Pub Date : 2024-02-08DOI: 10.1080/07038992.2023.2298575
Ziyi Gong, Hongchang He, Donglin Fan, You Zeng, Zhenhao Liu, Bozhi Pan
In this paper, the central Indian Ocean (60°–95°E, 0°–37°S) has been selected as the research area, and Argo salinity data are used as the measured values. The Catboost algorithm is introduced for ...
{"title":"Comparison of Machine Learning Inversion Methods for Salinity in the Central Indian Ocean Based on SMOS Satellite Data","authors":"Ziyi Gong, Hongchang He, Donglin Fan, You Zeng, Zhenhao Liu, Bozhi Pan","doi":"10.1080/07038992.2023.2298575","DOIUrl":"https://doi.org/10.1080/07038992.2023.2298575","url":null,"abstract":"In this paper, the central Indian Ocean (60°–95°E, 0°–37°S) has been selected as the research area, and Argo salinity data are used as the measured values. The Catboost algorithm is introduced for ...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139761652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-18DOI: 10.1080/07038992.2023.2295470
Matthew Guenther, Muditha K. Heenkenda, Brigitte Leblon, Dave Morris, Jason Freeburn
Traditional Diameter at Breast Height (DBH) mensuration is labor-intensive and costly. This scoping study explored the possibility of using the Apple iPad Pro Light Detection And Ranging (LiDAR) se...
传统的胸径（DBH）测量既耗费人力，又成本高昂。这项范围界定研究探讨了使用 Apple iPad Pro 的光探测和测距 (LiDAR) 接收器的可能性。
{"title":"Estimating Tree Diameter at Breast Height (DBH) Using iPad Pro LiDAR Sensor in Boreal Forests","authors":"Matthew Guenther, Muditha K. Heenkenda, Brigitte Leblon, Dave Morris, Jason Freeburn","doi":"10.1080/07038992.2023.2295470","DOIUrl":"https://doi.org/10.1080/07038992.2023.2295470","url":null,"abstract":"Traditional Diameter at Breast Height (DBH) mensuration is labor-intensive and costly. This scoping study explored the possibility of using the Apple iPad Pro Light Detection And Ranging (LiDAR) se...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139495761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-16DOI: 10.1080/07038992.2023.2300328
Kent Jones, Derek D. Lichti, Robert Radovanovic
Accurate three-dimensional mapping and digital twinning provides a powerful tool for effective maintenance of civil infrastructure and supports efficient future planning of new developments. Three-...
{"title":"Synthetic Images for Georeferencing Camera Images in Mobile Mapping Point-clouds","authors":"Kent Jones, Derek D. Lichti, Robert Radovanovic","doi":"10.1080/07038992.2023.2300328","DOIUrl":"https://doi.org/10.1080/07038992.2023.2300328","url":null,"abstract":"Accurate three-dimensional mapping and digital twinning provides a powerful tool for effective maintenance of civil infrastructure and supports efficient future planning of new developments. Three-...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139495758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-16DOI: 10.1080/07038992.2023.2298806
Xueyan Dong, Jiannong Cao, Weiheng Zhao
Deep-learning-based methods for building-edge-detection have been widely researched and applied in the field of image processing. However, these methods often emphasis the analysis of deep features...
{"title":"Dense Connected Edge Feature Enhancement Network for Building Edge Detection from High Resolution Remote Sensing Imagery","authors":"Xueyan Dong, Jiannong Cao, Weiheng Zhao","doi":"10.1080/07038992.2023.2298806","DOIUrl":"https://doi.org/10.1080/07038992.2023.2298806","url":null,"abstract":"Deep-learning-based methods for building-edge-detection have been widely researched and applied in the field of image processing. However, these methods often emphasis the analysis of deep features...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139495730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wetlands are considered one of the most valuable ecosystems around the world and provide numerous environmental services, including water purification, flood protection, and habitat for a variety o...
湿地被认为是全世界最宝贵的生态系统之一，可提供多种环境服务，包括水净化、防洪以及各种生物的栖息地。
{"title":"Comprehensive Landsat-Based Analysis of Long-Term Surface Water Dynamics over Wetlands and Waterbodies in North America","authors":"Mohammadali Hemati, Masoud Mahdianpari, Hodjat Shiri, Fariba Mohammadimanesh","doi":"10.1080/07038992.2023.2293058","DOIUrl":"https://doi.org/10.1080/07038992.2023.2293058","url":null,"abstract":"Wetlands are considered one of the most valuable ecosystems around the world and provide numerous environmental services, including water purification, flood protection, and habitat for a variety o...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138823790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-07DOI: 10.1080/07038992.2023.2289022
Kaushik Gupta, Jens K. Ehn
Numerous studies have been conducted to enhance our understanding of how climate change impacts landfast ice and its break-up in spring or summer. Yet, predictions of break-up timing have proven el...
{"title":"Terrestrial Snowmelt as a Precursor to Landfast Sea Ice Break-up in Hudson Bay and James Bay","authors":"Kaushik Gupta, Jens K. Ehn","doi":"10.1080/07038992.2023.2289022","DOIUrl":"https://doi.org/10.1080/07038992.2023.2289022","url":null,"abstract":"Numerous studies have been conducted to enhance our understanding of how climate change impacts landfast ice and its break-up in spring or summer. Yet, predictions of break-up timing have proven el...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138556673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.1080/07038992.2023.2285778
Hamdy Elsayed, Ahmed Shaker
This paper discusses a comprehensive methodology for transforming a static LiDAR (Light Detection and Ranging) system into a mobile mapping system. The initial step involves integrating various sen...
{"title":"From Stationary to Mobile: Unleashing the Full Potential of Terrestrial LiDAR through Sensor Integration","authors":"Hamdy Elsayed, Ahmed Shaker","doi":"10.1080/07038992.2023.2285778","DOIUrl":"https://doi.org/10.1080/07038992.2023.2285778","url":null,"abstract":"This paper discusses a comprehensive methodology for transforming a static LiDAR (Light Detection and Ranging) system into a mobile mapping system. The initial step involves integrating various sen...","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138530599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sea ice mapping using Synthetic Aperture Radar (SAR) in the melt season poses challenges, due to wet snow and melt ponds complicating sea ice type separability. To address this, we analyzed fully polarimetric (FP) and simulated compact polarimetric (CP) C- (RADARSAT-2) and L- (ALOS-2 PALSAR-2) band SAR, in the 2018 melt season in the Canadian Arctic Archipelago, for stage-wise separation of first year ice (FYI) and multiyear ice (MYI). SAR scenes at both near- (19.1–28.3°) and far- (35.8–42.1°) range incidence angles and coincident high-resolution optical scenes were used to assess the impact of surface melt ponds on separability within a landfast ice zone of diverse ice thickness. C-band provided better separability between FYI and MYI during pond onset, while L-band was superior during pond drainage due to MYI volumetric scattering. CP parameters matched FP performance across the melt season. HH and HV, commonly offered in ScanSAR mode for both frequencies, presented good separability during pond onset and drainage. Using both C-band and L-band SAR along with constraining incidence angle ranges, enhances sea ice type identification and separability. Our results can support ice type classification and seasonal stage detection for climate studies and enhance existing frameworks for ice motion vector retrievals.
{"title":"Melt Season Arctic Sea Ice Type Separability Using Fully and Compact Polarimetric C- and L-Band Synthetic Aperture Radar","authors":"Aikaterini Tavri, Randall Scharien, Torsten Geldsetzer","doi":"10.1080/07038992.2023.2271578","DOIUrl":"https://doi.org/10.1080/07038992.2023.2271578","url":null,"abstract":"Sea ice mapping using Synthetic Aperture Radar (SAR) in the melt season poses challenges, due to wet snow and melt ponds complicating sea ice type separability. To address this, we analyzed fully polarimetric (FP) and simulated compact polarimetric (CP) C- (RADARSAT-2) and L- (ALOS-2 PALSAR-2) band SAR, in the 2018 melt season in the Canadian Arctic Archipelago, for stage-wise separation of first year ice (FYI) and multiyear ice (MYI). SAR scenes at both near- (19.1–28.3°) and far- (35.8–42.1°) range incidence angles and coincident high-resolution optical scenes were used to assess the impact of surface melt ponds on separability within a landfast ice zone of diverse ice thickness. C-band provided better separability between FYI and MYI during pond onset, while L-band was superior during pond drainage due to MYI volumetric scattering. CP parameters matched FP performance across the melt season. HH and HV, commonly offered in ScanSAR mode for both frequencies, presented good separability during pond onset and drainage. Using both C-band and L-band SAR along with constraining incidence angle ranges, enhances sea ice type identification and separability. Our results can support ice type classification and seasonal stage detection for climate studies and enhance existing frameworks for ice motion vector retrievals.","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135813178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.1080/07038992.2023.2259504
Clovis Cechim Junior, Hideo Araki, Rodrigo de Campos Macedo
The purpose of this research was to distinguish and estimate natural forest areas at Paraná, Brazil. Forest plantations (Silviculture) and natural forests have high annual vegetative vigor, as well as agricultural areas in the periods of agricultural harvests, which can bring classification errors between these classes of Land Use and Land Cover (LULC), these classes have similar spectral signatures, but have a distinct texture that can be separated in the supervised classification process, with the joining of object and pixel-to-pixel classification method approaches. Thus, image segmentation techniques through Object-Based Image Analysis (OBIA) and Machine Learning (ML) made forest mapping possible over a large territorial extension. The Google Earth Engine (GEE) platform was used to calculate the vegetation indices (VIs) and Spectral Mixture Analysis (SMA) fraction spectral from Sentinel-2 images, and the creation of homogeneous spectrally shaped regions under supervised classification of phytoecological regions and mesoregions. The overall precision obtained in the mappings resulted in 0.94 Kappa Index (KI) and 96% of Overall Accuracy (OA), which indicates a high performance in large-scale forest mapping. The proposed dataset, source codes and trained models are available on Github (https://github.com/Cechim/simepar-brazil/), creating opportunities for further ad vances in the field.
{"title":"Object-Based Image Analysis (OBIA) and Machine Learning (ML) Applied to Tropical Forest Mapping Using Sentinel-2","authors":"Clovis Cechim Junior, Hideo Araki, Rodrigo de Campos Macedo","doi":"10.1080/07038992.2023.2259504","DOIUrl":"https://doi.org/10.1080/07038992.2023.2259504","url":null,"abstract":"The purpose of this research was to distinguish and estimate natural forest areas at Paraná, Brazil. Forest plantations (Silviculture) and natural forests have high annual vegetative vigor, as well as agricultural areas in the periods of agricultural harvests, which can bring classification errors between these classes of Land Use and Land Cover (LULC), these classes have similar spectral signatures, but have a distinct texture that can be separated in the supervised classification process, with the joining of object and pixel-to-pixel classification method approaches. Thus, image segmentation techniques through Object-Based Image Analysis (OBIA) and Machine Learning (ML) made forest mapping possible over a large territorial extension. The Google Earth Engine (GEE) platform was used to calculate the vegetation indices (VIs) and Spectral Mixture Analysis (SMA) fraction spectral from Sentinel-2 images, and the creation of homogeneous spectrally shaped regions under supervised classification of phytoecological regions and mesoregions. The overall precision obtained in the mappings resulted in 0.94 Kappa Index (KI) and 96% of Overall Accuracy (OA), which indicates a high performance in large-scale forest mapping. The proposed dataset, source codes and trained models are available on Github (https://github.com/Cechim/simepar-brazil/), creating opportunities for further ad vances in the field.","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135081525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.1080/07038992.2023.2259505
Karima Mazirh, Said El Goumi, Mounsif Ibnoussina, Omar Witam, Mohamed Nocairi, Rachida Kasimi, Salah Er-Raki
Climate change and rapid urbanization have significant impact on green spaces and natural resources in African countries. To investigate this impact in the city of Marrakech, this study develops remote-sensing data to monitor changes in land cover and land use from 1990 to 2020. Results show almost 35% diminution of vegetation cover over the investigation period. In 1990, the city of Marrakech had a vegetation cover of 4.2 km2, which fell to 2.7 km2 in 2020. The main change occurred between 1990 and 2000 with a decrease of 13.7%, which is essentially due to the increase in build-up areas, related to the rapid growth of the city’s population. This evolution in land cover affects the urban environment negatively including air quality and temperature regulation. This research provides a better understanding of changing trends, confirms the importance of using satellite imagery to monitor vegetation cover in urban settings, helps determine efficient environmental management, and affects successful green infrastructure policy and planning, thereby allowing for improved adaptation and mitigation to climate change.
{"title":"Using Remote Sensing to Address Green Heritage of the City of Marrakech, Morocco","authors":"Karima Mazirh, Said El Goumi, Mounsif Ibnoussina, Omar Witam, Mohamed Nocairi, Rachida Kasimi, Salah Er-Raki","doi":"10.1080/07038992.2023.2259505","DOIUrl":"https://doi.org/10.1080/07038992.2023.2259505","url":null,"abstract":"Climate change and rapid urbanization have significant impact on green spaces and natural resources in African countries. To investigate this impact in the city of Marrakech, this study develops remote-sensing data to monitor changes in land cover and land use from 1990 to 2020. Results show almost 35% diminution of vegetation cover over the investigation period. In 1990, the city of Marrakech had a vegetation cover of 4.2 km2, which fell to 2.7 km2 in 2020. The main change occurred between 1990 and 2000 with a decrease of 13.7%, which is essentially due to the increase in build-up areas, related to the rapid growth of the city’s population. This evolution in land cover affects the urban environment negatively including air quality and temperature regulation. This research provides a better understanding of changing trends, confirms the importance of using satellite imagery to monitor vegetation cover in urban settings, helps determine efficient environmental management, and affects successful green infrastructure policy and planning, thereby allowing for improved adaptation and mitigation to climate change.","PeriodicalId":48843,"journal":{"name":"Canadian Journal of Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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