2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)最新文献_第6页

Ionospheric dynamics of two geomagnetic storms at South America sector 南美洲两个地磁风暴的电离层动力学

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165599

José Augusto Gomes Vieira, E. Correia, C. M. Paulo, Lady Ângulo, E. P. Macho

{"title":"Ionospheric dynamics of two geomagnetic storms at South America sector","authors":"José Augusto Gomes Vieira, E. Correia, C. M. Paulo, Lady Ângulo, E. P. Macho","doi":"10.1109/LAGIRS48042.2020.9165599","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165599","url":null,"abstract":"The ionospheric dynamics at South America (SA) sector during the two strongest geomagnetic storms of the 24th solar cycle is investigated; one of them occurred within the period from 15 to 20 March 2015, and the other one, from 21 to 25 June 2015. The ionospheric analysis includes total electron content and F2-layer critical frequency, using GNSS receivers and ionosondes instruments from low to high latitudes at SA stations. Preliminary results show that geomagnetic storm started on 17/03/2015 at 6:00 UT, reaching -220 nT in the negative phase, classifying the geomagnetic storm as “Intense”. The Kp index reached 6 and was classified as “Very Disturbed”, and on the same day the AE index reached 1700 nT. According to the variation of the magnetic field, the recovery phase started on 18/03/2015, as shown by the Embrace Magnetometer Network. In the ionograms the storm affected the critical frequency of plasma in the foF2 layer, compared to the day before the storm there was little variation. The most altered ionogram was from the city of Fortaleza - CE (15/03/2015 22:00 UT) with a value of (15Mhz), local time 17: 00h. The TEC variation for the geomagnetic storm of 17/03/2015. Instruments such as Global Navigation Satellite System (GNSS) receivers and ionospheres are important tools for investigating the ionospheric response to a geomagnetic storm (Correia et al., 2017; Yizengaw et al., 2005; Mendillo et al., 2000; Skone et al., 2000). Investigations were conducted by Mansilla et al. (2018) using GNSS receivers to analyze the Total Electron Content (TEC) due to the June 2015 storm in a global context, showing important CETs at mid-latitude stations throughout the Northern Hemisphere (summer) during the development of the main phase. At equatorial and low latitudes, at the beginning of the geomagnetic storm, there were increases in CET due to PPEF. Such increases were also observed in the Southern Hemisphere (winter).","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"17 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":"132871794","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

Evaluation Of The Soil Moisture Agricultural Drought Index (SMADI) And Precipitation-Based Drought Indices In Argentina 阿根廷土壤水分农业干旱指数(SMADI)和基于降水的干旱指数评价

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165603

M. Salvia, N. Sánchez, M. Piles, Á. González-Zamora, J. Martínez-Fernández

{"title":"Evaluation Of The Soil Moisture Agricultural Drought Index (SMADI) And Precipitation-Based Drought Indices In Argentina","authors":"M. Salvia, N. Sánchez, M. Piles, Á. González-Zamora, J. Martínez-Fernández","doi":"10.1109/LAGIRS48042.2020.9165603","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165603","url":null,"abstract":"Agricultural drought is one of the most critical hazards with regard to intensity, severity, frequency, spatial extension and impact on livelihoods. This is especially true for Argentina, where agricultural exports can represent up to 10% of gross domestic product (GDP), and where drought events for 2018 led to a decrease of nearly 0.5% of GDP. In this work, we investigate the applicability of the Soil Moisture Agricultural Drought Index (SMADI) for detection of droughts in Argentina, and compare its performance with the use of two well-known precipitation-based indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evaporation Index (SPEI). SMADI includes satellite-based information of soil moisture, surface temperature and vegetation greenness, and was designed to capture the hydric stress on the soil-vegetation ensemble. Results indicate that SMADI has greater capabilities for agricultural drought detection than SPI and SPEI: it was able to recognize more than 83% of the registered emergencies, correctly classifying 75% of them as extreme droughts, and outperforming SPI and SPEI in all the analyzed metrics.","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":"134064614","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

Improved Biomass and Burning Efficiency Factors for Foerst Fir Emissions Estimation in Central Chile 改进的生物质和燃烧效率因子对森林冷杉排放估算在智利中部

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165644

P. Oliva, N. Medina, L. Durán, P. Vidal

引用次数: 1

Analyzing Long-Term Availability Of Urban Green Space By Socioeconomic Status In Medellin, Colombia, Using Open Data And Tools 利用开放数据和工具分析哥伦比亚麦德林市社会经济地位下城市绿地的长期可用性

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165672

Jorge E. Patiño

引用次数: 2

Can Smos Soil Moisture Dry-Downs Be Useful To Detect Flood Conditions Over The Argentinean Pampas Plains? 在阿根廷潘帕斯平原上，Smos土壤水分干涸是否有助于探测洪水状况?

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165658

L. Cappelletti, A. Sörensson, R. Ruscica, M. Salvia, E. Jobbágy, S. Kuppel, L. Fita

{"title":"Can Smos Soil Moisture Dry-Downs Be Useful To Detect Flood Conditions Over The Argentinean Pampas Plains?","authors":"L. Cappelletti, A. Sörensson, R. Ruscica, M. Salvia, E. Jobbágy, S. Kuppel, L. Fita","doi":"10.1109/LAGIRS48042.2020.9165658","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165658","url":null,"abstract":"The process of soil drying following a single rainfall input offers an integrated perspective on soil-vegetation water dynamics in responses to atmospheric conditions during periods without rainfall. In this work, the soil moisture dry-down time scale events $( tau)$ was calculated using surface soil moisture data from the SMOS mission, with the objective to explore if the spatio-temporal variability of $tau$ could be used as a proxy for regional flooding and waterlogging characterization. Our working hypothesis is that soil moisture dries up more slowly under flooded conditions as a result of slower surface water elimination by infiltration and capillary rise of water from the saturated zone close to the surface. A clear difference precipitation-moisture coupling was detected between two regions with different flooding dynamics. In a region where flooding is triggered by precipitation excesses on weekly-to-monthly time scales and where the coupling between precipitation and evapotranspiration is strong, a positive correlation between dry-down and 6-month accumulated precipitation anomaly was found for all seasons except winter. By contrast, in the other region where flooding is largely de-coupled from precipitation and evapotranspiration, but rather coupled to ground water table dynamics on time scales from several months to years, no significant correlations were found. These results are based on a short period of data: March 2010 – November 2014.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"16 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":"128389118","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

Assessment Of Pca And Mnf Influence In The Vhr Satellite Image Classifications Pca和Mnf在Vhr卫星图像分类中的影响评估

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165680

P. C. Molina, M. P. Castro, C. S. Anjos

{"title":"Assessment Of Pca And Mnf Influence In The Vhr Satellite Image Classifications","authors":"P. C. Molina, M. P. Castro, C. S. Anjos","doi":"10.1109/LAGIRS48042.2020.9165680","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165680","url":null,"abstract":"Orbital images have been increasingly refined spatially as spectrally as that is the case with those provided by satellite Earth observation WorldView-3 used in this paper. However, the images are very susceptible to noise interference, so it is difficult to identify and characterize objects. Therefore, it is essential to use techniques to minimize them. Thus, through increasingly innovative processing, it is possible to carry out detailed characterization mainly of urban areas. This work aims to perform the classification of images Worldview-3 using the advanced methods of classification Random Forest and Deep Learning for the region of Botafogo in the municipality of Rio de Janeiro, Brazil. Such classifications were performed for four different data sets, including the spectral bands and transformations (MNF and PCA) resulting from the original images. The results demonstrate that the use of transformations resulting from the original images as input data for the extraction of attributes in conjunction with the spectral bands improves the accuracy of the classifications generated by the Random Forest and Deep Learning method.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"22 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":"128646450","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

Atmospheric Methane Emissions for Argentina. Comparison with TROPOMI Satellite Mesurements 阿根廷的大气甲烷排放量。与TROPOMI卫星测量值的比较

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165602

S. Puliafito, L. Berná, A. López-Noreña, R. Pascual, T. Bolaño-Ortiz

{"title":"Atmospheric Methane Emissions for Argentina. Comparison with TROPOMI Satellite Mesurements","authors":"S. Puliafito, L. Berná, A. López-Noreña, R. Pascual, T. Bolaño-Ortiz","doi":"10.1109/LAGIRS48042.2020.9165602","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165602","url":null,"abstract":"Methane emissions have very important effect on global radiative forcing. Therefore, reducing these emissions has been proposed as an effective short-term strategy to mitigate global warming, in parallel with reductions in long-lived carbon dioxide (CO2) for long-term temperature stabilizations. In this context, Argentina emits 3645 Gg of CH4 mainly from livestock production, biomass burning and natural gas production. Since 2018, TROPOMI instruments provide global coverage on methane column-average mole fraction of dry air (XCH4), and height profiles of methane concentrations. We compare two available methane inventory: a national (a high resolution of own ellaboration: GEAA) and an international (EDGAR) emissions database with TROPOMI measurements. By performing inverse satellite retrieval we evaluate the ability of remote sensing information to detect possible hotspot methane emissions and compare these results with the two inventories. From these analyzes, we observe that the latitudinal averages of the continental sector increase at a rate of 10 ppb/degree, from south to north, while the maritime sector remains constant. From a temporary perspective, the average monthly concentration amplitude range varies 40 to 50 ppb, with minimum values in March and maximum values in September.","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":"134135141","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

Pasture Land Cover Change in São Paulo State, Brazil 巴西<s:1>圣保罗州牧场土地覆盖变化

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165662

J. D. Oliveira, R. Lamparelli, G. Figueiredo, E. Campbell, J. Soares, L. Monteiro, M. Vianna, D. Jaiswal, A. F. Bonamigo, J. Sheehan, L. Lynd

{"title":"Pasture Land Cover Change in São Paulo State, Brazil","authors":"J. D. Oliveira, R. Lamparelli, G. Figueiredo, E. Campbell, J. Soares, L. Monteiro, M. Vianna, D. Jaiswal, A. F. Bonamigo, J. Sheehan, L. Lynd","doi":"10.1109/LAGIRS48042.2020.9165662","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165662","url":null,"abstract":"Pastures are complex land covers with a variety of land use systems. This land cover occupies large areas in the globe and is mainly used for livestock production. Brazil is one of the largest livestock producers and has extensive pasture areas. We analyzed the pasture land cover change of the São Paulo State between the years 2000 to 2015. São Paulo was chosen as study case due to its large industrial and agricultural importance and its expressive land cover changes over past decades. It was analyzed land covers databases generated by the Brazilian Annual Land Use and Land Cover Mapping Project (MapBiomas Project) – Collection 4. Transition matrix was generated to analyze the land cover change during the period. Gain, loss, total change, net change and swap were calculated in terms of area. Total pasture area decreased but continues the largest land cover of the São Paulo State; with 79.5% of persistence in the area. Main changes were from losses of pastures and gains in agriculture. Most of the changes to pasture came from other non vegetated areas and grassland categories. These results demonstrated the relevance of pastures areas in land cover change dynamics to address land use policy and plan future land use scenarios.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"10 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":"126057349","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

Unsupervised Methodology to In-Season Mapping of Summer Crops in Uruguay with Modis EVI’s Temporal Series and Machine Learning. 使用Modis EVI时间序列和机器学习的乌拉圭夏季作物当季制图的无监督方法。

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165614

A. Cal, Guadalupe Tiscomia

{"title":"Unsupervised Methodology to In-Season Mapping of Summer Crops in Uruguay with Modis EVI’s Temporal Series and Machine Learning.","authors":"A. Cal, Guadalupe Tiscomia","doi":"10.1109/LAGIRS48042.2020.9165614","DOIUrl":"https://doi.org/10.1109/LAGIRS48042.2020.9165614","url":null,"abstract":"This paper presents a new methodology for mapping summer crops in Uruguay, during the season, based on time-series analysis of the EVI vegetation index derived from the MODIS sensor. Time-series were processed with the k-means unsupervised machine learning algorithm. For this algorithm, the ideal number of clusters was estimated using the elbow method. Once the clusters were obtained, for each one, the average phenological signature was adjusted using a nonlinear smoothing spline regression technique. Additionally, using the derivative analysis, the key points of the curve were estimated (minimum, maximum and inflection points). When analyzing the average signature of each cluster, those whose signature follows the seasonal pattern of an agricultural crop (similar to a Gaussian function) were selected to generate a binary map of crops/non-crops. The estimated crop area is 2,336,525 hectares, higher than the official statistics of l,667,400 hectares for the 2014–15 season. This overestimation can be explained by the resolution of the MODIS pixel (250 meters), where each has a different degree of purity; and commission errors. The methodology was validated with 5,317 ground truth points, with a general accuracy of 95.8%, kappa index of 85.6, production and user accuracy of 85.1% and 91.3% for crops/non-crops.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"28 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":"125997757","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

Impact Of Segmentation Parameters On The Classification Of VHR Images Acquired By RPAS 分割参数对RPAS获取的VHR图像分类的影响

2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) Pub Date : 2020-03-01 DOI: 10.1109/LAGIRS48042.2020.9165637

M. G. Lacerda, E. H. Shiguemori, A. Damiao, C. S. Anjos, M. Habermann

引用次数: 0