Pub Date : 2020-03-01DOI: 10.1109/lagirs48042.2020.9165626
A. Delsouc, M. Barber, W. Pérez-Martínez, I. Briceño-De-Urbaneja
Restricted episodic changes occurred in a short time period and over large spatial extents. Extreme weather conditions usually give rise to restricted episodic changes. Sentinel-1 radar images of the Salar de Aguas Calientes in Chile acquired in the Altiplanic winter (March 2015 and June 2017), 2018 austral winter and 2017-2018 springtime, demonstrates the ability to monitor episodic events remotely. The results of the backscattered power are encouraging and show episodic variations in VV polarization at C-band. The surface features in Salar de Aguas Calientes Sur change in response to snowfalls during either the Altiplanic or austral winter with an increase of the backscattering in presence of dry snow over the salt pan crust. Flooding events related to snow-melting during spring 2017-2018 showed a decrease in the backscattering signal over ponded water and an increase when wind blows over the water. Remote-sensing observations of the salar can provide a means for monitoring changes in the surface of the salar and a better understanding of the associated climatic episodic event processes. Furthermore, it can help to have a better understanding of environmental changes in arid regions and the understanding of global climate change.
{"title":"Episodic Events On Radar And Multispectral Remote Sensors From Salar De Aguas Calientes, Chile","authors":"A. Delsouc, M. Barber, W. Pérez-Martínez, I. Briceño-De-Urbaneja","doi":"10.1109/lagirs48042.2020.9165626","DOIUrl":"https://doi.org/10.1109/lagirs48042.2020.9165626","url":null,"abstract":"Restricted episodic changes occurred in a short time period and over large spatial extents. Extreme weather conditions usually give rise to restricted episodic changes. Sentinel-1 radar images of the Salar de Aguas Calientes in Chile acquired in the Altiplanic winter (March 2015 and June 2017), 2018 austral winter and 2017-2018 springtime, demonstrates the ability to monitor episodic events remotely. The results of the backscattered power are encouraging and show episodic variations in VV polarization at C-band. The surface features in Salar de Aguas Calientes Sur change in response to snowfalls during either the Altiplanic or austral winter with an increase of the backscattering in presence of dry snow over the salt pan crust. Flooding events related to snow-melting during spring 2017-2018 showed a decrease in the backscattering signal over ponded water and an increase when wind blows over the water. Remote-sensing observations of the salar can provide a means for monitoring changes in the surface of the salar and a better understanding of the associated climatic episodic event processes. Furthermore, it can help to have a better understanding of environmental changes in arid regions and the understanding of global climate change.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117216559","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 : 2020-03-01DOI: 10.1109/lagirs48042.2020.9165642
M. B. Pereira, J. A. D. Santos
High-resolution images for remote sensing applications are often not affordable or accessible, especially when in need of a wide temporal span of recordings. Given the easy access to low-resolution (LR) images from satellites, many remote sensing works rely on this type of data. The problem is that LR images are not appropriate for semantic segmentation, due to the need for high-quality data for accurate pixel prediction for this task. In this paper, we propose an end-to-end framework that unites a super-resolution and a semantic segmentation module in order to produce accurate thematic maps from LR inputs. It allows the semantic segmentation network to conduct the reconstruction process, modifying the input image with helpful textures. We evaluate the framework with three remote sensing datasets. The results show that the framework is capable of achieving a semantic segmentation performance close to native high-resolution data, while also surpassing the performance of a network trained with LR inputs.
{"title":"An End-To-End Framework For Low-Resolution Remote Sensing Semantic Segmentation","authors":"M. B. Pereira, J. A. D. Santos","doi":"10.1109/lagirs48042.2020.9165642","DOIUrl":"https://doi.org/10.1109/lagirs48042.2020.9165642","url":null,"abstract":"High-resolution images for remote sensing applications are often not affordable or accessible, especially when in need of a wide temporal span of recordings. Given the easy access to low-resolution (LR) images from satellites, many remote sensing works rely on this type of data. The problem is that LR images are not appropriate for semantic segmentation, due to the need for high-quality data for accurate pixel prediction for this task. In this paper, we propose an end-to-end framework that unites a super-resolution and a semantic segmentation module in order to produce accurate thematic maps from LR inputs. It allows the semantic segmentation network to conduct the reconstruction process, modifying the input image with helpful textures. We evaluate the framework with three remote sensing datasets. The results show that the framework is capable of achieving a semantic segmentation performance close to native high-resolution data, while also surpassing the performance of a network trained with LR inputs.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124909805","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165638
M. Lachaise, B. Schweißhelm, T. Fritz
Since 2017, the TanDEM-X mission aims to acquire data globally to generate another (updated) DEM. This new set of acquisitions, which will be complete in 2020, has a clear temporal separation from those used for the TanDEM-X global DEM. It will therefore allow the creation of a temporally independent DEM, the so-called “TanDEM-X Change DEM” enabling the characterization of terrain changes. Since only one global coverage is being acquired, improvements in e.g. the interferometric data processing are necessary. In particular, an edited version of the existing global TanDEM-X DEM is now the “starting point” for the interferometric processing as detailed in this paper.
{"title":"The New Tandem-X Change Dem: Specifications And Interferometric Processing","authors":"M. Lachaise, B. Schweißhelm, T. Fritz","doi":"10.1109/LAGIRS48042.2020.9165638","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165638","url":null,"abstract":"Since 2017, the TanDEM-X mission aims to acquire data globally to generate another (updated) DEM. This new set of acquisitions, which will be complete in 2020, has a clear temporal separation from those used for the TanDEM-X global DEM. It will therefore allow the creation of a temporally independent DEM, the so-called “TanDEM-X Change DEM” enabling the characterization of terrain changes. Since only one global coverage is being acquired, improvements in e.g. the interferometric data processing are necessary. In particular, an edited version of the existing global TanDEM-X DEM is now the “starting point” for the interferometric processing as detailed in this paper.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126781279","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165594
S. Mariscal, M. Ríos, F. Soria
Forest fires have negative effects on biodiversity, the atmosphere and human health. The paper presents a spatial risk model as a tool to assess them. Risk areas refer to sectors prone to the spread of fire, in addition to the influence of human activity through remote sensing and multi-criteria analysis. The analysis includes information on land cover, land use, topography (aspect, slope and elevation), climate (temperature and precipitation) and socio-economic factors (proximity to settlements and roads). Weights were assigned to each in order to generate the forest fire risk map. The investigation was carried for a Biological Reserve in Bolivia because of the continuous occurrence of forest fires. Five risk categories for forest fires were derived: very high, high, moderate, low and very low. In summary, results suggest that approximately 67% of the protected area presents a moderate to very high risk; in the latter, populated areas are not dense which reduces the actual risk to the type of events analyzed.
{"title":"Multicriteria Analysis For Identifying Forest Fire Risk Zones In The Biological Reserve Of The Sama Cordillera, Bolivia","authors":"S. Mariscal, M. Ríos, F. Soria","doi":"10.1109/LAGIRS48042.2020.9165594","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165594","url":null,"abstract":"Forest fires have negative effects on biodiversity, the atmosphere and human health. The paper presents a spatial risk model as a tool to assess them. Risk areas refer to sectors prone to the spread of fire, in addition to the influence of human activity through remote sensing and multi-criteria analysis. The analysis includes information on land cover, land use, topography (aspect, slope and elevation), climate (temperature and precipitation) and socio-economic factors (proximity to settlements and roads). Weights were assigned to each in order to generate the forest fire risk map. The investigation was carried for a Biological Reserve in Bolivia because of the continuous occurrence of forest fires. Five risk categories for forest fires were derived: very high, high, moderate, low and very low. In summary, results suggest that approximately 67% of the protected area presents a moderate to very high risk; in the latter, populated areas are not dense which reduces the actual risk to the type of events analyzed.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122954853","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165566
J. Doblas, A. Carneiro, Y. Shimabukuro, S. Sant’anna, L. Aragão
This work aims to determinate the relationship between C-band SAR backscattering measurements over Amazonian tropical forests and hourly precipitation rates, and to study the feasibility of a SAR-anomaly masking method based on orbital rain measurements. To do so, a comprehensive dataset of ESA’s Sentinel-1 backscattering data and the concomitant GPM-IMERG precipitation data was collected and analysed. Backscattering anomalies were characterized in a statistically meaningful way. GAM models were then adjusted to the backscatter-rain data pairs. The computed models show a positive correlation between non-anomalous backscattering values and accumulated rain, of approximately 0,2 dB/mm·h$^{-1}$ and 0,4 dB/mm·h$^{-1}$ for VV and VH polarizations. Negative anomalies, which can easily mislead deforestation algorithms, have a strong negative correlation with rain rate observed at the time of the SAR acquisition. This is especially true for VV measurements. The subsequent anomaly masking procedure, based on computed accumulated and hourly rain thresholding, yielded unsatisfactory results. These poor results are probably due to the coarse resolution of the 0.1° GPM-IMERG data, which is insufficient to track anomaly-generating atmospheric events such as storm rain cells. Rainrelated changes in SAR backscattering can compromise deforestation detection algorithms, and further research and sensor developing is needed to increase spatial resolution of precipitation measures, to reach an optimal backscattering anomaly screening
{"title":"Assessment of rainfall influence on sentinel-1 time series on amazonian tropical forests aiming deforestation detection improvement","authors":"J. Doblas, A. Carneiro, Y. Shimabukuro, S. Sant’anna, L. Aragão","doi":"10.1109/LAGIRS48042.2020.9165566","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165566","url":null,"abstract":"This work aims to determinate the relationship between C-band SAR backscattering measurements over Amazonian tropical forests and hourly precipitation rates, and to study the feasibility of a SAR-anomaly masking method based on orbital rain measurements. To do so, a comprehensive dataset of ESA’s Sentinel-1 backscattering data and the concomitant GPM-IMERG precipitation data was collected and analysed. Backscattering anomalies were characterized in a statistically meaningful way. GAM models were then adjusted to the backscatter-rain data pairs. The computed models show a positive correlation between non-anomalous backscattering values and accumulated rain, of approximately 0,2 dB/mm·h$^{-1}$ and 0,4 dB/mm·h$^{-1}$ for VV and VH polarizations. Negative anomalies, which can easily mislead deforestation algorithms, have a strong negative correlation with rain rate observed at the time of the SAR acquisition. This is especially true for VV measurements. The subsequent anomaly masking procedure, based on computed accumulated and hourly rain thresholding, yielded unsatisfactory results. These poor results are probably due to the coarse resolution of the 0.1° GPM-IMERG data, which is insufficient to track anomaly-generating atmospheric events such as storm rain cells. Rainrelated changes in SAR backscattering can compromise deforestation detection algorithms, and further research and sensor developing is needed to increase spatial resolution of precipitation measures, to reach an optimal backscattering anomaly screening","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114564623","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165641
N. S. Rocha, P. Käfer, D. Skokovic, G. Veeck, L. R. Diaz, E. Kaiser, C. M. Carvalho, Bijeesh K V, S. Costa, R. Cruz, D. Robérti, S. Rolim
Ecosystem evapotranspiration (ET) has been quantified around the world by different methodologies to understand the energy balance, especially to control the evolution of climate change. It is known that the vegetation of the pampa biome is natural grasslands, it has a large variety of species (flora and fauna), however is it different in the environmental aspects related to the energy balance when compared to the grassland cultivated? In this study the objective was to analyze the environmental differences of the Pampa Biome related to the energy balance in comparison with the pastures cultivated in Barrax, Spain. In the first one the minimum daily ET is 0.99 mm/day, while in the second is 1.57 mm/day. However, the highest differences between the sites occur during the summer period, in the maximum daily ET, the maximum is 16.25 mm/day in Pampa and in Barrax is 7. 31mm/day. The results of this study have indicated that the characteristics of the Pampa biome, both in terms of soil and climatic issues and land use, generate differences in the energy balance when compared to similar vegetation in other regions of the world.
{"title":"Pampa Biome Environmental Particularities Regarding to Energy Balance","authors":"N. S. Rocha, P. Käfer, D. Skokovic, G. Veeck, L. R. Diaz, E. Kaiser, C. M. Carvalho, Bijeesh K V, S. Costa, R. Cruz, D. Robérti, S. Rolim","doi":"10.1109/LAGIRS48042.2020.9165641","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165641","url":null,"abstract":"Ecosystem evapotranspiration (ET) has been quantified around the world by different methodologies to understand the energy balance, especially to control the evolution of climate change. It is known that the vegetation of the pampa biome is natural grasslands, it has a large variety of species (flora and fauna), however is it different in the environmental aspects related to the energy balance when compared to the grassland cultivated? In this study the objective was to analyze the environmental differences of the Pampa Biome related to the energy balance in comparison with the pastures cultivated in Barrax, Spain. In the first one the minimum daily ET is 0.99 mm/day, while in the second is 1.57 mm/day. However, the highest differences between the sites occur during the summer period, in the maximum daily ET, the maximum is 16.25 mm/day in Pampa and in Barrax is 7. 31mm/day. The results of this study have indicated that the characteristics of the Pampa biome, both in terms of soil and climatic issues and land use, generate differences in the energy balance when compared to similar vegetation in other regions of the world.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130552277","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165609
Eduarda T. C. Chagas, A. Frery, O. Rosso, Heitor S. Ramos
We propose a new technique for SAR image texture characterization based on ordinal pattern transition graphs. The proposal consists in (i) transforming a 2-D patch of data into a time series using a Hilbert Space Filling Curve, (ii) building an Ordinal Pattern Transition Graph with weighted edges; (iii) obtaining a probability distribution function from this graph; (iv) computing the Entropy and Statistical Complexity of this distribution. The weight of the edges is related to the absolute difference of observations. This modification takes into account the scattering properties of the target, and leads to a good characterization of several types of textures. Experiments with data from Munich urban areas, Guatemala forest regions, and Cape Canaveral ocean samples demonstrate the effectiveness of our technique, which achieves satisfactory levels of separability.
{"title":"Characterization Of Sar Images With Weighted Amplitude Transition Graphs","authors":"Eduarda T. C. Chagas, A. Frery, O. Rosso, Heitor S. Ramos","doi":"10.1109/LAGIRS48042.2020.9165609","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165609","url":null,"abstract":"We propose a new technique for SAR image texture characterization based on ordinal pattern transition graphs. The proposal consists in (i) transforming a 2-D patch of data into a time series using a Hilbert Space Filling Curve, (ii) building an Ordinal Pattern Transition Graph with weighted edges; (iii) obtaining a probability distribution function from this graph; (iv) computing the Entropy and Statistical Complexity of this distribution. The weight of the edges is related to the absolute difference of observations. This modification takes into account the scattering properties of the target, and leads to a good characterization of several types of textures. Experiments with data from Munich urban areas, Guatemala forest regions, and Cape Canaveral ocean samples demonstrate the effectiveness of our technique, which achieves satisfactory levels of separability.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116214620","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165647
D. Ballari, L. Campozano, E. Samaniego, D. Orellana
Climate teleconnections show remote and large-scale relationships between distant points on Earth. Their relations to precipitation are important to monitor and anticipate the anomalies that they can produce in the local climate, such as flood and drought events impacting agriculture, health, and hydropower generation. Climate teleconnections in relation to precipitation have been widely studied. Nevertheless, the spatial association of the teleconnection patterns (i.e., the spatial delineation of regions with teleconnections) has been unattended. Such spatial association allows to characterize how stable (heterogeneity/dependent and statistically significant) is the underlying spatial phenomena for a given pattern. Thus our objective was to characterize the spatial association of climate teleconnection patterns related to precipitation using an exploratory spatial data analysis approach. Global and local indicators of spatial association (Moran’s I and LISA) were used to detect spatial patterns of teleconnections based on TRMM satellite images and climate indices. Moran’s I depicted high positive spatial association for different climate indices, and LISA depicted two types of teleconnections patterns. The homogenous patterns were localized in the Coast and Amazonian regions, meanwhile the disperse patterns had a major presence in the Highlands. The results also showed some areas that, although with moderate to high teleconnection influences, had a random spatial patterns (i.e., non-significant spatial association). Other areas showed both teleconnections and significant spatial association, but with dispersed patterns. This pointed out the need to explore the local underlying features (topography, orientation, wind and micro-climates) that restrict (non-significant spatial association) or reaffirm (disperse patterns) the teleconnection patterns.
{"title":"Spatial Association To Characterize The Climate Teleconnection Patterns In Ecuador Based On Satellite Precipitation Estimates","authors":"D. Ballari, L. Campozano, E. Samaniego, D. Orellana","doi":"10.1109/LAGIRS48042.2020.9165647","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165647","url":null,"abstract":"Climate teleconnections show remote and large-scale relationships between distant points on Earth. Their relations to precipitation are important to monitor and anticipate the anomalies that they can produce in the local climate, such as flood and drought events impacting agriculture, health, and hydropower generation. Climate teleconnections in relation to precipitation have been widely studied. Nevertheless, the spatial association of the teleconnection patterns (i.e., the spatial delineation of regions with teleconnections) has been unattended. Such spatial association allows to characterize how stable (heterogeneity/dependent and statistically significant) is the underlying spatial phenomena for a given pattern. Thus our objective was to characterize the spatial association of climate teleconnection patterns related to precipitation using an exploratory spatial data analysis approach. Global and local indicators of spatial association (Moran’s I and LISA) were used to detect spatial patterns of teleconnections based on TRMM satellite images and climate indices. Moran’s I depicted high positive spatial association for different climate indices, and LISA depicted two types of teleconnections patterns. The homogenous patterns were localized in the Coast and Amazonian regions, meanwhile the disperse patterns had a major presence in the Highlands. The results also showed some areas that, although with moderate to high teleconnection influences, had a random spatial patterns (i.e., non-significant spatial association). Other areas showed both teleconnections and significant spatial association, but with dispersed patterns. This pointed out the need to explore the local underlying features (topography, orientation, wind and micro-climates) that restrict (non-significant spatial association) or reaffirm (disperse patterns) the teleconnection patterns.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114725876","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 : 2020-03-01DOI: 10.1109/LAGIRS48042.2020.9165565
E. Schwalbe, R. Koschitzki, E. Johnson, D. F. Mojica Moncada, B. Schröter, C. Cárdenas, G. Casassa, H. Maas
A network consisting of six cameras was set up on both sides of Lange Glacier on King George Island, Antarctica, for a period of two years to monitor changes in the glacier’s motion behaviour. The cameras were observing spatio-temporal glacier surface velocity vector fields as well as the position of the glacier front. Velocity field information was obtained from image sequences by applying subpixel accuracy photogrammetric image sequence analysis techniques. Georeferencing in a superordinate coordinate system was performed via integrated photogrammetric-geodetic network adjustment. As a result, velocity fields were determined with maximum glacier surface velocities in the order of 1.5 meter per day. The results of terrestrial camera image sequence processing can be used as validation and calibration reference for satellite image based glacier velocity dynamics calculations. Moreover, the very high temporal resolution of the image sequences taken at 20 minute time intervals can also be used to analyse highly dynamic processes.
在南极洲乔治王岛的兰格冰川两侧建立了一个由6台摄像机组成的网络，为期两年，以监测冰川运动行为的变化。相机观测了冰川表面的时空速度矢量场和冰川锋的位置。采用亚像素精度摄影测量图像序列分析技术，从图像序列中获取速度场信息。通过综合摄影测量-大地测量网平差实现上坐标系的地理参考。结果，以最大冰川表面速度为1.5 m / d确定速度场。陆地相机图像序列处理结果可作为基于卫星图像的冰川速度动力学计算的验证和定标参考。此外，以20分钟的时间间隔拍摄的图像序列的非常高的时间分辨率也可用于分析高度动态的过程。
{"title":"Stereo-Photogrammetric Measurement Of Spatio-Temporal Velocity Fields At Lange Glacier, King George Island","authors":"E. Schwalbe, R. Koschitzki, E. Johnson, D. F. Mojica Moncada, B. Schröter, C. Cárdenas, G. Casassa, H. Maas","doi":"10.1109/LAGIRS48042.2020.9165565","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165565","url":null,"abstract":"A network consisting of six cameras was set up on both sides of Lange Glacier on King George Island, Antarctica, for a period of two years to monitor changes in the glacier’s motion behaviour. The cameras were observing spatio-temporal glacier surface velocity vector fields as well as the position of the glacier front. Velocity field information was obtained from image sequences by applying subpixel accuracy photogrammetric image sequence analysis techniques. Georeferencing in a superordinate coordinate system was performed via integrated photogrammetric-geodetic network adjustment. As a result, velocity fields were determined with maximum glacier surface velocities in the order of 1.5 meter per day. The results of terrestrial camera image sequence processing can be used as validation and calibration reference for satellite image based glacier velocity dynamics calculations. Moreover, the very high temporal resolution of the image sequences taken at 20 minute time intervals can also be used to analyse highly dynamic processes.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131530249","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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