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Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi / Brad G. Peter in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 2 (February 2020) . - pp 107 - 119 Titre : Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi Type de document : Article/Communication Auteurs : Brad G. Peter, Auteur ; Joseph P. Messina, Auteur ; Jon W. Carroll, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 107 - 119 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] agriculture de précision [Termes descripteurs IGN] analyse multirésolution [Termes descripteurs IGN] exploitation agricole [Termes descripteurs IGN] image Pléiades [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image SPOT 6 [Termes descripteurs IGN] Malawi Résumé : (Auteur) A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral images with crop status. Single and multiple linear regressions were tested for spatial resolutions ranging from 7 cm to 20 m using a small unmanned aerial system (sUAS) and satellite imagery from Planet, SPOT 6, Pléiades, and Sentinel-2. Results suggest that imagery with spatial resolutions nearer the maize plant scale (i.e., 14–27 cm) are most effective for relating spectral signals with crop health on smallholder farms in Malawi. Consistent with other studies, green-band indices were more strongly correlated with maize chlorophyll content and yield than conventional red-band indices, and multivariable models often outperformed single variable models. Numéro de notice : A2020-127 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.2.107 date de publication en ligne : 01/02/2020 En ligne : https://doi.org/10.14358/PERS.86.2.107 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94796 [article]

Forest change detection in incomplete satellite images with deep neural networks / Salman H. Khan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 9 (September 2017) . - pp 5407 - 5423 Titre : Forest change detection in incomplete satellite images with deep neural networks Type de document : Article/Communication Auteurs : Salman H. Khan, Auteur ; Xuming He, Auteur ; Fatih Porikli, Auteur ; Mohammed Bennamoun, Auteur Année de publication : 2017 Article en page(s) : pp 5407 - 5423 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] analyse multirésolution [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] forêt [Termes descripteurs IGN] réflectance de surface [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] retouche [Termes descripteurs IGN] surveillance de la végétation Résumé : (Auteur) Land cover change monitoring is an important task from the perspective of regional resource monitoring, disaster management, land development, and environmental planning. In this paper, we analyze imagery data from remote sensing satellites to detect forest cover changes over a period of 29 years (1987-2015). Since the original data are severely incomplete and contaminated with artifacts, we first devise a spatiotemporal inpainting mechanism to recover the missing surface reflectance information. The spatial filling process makes use of the available data of the nearby temporal instances followed by a sparse encoding-based reconstruction. We formulate the change detection task as a region classification problem. We build a multiresolution profile (MRP) of the target area and generate a candidate set of bounding-box proposals that enclose potential change regions. In contrast to existing methods that use handcrafted features, we automatically learn region representations using a deep neural network in a data-driven fashion. Based on these highly discriminative representations, we determine forest changes and predict their onset and offset timings by labeling the candidate set of proposals. Our approach achieves the state-of-the-art average patch classification rate of 91.6% (an improvement of ~16%) and the mean onset/offset prediction error of 4.9 months (an error reduction of five months) compared with a strong baseline. We also qualitatively analyze the detected changes in the unlabeled image regions, which demonstrate that the proposed forest change detection approach is scalable to new regions. Numéro de notice : A2017-663 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2707528 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2707528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87105 [article]

Describing contrast across scales / Sohaib Ali Syed in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 128 (June 2017) . - pp 326 - 337 Titre : Describing contrast across scales Type de document : Article/Communication Auteurs : Sohaib Ali Syed, Auteur ; Muhammad Zafar Iqbal, Auteur ; Muhammad Mohsin Riaz, Auteur Année de publication : 2017 Article en page(s) : pp 326 - 337 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] accentuation d'image [Termes descripteurs IGN] affinage d'image [Termes descripteurs IGN] amélioration du contraste [Termes descripteurs IGN] analyse multirésolution [Termes descripteurs IGN] contraste local [Termes descripteurs IGN] image numérique [Termes descripteurs IGN] pansharpening (fusion d'images) Résumé : (Auteur) Due to its sensitive nature against illumination and noise distributions, contrast is not widely used for image description. On the contrary, the human perception of contrast along different spatial frequency bandwidths provides a powerful discriminator function that can be modeled in a robust manner against local illumination. Based upon this observation, a dense local contrast descriptor is proposed and its potential in different applications of computer vision is discussed. Extensive experiments reveal that this simple yet effective description performs well in comparison with state of the art image descriptors. We also show the importance of this description in multiresolution pansharpening framework. Numéro de notice : A2017-337 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.04.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.04.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85504 [article]

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A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products / Yuxin Zhu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 9 (September 2015) . - pp 5021 - 5035 Titre : A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products Type de document : Article/Communication Auteurs : Yuxin Zhu, Auteur ; Emily Lei Kang, Auteur ; Yanchen Bo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 5021 - 5035 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme de correction [Termes descripteurs IGN] analyse multirésolution [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] climat terrestre [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] exhaustivité des données [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] interpolation linéaire [Termes descripteurs IGN] krigeage [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] température de surface de la mer Résumé : (Auteur) Sea surface temperature (SST) plays a vital role in the Earth's atmosphere and climate systems. Complete and accurate SST observations are in great demand for forecasting tropical cyclones and projecting climate change. Satellite remote sensing has been used to retrieve SST globally, but missing values and biased observations impose difficulties on practical applications of these satellite-derived SST data. Conventional spatial statistics methods such as kriging have been widely used to fill the gaps. However, when such conventional methods are used to analyze a massive satellite data set of size n, the inversion of the n × n covariance matrix may require O(n3) computations, which make the computation very intensive or even infeasible. The fixed rank kriging (FRK) performs dimension reduction through multiresolution wavelet analysis so that it can dramatically reduce the computation cost of various kriging methods. However, the FRK cannot directly be used for incomplete data over spatially irregular regions such as SSTs, and the potential bias in the satellite data is not addressed. In this paper, we construct a data-driven bias-correction model for the correction of the bias in satellite SSTs and develop a robust FRK (R-FRK) method so that the dimension reduction can be used to the satellite data in irregular regions with missing data. We implement the bias-correction model and the R-FRK to the level-3 mapped night Moderate Resolution Imaging Spectroradiometer SSTs. The accuracy of the resulting predictions is assessed using the colocated drifting buoy SST observations, in terms of mean bias (bias), root-mean-squared error, and R squared (R2). The spatial completeness is assessed by the availability of ocean pixels. The assessment results show that the spatially. Numéro de notice : A2015-530 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2416351 date de publication en ligne : 17/04/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2416351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77558 [article]

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MTF-adjusted pansharpening approach based on coupled multiresolution decompositions / Abdelaziz Kallel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3124 - 3145 Titre : MTF-adjusted pansharpening approach based on coupled multiresolution decompositions Type de document : Article/Communication Auteurs : Abdelaziz Kallel, Auteur Année de publication : 2015 Article en page(s) : pp 3124 - 3145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse multirésolution [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] fonction de transfert de modulation [Termes descripteurs IGN] image Geoeye [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image Pléiades-HR [Termes descripteurs IGN] image SPOT 6 [Termes descripteurs IGN] pansharpening (fusion d'images) [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Among others, the wavelet-based pansharpening approach tries to enhance the resolution of the multispectral (MS) image by injection of spatial details extracted from the high-resolution panchromatic (PAN) image. The problem is presented as follows, the inputs are a coarse-resolution MS image and a high-resolution detail image provided from the PAN image; therefore, one would think that the wavelet reconstruction allows combining approximations and details to construct the high-resolution MS image. However, the wavelet transform (WT) assumes that details and approximations are calculated using the same wavelet decomposition. Now, in the pansharpening case, the MS low-resolution image is assumed to be aliased and blurred due to the imaging system modulation transfer function (MTF) that is approximated as a specific low-pass filter. Meanwhile, there are no constraints about details that can be extracted from PAN using discrete WT (DWT). Approximation and details are not any more orthogonal as needed in the reconstruct of the MS high-resolution image based on DWT. For that, we propose in this paper a new fusion schema [coupled multiresolution decomposition model (CMD)] allowing the reconstruction of a high-resolution MS given its approximation and details obtained by MTF-tailored downsampling and wavelet decomposition, respectively. For validation, CMD is applied to Pléiades, GeoEye-1, and SPOT 6 images. Compared to other approaches [i.e., Gram-Schmidt (GS) adaptive, GS mode 2 (GS2), “À trous' WT (AWT), generalized Laplacian pyramid (GLP), DWT, and PCI Geomatics software algorithm], our method performs generally better. Numéro de notice : A2015-282 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2369056 date de publication en ligne : 19/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2369056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76399 [article]

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A critical comparison among pansharpening algorithms / Gemine Vivone in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)

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Crop type classification by simultaneous use of satellite images of different resolutions / Mark W. Liu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)

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A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data / Chuanfa Chen in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)

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Development of a modified neural network-based land cover classification system using automated data selector and multiresolution remotely sensed data / S. Khorram in Geocarto international, vol 26 n° 6 (October 2011)  

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Urban-trees extraction from Quickbird imagery using multiscale spectex-filtering and non-parametric classification / Y.O. Ouma in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 3 (May - June 2008)

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The wavelet method as an alternative for reducing ionospheric effects from single-frequency GPS receivers / E.M. DE Souza in Journal of geodesy, vol 81 n° 12 (December 2007)

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An integrated TIN and Grid method for constructing multi-resolution digital terrain models / B. Yang in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)

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Linear feature detection using multi-resolution wavelet filters / S.P. Kozaitis in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 6 (June 2005)

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Filtering airborne Laser scanner data: a wavelet-based clustering method / T. Thuy in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 11 (November 2004)

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A wavelet approach to road extraction from high spatial resolution remotely-sensed imagery / Qian Zhang in Geomatica, vol 58 n° 1 (March 2004)

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