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Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])  

Public [article]  inGeocarto international > vol 35 n° 16 [01/12/2020] . - pp 1800 - 1813 Titre : Quantification of cotton water consumption by remote sensing Type de document : Article/Communication Auteurs : Jefferson Vieira José, Auteur ; Niclene Ponce Rodrigues de Oliveira, Auteur ; Tonny José de Araújo da Silva, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1800 - 1813 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biome [Termes descripteurs IGN] cultures irriguées [Termes descripteurs IGN] évapotranspiration [Termes descripteurs IGN] gestion de l'eau [Termes descripteurs IGN] Gossypium (genre) [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] irrigation [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] Mato Grosso Résumé : (auteur) Quantifying crop water consumption is essential for water resource management. The objective was to estimate the current evapotranspiration (ETa) of the cotton crop (Gossypium hirsutum L.) in the rainfed system, as well as the components of the radiation and energy balance in the Cerrado biome conditions using orbital images and the SEBAL algorithm and validate the estimates of evapotranspiration (ET) using FAO guidelines for crop coefficient (K c) of the cotton crop. Research was carried out in the State of Mato Grosso, Brazil, in areas with three cotton cultivars. Images of the Operational Land Imager and Thermal Infrared Sensor sensors were used and ET estimation was made based on the SEBAL algorithm. Mean ETa in the cotton cycle was 3.5 mm dia−1 and the K c values ranged from 0.22 and 1.12, on average, in the smaller and larger leaf area, respectively. Numéro de notice : A2020-726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1583777 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1583777 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96329 [article]

Crater detection and registration of planetary images through marked point processes, multiscale decomposition, and region-based analysis / David Solarna in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 9 (September 2020) . - pp 6039 - 6058 Titre : Crater detection and registration of planetary images through marked point processes, multiscale decomposition, and region-based analysis Type de document : Article/Communication Auteurs : David Solarna, Auteur ; Alberto Gotelli, Auteur ; Jacqueline Le Moigne, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 6039 - 6058 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] cratère [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] distance de Hausdorff [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] Mars (planète) [Termes descripteurs IGN] ondelette [Termes descripteurs IGN] processus ponctuel marqué [Termes descripteurs IGN] séparateur à vaste marge [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] zone d'intérêt Résumé : (auteur) Because of the large variety of planetary sensors and spacecraft already collecting data and with many new and improved sensors being planned for future missions, planetary science needs to integrate numerous multimodal image sources, and, as a consequence, accurate and robust registration algorithms are required. In this article, we develop a new framework for crater detection based on marked point processes (MPPs) that can be used for planetary image registration. MPPs were found to be effective for various object detection tasks in Earth observation, and a new MPP model is proposed here for detecting craters in planetary data. The resulting spatial features are exploited for registration, together with fitness functions based on the MPP energy, on the mean directed Hausdorff distance, and on the mutual information. Two different methods—one based on birth–death processes and region-of-interest analysis and the other based on graph cuts and decimated wavelets—are developed within the proposed framework. Experiments with a large set of images, including 13 thermal infrared and visible images of the Mars surface, 20 semisimulated multitemporal pairs of images of the Mars surface, and a real multitemporal image pair of the Lunar surface, demonstrate the effectiveness of the proposed framework in terms of crater detection performance as well as for subpixel registration accuracy. Numéro de notice : A2020-526 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2970908 date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2970908 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95704 [article]

Thermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings / Paulina Lewińska in Photogrammetric record, vol 35 n° 171 (September 2020)  

Public [article]  inPhotogrammetric record > vol 35 n° 171 (September 2020) . - pp 402-425 Titre : Thermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings Type de document : Article/Communication Auteurs : Paulina Lewińska, Auteur ; Kamil Maciuk, Auteur Année de publication : 2020 Article en page(s) : pp 402-425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] conservation du patrimoine [Termes descripteurs IGN] diffusion de données [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] image virtuelle [Termes descripteurs IGN] inventaire du bâti [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] patrimoine immobilier [Termes descripteurs IGN] reconstruction 3D du bâti [Termes descripteurs IGN] structure-from-motion [Termes descripteurs IGN] texture d'image Résumé : (Auteur) This paper describes the means of supporting virtual reconstruction of wooden and masonry buildings with the use of thermal infrared images. Not all remaining architectural heritage can be physically preserved. War, climate change and rapidly growing cities have caused damage and degradation to valuable historical buildings. In order to preserve them virtually, various methods of 3D modelling have been employed. This paper presents information on how to create a full 3D inventory of a building’s exterior. This includes a 3D thermal model of the building, merging thermal camera data with a spatial model, which aids the reconstruction of previous stages of a building’s existence. The authors argue that in cases when it is impossible to force heat transfer from inside the structure (via man‐made heating), 24 hours of observations using only solar heating can be sufficient to find heat bridges and other thermal anomalies that can be used for virtual reconstruction. Numéro de notice : A2020-438 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12332 date de publication en ligne : 20/09/2020 En ligne : https://doi.org/10.1111/phor.12332 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95844 [article]

Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 27 - 40 Titre : Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis Type de document : Article/Communication Auteurs : T. Poblete, Auteur ; C. Camino, Auteur ; P.S.A. Beck, Auteur Année de publication : 2020 Article en page(s) : pp 27 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] chlorophylle [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] espèce végétale [Termes descripteurs IGN] fluorescence [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] Italie [Termes descripteurs IGN] maladie bactérienne [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] Olea europaea [Termes descripteurs IGN] stress hydrique [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] télédétection aérienne [Termes descripteurs IGN] traitement d'image Résumé : (auteur) Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful eradication and containment strategies for harmful pathogens require large-scale monitoring techniques for the detection of infected hosts, even when they do not display visual symptoms. Although a previous study using airborne hyperspectral and thermal imagery has shown promising results for the early detection of Xf-infected olive (Olea europaea) trees, further work is needed when adopting these techniques for large scale monitoring using multispectral cameras on board airborne platforms and satellites. We used hyperspectral and thermal imagery collected during a two-year airborne campaign in a Xf-infected area in southern Italy to assess the performance of spectrally constrained machine-learning algorithms for this task. The algorithms were used to assess multispectral bandsets, selected from the original hyperspectral imagery, that were compatible with large-scale monitoring from unmanned platforms and manned aircraft. In addition, the contribution of solar–induced chlorophyll fluorescence (SIF) and the temperature-based Crop Water Stress Index (CWSI) retrieved from hyperspectral and thermal imaging, respectively, were evaluated to quantify their relative importance in the algorithms used to detect Xf infection. The detection performance using support vector machine algorithms decreased from ∼80% (kappa, κ = 0.42) when using the original full hyperspectral dataset including SIF and CWSI to ∼74% (κ = 0.36) when the optimal set of six spectral bands most sensitive to Xf infection were used in addition to the CWSI thermal indicator. When neither SIF nor CWSI were used, the detection yielded less than 70% accuracy (decreasing κ to very low performance, 0.29), revealing that tree temperature was more important than chlorophyll fluorescence for the Xf detection. This work demonstrates that large-scale Xf monitoring can be supported using airborne platforms carrying multispectral and thermal cameras with a limited number of spectral bands (e.g., six to 12 bands with 10 nm bandwidths) as long as they are carefully selected by their sensitivity to the Xf symptoms. More precisely, the blue (bands between 400 and 450 nm to derive the NPQI index) and thermal (to derive CWSI from tree temperature) were the most critical spectral regions for their sensitivity to Xf symptoms in olive. Numéro de notice : A2020-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.010 date de publication en ligne : 18/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.010 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94745 [article]

MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n°1 (2020)  

Public [article]  inEuropean journal of remote sensing > vol 53 n°1 (2020) . - pp 81 - 90 Titre : MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment Type de document : Article/Communication Auteurs : Salahuddin M. Jaber, Auteur ; Mahmoud M. Abu-Allaban, Auteur Année de publication : 2020 Article en page(s) : pp 81 - 90 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] action anthropique [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] climat aride [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] Jordanie [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] nuit [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] variation diurne [Termes descripteurs IGN] zone semi-aride Résumé : (auteur) This study aims to (1) determine the seasonalities and spatial and temporal rates of change of MODIS-based daytime and nighttime land surface temperature (LST) for the last 19 years from 2000 to 2018 and (2) investigate whether these rates are induced by natural (represented by elevation) or anthropogenic (represented by population counts) forcing. The study area is Jordan – a typical Middle Eastern semi-arid to arid country. Time-series additive seasonal decomposition and simple linear regression produced the following results. (1) For both daytime and nighttime the highest LST values were observed in June while the lowest LST values were observed in December. (2) No significant linear rates of change of LST were noticed in daytime, while significant linear rates of increase of LST, which varied from 0.041°C/year to 0.119°C/year, were observed in nighttime in about one-third of the area of the country mainly in the western parts. (3) The significant linear rates of increase of nighttime LST increased significantly by 0.005°C/year for every 1,000 m increase in elevation and by 0.003°C/year for every 1,000 people increase in population counts. (4) Both natural and anthropogenic factors affected LST in nighttime; however, anthropogenic factors seemed to be more important than natural factors. Numéro de notice : A2020-166 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1735264 date de publication en ligne : 06/03/2020 En ligne : https://doi.org/10.1080/22797254.2020.1735264 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94834 [article]

Uncertainty analysis of remotely-acquired thermal infrared data to extract the thermal Properties of active lava surfaces / James A. Thompson in Remote sensing, vol 12 n° 1 (January 2020)  

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WeCount, le trafic compté par les citoyens / Victor Oxombre (2020) 

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Combining thermal imaging with photogrammetry of an active volcano using UAV: an example from Stromboli, Italy / Zoë E. Wakeford in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Quantification of the adjacency effect on measurements in the thermal infrared region / Xiaopo Zheng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)  

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sUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar / Paul J. Kinzel in Remote sensing, vol 11 n° 19 (October 2019)  

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Development and evaluation of a deep learning model for real-time ground vehicle semantic segmentation from UAV-based thermal infrared imagery / Mehdi Khoshboresh Masouleh in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

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Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, sans n° (2019)  

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Calculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2 / Ali Mokhtari in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Mapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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Fusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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