination de la localisation de la victime, plus particulièrement dans le contexte du secours en montagne. Nous avons formalisé le raisonnement du secouriste et les informations sur lesquelles il ou elle s’appuie à l’aide d’une ontologie. L’Ontologie d’Alerte Choucas structure les concepts exploités par le secouriste qui élabore des hypothèses de localisation probable de la victime à partir d’informations (telles qu’une position relative, un temps de marche, une direction) fournies lors d’un échange verbal. Dans notre approche, l’ontologie est en outre exploitée pour dériver les composants d’interface d’un prototype de géovisualisation facilitant le raisonnement du secouriste. Ces composants sont une aide à la saisie des informations, en fournissant une restitution cartographique adaptée, et contribuent à construire et à affiner la zone de localisation. Notre approche présente une chaine de traitements originale, menant de la représentation des connaissances à la génération automatisée d’une interface fonctionnelle d’aide au raisonnement visant à localiser des victimes en montagne.
{"title":"Ontologie d’Alerte Choucas : de la modélisation des connaissances à un outil support d’un raisonnement géovisuel","authors":"Matthieu Viry, Marlène Villanova-Oliver","doi":"10.1139/geomat-2020-0005","DOIUrl":"https://doi.org/10.1139/geomat-2020-0005","url":null,"abstract":"Lorsqu’une intervention de secours est nécessaire, localiser précisément et rapidement le site sur lequel envoyer les équipes est primordial. La littérature montre que des outils de géovisualisation constituent des solutions pertinentes pour supporter des processus d’analyse d’informations dans des contextes variés. Nous nous intéressons ici au raisonnement du secouriste réceptionnant un appel à l’aide et visons des solutions conceptuelles et logicielles dédiées à la tâche de détermination de la localisation de la victime, plus particulièrement dans le contexte du secours en montagne. Nous avons formalisé le raisonnement du secouriste et les informations sur lesquelles il ou elle s’appuie à l’aide d’une ontologie. L’Ontologie d’Alerte Choucas structure les concepts exploités par le secouriste qui élabore des hypothèses de localisation probable de la victime à partir d’informations (telles qu’une position relative, un temps de marche, une direction) fournies lors d’un échange verbal. Dans notre approche, l’ontologie est en outre exploitée pour dériver les composants d’interface d’un prototype de géovisualisation facilitant le raisonnement du secouriste. Ces composants sont une aide à la saisie des informations, en fournissant une restitution cartographique adaptée, et contribuent à construire et à affiner la zone de localisation. Notre approche présente une chaine de traitements originale, menant de la représentation des connaissances à la génération automatisée d’une interface fonctionnelle d’aide au raisonnement visant à localiser des victimes en montagne.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47039660","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}
Pub Date : 2019-11-13DOI: 10.1139/geomat-2020-0009
Safaâ Amarouch, Jean-Baptiste Durand, D. Josselin, Louisette Garcin, Nathalie Brachet, Frédéric Audard, Samuel Carpentier-Postel
Cet article réinvestit la modélisation des flux de déplacement domicile–travail au moyen des modèles gravitaires de flux. À partir d’une demande émanant de la région Provence-Alpes-Côte d’Azur, un modèle répondant au principe de parcimonie, basé sur des données publiques ouvertes et facilement mobilisables, a été établi afin de répondre au besoin de prévision tout en assurant la transparence et la réplicabilité de la démarche. À partir de ce modèle, différentes hypothèses (type de variable sur les masses des entités géographiques, variations des calculs des courtes distances à vol d’oiseau, contrainte de portée spatiale due au budget-temps de déplacement, ré-échantillonnage aléatoire) ont été modélisées dans une optique de prospective et d’aide à la décision. Les résultats montrent qu’il est possible d’obtenir un modèle assez robuste avec les données disponibles de l’Institut national de la statistique et des études économiques (INSEE) et un modèle gravitaire log-linéaire, tout en réduisant sensiblement la taille de l’échantillon traité.
{"title":"Estimer des flux de navetteurs avec un modèle gravitaire : application géomatique en région Provence-Alpes-Côte d’Azur (France)1","authors":"Safaâ Amarouch, Jean-Baptiste Durand, D. Josselin, Louisette Garcin, Nathalie Brachet, Frédéric Audard, Samuel Carpentier-Postel","doi":"10.1139/geomat-2020-0009","DOIUrl":"https://doi.org/10.1139/geomat-2020-0009","url":null,"abstract":"Cet article réinvestit la modélisation des flux de déplacement domicile–travail au moyen des modèles gravitaires de flux. À partir d’une demande émanant de la région Provence-Alpes-Côte d’Azur, un modèle répondant au principe de parcimonie, basé sur des données publiques ouvertes et facilement mobilisables, a été établi afin de répondre au besoin de prévision tout en assurant la transparence et la réplicabilité de la démarche. À partir de ce modèle, différentes hypothèses (type de variable sur les masses des entités géographiques, variations des calculs des courtes distances à vol d’oiseau, contrainte de portée spatiale due au budget-temps de déplacement, ré-échantillonnage aléatoire) ont été modélisées dans une optique de prospective et d’aide à la décision. Les résultats montrent qu’il est possible d’obtenir un modèle assez robuste avec les données disponibles de l’Institut national de la statistique et des études économiques (INSEE) et un modèle gravitaire log-linéaire, tout en réduisant sensiblement la taille de l’échantillon traité.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42245204","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}
Pub Date : 2019-09-12DOI: 10.1139/geomat-2018-0019
D. Muthama, E. Tompkins, M. Barry
Two case narratives illustrate the difficulties in resolving historical land restitution in different contexts. Cases from Canada and Kenya illustrate how different land conflicts between Indigenous land rights and registered title may be addressed. In Canada, Williams Lake involved an Indigenous community with a long settlement history in the region with a claim going back to early European settlement. In Kenya, Waitiki Farm involved a post-colonial population established by local Indigenous and migrant groups. The Williams Lake decision resulted in a First Nations land claim being settled in the form of monetary compensation in a dedicated tribunal. The Waitiki Farm decision led to a negotiated settlement in which the owner was compensated financially, and the current residents who had occupied the land were awarded long-term leases. The two cases are illustrative of historical land restitution and identify enabling conditions for the effective functioning of land restitution mechanisms in different contexts.
{"title":"Conflict between Indigenous land claims and registered title: case studies from Canada and Kenya","authors":"D. Muthama, E. Tompkins, M. Barry","doi":"10.1139/geomat-2018-0019","DOIUrl":"https://doi.org/10.1139/geomat-2018-0019","url":null,"abstract":"Two case narratives illustrate the difficulties in resolving historical land restitution in different contexts. Cases from Canada and Kenya illustrate how different land conflicts between Indigenous land rights and registered title may be addressed. In Canada, Williams Lake involved an Indigenous community with a long settlement history in the region with a claim going back to early European settlement. In Kenya, Waitiki Farm involved a post-colonial population established by local Indigenous and migrant groups. The Williams Lake decision resulted in a First Nations land claim being settled in the form of monetary compensation in a dedicated tribunal. The Waitiki Farm decision led to a negotiated settlement in which the owner was compensated financially, and the current residents who had occupied the land were awarded long-term leases. The two cases are illustrative of historical land restitution and identify enabling conditions for the effective functioning of land restitution mechanisms in different contexts.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2018-0019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44477815","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}
Pub Date : 2019-09-01DOI: 10.1139/geomat-2018-0020
M. Mobasheri, M. Amani, Mahin Beikpour, S. Mahdavi
Soil moisture content (SMC) is a crucial component in various environmental studies. Although many models have been proposed for SMC estimation, developing new models for accurate estimation of SMC is still an interesting subject. This study aimed to develop new models for SMC estimation using the water absorption bands in the spectral signatures of three different soil types: loam, silty loam, and sandy loam. Based on the three absorption bands (i.e., 1400, 1900, and 2200 nm) and regression analyses, six approaches were considered. These scenarios were generally based on the reflectance value and its logarithm, as well as the difference between the wet and dry reflectance values for the absorption bands. Finally, 24 models were developed for SMC estimation from the three different soil types, as well as the entire soil samples. The most accurate SMC, as indicated by the lowest root mean squared error (RMSE) and the highest correlation coefficient (r), was obtained from the model developed using the logarithm of the average values reflectance in the three water absorption bands for sandy loam (RMSE = 0.31 g/kg, r = 0.99). Overall, using the spectrometry data derived in the lab, the results of the proposed models were promising and demonstrate great potential for SMC estimation using spectral data collected by satellites in the future studies.
{"title":"Soil moisture content estimation using water absorption bands","authors":"M. Mobasheri, M. Amani, Mahin Beikpour, S. Mahdavi","doi":"10.1139/geomat-2018-0020","DOIUrl":"https://doi.org/10.1139/geomat-2018-0020","url":null,"abstract":"Soil moisture content (SMC) is a crucial component in various environmental studies. Although many models have been proposed for SMC estimation, developing new models for accurate estimation of SMC is still an interesting subject. This study aimed to develop new models for SMC estimation using the water absorption bands in the spectral signatures of three different soil types: loam, silty loam, and sandy loam. Based on the three absorption bands (i.e., 1400, 1900, and 2200 nm) and regression analyses, six approaches were considered. These scenarios were generally based on the reflectance value and its logarithm, as well as the difference between the wet and dry reflectance values for the absorption bands. Finally, 24 models were developed for SMC estimation from the three different soil types, as well as the entire soil samples. The most accurate SMC, as indicated by the lowest root mean squared error (RMSE) and the highest correlation coefficient (r), was obtained from the model developed using the logarithm of the average values reflectance in the three water absorption bands for sandy loam (RMSE = 0.31 g/kg, r = 0.99). Overall, using the spectrometry data derived in the lab, the results of the proposed models were promising and demonstrate great potential for SMC estimation using spectral data collected by satellites in the future studies.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2018-0020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44372180","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}
Pub Date : 2019-06-01DOI: 10.1139/geomat-2019-0011
Jiaao Guo, Victoria Fast
The spatial distribution of population and related density characteristics has a significant impact on urban form; a low-density urban form is typically associated with low efficiency of service delivery, poor connectivity between communities, and a high tendency of urban sprawl, whereas higher density urban form is associated with transit-oriented development, efficient service delivery, and lower overall infrastructure costs. However, an urban area is never a homogenous environment. Depending on the general community designs, natural barriers, and massive functional infrastructures (airports, large parks), the urban population be may spread out evenly or condensed into some disjointed, isolated clusters. Given the context that Canadian cities have typically low population densities, their population distributions are subject to high spatial variabilities. We use geographic information system (GIS) techniques and geostatistical approaches (Getis–Ord [Formula: see text] hot spot analysis and HDBSCAN) to visualize and compare sub-municipal level population density of the 10 most populous census subdivisions (CSDs) in Canada. Results reveal both low-density forms and density segmentations in most municipalities, especially those without a natural or political border to constrain growth. Population segmentation is sometimes unsolvable due to natural landscapes or massive infrastructures initially planned by local municipalities; however, segmentations may be mitigated if future growth strategies maximize existing population clusters.
{"title":"Correction: Growing up, growing out: comparing spatial patterns of urban populations in Canada","authors":"Jiaao Guo, Victoria Fast","doi":"10.1139/geomat-2019-0011","DOIUrl":"https://doi.org/10.1139/geomat-2019-0011","url":null,"abstract":"The spatial distribution of population and related density characteristics has a significant impact on urban form; a low-density urban form is typically associated with low efficiency of service delivery, poor connectivity between communities, and a high tendency of urban sprawl, whereas higher density urban form is associated with transit-oriented development, efficient service delivery, and lower overall infrastructure costs. However, an urban area is never a homogenous environment. Depending on the general community designs, natural barriers, and massive functional infrastructures (airports, large parks), the urban population be may spread out evenly or condensed into some disjointed, isolated clusters. Given the context that Canadian cities have typically low population densities, their population distributions are subject to high spatial variabilities. We use geographic information system (GIS) techniques and geostatistical approaches (Getis–Ord [Formula: see text] hot spot analysis and HDBSCAN) to visualize and compare sub-municipal level population density of the 10 most populous census subdivisions (CSDs) in Canada. Results reveal both low-density forms and density segmentations in most municipalities, especially those without a natural or political border to constrain growth. Population segmentation is sometimes unsolvable due to natural landscapes or massive infrastructures initially planned by local municipalities; however, segmentations may be mitigated if future growth strategies maximize existing population clusters.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2019-0011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44555978","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}
Pub Date : 2019-06-01DOI: 10.1139/geomat-2019-0008
W. Jung, F. Naveed, Baoxin Hu, Jianguo Wang, Ning Li
With the advance of deep learning networks, their applications in the assessment of pavement conditions are gaining more attention. A convolutional neural network (CNN) is the most commonly used network in image classification. In terms of pavement assessment, most existing CNNs are designed to only distinguish between cracks and non-cracks. Few networks classify cracks in different levels of severity. Information on the severity of pavement cracks is critical for pavement repair services. In this study, the state-of-the-art CNN used in the detection of pavement cracks was improved to localize the cracks and identify their distress levels based on three categories (low, medium, and high). In addition, a fully convolutional network (FCN) was, for the first time, utilized in the detection of pavement cracks. These designed architectures were validated using the data acquired on four highways in Ontario, Canada, and compared with the ground truth that was provided by the Ministry of Transportation of Ontario (MTO). The results showed that with the improved CNN, the prediction precision on a series of test image patches were 72.9%, 73.9%, and 73.1% for cracks with the severity levels of low, medium, and high, respectively. The precision for the FCN was tested on whole pavement images, resulting in 62.8%, 63.3%, and 66.4%, respectively, for cracks with the severity levels of low, medium, and high. It is worth mentioning that the ground truth contained some uncertainties, which partially contributed to the relatively low precision.
{"title":"Exploitation of deep learning in the automatic detection of cracks on paved roads","authors":"W. Jung, F. Naveed, Baoxin Hu, Jianguo Wang, Ning Li","doi":"10.1139/geomat-2019-0008","DOIUrl":"https://doi.org/10.1139/geomat-2019-0008","url":null,"abstract":"With the advance of deep learning networks, their applications in the assessment of pavement conditions are gaining more attention. A convolutional neural network (CNN) is the most commonly used network in image classification. In terms of pavement assessment, most existing CNNs are designed to only distinguish between cracks and non-cracks. Few networks classify cracks in different levels of severity. Information on the severity of pavement cracks is critical for pavement repair services. In this study, the state-of-the-art CNN used in the detection of pavement cracks was improved to localize the cracks and identify their distress levels based on three categories (low, medium, and high). In addition, a fully convolutional network (FCN) was, for the first time, utilized in the detection of pavement cracks. These designed architectures were validated using the data acquired on four highways in Ontario, Canada, and compared with the ground truth that was provided by the Ministry of Transportation of Ontario (MTO). The results showed that with the improved CNN, the prediction precision on a series of test image patches were 72.9%, 73.9%, and 73.1% for cracks with the severity levels of low, medium, and high, respectively. The precision for the FCN was tested on whole pavement images, resulting in 62.8%, 63.3%, and 66.4%, respectively, for cracks with the severity levels of low, medium, and high. It is worth mentioning that the ground truth contained some uncertainties, which partially contributed to the relatively low precision.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/geomat-2019-0008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48744358","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}
Pub Date : 2019-03-01DOI: 10.1139/GEOMAT-2018-0021
Benoit Crépeau Gendron, Mohamed Ali Chouaer, R. Santerre, Mathieu Rondeau, N. Seube
One of the CIDCO’s (The Interdisciplinary Center for the Development of Ocean Mapping) HydroBall® GNSS buoys has been specifically adapted to evaluate its potential for wave measurement at centimeter accuracy level. Multiple GNSS processing strategies were tested, namely PPK (Post-Processed Kinematic), PPP (Precise Point Positioning), and TRP (Time Relative Positioning). Experiments were carried out in a hydraulic flume where waves of different amplitudes and periods were generated in a controlled environment. The wave heights obtained by the various GNSS solutions were compared with ultrasonic gauge measurements placed along the flume. The best results were obtained with the PPK and TRP solutions with root mean squared (RMS) values of 2 cm (on average). The main advantages of the TRP solution are that it does not require any reference station nearby (contrary to PPK) or precise ephemerides (required by PPP). A sinusoidal regression comparison of the wave height time series allowed determination of the wave period and amplitude with mean errors of 0.06 s and 0.8 cm, respectively.
{"title":"Wave measurements with a modified HydroBall® buoy using different GNSS processing strategies","authors":"Benoit Crépeau Gendron, Mohamed Ali Chouaer, R. Santerre, Mathieu Rondeau, N. Seube","doi":"10.1139/GEOMAT-2018-0021","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0021","url":null,"abstract":"One of the CIDCO’s (The Interdisciplinary Center for the Development of Ocean Mapping) HydroBall® GNSS buoys has been specifically adapted to evaluate its potential for wave measurement at centimeter accuracy level. Multiple GNSS processing strategies were tested, namely PPK (Post-Processed Kinematic), PPP (Precise Point Positioning), and TRP (Time Relative Positioning). Experiments were carried out in a hydraulic flume where waves of different amplitudes and periods were generated in a controlled environment. The wave heights obtained by the various GNSS solutions were compared with ultrasonic gauge measurements placed along the flume. The best results were obtained with the PPK and TRP solutions with root mean squared (RMS) values of 2 cm (on average). The main advantages of the TRP solution are that it does not require any reference station nearby (contrary to PPK) or precise ephemerides (required by PPP). A sinusoidal regression comparison of the wave height time series allowed determination of the wave period and amplitude with mean errors of 0.06 s and 0.8 cm, respectively.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42090620","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}
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