2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)最新文献_第8页

Potentialities of Sentinel-1 for mapping and monitoring geological and cryospheric processes in the Patagonia region (Chile) 哨兵-1在巴塔哥尼亚地区测绘和监测地质和冰冻圈过程方面的潜力(智利)

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165564

O. Monserrat, C. Cárdenas, P. Olea, V. Krishnakumar, B. Crippa

{"title":"Potentialities of Sentinel-1 for mapping and monitoring geological and cryospheric processes in the Patagonia region (Chile)","authors":"O. Monserrat, C. Cárdenas, P. Olea, V. Krishnakumar, B. Crippa","doi":"10.1109/LAGIRS48042.2020.9165564","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165564","url":null,"abstract":"This work shows two examples on the use of Sentinel-1 data for monitoring different natural processes, like active geohazards or glacier dynamics in the Patagonia region. Sentinel-1 is a two-satellite constellation, launched by the European Space Agency (ESA), that provides SAR imagery with interferometric capabilities. It is in operation since 2014 and has supposed a significant improvement in the exploitation of these type of data for applications like natural hazards mapping and monitoring. The acquisition policy, that guarantees an acquisition each few days (12 days in Patagonia region) for both ascending and descending trajectories, and the data distribution policy, that allows free access to the images without legal constrains, are the main reasons for this improvement. These two aspects allowed not only to assure the data in the past but also to perform monitoring plans at medium-long term. In this work we show the potentialities of the use of these data in the Patagonia region through the application of two different techniques in two different application test sites: urban areas and glaciers.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"9 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":"115535008","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}

引用次数: 0

Application of Semantic Segmentation with Few Labels in the Detection of Water Bodies from Perusat-1 Satellite’s Images 少标签语义分割在Perusat-1卫星图像水体检测中的应用

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165643

J. González, K. Sankaran, V. Ayma, C. Beltrán

{"title":"Application of Semantic Segmentation with Few Labels in the Detection of Water Bodies from Perusat-1 Satellite’s Images","authors":"J. González, K. Sankaran, V. Ayma, C. Beltrán","doi":"10.1109/LAGIRS48042.2020.9165643","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165643","url":null,"abstract":"Remote sensing is widely used to monitor earth surfaces with the main objective of extracting information from it. Such is the case of water surface, which is one of the most affected extensions when flood events occur, and its monitoring helps in the analysis of detecting such affected areas, considering that adequately defining water surfaces is one of the biggest problems that Peruvian authorities are concerned with. In this regard, semiautomatic mapping methods improve this monitoring, but this process remains a time-consuming task and into the subjectivity of the experts.In this work, we present a new approach for segmenting water surfaces from satellite images based on the application of convolutional neural networks. First, we explore the application of a U-Net model and then a transfer knowledge-based model. Our results show that both approaches are comparable when trained using an 680-labelled satellite image dataset; however, as the number of training samples is reduced, the performance of the transfer knowledge-based model, which combines high and very high image resolution characteristics, is improved.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"22 4 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":"123728203","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}

引用次数: 4

Mapping Extension and Magnitude of Changes Induced by Cyclone Idai with Multi-Temporal Landsat and Sar Images 基于多时相Landsat和Sar影像的气旋伊代的制图扩展和变化幅度

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165657

C. Amisse, M. E. Jijón-Palma, Jorge Antonio Silva Centeno

引用次数: 1

Cellular Automata Model - Landscape Dynamics Simulation Tool in the Process of Change in Land Use and Cover in the City of GaÚCha Do Norte – Mt 元胞自动机模型——GaÚCha城市土地利用/覆被变化过程中的景观动态模拟工具

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165590

E. Pinheiro, N. A. Camini, M. Soares, S. Sumida

{"title":"Cellular Automata Model - Landscape Dynamics Simulation Tool in the Process of Change in Land Use and Cover in the City of GaÚCha Do Norte – Mt","authors":"E. Pinheiro, N. A. Camini, M. Soares, S. Sumida","doi":"10.1109/LAGIRS48042.2020.9165590","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165590","url":null,"abstract":"The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"1 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":"130153693","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}

引用次数: 2

Multi-Scale Time Series Analysis Of Evapotranspiration For High-Throughput Phenotyping Frequency Optimization 高通量表型频率优化的蒸散发多尺度时间序列分析

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165630

Soumyashree Kar, Ryokei Tanaka, H. Iwata, J. Kholová, S. Durbha, J. Adinarayana, V. Vadez

{"title":"Multi-Scale Time Series Analysis Of Evapotranspiration For High-Throughput Phenotyping Frequency Optimization","authors":"Soumyashree Kar, Ryokei Tanaka, H. Iwata, J. Kholová, S. Durbha, J. Adinarayana, V. Vadez","doi":"10.1109/LAGIRS48042.2020.9165630","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165630","url":null,"abstract":"This work is undertaken considering the significance of functional phenotyping (primarily measured from continuous profiles of plant-water relations) for crop selection purposes. High-Throughput Plant Phenotyping (HTPP) platforms which largely employ state-of-the-art sensor technologies for acquisition of vast amount of field data, often fail to efficiently translate sensor information into knowledge due to the major challenges of data handling and processing. Hence, it is imperative to concurrently find a way for dissociating noise from useful data. Additionally, another important aspect is understanding how frequent should be the data collection, so that information is maximized. This paper presents a novel approach for identifying the optimal frequency for phenotyping evapotranspiration (ET) by assimilating results from both time series forecast as well as classification models. Thus, at the optimal frequency, plant-water relations can not only be desirably predicted but genotypes can also be classified based on the characteristics of their ET profiles. Consequently, this will aid better crop selection, besides minimizing noise, redundancy, cost and effort in HTPP data collection. High frequency (15 min) ET time series data of 48 chickpea varieties (with considerable genotypic diversity) collected at the LeasyScan HTPP platform, ICRISAT is used for this study. Time series forecast and classification is performed by varying frequency up to 180 min. Multiple performance measures of time series forecast and classification are combined, followed by implementation of entropy theory for sampling frequency optimization. The results demonstrate that ET time series with a frequency of 60 min per day potentially yield the optimum information.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"35 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":"128532645","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}

引用次数: 0

From Space to Earth: physical and biological impacts of glacier dynamics in the marine system by means of Remote Sensing at Almirantazgo Bay, Antarctica 从空间到地球:南极Almirantazgo湾冰川动态在海洋系统中的物理和生物影响的遥感研究

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165686

C. Cárdenas, G. Casassa, X. Aguilar, D. Mojica, E. Johnson, F. Brondi

{"title":"From Space to Earth: physical and biological impacts of glacier dynamics in the marine system by means of Remote Sensing at Almirantazgo Bay, Antarctica","authors":"C. Cárdenas, G. Casassa, X. Aguilar, D. Mojica, E. Johnson, F. Brondi","doi":"10.1109/LAGIRS48042.2020.9165686","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165686","url":null,"abstract":"To determine the biological and physical mechanisms between Lange glacier and its pro-glacier marine system located in Almirantazgo bay, King George Island, Antarctica, specific variables were determined through remote sensing approaches shown in this work. These preliminary results will allow relating the dynamics of both systems, the glacier, and the marine ecosystem. The information for the estimation of surface flux velocity of the glacier was derived through Radar satellite images (Sentinel-1) by means of offset tracking, the bathymetry was derived from a Multi-beam Echo Sounder, and the Digital Elevation Modell was obtained by means of a Remotely Piloted Aircraft; Finally, the biological parameters were derived from MODIS and OLCI images for the analysis of satellite data to have a first insight to the characteristics of the marine system. This information will help to build the first frame needed to study through remote sensing approaches, the mechanisms that govern the interface among “Lang Glacier” and the “Almirantazgo Bay” at King George Island, Antarctica.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"1 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":"130441899","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}

引用次数: 4

Which Variables in Forest Survey Data Can Better Distinguish Conserved and Degraded Tropical Dry Forest? 森林调查数据中哪些变量能更好地区分保存和退化的热带干林?

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/lagirs48042.2020.9165631

Yan Gao, D. Jimenez, M. Skutsch, M. Salinas, J. Solórzano

引用次数: 0

Wetland Mapping With Multitemporal Sentinel Radar Remote Sensing In The Southeast Region Of Brazil 巴西东南部多时相哨兵雷达湿地遥感制图

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165593

J. Salinas, M. K. P. Eggerth, M. E. Miller, R. R. B. Meza, J. Chacaltana, J. Acuña, G. Barroso

{"title":"Wetland Mapping With Multitemporal Sentinel Radar Remote Sensing In The Southeast Region Of Brazil","authors":"J. Salinas, M. K. P. Eggerth, M. E. Miller, R. R. B. Meza, J. Chacaltana, J. Acuña, G. Barroso","doi":"10.1109/LAGIRS48042.2020.9165593","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165593","url":null,"abstract":"A classification method with multi-temporal images of synthetic aperture radar (SAR) combined with Geographic information system, geoinformation data, and field validation, was applied for wetland mapping accuracy and typology. Wetland mapping is vital for management and conservation, particularly under environmental pressures such as wetland drainage and land reclamation. The aim of this study is to develop an accurate mapping of wetlands and open water systems of the Lower Doce River Valley - LDRV (Southeastern Brazil) with Synthetic Aperture Radar (SAR) imagery, using multitemporal classification techniques and ground truth validation. Sentinel-1B SAR imagery from 2016 and 2019 was processed with Google Earth Engine (GEE). Monthly median imagery condition for the rainy season was obtained and K-means unsupervised classification was applied. The study yields 4,157 wetlands, 262.27 km2 with predominant small patches. Fieldwork revealed three main wetlands categories: coastal wetlands, inland wetlands and artificial wetlands. The results have shown an overall accuracy of 81.9% and a Kappa coefficient of 0.71. Wetlands, non-wetlands, and open waters classes present accuracy of 50, 80 and 95%, respectively.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"13 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":"134543546","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}

引用次数: 5

Assessment of Volume and Above-Ground Biomass in Araucaria Forest Through Satellite Images, Comparing Different Methods in the South of Chile 通过卫星图像评估智利南部Araucaria森林的体积和地上生物量，比较不同方法

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165668

F. Pirotti, E. Kutchartt, E. Csaplovics

引用次数: 2

Automatic Building Change Detection Using Multi-Temporal Airborne Lidar Data 基于多时相机载激光雷达数据的楼宇变化自动检测

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165628

R. C. dos Santos, M. Galo, A. C. Carrilho, G. G. Pessoa, R. A. R. de Oliveira

引用次数: 8