Pub Date : 2023-03-21DOI: 10.3389/frsen.2023.1146110
A. Gilerson, Eder Herrera-Estrella, Jacopo Agagliate, Robert Foster, J. I. Gossn, D. Dessailly, E. Kwiatkowska
Uncertainties in remote sensing reflectance R r s for the Ocean Color sensors strongly affect the quality of the retrieval of concentrations of chlorophyll-a and water properties. By comparison of data from SNPP VIIRS and several AERONET-OC stations and MOBY, it was recently shown that the main uncertainties come from the Rayleigh-type spectral component (Gilerson et al., 2022), which was associated with small variability in the Rayleigh optical thickness in the atmosphere and/or its calculation. In addition, water variability spectra proportional to R r s were found to play a significant role in coastal waters, while other components including radiances from aerosols and glint were small. This work expands on the previous study, following a similar procedure and applying the same model for the characterization of uncertainties to the Sentinel-3A and B OLCI sensors. It is shown that the primary sources of uncertainties are the same as for VIIRS, i.e., dominated by the Rayleigh-type component, with the total uncertainties for OLCI sensors typically higher in coastal areas than for VIIRS.
海洋颜色传感器遥感反射率R R s的不确定性强烈影响叶绿素-a浓度和水性质的反演质量。通过比较SNPP VIIRS和几个AERONET-OC站以及MOBY的数据，最近发现主要的不确定性来自瑞利型光谱分量(Gilerson et al.， 2022)，这与大气中瑞利光学厚度和/或其计算的小变率有关。此外，发现与R R s成比例的水变率光谱在沿海水域发挥重要作用，而其他组分，包括气溶胶辐射和闪烁，则较小。这项工作扩展了先前的研究，遵循类似的程序，并将相同的模型应用于Sentinel-3A和B OLCI传感器的不确定性表征。结果表明，不确定性的主要来源与VIIRS相同，即以瑞利型分量为主，沿海地区OLCI传感器的总不确定性通常高于VIIRS。
{"title":"Determining the primary sources of uncertainty in the retrieval of marine remote sensing reflectance from satellite ocean color sensors II. Sentinel 3 OLCI sensors","authors":"A. Gilerson, Eder Herrera-Estrella, Jacopo Agagliate, Robert Foster, J. I. Gossn, D. Dessailly, E. Kwiatkowska","doi":"10.3389/frsen.2023.1146110","DOIUrl":"https://doi.org/10.3389/frsen.2023.1146110","url":null,"abstract":"Uncertainties in remote sensing reflectance R r s for the Ocean Color sensors strongly affect the quality of the retrieval of concentrations of chlorophyll-a and water properties. By comparison of data from SNPP VIIRS and several AERONET-OC stations and MOBY, it was recently shown that the main uncertainties come from the Rayleigh-type spectral component (Gilerson et al., 2022), which was associated with small variability in the Rayleigh optical thickness in the atmosphere and/or its calculation. In addition, water variability spectra proportional to R r s were found to play a significant role in coastal waters, while other components including radiances from aerosols and glint were small. This work expands on the previous study, following a similar procedure and applying the same model for the characterization of uncertainties to the Sentinel-3A and B OLCI sensors. It is shown that the primary sources of uncertainties are the same as for VIIRS, i.e., dominated by the Rayleigh-type component, with the total uncertainties for OLCI sensors typically higher in coastal areas than for VIIRS.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"629 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128335897","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 : 2023-03-20DOI: 10.3389/frsen.2023.1182973
Frontiers Production Office
{"title":"Erratum: Accuracy of UAV photogrammetry in glacial and periglacial alpine terrain: A comparison with airborne and terrestrial datasets","authors":"Frontiers Production Office","doi":"10.3389/frsen.2023.1182973","DOIUrl":"https://doi.org/10.3389/frsen.2023.1182973","url":null,"abstract":"","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130048276","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 : 2023-03-17DOI: 10.3389/frsen.2023.1140999
Anna E. Windle, L. Staver, A. Elmore, Stephanie Scherer, Seth Keller, Ben Malmgren, G. Silsbe
Coastal wetlands are among the most productive ecosystems in the world and provide important ecosystem services related to improved water quality, carbon sequestration, and biodiversity. In many locations, wetlands are threatened by coastal development and rising sea levels, prompting an era of tidal wetland restoration. The creation and restoration of tidal marshes necessitate the need for ecosystem monitoring. While satellite remote sensing is a valuable monitoring tool; the spatial and temporal resolution of imagery often places operational constraints, especially in small or spatially complex environments. Unoccupied aircraft systems (UAS) are an emerging remote sensing platform that collects data with flexible on-demand capabilities at much greater spatial resolution than sensors on aircraft and satellites, and resultant imagery can be readily rendered in three dimensions through Structure from Motion (SfM) photogrammetric processing. In this study, UAS data at 5 cm resolution was collected at an engineered wetland at Poplar Island, located in Chesapeake Bay, MD United States five times throughout 2019 to 2022. The wetland is dominated by two vegetation species: Spartina alterniflora and Spartina patens that were originally planted in 2005 in low and high marsh elevation zones respectively. During each survey, UAS multispectral reflectance, canopy elevation, and texture were derived and used as input into supervised random forest classification models to classify species-specific marsh vegetation. Overall accuracy ranged from 97% to 99%, with texture and canopy elevation variables being the most important across all datasets. Random forest classifications were also applied to down-sampled UAS data which resulted in a decline in classification accuracy as spatial resolution decreased (pixels became larger), indicating the benefit of using ultra-high resolution imagery to accurately and precisely distinguish between wetland vegetation. High resolution vegetation classification maps were compared to the 2005 as-built planting plans, demonstrating significant changes in vegetation and potential instances of marsh migration. The amount of vegetation change in the high marsh zone positively correlated with interannual variations in local sea level, suggesting a feedback between vegetation and tidal inundation. This study demonstrates that UAS remote sensing has great potential to assist in large-scale estimates of vegetation changes and can improve restoration monitoring success.
{"title":"Multi-temporal high-resolution marsh vegetation mapping using unoccupied aircraft system remote sensing and machine learning","authors":"Anna E. Windle, L. Staver, A. Elmore, Stephanie Scherer, Seth Keller, Ben Malmgren, G. Silsbe","doi":"10.3389/frsen.2023.1140999","DOIUrl":"https://doi.org/10.3389/frsen.2023.1140999","url":null,"abstract":"Coastal wetlands are among the most productive ecosystems in the world and provide important ecosystem services related to improved water quality, carbon sequestration, and biodiversity. In many locations, wetlands are threatened by coastal development and rising sea levels, prompting an era of tidal wetland restoration. The creation and restoration of tidal marshes necessitate the need for ecosystem monitoring. While satellite remote sensing is a valuable monitoring tool; the spatial and temporal resolution of imagery often places operational constraints, especially in small or spatially complex environments. Unoccupied aircraft systems (UAS) are an emerging remote sensing platform that collects data with flexible on-demand capabilities at much greater spatial resolution than sensors on aircraft and satellites, and resultant imagery can be readily rendered in three dimensions through Structure from Motion (SfM) photogrammetric processing. In this study, UAS data at 5 cm resolution was collected at an engineered wetland at Poplar Island, located in Chesapeake Bay, MD United States five times throughout 2019 to 2022. The wetland is dominated by two vegetation species: Spartina alterniflora and Spartina patens that were originally planted in 2005 in low and high marsh elevation zones respectively. During each survey, UAS multispectral reflectance, canopy elevation, and texture were derived and used as input into supervised random forest classification models to classify species-specific marsh vegetation. Overall accuracy ranged from 97% to 99%, with texture and canopy elevation variables being the most important across all datasets. Random forest classifications were also applied to down-sampled UAS data which resulted in a decline in classification accuracy as spatial resolution decreased (pixels became larger), indicating the benefit of using ultra-high resolution imagery to accurately and precisely distinguish between wetland vegetation. High resolution vegetation classification maps were compared to the 2005 as-built planting plans, demonstrating significant changes in vegetation and potential instances of marsh migration. The amount of vegetation change in the high marsh zone positively correlated with interannual variations in local sea level, suggesting a feedback between vegetation and tidal inundation. This study demonstrates that UAS remote sensing has great potential to assist in large-scale estimates of vegetation changes and can improve restoration monitoring success.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133698845","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}
Ecosystems are under a multitude of pressures, including land-use change, overexploitation, pollution, and climate change. Most studies, resources, and conservation efforts are allocated to protected areas, while anthropogenic activities in their surroundings may affect them in ways that are poorly understood. We evaluated soundscape structure in forests surrounded by protected or productive areas in central Costa Rica. We sampled soundscapes in 91 recording sites in Grecia Forest Reserve and Poas Volcano National Park, and surrounding areas with productive activities (predominantly agricultural and urban). We classified sampling sites into three clusters according to landscape entropy, forest amount, and fragmentation surrounding recording points: more fragmented, more conserved, and intermediate. The conserved cluster showed higher acoustic diversity or entropy, but lower acoustic complexity, shorter duration of sounds in all frequency ranges, and lower amount of energy in the biological frequency bands than the fragmented cluster. We additionally found a positive significant relationship between the amount of forest and acoustic entropy or diversity indices, but a negative relationship with acoustic activity or energy indices. Indices, such as spectral and temporal entropy, the entropy of spectral variance, and total entropy, seemed to be a better fit than acoustic complexity and bioacoustic indices as indicators of habitat conservation in this study. Acoustic indices revealed that the surrounding matrices of protected areas have an impact on acoustic environments. We encourage researchers and decision-makers to carefully interpret acoustic indices when evaluating habitats showing a higher value in acoustic energy or activity because this might not necessarily reflect either a high level of biodiversity or habitat conservation. Also, we highlight the importance of preserving undisturbed forested matrices around protected areas, as they are important for maintaining acoustic diversity.
{"title":"Soundscape structure in forests surrounded by protected and productive areas in central Costa Rica","authors":"Mónica Retamosa Izaguirre, Jimy Barrantes Madrigal","doi":"10.3389/frsen.2023.1051555","DOIUrl":"https://doi.org/10.3389/frsen.2023.1051555","url":null,"abstract":"Ecosystems are under a multitude of pressures, including land-use change, overexploitation, pollution, and climate change. Most studies, resources, and conservation efforts are allocated to protected areas, while anthropogenic activities in their surroundings may affect them in ways that are poorly understood. We evaluated soundscape structure in forests surrounded by protected or productive areas in central Costa Rica. We sampled soundscapes in 91 recording sites in Grecia Forest Reserve and Poas Volcano National Park, and surrounding areas with productive activities (predominantly agricultural and urban). We classified sampling sites into three clusters according to landscape entropy, forest amount, and fragmentation surrounding recording points: more fragmented, more conserved, and intermediate. The conserved cluster showed higher acoustic diversity or entropy, but lower acoustic complexity, shorter duration of sounds in all frequency ranges, and lower amount of energy in the biological frequency bands than the fragmented cluster. We additionally found a positive significant relationship between the amount of forest and acoustic entropy or diversity indices, but a negative relationship with acoustic activity or energy indices. Indices, such as spectral and temporal entropy, the entropy of spectral variance, and total entropy, seemed to be a better fit than acoustic complexity and bioacoustic indices as indicators of habitat conservation in this study. Acoustic indices revealed that the surrounding matrices of protected areas have an impact on acoustic environments. We encourage researchers and decision-makers to carefully interpret acoustic indices when evaluating habitats showing a higher value in acoustic energy or activity because this might not necessarily reflect either a high level of biodiversity or habitat conservation. Also, we highlight the importance of preserving undisturbed forested matrices around protected areas, as they are important for maintaining acoustic diversity.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124832850","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 : 2023-03-06DOI: 10.3389/frsen.2023.1073765
D. Long, M. Brodzik, M. Hardman
The MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) includes conventional- and enhanced-resolution radiometer brightness temperature (T B ) images on standard, compatible grids from calibrated satellite radiometer measurements collected over a multi-decade period. Recently, the CETB team processed the first 4 years of enhanced resolution Soil Moisture Active Passive (SMAP) L-band (1.41 GHz) radiometer T B images. The CETB processing employs the radiometer form of the Scatterometer Image Reconstruction (rSIR) algorithm to create enhanced resolution images, which are posted on fine resolution grids. In this paper, we evaluate the effective resolution of the SMAP T B image products using coastline and island crossings. We similarly evaluate the effective resolution of the SMAP L1C_TB_E enhanced resolution product that is based on Backus-Gilbert processing. We present a comparison of the spatial resolution of the rSIR and L1C_TB_E enhanced resolution products with conventionally-processed (gridded) SMAP data. We find that the effective resolution of daily CETB rSIR SMAP T B images is slightly finer than that of L1C_TB_E and about 30% finer than conventionally processed data.
校准的增强分辨率被动微波日等面积可扩展地球网格2.0亮度温度(CETB)地球系统数据记录(ESDR)包括标准兼容网格上的常规分辨率和增强分辨率辐射计亮度温度(tb)图像，这些图像来自校准的卫星辐射计测量数据，收集了几十年的时间。最近，CETB团队处理了前4年的增强分辨率土壤湿度主被动(SMAP) l波段(1.41 GHz)辐射计TB图像。CETB处理采用辐射计形式的散射图像重建(rSIR)算法来创建增强分辨率的图像，这些图像被张贴在精细分辨率网格上。本文利用海岸线和岛屿交叉点对SMAP T - B图像产品的有效分辨率进行了评价。我们同样评估了基于Backus-Gilbert处理的SMAP L1C_TB_E增强分辨率产品的有效分辨率。我们将rSIR和L1C_TB_E增强分辨率产品的空间分辨率与常规处理(网格化)SMAP数据进行了比较。我们发现每日CETB rSIR SMAP TB图像的有效分辨率略高于L1C_TB_E，比常规处理数据的有效分辨率高30%左右。
{"title":"Evaluating the effective resolution of enhanced resolution SMAP brightness temperature image products","authors":"D. Long, M. Brodzik, M. Hardman","doi":"10.3389/frsen.2023.1073765","DOIUrl":"https://doi.org/10.3389/frsen.2023.1073765","url":null,"abstract":"The MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) includes conventional- and enhanced-resolution radiometer brightness temperature (T B ) images on standard, compatible grids from calibrated satellite radiometer measurements collected over a multi-decade period. Recently, the CETB team processed the first 4 years of enhanced resolution Soil Moisture Active Passive (SMAP) L-band (1.41 GHz) radiometer T B images. The CETB processing employs the radiometer form of the Scatterometer Image Reconstruction (rSIR) algorithm to create enhanced resolution images, which are posted on fine resolution grids. In this paper, we evaluate the effective resolution of the SMAP T B image products using coastline and island crossings. We similarly evaluate the effective resolution of the SMAP L1C_TB_E enhanced resolution product that is based on Backus-Gilbert processing. We present a comparison of the spatial resolution of the rSIR and L1C_TB_E enhanced resolution products with conventionally-processed (gridded) SMAP data. We find that the effective resolution of daily CETB rSIR SMAP T B images is slightly finer than that of L1C_TB_E and about 30% finer than conventionally processed data.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125262323","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 : 2023-03-06DOI: 10.3389/frsen.2023.1107275
M. Pinardi, D. Stroppiana, R. Caroni, Lorenzo Parigi, Giulio Tellina, G. Free, C. Giardino, C. Albergel, M. Bresciani
Lakes have been observed as sentinels of climate change. In the last decades, global warming and increasing aridity has led to an increase in both the number and severity of wildfires. This has a negative impact on lake catchments by reducing forest cover and triggering cascading effects in freshwater ecosystems. In this work we used satellite remote sensing to analyse potential fire effects on lake water quality of Lake Baikal (Russia), considering the role of runoff and sediment transport, a less studied pathway compared to fire emissions transport. The main objectives of this study were to analyse time series and investigate relationships among fires (i.e., burned area), meteo-climatic parameters and water quality variables (chlorophyll-a, turbidity) for the period 2003–2020. Because Lake Baikal is oligotrophic, we expected detectable changes in water quality variables at selected areas near the three mains tributaries (Upper Angara, Barguzin, Selenga) due to river transport of fire-derived burned material and nutrients. Time series analysis showed seasonal (from April to June) and inter-annual fire occurrence, precipitation patterns (high intensity in summer) and no significant temporal changes for water quality variables during the studied periods. The most severe wildfires occurred in 2003 with the highest burned area detected (36,767 km2). The three lake sub-basins investigated have shown to respond differently according to their morphology, land cover types and meteo-climatic conditions, indicating their importance in determining the response of water variables to the impact of fires. Overall, our finding suggests that Lake Baikal shows resilience in the medium-long term to potential effects of fires and climate change in the region.
{"title":"Assessing the impact of wildfires on water quality using satellite remote sensing: the Lake Baikal case study","authors":"M. Pinardi, D. Stroppiana, R. Caroni, Lorenzo Parigi, Giulio Tellina, G. Free, C. Giardino, C. Albergel, M. Bresciani","doi":"10.3389/frsen.2023.1107275","DOIUrl":"https://doi.org/10.3389/frsen.2023.1107275","url":null,"abstract":"Lakes have been observed as sentinels of climate change. In the last decades, global warming and increasing aridity has led to an increase in both the number and severity of wildfires. This has a negative impact on lake catchments by reducing forest cover and triggering cascading effects in freshwater ecosystems. In this work we used satellite remote sensing to analyse potential fire effects on lake water quality of Lake Baikal (Russia), considering the role of runoff and sediment transport, a less studied pathway compared to fire emissions transport. The main objectives of this study were to analyse time series and investigate relationships among fires (i.e., burned area), meteo-climatic parameters and water quality variables (chlorophyll-a, turbidity) for the period 2003–2020. Because Lake Baikal is oligotrophic, we expected detectable changes in water quality variables at selected areas near the three mains tributaries (Upper Angara, Barguzin, Selenga) due to river transport of fire-derived burned material and nutrients. Time series analysis showed seasonal (from April to June) and inter-annual fire occurrence, precipitation patterns (high intensity in summer) and no significant temporal changes for water quality variables during the studied periods. The most severe wildfires occurred in 2003 with the highest burned area detected (36,767 km2). The three lake sub-basins investigated have shown to respond differently according to their morphology, land cover types and meteo-climatic conditions, indicating their importance in determining the response of water variables to the impact of fires. Overall, our finding suggests that Lake Baikal shows resilience in the medium-long term to potential effects of fires and climate change in the region.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122716469","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 : 2023-03-06DOI: 10.3389/frsen.2023.1116817
M. McGill, P. Selmer, A. Kupchock, J. Yorks
Lidar profiling of the atmosphere provides information on existence of cloud and aerosol layers and the height and structure of those layers. Knowledge of feature boundaries is a key input to assimilation models. Moreover, identifying feature boundaries with minimal latency is essential to impact operational assimilation and real-time decision making. Using advanced convolution neural network algorithms, we demonstrate real-time determination of atmospheric feature boundaries using an airborne backscatter lidar. Results are shown to agree well with traditional processing methods and are produced with higher horizontal resolution than the traditional method. Demonstrated using airborne lidar, the algorithms and process are extendable to real-time generation of data products from a future spaceborne sensor.
{"title":"Machine learning-enabled real-time detection of cloud and aerosol layers using airborne lidar","authors":"M. McGill, P. Selmer, A. Kupchock, J. Yorks","doi":"10.3389/frsen.2023.1116817","DOIUrl":"https://doi.org/10.3389/frsen.2023.1116817","url":null,"abstract":"Lidar profiling of the atmosphere provides information on existence of cloud and aerosol layers and the height and structure of those layers. Knowledge of feature boundaries is a key input to assimilation models. Moreover, identifying feature boundaries with minimal latency is essential to impact operational assimilation and real-time decision making. Using advanced convolution neural network algorithms, we demonstrate real-time determination of atmospheric feature boundaries using an airborne backscatter lidar. Results are shown to agree well with traditional processing methods and are produced with higher horizontal resolution than the traditional method. Demonstrated using airborne lidar, the algorithms and process are extendable to real-time generation of data products from a future spaceborne sensor.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123690093","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 : 2023-02-22DOI: 10.3389/frsen.2023.1118745
Joseph Nied, Michael Jones, S. Seaman, Taylor J. Shingler, J. Hair, B. Cairns, D. V. Gilst, A. Bucholtz, S. Schmidt, S. Chellappan, P. Zuidema, B. van Diedenhoven, A. Sorooshian, S. Stamnes
For aerosol, cloud, land, and ocean remote sensing, the development of accurate cloud detection methods, or cloud masks, is extremely important. For airborne passive remotesensing, it is also important to identify when clouds are above the aircraft since their presence contaminates the measurements of nadir-viewing passive sensors. We describe the development of a camera-based approach to detecting clouds above the aircraft via a convolutional neural network called the cloud detection neural network (CDNN). We quantify the performance of this CDNN using human-labeled validation data where we report 96% accuracy in detecting clouds in testing datasets for both zenith viewing and forward-viewing models. We present results from the CDNN basedon airborne imagery from the NASA Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). We quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward-looking camera mounted inside the aircraft cockpit compared to the use of an all-sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. A comparison of the CDNN with the SPN-S on time-specific intervals resulted in 93% accuracy for the zenith viewing CDNN and 84% for the forward-viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of .15 for the forward CDNN and .07 for the zenith CDNN. For CAMP2Ex, 53% of flight dates had above-aircraft cloud fraction above 50%, while for ACTIVATE, 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively. The CDNN enables cost-effective detection of clouds above the aircraft using an inexpensive camera installed in the cockpit for airborne science research flights where there are no dedicated upward-looking instruments for cloud detection, the installation of which requires time-consuming and expensive aircraft modifications, in addition to added mission cost and complexity of operating additional instruments.
{"title":"A cloud detection neural network for above-aircraft clouds using airborne cameras","authors":"Joseph Nied, Michael Jones, S. Seaman, Taylor J. Shingler, J. Hair, B. Cairns, D. V. Gilst, A. Bucholtz, S. Schmidt, S. Chellappan, P. Zuidema, B. van Diedenhoven, A. Sorooshian, S. Stamnes","doi":"10.3389/frsen.2023.1118745","DOIUrl":"https://doi.org/10.3389/frsen.2023.1118745","url":null,"abstract":"For aerosol, cloud, land, and ocean remote sensing, the development of accurate cloud detection methods, or cloud masks, is extremely important. For airborne passive remotesensing, it is also important to identify when clouds are above the aircraft since their presence contaminates the measurements of nadir-viewing passive sensors. We describe the development of a camera-based approach to detecting clouds above the aircraft via a convolutional neural network called the cloud detection neural network (CDNN). We quantify the performance of this CDNN using human-labeled validation data where we report 96% accuracy in detecting clouds in testing datasets for both zenith viewing and forward-viewing models. We present results from the CDNN basedon airborne imagery from the NASA Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). We quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward-looking camera mounted inside the aircraft cockpit compared to the use of an all-sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. A comparison of the CDNN with the SPN-S on time-specific intervals resulted in 93% accuracy for the zenith viewing CDNN and 84% for the forward-viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of .15 for the forward CDNN and .07 for the zenith CDNN. For CAMP2Ex, 53% of flight dates had above-aircraft cloud fraction above 50%, while for ACTIVATE, 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively. The CDNN enables cost-effective detection of clouds above the aircraft using an inexpensive camera installed in the cockpit for airborne science research flights where there are no dedicated upward-looking instruments for cloud detection, the installation of which requires time-consuming and expensive aircraft modifications, in addition to added mission cost and complexity of operating additional instruments.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122783262","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 : 2023-02-22DOI: 10.3389/frsen.2023.988366
P. Feldens, P. Held, F. Otero-Ferrer, L. Bramanti, F. Espino, J. Schneider von Deimling
The black coral Anthipatella wollastoni forms marine animal forests in the mesophotic zone. The spatial extent of black coral forests is not well known in many regions. Due to its protein and chitin skeleton, the coral is difficult to image using acoustic remote sensing techniques compared to corals with carbonate skeletons. Several manufacturers have recently introduced an additional data type to their multibeam echosounders, called “multi-detection,” which provides additional target detections per beam in addition to the primary bottom detection. In this study, we used a Norbit chirp multibeam echosounder in multi-detect mode to acquire up to three targets in each beam in an area of black coral below 45 m depth off the coast of Lanzarote (Canary Islands, Spain). Multi-detect allows features above and below the primary bottom detection to be identified without the need to store and process water-column data. Black coral can be detected by comparing “multi-detection” data with ground truthing by technical divers and underwater cameras. However, the repeatability of the detections is limited and further sensitivity studies are required.
{"title":"Can black coral forests be detected using multibeam echosounder “multi-detect” data?","authors":"P. Feldens, P. Held, F. Otero-Ferrer, L. Bramanti, F. Espino, J. Schneider von Deimling","doi":"10.3389/frsen.2023.988366","DOIUrl":"https://doi.org/10.3389/frsen.2023.988366","url":null,"abstract":"The black coral Anthipatella wollastoni forms marine animal forests in the mesophotic zone. The spatial extent of black coral forests is not well known in many regions. Due to its protein and chitin skeleton, the coral is difficult to image using acoustic remote sensing techniques compared to corals with carbonate skeletons. Several manufacturers have recently introduced an additional data type to their multibeam echosounders, called “multi-detection,” which provides additional target detections per beam in addition to the primary bottom detection. In this study, we used a Norbit chirp multibeam echosounder in multi-detect mode to acquire up to three targets in each beam in an area of black coral below 45 m depth off the coast of Lanzarote (Canary Islands, Spain). Multi-detect allows features above and below the primary bottom detection to be identified without the need to store and process water-column data. Black coral can be detected by comparing “multi-detection” data with ground truthing by technical divers and underwater cameras. However, the repeatability of the detections is limited and further sensitivity studies are required.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123962277","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 : 2023-02-17DOI: 10.3389/frsen.2023.952091
C. Gabarró, N. Hughes, J. Wilkinson, Laurent Bertino, A. Bracher, T. Diehl, W. Dierking, V. González-Gambau, T. Lavergne, T. Madurell, E. Malnes, P. Wagner
We present a comprehensive review of the current status of remotely sensed and in situ sea ice, ocean, and land parameters acquired over the Arctic and Antarctic and identify current data gaps through comparison with the portfolio of products provided by Copernicus services. While we include several land parameters, the focus of our review is on the marine sector. The analysis is facilitated by the outputs of the KEPLER H2020 project. This project developed a road map for Copernicus to deliver an improved European capacity for monitoring and forecasting of the Polar Regions, including recommendations and lessons learnt, and the role citizen science can play in supporting Copernicus’ capabilities and giving users ownership in the system. In addition to summarising this information we also provide an assessment of future satellite missions (in particular the Copernicus Sentinel Expansion Missions), in terms of the potential enhancements they can provide for environmental monitoring and integration/assimilation into modelling/forecast products. We identify possible synergies between parameters obtained from different satellite missions to increase the information content and the robustness of specific data products considering the end-users requirements, in particular maritime safety. We analyse the potential of new variables and new techniques relevant for assimilation into simulations and forecasts of environmental conditions and changes in the Polar Regions at various spatial and temporal scales. This work concludes with several specific recommendations to the EU for improving the satellite-based monitoring of the Polar Regions.
{"title":"Improving satellite-based monitoring of the polar regions: Identification of research and capacity gaps","authors":"C. Gabarró, N. Hughes, J. Wilkinson, Laurent Bertino, A. Bracher, T. Diehl, W. Dierking, V. González-Gambau, T. Lavergne, T. Madurell, E. Malnes, P. Wagner","doi":"10.3389/frsen.2023.952091","DOIUrl":"https://doi.org/10.3389/frsen.2023.952091","url":null,"abstract":"We present a comprehensive review of the current status of remotely sensed and in situ sea ice, ocean, and land parameters acquired over the Arctic and Antarctic and identify current data gaps through comparison with the portfolio of products provided by Copernicus services. While we include several land parameters, the focus of our review is on the marine sector. The analysis is facilitated by the outputs of the KEPLER H2020 project. This project developed a road map for Copernicus to deliver an improved European capacity for monitoring and forecasting of the Polar Regions, including recommendations and lessons learnt, and the role citizen science can play in supporting Copernicus’ capabilities and giving users ownership in the system. In addition to summarising this information we also provide an assessment of future satellite missions (in particular the Copernicus Sentinel Expansion Missions), in terms of the potential enhancements they can provide for environmental monitoring and integration/assimilation into modelling/forecast products. We identify possible synergies between parameters obtained from different satellite missions to increase the information content and the robustness of specific data products considering the end-users requirements, in particular maritime safety. We analyse the potential of new variables and new techniques relevant for assimilation into simulations and forecasts of environmental conditions and changes in the Polar Regions at various spatial and temporal scales. This work concludes with several specific recommendations to the EU for improving the satellite-based monitoring of the Polar Regions.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131676276","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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