Pub Date : 2023-05-10DOI: 10.3389/frsen.2023.1204667
Guoxiong Zheng, Sher Muhammad, A. Sattar, J. Ballesteros-Cánovas
The cryosphere, including ice caps, ice sheets, ice shelves, mountain glaciers, snow cover, permafrost, and sea ice, is a key component of the Earth system. It plays a critical role in response to climate change and serves as a primary source of freshwater (Li et al., 2018; Yao et al., 2022). In recent decades, the cryosphere has undergone rapid changes, such as the melting of glaciers and sea ice, the decrease of snow cover and the degradation of permafrost. These changes have far-reaching consequences for both Earth’s climate system and the living environment of humans. Therefore, cryosphere research is of great importance to understand cryospheric change and its potential impacts on other spheres of the Earth. Over the last decades, there have been notable advancements in cryosphere monitoring through remote sensing technology. The improvement in spatial and temporal resolution of satellite imagery has contributed significantly to enhancing the understanding of cryosphere processes as well as allowing the development of new algorithms, data products and interdisciplinary integration with other fields of study. Despite significant advancements in cryosphere research, certain limitations still exist. Satellite images can be affected by cloud cover, atmospheric interference, and other factors that can limit accuracy and reliability. Furthermore, integrating these data with ground-based measurements and other forms of data is still challenging to comprehensively understand the changes in the cryosphere and its response to climate change. Remote sensing provides a viable option for studying the cryosphere in space due to its inaccessibility. Modern satellites and high-quality data provide a rich resource for cryosphere-related studies, while efficient algorithms make it more capable. Remote sensing is typically used to evaluate past changes and regularly monitor different components of the cryosphere. This facilitates better attribution and prediction of climatic parameters and their potential impacts on the cryosphere. In this Research Topic, we have collated three research articles that demonstrate the importance of remote sensing in cryosphere research and highlight recent significant advances in related fields. Small and Sousa explore the potential of spectral analysis in characterizing the spectral feature space of the cryosphere. Specifically, they analyse the hyperspectral reflectance measurements collected over the Greenland Ice Sheet using principal component analysis and clustering methods. They find that the hyperspectral reflectance data from the Greenland Ice Sheet exhibit a complex and heterogeneous spectral OPEN ACCESS
冰冻圈，包括冰帽、冰原、冰架、高山冰川、积雪、永久冻土和海冰，是地球系统的关键组成部分。它在应对气候变化方面发挥着关键作用，是淡水的主要来源(Li et al.， 2018;姚等人，2022)。近几十年来，冰冻圈发生了快速变化，如冰川和海冰融化、积雪减少和永久冻土退化。这些变化对地球的气候系统和人类的生活环境都产生了深远的影响。因此，冰冻圈研究对于了解冰冻圈的变化及其对地球其他圈的潜在影响具有重要意义。在过去几十年中，通过遥感技术监测冰冻圈取得了显著进展。卫星图像空间和时间分辨率的提高大大有助于加强对冰冻圈过程的了解，并允许开发新的算法、数据产品和与其他研究领域的跨学科整合。尽管冰冻圈研究取得了重大进展，但仍存在某些局限性。卫星图像可能受到云层覆盖、大气干扰和其他可能限制精度和可靠性的因素的影响。此外，将这些数据与地面测量和其他形式的数据相结合，对全面了解冰冻圈的变化及其对气候变化的响应仍然具有挑战性。遥感由于其不可接近性，为研究空间冰冻圈提供了一个可行的选择。现代卫星和高质量的数据为冰冻圈相关研究提供了丰富的资源，而高效的算法使其更有能力。遥感通常用于评估过去的变化，并定期监测冰冻圈的不同组成部分。这有助于更好地归因和预测气候参数及其对冰冻圈的潜在影响。在本研究主题中，我们整理了三篇研究论文，展示了遥感在冰冻圈研究中的重要性，并重点介绍了相关领域的最新重大进展。Small和Sousa探索了光谱分析在表征冰冻圈光谱特征空间方面的潜力。具体来说，他们使用主成分分析和聚类方法分析了在格陵兰冰盖上收集的高光谱反射测量数据。他们发现格陵兰冰盖的高光谱反射率数据呈现出复杂的非均匀光谱
{"title":"Editorial: Cryospheric remote sensing","authors":"Guoxiong Zheng, Sher Muhammad, A. Sattar, J. Ballesteros-Cánovas","doi":"10.3389/frsen.2023.1204667","DOIUrl":"https://doi.org/10.3389/frsen.2023.1204667","url":null,"abstract":"The cryosphere, including ice caps, ice sheets, ice shelves, mountain glaciers, snow cover, permafrost, and sea ice, is a key component of the Earth system. It plays a critical role in response to climate change and serves as a primary source of freshwater (Li et al., 2018; Yao et al., 2022). In recent decades, the cryosphere has undergone rapid changes, such as the melting of glaciers and sea ice, the decrease of snow cover and the degradation of permafrost. These changes have far-reaching consequences for both Earth’s climate system and the living environment of humans. Therefore, cryosphere research is of great importance to understand cryospheric change and its potential impacts on other spheres of the Earth. Over the last decades, there have been notable advancements in cryosphere monitoring through remote sensing technology. The improvement in spatial and temporal resolution of satellite imagery has contributed significantly to enhancing the understanding of cryosphere processes as well as allowing the development of new algorithms, data products and interdisciplinary integration with other fields of study. Despite significant advancements in cryosphere research, certain limitations still exist. Satellite images can be affected by cloud cover, atmospheric interference, and other factors that can limit accuracy and reliability. Furthermore, integrating these data with ground-based measurements and other forms of data is still challenging to comprehensively understand the changes in the cryosphere and its response to climate change. Remote sensing provides a viable option for studying the cryosphere in space due to its inaccessibility. Modern satellites and high-quality data provide a rich resource for cryosphere-related studies, while efficient algorithms make it more capable. Remote sensing is typically used to evaluate past changes and regularly monitor different components of the cryosphere. This facilitates better attribution and prediction of climatic parameters and their potential impacts on the cryosphere. In this Research Topic, we have collated three research articles that demonstrate the importance of remote sensing in cryosphere research and highlight recent significant advances in related fields. Small and Sousa explore the potential of spectral analysis in characterizing the spectral feature space of the cryosphere. Specifically, they analyse the hyperspectral reflectance measurements collected over the Greenland Ice Sheet using principal component analysis and clustering methods. They find that the hyperspectral reflectance data from the Greenland Ice Sheet exhibit a complex and heterogeneous spectral OPEN ACCESS","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133921023","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 : 2023-04-21DOI: 10.3389/frsen.2023.1156519
K. Kapper, Thomas Goelles , Stefan Muckenhuber , Andreas Trügler , Jakob Abermann , Birgit Schlager , Christoph Gaisberger , Markus Eckerstorfer , Jakob Grahn , Eirik Malnes , Alexander Prokop , Wolfgang Schöner
Avalanches pose a significant threat to the population and infrastructure of mountainous regions. The mapping and documentation of avalanches in Austria is mostly done by experts during field observations and covers usually only specific localized areas. A comprehensive mapping of avalanches is, however, crucial for the work of local avalanche commissions as well as avalanche warning services to assess, e.g., the avalanche danger. Over the past decade, mapping avalanches from satellite imagery has proven to be a promising and rapid approach to monitor avalanche activity in specific regions. Several recent avalanche detection approaches use deep learning-based algorithms to improve detection rates compared to traditional segmentation algorithms. Building on the success of these deep learning-based approaches, we present the first steps to build a modular data pipeline to map historical avalanche cycles in Copernicus Sentinel-1 imagery of the Austrian Alps. The Sentinel-1 mission has provided free all-weather synthetic aperture radar data since 2014, which has proven suitable for avalanche mapping in a Norwegian test area. In addition, we present a roadmap for setting up a segmentation algorithm, in which a general U-Net approach will serve as a baseline and will be compared with the mapping results of additional algorithms initially applied to autonomous driving. We propose to train the U-Net using labeled training dataset of avalanche outlines from Switzerland, Norway and Greenland. Due to the lack of training and validation data from Austria, we plan to compile the first avalanche archive for Austria. Meteorological variables, e.g., precipitation or wind, are highly important for the release of avalanches. In a completely new approach, we will therefore consider weather station data or outputs of numerical weather models in the learning-based algorithm to improve the detection performance. The mapping results in Austria will be complemented with pointwise field measurements of the MOLISENS platform and the RIEGL VZ-6000 terrestrial laser scanner.
{"title":"Automated snow avalanche monitoring for Austria: State of the art and roadmap for future work","authors":"K. Kapper, Thomas Goelles , Stefan Muckenhuber , Andreas Trügler , Jakob Abermann , Birgit Schlager , Christoph Gaisberger , Markus Eckerstorfer , Jakob Grahn , Eirik Malnes , Alexander Prokop , Wolfgang Schöner ","doi":"10.3389/frsen.2023.1156519","DOIUrl":"https://doi.org/10.3389/frsen.2023.1156519","url":null,"abstract":"Avalanches pose a significant threat to the population and infrastructure of mountainous regions. The mapping and documentation of avalanches in Austria is mostly done by experts during field observations and covers usually only specific localized areas. A comprehensive mapping of avalanches is, however, crucial for the work of local avalanche commissions as well as avalanche warning services to assess, e.g., the avalanche danger. Over the past decade, mapping avalanches from satellite imagery has proven to be a promising and rapid approach to monitor avalanche activity in specific regions. Several recent avalanche detection approaches use deep learning-based algorithms to improve detection rates compared to traditional segmentation algorithms. Building on the success of these deep learning-based approaches, we present the first steps to build a modular data pipeline to map historical avalanche cycles in Copernicus Sentinel-1 imagery of the Austrian Alps. The Sentinel-1 mission has provided free all-weather synthetic aperture radar data since 2014, which has proven suitable for avalanche mapping in a Norwegian test area. In addition, we present a roadmap for setting up a segmentation algorithm, in which a general U-Net approach will serve as a baseline and will be compared with the mapping results of additional algorithms initially applied to autonomous driving. We propose to train the U-Net using labeled training dataset of avalanche outlines from Switzerland, Norway and Greenland. Due to the lack of training and validation data from Austria, we plan to compile the first avalanche archive for Austria. Meteorological variables, e.g., precipitation or wind, are highly important for the release of avalanches. In a completely new approach, we will therefore consider weather station data or outputs of numerical weather models in the learning-based algorithm to improve the detection performance. The mapping results in Austria will be complemented with pointwise field measurements of the MOLISENS platform and the RIEGL VZ-6000 terrestrial laser scanner.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"563 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123317420","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 : 2023-04-17DOI: 10.3389/frsen.2023.1149900
V. Lucieer, E. Flukes, J. Keane, S. Ling, A. Nau, Victor Shelamoff
Robust definition of the spatial extent of seafloor habitats and how they may be changing through time is a holy grail for ecosystem management, particularly if an ecosystem is approaching a tipping point beyond which irreversible changes may occur. Here we generate and explore a new data set for the management of warming reefs in eastern Tasmania, Australia that will significantly improve the baseline maps required for fine-scaled spatial modelling and management that is, both robust at regional scales and is highly resolved within the water column. This procedure enabled the relative density of kelp vegetation to be identified in a region that is being overwhelmed by the range extension of a destructive grazer, the Longspined Sea Urchin, Centrostephanus rodgersii. We present a new online tool to visualize multibeam water column acoustic data as surfaces of kelp density at high resolution (50 cm) scale over seafloor terrain maps (spanning a total straight-line distance of 594 km and a total area of 29.14 km2) to reveal the types of reef structure on the East Coast of Tasmania where abalone habitat is threatened by kelp loss.
{"title":"Mapping warming reefs—An application of multibeam acoustic water column analysis to define threatened abalone habitat","authors":"V. Lucieer, E. Flukes, J. Keane, S. Ling, A. Nau, Victor Shelamoff","doi":"10.3389/frsen.2023.1149900","DOIUrl":"https://doi.org/10.3389/frsen.2023.1149900","url":null,"abstract":"Robust definition of the spatial extent of seafloor habitats and how they may be changing through time is a holy grail for ecosystem management, particularly if an ecosystem is approaching a tipping point beyond which irreversible changes may occur. Here we generate and explore a new data set for the management of warming reefs in eastern Tasmania, Australia that will significantly improve the baseline maps required for fine-scaled spatial modelling and management that is, both robust at regional scales and is highly resolved within the water column. This procedure enabled the relative density of kelp vegetation to be identified in a region that is being overwhelmed by the range extension of a destructive grazer, the Longspined Sea Urchin, Centrostephanus rodgersii. We present a new online tool to visualize multibeam water column acoustic data as surfaces of kelp density at high resolution (50 cm) scale over seafloor terrain maps (spanning a total straight-line distance of 594 km and a total area of 29.14 km2) to reveal the types of reef structure on the East Coast of Tasmania where abalone habitat is threatened by kelp loss.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126635658","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 : 2023-04-13DOI: 10.3389/frsen.2023.1111825
N. Oliveira, A. Lavagnino, Gabriela Aleixo Rocha, R. Moura, A. Bastos
Geomorphology provides the core attributes for outlining marine seascapes, once the structural complexity of the seafloor mediates several oceanographic processes and ecosystem services, and is positively associated with biodiversity. Shelf-incised valleys and other prominent meso-scale structures such as reefs and sinkholes have a great potential for the discrimination of benthic habitat groups. Here, we investigate shelf-incised valleys as a mesophotic habitat, by focusing on their geomorphological control in defining distinct habitats in comparison with the flat surrounding area. The study was based on the integration of high-resolution bathymetry data (multibeam echosounder), video imaging, and physical-chemical parameters of the water column. Habitat mapping was conducted using object-based image analysis segmentation and clustering. Principal Component Analysis was used to assess the variables associated with habitat distribution at each morphological region of the valleys. Bathymetric data revealed the presence of 5 shelf-incised valleys and 5 seabed classes were defined as carbonate crusts, Rhodoliths (3 distinct classes) and unconsolidated sediments. A comprehensive habitat map with 17 classes was produced, and 13 are associated with valley´s relief. Extensive rhodolith beds were mapped in the valley flanks/bottom and in the flat areas. Shelf-incised valleys are prominent morphological features that add complexity to the seascape, contrasting with the flat relief that dominates the seascape. The seabed footage obtained in the valleys revealed that their heterogeneous, complex and irregular topography harbors a great diversity of epibionts, such as scleractinian corals, coralline algae, sponges and bryozoans. Most of the variability in the dataset is correlated with salinity, temperature and carbonate sediments, which seem to be the most influential variables over the biological assemblage, together with water depth and seabed slope. Shelf-incised valleys, similarly to submarine canyons, can define a complex mesophotic habitat and sustain distinct biodiversity, and even form mesophotic reefs. These features are the legacy of Quaternary sea-level changes and should be further investigated as important mesophotic habitats.
{"title":"Geomorphological significance of shelf-incised valleys as mesophotic habitats","authors":"N. Oliveira, A. Lavagnino, Gabriela Aleixo Rocha, R. Moura, A. Bastos","doi":"10.3389/frsen.2023.1111825","DOIUrl":"https://doi.org/10.3389/frsen.2023.1111825","url":null,"abstract":"Geomorphology provides the core attributes for outlining marine seascapes, once the structural complexity of the seafloor mediates several oceanographic processes and ecosystem services, and is positively associated with biodiversity. Shelf-incised valleys and other prominent meso-scale structures such as reefs and sinkholes have a great potential for the discrimination of benthic habitat groups. Here, we investigate shelf-incised valleys as a mesophotic habitat, by focusing on their geomorphological control in defining distinct habitats in comparison with the flat surrounding area. The study was based on the integration of high-resolution bathymetry data (multibeam echosounder), video imaging, and physical-chemical parameters of the water column. Habitat mapping was conducted using object-based image analysis segmentation and clustering. Principal Component Analysis was used to assess the variables associated with habitat distribution at each morphological region of the valleys. Bathymetric data revealed the presence of 5 shelf-incised valleys and 5 seabed classes were defined as carbonate crusts, Rhodoliths (3 distinct classes) and unconsolidated sediments. A comprehensive habitat map with 17 classes was produced, and 13 are associated with valley´s relief. Extensive rhodolith beds were mapped in the valley flanks/bottom and in the flat areas. Shelf-incised valleys are prominent morphological features that add complexity to the seascape, contrasting with the flat relief that dominates the seascape. The seabed footage obtained in the valleys revealed that their heterogeneous, complex and irregular topography harbors a great diversity of epibionts, such as scleractinian corals, coralline algae, sponges and bryozoans. Most of the variability in the dataset is correlated with salinity, temperature and carbonate sediments, which seem to be the most influential variables over the biological assemblage, together with water depth and seabed slope. Shelf-incised valleys, similarly to submarine canyons, can define a complex mesophotic habitat and sustain distinct biodiversity, and even form mesophotic reefs. These features are the legacy of Quaternary sea-level changes and should be further investigated as important mesophotic habitats.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115323369","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 : 2023-04-12DOI: 10.3389/frsen.2023.1111696
B. C. Carvalho, Carolina Gomes, J. V. Guerra
Barrier islands are low-lying elongated, narrow sandy deposits, usually parallel to the coastline, separated from the continent by a lagoon. Due to their low elevation above sea level, barrier islands are environments susceptible to drastic morphological changes depending on the meteo-oceanographic conditions to which they are subjected. This work presents the morphological changes between 1985 and 2021 in “Restinga da Marambaia”—a 40 km long barrier island on Brazil’s Southeastern coast. One hundred thirty-four scenes from the Landsat collection were processed, enabling the quantification of the barrier island area. Additionally, the rates of change in the position of the shorelines facing the Atlantic Ocean, Sepetiba Bay, and Marambaia Bay were computed. The barrier island’s total area and the central sector’s width present significant seasonal variability, which is maximum during the austral fall and winter seasons. On the shores facing the Atlantic Ocean and Sepetiba Bay, it is noted that the central and far eastern sectors show an erosional trend. In contrast, the coastline is more stable on the shore facing Marambaia Bay. The seasonal variations of the barrier island area occur during a period of low rainfall and more energetic waves associated with local winds, which produce coastal currents, transporting the available sediments.
堰洲岛是低洼狭长的沙质沉积物，通常与海岸线平行，由泻湖与大陆隔开。由于其海拔较低，堰洲岛的环境容易受到剧烈形态变化的影响，这取决于它们所处的气象海洋条件。本作品呈现了巴西东南海岸40公里长的堰洲岛“Restinga da Marambaia”在1985年至2021年间的形态变化。对陆地卫星收集的134个场景进行了处理，使障壁岛区域得以量化。此外，还计算了面向大西洋、Sepetiba湾和Marambaia湾的海岸线位置的变化率。堰洲岛的总面积和中部的宽度呈现出明显的季节性变化，在南部的秋季和冬季最大。在面向大西洋和Sepetiba湾的海岸上，可以注意到中部和远东地区显示出侵蚀趋势。相比之下，面对马兰巴亚湾的海岸线更加稳定。堰洲岛地区的季节性变化发生在降雨量少和与当地风有关的更有活力的波浪期间，这些波浪产生海岸流，运输可用的沉积物。
{"title":"Spatio-temporal morphological variability of a tropical barrier island derived from the Landsat collection","authors":"B. C. Carvalho, Carolina Gomes, J. V. Guerra","doi":"10.3389/frsen.2023.1111696","DOIUrl":"https://doi.org/10.3389/frsen.2023.1111696","url":null,"abstract":"Barrier islands are low-lying elongated, narrow sandy deposits, usually parallel to the coastline, separated from the continent by a lagoon. Due to their low elevation above sea level, barrier islands are environments susceptible to drastic morphological changes depending on the meteo-oceanographic conditions to which they are subjected. This work presents the morphological changes between 1985 and 2021 in “Restinga da Marambaia”—a 40 km long barrier island on Brazil’s Southeastern coast. One hundred thirty-four scenes from the Landsat collection were processed, enabling the quantification of the barrier island area. Additionally, the rates of change in the position of the shorelines facing the Atlantic Ocean, Sepetiba Bay, and Marambaia Bay were computed. The barrier island’s total area and the central sector’s width present significant seasonal variability, which is maximum during the austral fall and winter seasons. On the shores facing the Atlantic Ocean and Sepetiba Bay, it is noted that the central and far eastern sectors show an erosional trend. In contrast, the coastline is more stable on the shore facing Marambaia Bay. The seasonal variations of the barrier island area occur during a period of low rainfall and more energetic waves associated with local winds, which produce coastal currents, transporting the available sediments.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114487847","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 : 2023-04-06DOI: 10.3389/frsen.2023.1125898
Juzer Noman, Willian Ney Cassol, S. Daniel, Damien Pham Van Bang
The identification of bedforms has an important role in the study of seafloor morphology. The presence of these dynamic structures on the seafloor represents a hazard for navigation. They also influence the hydrodynamic simulation models used in the context, for example, of coastal flooding. Generally, MultiBeam EchoSounders (MBES) are used to survey these bedforms. Unfortunately, the coverage of the MBES is limited to small areas per survey. Therefore, the analysis of large areas of interest (like navigation channels) requires the integration of different datasets acquired over overlapping areas at different times. The presence of spatial and temporal inconsistencies between these datasets may significantly affect the study of bedforms, which are subject to many natural processes (e.g., Tides; flow). This paper proposes a novel approach to integrate multisource bathymetric datasets to study bedforms. The proposed approach is based on consolidating multisource datasets and applying the Empirical Bayesian Kriging interpolation for the creation of a multisource Digital Bathymetric Model (DBM). It has been designed to be adapted for estuarine areas with a high dynamism of the seafloor, characteristic of the fluvio-marine regime of the Estuary of the Saint-Lawrence River. This area is distinguished by a high tidal cycle and the presence of fields of dunes. The study involves MBES data that was acquired daily over a field of dunes in this area over the span of 4 days for the purpose of monitoring the morphology and migration of dunes. The proposed approach performs well with a resulting surface with a reduced error relative to the original data compared to existing approaches and the conservation of the dune shape through the integration of the data sets despite the highly dynamic fluvio-marine environments.
{"title":"Bathymetric data integration approach to study bedforms in the estuary of the Saint‐Lawrence River","authors":"Juzer Noman, Willian Ney Cassol, S. Daniel, Damien Pham Van Bang","doi":"10.3389/frsen.2023.1125898","DOIUrl":"https://doi.org/10.3389/frsen.2023.1125898","url":null,"abstract":"The identification of bedforms has an important role in the study of seafloor morphology. The presence of these dynamic structures on the seafloor represents a hazard for navigation. They also influence the hydrodynamic simulation models used in the context, for example, of coastal flooding. Generally, MultiBeam EchoSounders (MBES) are used to survey these bedforms. Unfortunately, the coverage of the MBES is limited to small areas per survey. Therefore, the analysis of large areas of interest (like navigation channels) requires the integration of different datasets acquired over overlapping areas at different times. The presence of spatial and temporal inconsistencies between these datasets may significantly affect the study of bedforms, which are subject to many natural processes (e.g., Tides; flow). This paper proposes a novel approach to integrate multisource bathymetric datasets to study bedforms. The proposed approach is based on consolidating multisource datasets and applying the Empirical Bayesian Kriging interpolation for the creation of a multisource Digital Bathymetric Model (DBM). It has been designed to be adapted for estuarine areas with a high dynamism of the seafloor, characteristic of the fluvio-marine regime of the Estuary of the Saint-Lawrence River. This area is distinguished by a high tidal cycle and the presence of fields of dunes. The study involves MBES data that was acquired daily over a field of dunes in this area over the span of 4 days for the purpose of monitoring the morphology and migration of dunes. The proposed approach performs well with a resulting surface with a reduced error relative to the original data compared to existing approaches and the conservation of the dune shape through the integration of the data sets despite the highly dynamic fluvio-marine environments.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124668994","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 : 2023-04-04DOI: 10.3389/frsen.2023.1096000
T. Park, S. Sim
The Chimney Tops 2 wildfire (CT2) in 2016 at Great Smoky Mountains National Park (GSMNP) was recorded as the largest fire in GSMNP history. Understanding spatial patterns of burn severity and its underlying controlling factors is essential for managing the forests affected and reducing future fire risks; however, this has not been well understood. Here, we formulated two research questions: 1) What were the most important factors characterizing the patterns of burn severity in the CT2 fire? 2) Were burn severity measures from passive and active optical remote sensing sensors providing consistent views of fire damage? To address these questions, we used multitemporal Landsat- and lidar-based burn severity measures, i.e., relativized differenced Normalized Burn Ratio (RdNBR) and relativized differenced Mean Tree Height (RdMTH). A random forest approach was used to identify key drivers in characterizing spatial variability of burn severity, and the partial dependence of each explanatory variable was further evaluated. We found that pre-fire vegetation structure and topography both play significant roles in characterizing heterogeneous mixed burn severity patterns in the CT2 fire. Mean tree height, elevation, and topographic position emerged as key factors in explaining burn severity variation. We observed generally consistent spatial patterns from Landsat- and lidar-based burn severity measures. However, vegetation type and structure-dependent relations between RdNBR and RdMTH caused locally inconsistent burn severity patterns, particularly in high RdNBR regions. Our study highlights the important roles of pre-fire vegetation structure and topography in understanding burn severity patterns and urges to integrate both spectral and structural changes to fully map and understand fire impacts on forest ecosystems.
{"title":"Characterizing spatial burn severity patterns of 2016 Chimney Tops 2 fire using multi-temporal Landsat and NEON LiDAR data","authors":"T. Park, S. Sim","doi":"10.3389/frsen.2023.1096000","DOIUrl":"https://doi.org/10.3389/frsen.2023.1096000","url":null,"abstract":"The Chimney Tops 2 wildfire (CT2) in 2016 at Great Smoky Mountains National Park (GSMNP) was recorded as the largest fire in GSMNP history. Understanding spatial patterns of burn severity and its underlying controlling factors is essential for managing the forests affected and reducing future fire risks; however, this has not been well understood. Here, we formulated two research questions: 1) What were the most important factors characterizing the patterns of burn severity in the CT2 fire? 2) Were burn severity measures from passive and active optical remote sensing sensors providing consistent views of fire damage? To address these questions, we used multitemporal Landsat- and lidar-based burn severity measures, i.e., relativized differenced Normalized Burn Ratio (RdNBR) and relativized differenced Mean Tree Height (RdMTH). A random forest approach was used to identify key drivers in characterizing spatial variability of burn severity, and the partial dependence of each explanatory variable was further evaluated. We found that pre-fire vegetation structure and topography both play significant roles in characterizing heterogeneous mixed burn severity patterns in the CT2 fire. Mean tree height, elevation, and topographic position emerged as key factors in explaining burn severity variation. We observed generally consistent spatial patterns from Landsat- and lidar-based burn severity measures. However, vegetation type and structure-dependent relations between RdNBR and RdMTH caused locally inconsistent burn severity patterns, particularly in high RdNBR regions. Our study highlights the important roles of pre-fire vegetation structure and topography in understanding burn severity patterns and urges to integrate both spectral and structural changes to fully map and understand fire impacts on forest ecosystems.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125714939","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 : 2023-04-03DOI: 10.3389/frsen.2023.1143944
R. Ferrare, J. Hair, C. Hostetler, Taylor J. Shingler, S. Burton, M. Fenn, M. Clayton, A. Scarino, D. Harper, S. Seaman, A. Cook, E. Crosbie, E. Winstead, L. Ziemba, L. Thornhill, C. Robinson, R. Moore, M. Vaughan, A. Sorooshian, J. Schlosser, Hongyu Liu, Bo Zhang, G. Diskin, J. Digangi, J. Nowak, Yonghoon Choi, P. Zuidema, S. Chellappan
Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA Earth Venture Suborbital-3 (EVS-3) Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed elevated particulate linear depolarization associated with aerosols within the marine boundary layer. These observations were acquired off the east coast of the United States during both winter and summer 2020 and 2021 when the HSRL-2 was deployed on the NASA LaRC King Air aircraft. During 20 of 63 total flight days, particularly on days with cold air outbreaks, linear particulate depolarization at 532 nm exceeded 0.15–0.20 within the lowest several hundred meters of the atmosphere, indicating that these particles were non-spherical. Higher values of linear depolarization typically were measured at 355 nm and lower values were measured at 1,064 nm. Several lines of evidence suggest that these non-spherical particles were sea salt including aerosol extinction/backscatter ratio (“lidar ratio”) values of 20–25 sr measured at both 355 and 532 nm by the HSRL-2, higher values of particulate depolarization measured at low (< 60%) relative humidity, coincident airborne in situ size and composition measurements, and aerosol transport simulations. The elevated aerosol depolarization values were not correlated with wind speed but were correlated with salt mass fraction and effective radius of the aerosol when the relative humidity was below 60%. HSRL-2 measured median particulate extinction values of about 20 Mm−1 at 532 nm associated with these non-spherical sea salt particles and found that the aerosol optical depth (AOD) contributed by these particles remained small (0.03–0.04) but represented on average about 30%–40% of the total column AOD. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar aerosol measurements during several cold air outbreaks and CALIOP retrievals of column aerosol lidar ratio using column AOD constraints suggest that CALIOP operational aerosol algorithms can misclassify these aerosols as dusty marine rather than marine aerosols. Such misclassification leads to ∼40–50% overestimates in the assumed lidar ratio and in subsequent retrievals of aerosol optical depth and aerosol extinction.
{"title":"Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt","authors":"R. Ferrare, J. Hair, C. Hostetler, Taylor J. Shingler, S. Burton, M. Fenn, M. Clayton, A. Scarino, D. Harper, S. Seaman, A. Cook, E. Crosbie, E. Winstead, L. Ziemba, L. Thornhill, C. Robinson, R. Moore, M. Vaughan, A. Sorooshian, J. Schlosser, Hongyu Liu, Bo Zhang, G. Diskin, J. Digangi, J. Nowak, Yonghoon Choi, P. Zuidema, S. Chellappan","doi":"10.3389/frsen.2023.1143944","DOIUrl":"https://doi.org/10.3389/frsen.2023.1143944","url":null,"abstract":"Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA Earth Venture Suborbital-3 (EVS-3) Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed elevated particulate linear depolarization associated with aerosols within the marine boundary layer. These observations were acquired off the east coast of the United States during both winter and summer 2020 and 2021 when the HSRL-2 was deployed on the NASA LaRC King Air aircraft. During 20 of 63 total flight days, particularly on days with cold air outbreaks, linear particulate depolarization at 532 nm exceeded 0.15–0.20 within the lowest several hundred meters of the atmosphere, indicating that these particles were non-spherical. Higher values of linear depolarization typically were measured at 355 nm and lower values were measured at 1,064 nm. Several lines of evidence suggest that these non-spherical particles were sea salt including aerosol extinction/backscatter ratio (“lidar ratio”) values of 20–25 sr measured at both 355 and 532 nm by the HSRL-2, higher values of particulate depolarization measured at low (< 60%) relative humidity, coincident airborne in situ size and composition measurements, and aerosol transport simulations. The elevated aerosol depolarization values were not correlated with wind speed but were correlated with salt mass fraction and effective radius of the aerosol when the relative humidity was below 60%. HSRL-2 measured median particulate extinction values of about 20 Mm−1 at 532 nm associated with these non-spherical sea salt particles and found that the aerosol optical depth (AOD) contributed by these particles remained small (0.03–0.04) but represented on average about 30%–40% of the total column AOD. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar aerosol measurements during several cold air outbreaks and CALIOP retrievals of column aerosol lidar ratio using column AOD constraints suggest that CALIOP operational aerosol algorithms can misclassify these aerosols as dusty marine rather than marine aerosols. Such misclassification leads to ∼40–50% overestimates in the assumed lidar ratio and in subsequent retrievals of aerosol optical depth and aerosol extinction.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132003504","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 : 2023-03-27DOI: 10.3389/frsen.2023.940627
Giacomo Giorli, M. Pinkerton
We investigated the seasonal and spatial occurrence of sperm whale (Physeter macrocephalus) in the Ross Sea region of the Southern Ocean derived from passive acoustic data. Two Autonomous Multichannel Acoustic Recorders (AMARs) moored about 10 m above the seabed were deployed in the austral summer of 2018 and recovered 1 year later. The northern AMAR (A3) was located on the Pacific-Antarctic Ridge at 63.7°S and the southern AMAR (A1) at 73.1°S on the Iselin Bank, part of the continental slope of the Ross Sea. Sperm whale echolocation signals were detected using signal processing scripts and validated by visual inspection of spectrograms. Our results demonstrate that sperm whales are present in the Ross Sea region year-round. At A1, sperm whale vocalisations were detected in every month between February and November, but absent in December and January. Whales were detected most often in February with an average of 0.310 detections per hour. Sperm whale vocalisations were detected at station A3 in every month except February when we had no observations. Our results contrast to a paucity of reported sightings of sperm whales from fishing and research vessels in the Ross Sea region between December and February. Probabilities of detecting sperm whales at A3 were on average 14.2 times higher than at A1 for the same month and monthly mean detections per hour were an average of 74.4 times higher at A3 than A1. At A1, we found a significant preference for day-time foraging rather than during the night or nautical twilight. In contrast, at A3, no clear day/dusk/night/dawn differences in sperm whale occurrence were found. Low sea-ice concentration (< 80%) and open water within ∼50 km were necessary but not sufficient conditions for higher detection rates of sperm whales (>0.1 detections per hour). Overall, our research provides baseline information on sperm whale occurrence and establishes a method to track long-term change to help evaluate the conservation value of the Ross Sea region Marine Protected Area.
{"title":"Sperm whales forage year-round in the ross sea region","authors":"Giacomo Giorli, M. Pinkerton","doi":"10.3389/frsen.2023.940627","DOIUrl":"https://doi.org/10.3389/frsen.2023.940627","url":null,"abstract":"We investigated the seasonal and spatial occurrence of sperm whale (Physeter macrocephalus) in the Ross Sea region of the Southern Ocean derived from passive acoustic data. Two Autonomous Multichannel Acoustic Recorders (AMARs) moored about 10 m above the seabed were deployed in the austral summer of 2018 and recovered 1 year later. The northern AMAR (A3) was located on the Pacific-Antarctic Ridge at 63.7°S and the southern AMAR (A1) at 73.1°S on the Iselin Bank, part of the continental slope of the Ross Sea. Sperm whale echolocation signals were detected using signal processing scripts and validated by visual inspection of spectrograms. Our results demonstrate that sperm whales are present in the Ross Sea region year-round. At A1, sperm whale vocalisations were detected in every month between February and November, but absent in December and January. Whales were detected most often in February with an average of 0.310 detections per hour. Sperm whale vocalisations were detected at station A3 in every month except February when we had no observations. Our results contrast to a paucity of reported sightings of sperm whales from fishing and research vessels in the Ross Sea region between December and February. Probabilities of detecting sperm whales at A3 were on average 14.2 times higher than at A1 for the same month and monthly mean detections per hour were an average of 74.4 times higher at A3 than A1. At A1, we found a significant preference for day-time foraging rather than during the night or nautical twilight. In contrast, at A3, no clear day/dusk/night/dawn differences in sperm whale occurrence were found. Low sea-ice concentration (< 80%) and open water within ∼50 km were necessary but not sufficient conditions for higher detection rates of sperm whales (>0.1 detections per hour). Overall, our research provides baseline information on sperm whale occurrence and establishes a method to track long-term change to help evaluate the conservation value of the Ross Sea region Marine Protected Area.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129559921","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 : 2023-03-27DOI: 10.3389/frsen.2023.1136289
Sude Gul Yel, Esra Tunc Gormus
Classification of tree species provides important data in forest monitoring, sustainable forest management and planning. The recent developments in Multi Spectral (MS) and Hyper Spectral (HS) Imaging sensors in remote sensing have made the detection of tree species easier and accurate. With this systematic review study, it is aimed to understand the contribution of using the Multi Spectral and Hyper Spectral Imaging data in the detection of tree species while highlighting recent advances in the field and emphasizing important directions together with new possibilities for future inquiries. In this review, researchers and decision makers will be informed in two different subjects: First one is about the processing steps of exploiting Multi Spectral and HS images and the second one is about determining the advantages of exploiting Multi Spectral and Hyper Spectral images in the application area of detecting tree species. In this way exploiting satellite data will be facilitated. This will also provide an economical gain for using commercial Multi Spectral and Hyper Spectral Imaging data. Moreover, it should be also kept in mind that, as the number of spectral tags that will be obtained from each tree type are different, both the processing method and the classification method will change accordingly. This review, studies were grouped according to the data exploited (only Hyper Spectral images, only Multi Spectral images and their combinations), type of tree monitored and the processing method used. Then, the contribution of the image data used in the study was evaluated according to the accuracy of classification, the suitable type of tree and the classification method.
{"title":"Exploiting hyperspectral and multispectral images in the detection of tree species: A review","authors":"Sude Gul Yel, Esra Tunc Gormus","doi":"10.3389/frsen.2023.1136289","DOIUrl":"https://doi.org/10.3389/frsen.2023.1136289","url":null,"abstract":"Classification of tree species provides important data in forest monitoring, sustainable forest management and planning. The recent developments in Multi Spectral (MS) and Hyper Spectral (HS) Imaging sensors in remote sensing have made the detection of tree species easier and accurate. With this systematic review study, it is aimed to understand the contribution of using the Multi Spectral and Hyper Spectral Imaging data in the detection of tree species while highlighting recent advances in the field and emphasizing important directions together with new possibilities for future inquiries. In this review, researchers and decision makers will be informed in two different subjects: First one is about the processing steps of exploiting Multi Spectral and HS images and the second one is about determining the advantages of exploiting Multi Spectral and Hyper Spectral images in the application area of detecting tree species. In this way exploiting satellite data will be facilitated. This will also provide an economical gain for using commercial Multi Spectral and Hyper Spectral Imaging data. Moreover, it should be also kept in mind that, as the number of spectral tags that will be obtained from each tree type are different, both the processing method and the classification method will change accordingly. This review, studies were grouped according to the data exploited (only Hyper Spectral images, only Multi Spectral images and their combinations), type of tree monitored and the processing method used. Then, the contribution of the image data used in the study was evaluated according to the accuracy of classification, the suitable type of tree and the classification method.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129848966","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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