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Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information / Murali Krishna Gumma in Geocarto international, vol 37 n° 7 ([15/04/2022])
[article]
Titre : Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information Type de document : Article/Communication Auteurs : Murali Krishna Gumma, Auteur ; Kimeera Tummala, Auteur ; Sreenath Dixit, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1833 - 1849 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement spectral
[Termes IGN] blé (céréale)
[Termes IGN] carte de la végétation
[Termes IGN] distribution spatiale
[Termes IGN] image Sentinel-MSI
[Termes IGN] Inde
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelle
[Termes IGN] surface cultivée
[Termes IGN] variation saisonnièreRésumé : (auteur) Accurate monitoring of croplands helps in making decisions (for insurance claims, crop management and contingency plans) at the macro-level, especially in drylands where variability in cropping is very high owing to erratic weather conditions. Dryland cereals and grain legumes are key to ensuring the food and nutritional security of a large number of vulnerable populations living in the drylands. Reliable information on area cultivated to such crops forms part of the national accounting of food production and supply in many Asian countries, many of which are employing remote sensing tools to improve the accuracy of assessments of cultivated areas. This paper assesses the capabilities and limitations of mapping cultivated areas in the Rabi (winter) season and corresponding cropping patterns in three districts characterized by small-plot agriculture. The study used Sentinel-2 Normalized Difference Vegetation Index (NDVI) 15-day time-series at 10 m resolution by employing a Spectral Matching Technique (SMT) approach. The use of SMT is based on the well-studied relationship between temporal NDVI signatures and crop phenology. The rabi season in India, dominated by non-rainy days, is best suited for the application of this method, as persistent cloud cover will hamper the availability of images necessary to generate clearly differentiating temporal signatures. Our study showed that the temporal signatures of wheat, chickpea and mustard are easily distinguishable, enabling an overall accuracy of 84%, with wheat and mustard achieving 86% and 94% accuracies, respectively. The most significant misclassifications were in irrigated areas for mustard and wheat, in small-plot mustard fields covered by trees and in fragmented chickpea areas. A comparison of district-wise national crop statistics and those obtained from this study revealed a correlation of 96%. Numéro de notice : A2022-497 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1805029 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1080/10106049.2020.1805029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100989
in Geocarto international > vol 37 n° 7 [15/04/2022] . - pp 1833 - 1849[article]Spectral identification of materials by reflectance spectral library search / Rama Rao Nidamanuri in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
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Titre : Spectral identification of materials by reflectance spectral library search Type de document : Article/Communication Auteurs : Rama Rao Nidamanuri, Auteur ; A. M. Ramiya, Auteur Année de publication : 2014 Article en page(s) : pp 609-624 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] appariement spectral
[Termes IGN] image hyperspectrale
[Termes IGN] réflectance spectrale
[Termes IGN] signature spectraleRésumé : (auteur) Spectral library search is emerging as a viable approach for material identification and mapping by reusing spectral knowledge gained from hyperspectral remote sensing across space and time. The potential of retrieving meaningful spectral material identifications in the presence of reflectance of spectra of various material types and with various similarity metrics has been assessed in this study. Test reflectance spectra of various vegetation, minerals, soils and urban material types are identified by searching through the composite reflectance spectral library obtained by combining various institutional reflectance spectral libraries. The accuracy of material identifications under various conditions: (i) in the presence of identical, similar and dissimilar spectra; (ii) in the presence of only identical and dissimilar spectra; and (iii) in the presence of only dissimilar spectra has been assessed with several similarity metrics. Results indicate the possibility of obtaining 100% accurate material identifications by library search if the spectral library contains identical spectra. However, the presence of a large number of similar spectra, despite the presence of identical spectra, is found to increase false positives, thereby reducing the accuracy of retrievals to 82% at best. Further, the accuracy of material identifications in the presence of similar spectra is similarity metric-dependent and varied from about 52% (obtained from Binary Encoding) to 82% (obtained from Normalized Spectral Similarity Score). Overall, results support the possibility of using independent reflectance spectral libraries for material identification while calling for robust spectral similarity metrics. Numéro de notice : A2014-418 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.821175 En ligne : https://doi.org/10.1080/10106049.2013.821175 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73953
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 609-624[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Spectral material mapping using hyperspectral imagery : a review of spectral matching and library search methods / Sennaraj Vishnu in Geocarto international, vol 28 n° 1-2 (February - May 2013)
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Titre : Spectral material mapping using hyperspectral imagery : a review of spectral matching and library search methods Type de document : Article/Communication Auteurs : Sennaraj Vishnu, Auteur ; Rama Rao Nidamanuri, Auteur ; R. Bremananth, Auteur Année de publication : 2013 Article en page(s) : pp 171 - 190 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement spectral
[Termes IGN] image hyperspectrale
[Termes IGN] réflectance spectrale
[Termes IGN] spectroscopieRésumé : (Auteur) Imaging spectroscopy is an emerging and versatile technique that finds applications in diverse fields concerned with remote identification, discrimination and mapping of materials. The large amount of spectral data produced by hyperspectral imaging necessitates the development of automated techniques that convert imagery directly into thematic maps. Spectral library search method, a method of choice for organic compound identification by the mass spectroscopy, has caught the attention of researchers as one of the appropriate methods for an efficient exploitation of high quality spectral data available from the hyperspectral imaging systems. Given the apparent increase in the number of papers appearing on the subject as well as the variety of methods proposed, it is reasonable to say that the field of automated interpretation of reflectance spectral data has passed its infancy now gaining important space in the scientific community. We present an overall view of the literature relevant to the development of library search method, the various search algorithms and systems available in the purview for developing an automated hyperspectral data analysis system for material identification. Numéro de notice : A2013-279 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.665498 Date de publication en ligne : 25/04/2012 En ligne : https://doi.org/10.1080/10106049.2012.665498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32417
in Geocarto international > vol 28 n° 1-2 (February - May 2013) . - pp 171 - 190[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2013011 RAB Revue Centre de documentation En réserve L003 Disponible A comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper / P.E. Dennison in Remote sensing of environment, vol 93 n° 3 (15/11/2004)
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Titre : A comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper Type de document : Article/Communication Auteurs : P.E. Dennison, Auteur ; K. Halligan, Auteur ; D.A. Roberts, Auteur Année de publication : 2004 Article en page(s) : pp 359 - 367 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] albedo
[Termes IGN] analyse comparative
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] appariement spectral
[Termes IGN] calcul d'erreur
[Termes IGN] classe d'objets
[Termes IGN] classification Spectral angle mapper
[Termes IGN] erreur moyenne quadratique
[Termes IGN] métriqueRésumé : (Auteur) Spectral matching algorithms can be used for the identification of unknown spectra based on a measure of similarity with one or more known spectra. Two popular spectral matching algorithms use different error metrics and constraints to determine the existence of a spectral match. Multiple endmember spectral mixture analysis (MESMA) is a linear mixing model that uses a root mean square error (RMSE) error metric. Spectral angle mapper (SAM) compares two spectra using a spectral angle error metric. This paper compares two endmember MESMA and SAM using a spectral library containing six land cover classes. RMSE and spectral angle for models within each land cover class were directly compared. The dependence of RMSE on the albedo of the modeled spectrum was also explored. RMSE and spectral angle were found to be closely related, although not equivalent, due to variations in the albedo of the modeled spectra. Error constraints applied to both models resulted in large differences in the number of spectral matches. Using MESMA, the number of spectra modeled within the error constraint increased as the albedo of the modeled spectra decreased. The value of the error constraint used was shown to make a much larger difference in the number of spectra modeled than the choice of spectral matching algorithm. Numéro de notice : A2004-440 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.07.013 En ligne : https://doi.org/10.1016/j.rse.2004.07.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26960
in Remote sensing of environment > vol 93 n° 3 (15/11/2004) . - pp 359 - 367[article]