ORCID Profile
0000-0003-3405-5096
Current Organisation
Universidade Federal de Minas Gerais
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Publisher: Elsevier BV
Date: 2015
Publisher: Copernicus GmbH
Date: 23-06-2016
DOI: 10.5194/ISPRS-ARCHIVES-XLI-B8-327-2016
Abstract: Abstract. Satellite altimetry is becoming a major tool for measuring water levels in rivers and lakes offering accuracies compatible with many hydrological applications, especially in uninhabited regions of difficult access. The Pantanal is considered the largest tropical wetland in the world and the sparsity of in situ gauging station make remote methods of water level measurements an attractive alternative. This article describes how satellites altimetry data from Envisat and Saral was used to determine water level in two small lakes in the Pantanal. By combining the water level with the water surface area extracted from satellite imagery, water volume fluctuations were also estimated for a few periods. The available algorithms (retrackers) that compute a range solution from the raw waveforms do not always produce reliable measurements in small lakes. This is because the return signal gets often “contaminated” by the surrounding land. To try to solve this, we created a “lake” retracker that rejects waveforms that cannot be attributed to “calm water” and convert them to altitude. Elevation data are stored in a database along with the water surface area to compute the volume fluctuations. Satellite water level time series were also produced and compared with the only nearby in situ gauging station. Although the “lake” retracker worked well with calm water, the presence of waves and other factors was such that the standard “ice1” retracker performed better on the overall. We estimate our water level accuracy to be around 75 cm. Although the return time of both satellites is only 35 days, the next few years promise to bring new altimetry satellite missions that will significantly increase this frequency.
Publisher: SPIE
Date: 21-10-2014
DOI: 10.1117/12.2067270
Publisher: Unpublished
Date: 2016
Publisher: Informa UK Limited
Date: 18-06-2015
Publisher: Informa UK Limited
Date: 2010
DOI: 10.5589/M10-059
Publisher: Elsevier BV
Date: 06-2018
Publisher: FapUNIFESP (SciELO)
Date: 2022
DOI: 10.1590/2318-0331.272220210110
Abstract: Abstract The “Mean Ordinary Flood Line” (MOFL) is a conceptual line adopted by Brazil’s Federal Government to delineate land within the floodplain under its ownership and jurisdiction having major social implications. Past attempts at the cartography of this line have encountered strong difficulties brought either by a low precision or an excessive cost. In this article, we propose a method based on historical water gauge data to determine the water level corresponding to the MOFL. Satellite images coincident with past dates when the MOFL was reached are selected and processed to extract the water surface from which the MOFL can then be produced. The approach was implemented in a 600 km reach of the São Francisco River in Minas Gerais as a pilot project. A field survey served to validate the results. The positional accuracy of the MOFL was estimated at 24 m which was considered excellent since mostly Landsat images with a spatial resolution of 30 m were used.
Publisher: IEEE
Date: 2005
DOI: 10.1109/CRV.2005.28
Publisher: Unpublished
Date: 2006
Publisher: Copernicus GmbH
Date: 03-08-2020
DOI: 10.5194/ISPRS-ANNALS-V-3-2020-401-2020
Abstract: Abstract. The low operational cost of using freely available remote sensing data is a strong incentive for water agencies to complement their field c aigns and produce spatially distributed maps of some water quality parameters. The objective of this study is to compare the performance of Sentinel-2 MSI and Landsat-8 OLI sensors to produce multiple regression models of water quality parameters in a hydroelectric reservoir in Brazil. Physical-chemistry water quality parameters were measured in loco using sensors and also analysed in laboratory from water s les collected simultaneously. The date of s ling corresponded to the almost simultaneous overflight of Sentinel-2B and Landsat-8 satellites which provided a means to perform a fair comparison of the two sensors. Four optically active parameters were considered: chlorophyll-a, Secchi disk depth, turbidity and temperature (the latter using Landsat-8 TIR sensor). Other six optically non-active parameters were also considered. The multiple regression models used the spectral reflectance bands from both sensors (separately) as predictors. The reflectance values were based on averaging kernels of 30 m and 90 m. Stepwise variable selection combined with a priori knowledge based on other studies were used to optimize the choice of predictors. With the exception of temperature, the other optically active parameters yielded strong regression models from both the Sentinel and Landsat sensors, all with r2 0.75. The models for the optically non-active parameters produced less striking results with r2 as low as 0.03 (temperature) and as high or better than 0.8 (pH and Dissolved oxygen).
Publisher: SPIE
Date: 16-10-2013
DOI: 10.1117/12.2028371
Publisher: SPIE
Date: 10-10-2018
DOI: 10.1117/12.2325382
Publisher: Informa UK Limited
Date: 04-05-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2005
Publisher: Copernicus GmbH
Date: 03-08-2020
DOI: 10.5194/ISPRS-ANNALS-V-3-2020-387-2020
Abstract: Abstract. A method is presented to produce river cross section profiles from a time series of Sentinel-1 images paired with water level data. Four programs are presented that generate river width data and cross section profiles from SAR or optical images. The programs generate a river bank and island width database with minimum manual intervention. Water level data from in situ stations are interpolated to match the width data and create elevation points from which the cross section profiles are produced. The method is fully described and tested on the São Francisco River in Brazil. The width data are plotted against discharge data to compare their progression. Over 1700 cross sections were produced and classified by their shape. Potential and limitations are presented.
Publisher: MDPI AG
Date: 26-09-2008
DOI: 10.3390/S8096055
Publisher: Elsevier BV
Date: 03-2017
Publisher: Informa UK Limited
Date: 17-09-2013
Publisher: Elsevier BV
Date: 2008
DOI: 10.1016/J.JENVMAN.2006.12.009
Abstract: In this article, a methodology for evaluating the effect of land use/land cover on the quality of nearby stream water in a semiarid environment is described and tested on a large watershed in Southeastern Brazil. The approach aims at identifying the width of the riparian area having the strongest effect on different water quality parameters. The land use/land cover data were generated from remotely sensed data while water quality point data were supplied by a government agency. Testing was conducted for both the rainy and dry seasons in an effort to understand the direct effect of surface runoff. The approach combines cartographic modelling using a geographical information system (GIS) and statistics to establish the strength of the relationship between water quality, land use and the distance from the stream. Results suggest a strong relationship between land use/land cover and turbidity, nitrogen and fecal coliforms. They also suggest that each of these parameters has a unique behavior when distance from the stream is considered. Finally, although it was expected that the models would apply better during the wet season, some parameters had the opposite behavior and displayed a better fit during the dry season.
Publisher: InTech
Date: 27-01-2012
DOI: 10.5772/32414
Publisher: SPIE
Date: 10-10-2018
DOI: 10.1117/12.2325804
Publisher: Universidade Federal de Minas Gerais - Pro-Reitoria de Pesquisa
Date: 12-2011
DOI: 10.35699/2237-549X..13317
Abstract: A presença das veredas justificou a criação do Parque Estadual Veredas do Peruaçu – PEVP na região norte de Minas Gerais. Neste trabalho, uma metodologia é apresentada para delimitação do ambiente de vereda e classificação dos seus estratos fitofisionômicos. Uma nova chave de classificação dos diferentes tipos de veredas é também proposta, uma vez que as veredas do PEVP não são homogêneas. A abordagem metodológica baseia-se em técnicas de processamento digital de imagem de satélite (segmentação e classificação de imagem) e coleta de dados de c o. Os resultados obtidos nesta pesquisa apontam para a delimitação de 58,8% das veredas da região do PEVP e para um sucesso de classificação de seus estratos fitofisionômicos de 73,5%.
Publisher: American Society for Photogrammetry and Remote Sensing
Date: 04-2003
Publisher: Informa UK Limited
Date: 2010
DOI: 10.5589/M10-008
Publisher: SPIE
Date: 10-10-2018
DOI: 10.1117/12.2325725
Publisher: Informa UK Limited
Date: 10-1989
Publisher: Copernicus GmbH
Date: 23-06-2016
DOI: 10.5194/ISPRSARCHIVES-XLI-B8-327-2016
Abstract: Satellite altimetry is becoming a major tool for measuring water levels in rivers and lakes offering accuracies compatible with many hydrological applications, especially in uninhabited regions of difficult access. The Pantanal is considered the largest tropical wetland in the world and the sparsity of & i& in situ& /i& gauging station make remote methods of water level measurements an attractive alternative. This article describes how satellites altimetry data from Envisat and Saral was used to determine water level in two small lakes in the Pantanal. By combining the water level with the water surface area extracted from satellite imagery, water volume fluctuations were also estimated for a few periods. The available algorithms (retrackers) that compute a range solution from the raw waveforms do not always produce reliable measurements in small lakes. This is because the return signal gets often “contaminated” by the surrounding land. To try to solve this, we created a “lake” retracker that rejects waveforms that cannot be attributed to “calm water” and convert them to altitude. Elevation data are stored in a database along with the water surface area to compute the volume fluctuations. Satellite water level time series were also produced and compared with the only nearby & i& in situ& /i& gauging station. Although the “lake” retracker worked well with calm water, the presence of waves and other factors was such that the standard “ice1” retracker performed better on the overall. We estimate our water level accuracy to be around 75 cm. Although the return time of both satellites is only 35 days, the next few years promise to bring new altimetry satellite missions that will significantly increase this frequency.
Publisher: FapUNIFESP (SciELO)
Date: 2021
DOI: 10.1590/2318-0331.262120210069
Abstract: ABSTRACT Radar altimeters are instruments carried on space missions and allow for determination of heights, particularly in oceans and ice sheets. The use of altimetry data on continental waters involves several challenges, such as the revisit frequency (typically 27 to 35 days), an accuracy of decimeters, data handling and processing, particularly for narrow rivers such as the São Francisco River (width km). Radar satellite altimetry has advantages over the conventional in situ monitoring network, including in terms of spatial coverage and global altimetric reference of data. Thus, altimetry data should be used as a complementary and/or alternative source to in situ data. In this context, this study consolidates and evaluates the altimetric series of five different altimetry missions: Envisat in two orbits, Saral, Sentinel 3-A, and Sentinel 3-B. The altimetry water level time series of 17 Virtual stations were compared with leveled gauging stations series to calculate absolute and relative errors. Ultimately, the errors varied from 0.13 m to 0.36 m in the best cases (41%), in line with recent literature. Sentinel-3 satellites showed the best RMSE absolute/relative results: 0.95/0.49 m (S-3A) and 0.96/0.52 m (S-3B). The second best RMSEs was Envisat-X (1.39/0.50 m), then Envisat (1.87/0.56 m) and Saral (1.74/0.60 m).
Publisher: Unpublished
Date: 2013
Publisher: SPIE
Date: 24-10-2013
DOI: 10.1117/12.2028480
Publisher: Informa UK Limited
Date: 2010
DOI: 10.5589/M10-065
Publisher: SPIE
Date: 23-10-2014
DOI: 10.1117/12.2066848
Publisher: Springer Science and Business Media LLC
Date: 06-05-2016
DOI: 10.1007/S10661-016-5323-2
Abstract: Non-point source water pollution is a major problem in most parts of the world, but is also very difficult to quantify and control since it is not easily separated from point sources and can theoretically originate from the whole watershed. In this article, we evaluate the relationship between land use and land cover and four water pollution parameters in a watershed in Southeast Brazil. The four parameters are nitrate, total ammonia nitrogen, total phosphorous, and dissolved oxygen. To help concentrate on non-point source pollution, only data from the wet seasons of the time period (2001-2013) were analysed, based on the fact that precipitation causes runoff which is the main cause of diffuse pollution. The parameters measured were transformed into loads, which were in turn associated with an exclusive contribution area, so that every measuring station could be considered independent. Analyses were also performed on riparian zones of different widths to verify if the effect of the land cover on the water quality of the stream decreases with the increased distance. Pearson correlation coefficients indicate that urban areas and agriculture asture tend to worsen water quality (source). Conversely, forest and riparian areas have a reducing effect on pollution (sink). The best results were obtained for total ammonia nitrogen and dissolved oxygen using the whole exclusive contribution areas with determination coefficients better than R (2)≈0.8. Nitrate and total phosphorous did not produce valid models. We suspect that the transformation delay from total ammonia nitrogen to nitrate might be an important factor for the poor result for this parameter. For phosphorous, we think that the phosphorous sink in the bottom sediment might be the most limiting factor explaining the failure of our models.
Publisher: SPIE
Date: 21-10-2014
DOI: 10.1117/12.2066889
Publisher: IEEE
Date: 12-2008
Publisher: Unpublished
Date: 2001
Publisher: Copernicus GmbH
Date: 07-06-2016
DOI: 10.5194/ISPRS-ANNALS-III-7-75-2016
Abstract: Abstract. This article presents an original algorithm created to detect and count trees in orchards using very high resolution images. The algorithm is based on an adaptation of the “template matching” image processing approach, in which the template is based on a “geometricaloptical” model created from a series of parameters, such as illumination angles, maximum and ambient radiance, and tree size specifications. The algorithm is tested on four images from different regions of the world and different crop types. These images all have 1 meter spatial resolution and were downloaded from the GoogleEarth application. Results show that the algorithm is very efficient at detecting and counting trees as long as their spectral and spatial characteristics are relatively constant. For walnut, mango and orange trees, the overall accuracy was clearly above 90%. However, the overall success rate for apple trees fell under 75%. It appears that the openness of the apple tree crown is most probably responsible for this poorer result. The algorithm is fully explained with a step-by-step description. At this stage, the algorithm still requires quite a bit of user interaction. The automatic determination of most of the required parameters is under development.
Publisher: SPIE
Date: 24-10-2013
DOI: 10.1117/12.2029073
Publisher: Informa UK Limited
Date: 02-09-2020
No related grants have been discovered for Philippe Maillard.