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Spatial-temporal variation of satellite-based gross primary production estimation in wheat-maize rotation area during 2000–2015 / Wenquan Xie in Geocarto international, vol 37 n° 9 ([15/05/2022])  

Public [article]  inGeocarto international > vol 37 n° 9 [15/05/2022] . - pp 2506 - 2523 Titre : Spatial-temporal variation of satellite-based gross primary production estimation in wheat-maize rotation area during 2000–2015 Type de document : Article/Communication Auteurs : Wenquan Xie, Auteur ; Huini Wang, Auteur ; Hong Chi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2506 - 2523 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] blé (céréale) [Termes IGN] Chine [Termes IGN] image Terra-MODIS [Termes IGN] maïs (céréale) [Termes IGN] photosynthèse [Termes IGN] production primaire brute [Termes IGN] rotation de culture [Termes IGN] série temporelle [Termes IGN] variation temporelle Résumé : (auteur) North China Plain is the largest agricultural production center in China and wheat-maize rotation is a widespread cultivation practice in this area. As gross primary production (GPP) is a proxy of land productivity, research on its spatial-temporal dynamics helps understand the variation of grain production in wheat-maize rotation. Here, Moderate Resolution Imaging Spectroradiometer (MODIS) data and ground observation data were combined to drive Vegetation Photosynthesis Model (VPM) in GPP estimation over wheat-maize rotation area during 2000–2015. Annual GPP has increased by 540.95 g C m−2 year−1 from 2000 to 2015, while total annual GPP has grown ∼150% than that of 2000. Moreover, annual GPP showed an increasing trend in the consecutively wheat-maize rotation area between 2000 and 2015. A strong linear relationship between GPP estimates and grain production demonstrated the potential of using VPM model to evaluate grain production in wheat-maize rotation area of Henan province, China. Numéro de notice : A2022-566 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1822928 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1080/10106049.2020.1822928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101249 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2022091	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Alternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation / Toshihiro Sakamoto in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 5 (May 2022) . - pp 323 - 332 Titre : Alternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation Type de document : Article/Communication Auteurs : Toshihiro Sakamoto, Auteur ; Daisuke Ogawa, Auteur ; Satoko Hiura, Auteur ; Nobusuke Iwasaki, Auteur Année de publication : 2022 Article en page(s) : pp 323 - 332 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] bande spectrale [Termes IGN] blé (céréale) [Termes IGN] chlorophylle [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] indice de végétation [Termes IGN] orthophotoplan numérique [Termes IGN] point d'appui [Termes IGN] précision du positionnement [Termes IGN] rizière [Termes IGN] structure-from-motion Résumé : (Auteur) Vegetation indices (VIs), such as the green chlorophyll index and normalized difference vegetation index, are calculated from visible and near-infrared band images for plant diagnosis in crop breeding and field management. The DJI P4 Multispectral drone combined with the Agisoft Metashape Structure from Motion/Multi View Stereo software is some of the most cost-effective equipment for creating high-resolution orthomosaic VI images. However, the manufacturer's procedure results in remarkable location estimation inaccuracy (average error: 3.27–3.45 cm) and alignment errors between spectral bands (average error: 2.80–2.84 cm). We developed alternative processing procedures to overcome these issues, and we achieved a higher positioning accuracy (average error: 1.32–1.38 cm) and better alignment accuracy between spectral bands (average error: 0.26–0.32 cm). The proposed procedure enables precise VI analysis, especially when using the green chlorophyll index for corn, and may help accelerate the application of remote sensing techniques to agriculture. Numéro de notice : A2022-528 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00064R2 Date de publication en ligne : 01/05/2022 En ligne : https://doi.org/10.14358/PERS.21-00064R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101379 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2022052	SL	Revue	Centre de documentation	Revues en salle	Disponible
105-2022051	SL	Revue	Centre de documentation	Revues en salle	Disponible

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])  

Public [article]  inGeocarto international > vol 37 n° 7 [15/04/2022] . - pp 1833 - 1849 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 saisonnière Résumé : (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 [article]

Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) / Safwan Mohammed in Geocarto international, vol 37 n° 6 ([01/04/2022])  

Public [article]  inGeocarto international > vol 37 n° 6 [01/04/2022] . - pp 1645 - 1663 Titre : Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) Type de document : Article/Communication Auteurs : Safwan Mohammed, Auteur ; Karam Alsafadi, Auteur ; Haidar Ali, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1645 - 1663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] blé (céréale) [Termes IGN] cultures [Termes IGN] données météorologiques [Termes IGN] état du sol [Termes IGN] MNS SRTM [Termes IGN] outil d'aide à la décision [Termes IGN] qualité du sol [Termes IGN] Syrie [Termes IGN] système d'information géographique Résumé : (auteur) In the last few years, the agricultural sector in Syria has suffered from major problems related to land degradation. To cope with this problem, a land suitability assessment has become an essential tool for sustainable land use management. The present research qualitatively evaluated the suitability of land in the Al-Yarmouk Basin (S-Syria) for rainfed winter wheat (Triticum aestivum) cultivation. In this study, a regional spatial approach involving three steps was developed, based on the method proposed by Sys et al. In the first step, a soil survey was carried out and 107 soil profiles were described, sampled and analyzed. In the second step, climatic gridded datasets from 1984–2014 MRm at a high spatial resolution (30 meters) and the Digital Elevation Model (DEM) were clipped from NASA's Shuttle Radar Topography Mission (SRTM) and prepared for the study area. In the third step, a land suitability assessment was performed using the geographical information system (GIS) and multi criteria decision support (MCDS). Soil survey outcomes showed that the study area was dominated by five soil orders: Mollisols, Inceptisols, Vertisols, Entisols and Aridisols. Also, results from the Sys model illustrated that more than 23.8% of the study area is highly suitable (S1–0) for wheat production without any limitations, whereas 38.7% and 37.5% are highly suitable (S1–1) and moderately suitable (S2), respectively. Also, the study emphasizes the important role of topographical factors in the study area for wheat cultivation. All in all, this research suggests W-Syria as a potential region for wheat cultivation, instead of the eastern area which is subject to climate change and a shortage of water. Integrating the Sys-approach and the GIS framework offers a good tool for policy-makers to apply in Syria for land suitability assessments. Numéro de notice : A2022-474 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1790674 Date de publication en ligne : 15/07/2020 En ligne : https://doi.org/10.1080/10106049.2020.1790674 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100821 [article]

Parcel-based summer maize mapping and phenology estimation combined using Sentinel-2 and time series Sentinel-1 data / Yanyan Wang in International journal of applied Earth observation and geoinformation, vol 108 (April 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 108 (April 2022) . - n° 102720 Titre : Parcel-based summer maize mapping and phenology estimation combined using Sentinel-2 and time series Sentinel-1 data Type de document : Article/Communication Auteurs : Yanyan Wang, Auteur ; Shenghui Fang, Auteur ; Lingli Zhao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102720 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] carte de la végétation [Termes IGN] Chine [Termes IGN] croissance végétale [Termes IGN] données spatiotemporelles [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] maïs (céréale) [Termes IGN] mesure de similitude [Termes IGN] phénologie [Termes IGN] saison [Termes IGN] segmentation d'image [Termes IGN] série temporelle [Termes IGN] surface cultivée Résumé : (auteur) This study aims to map the planting area of summer maize and estimate the spatiotemporal phenology information with parcel-based classification method through integration of Sentinel-1/2 data in Jiaozuo located in North China Plain. For the maize mapping, the combination of Sentinel-1/2 data with the parcel-based method has the highest classification accuracy, suggesting that the integration of Sentinel-1/2 data with parcel-based method has great potential for regional maize mapping. For the estimation of maize phenology, the dynamic threshold method is used to extract the tasseling and milk ripening date through the time series σ0VH. In order to reduce the influence of precipitation or irrigation on SAR data, a Local Minimum Value Composite (LMVC) method is proposed to filter the original time series SAR data. The systematic phenology estimation method mainly includes LMVC, S-G filtering, Fourier curve fitting and dynamic threshold points extracting. Compared with the actual phenology date by field investigation, the errors of estimated tasseling and milk ripening date are 4.3 days and 5.5 days respectively, indicating that the time series σ0VH derived from the SAR data has great potential in spatiotemporal phenology estimation of field maize. Finally, the scattering mechanism of the maize field to C-band microwave in different growth periods was analyzed. It was also found that the phenology of maize was delayed in the coal mining subsidence areas and the areas with insufficient field management. Numéro de notice : A2022-232 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102720 Date de publication en ligne : 24/02/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102720 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100121 [article]

In situ C-band data for wheat physiological functioning monitoring in the South Mediterranean region / Nadia Ouaadi (2022)  

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Field scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques / Rajkumar Dhakar in Geocarto international, vol 36 n° 18 ([01/10/2021])  

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Geoglam, l'agriculture par satellite / Laurent Polidori in Géomètre, n° 2194 (septembre 2021)

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Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])  

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Leaf area index estimation of wheat crop using modified water cloud model from the time-series SAR and optical satellite data / Vijay Pratap Yadav in Geocarto international, vol 36 n° 7 ([15/04/2021])  

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A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)  

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GIS-based multi-criteria analysis of the suitability of western Siberian forest-steppe lands / V.K. Kalichkin in Annals of GIS, vol 27 n° 2 (April 2021)  

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Apport des données satellitaires Sentinel-1 et Sentinel-2 pour la détection des surfaces irriguées et l'estimation des besoins et des consommations en eau des cultures d'été dans les zones tempérées / Yann Pageot (2021)  

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Apport de la télédétection pour la simulation spatialisée des composantes du bilan carbone des cultures et des effets d'atténuation biogéochimiques et biogéophysiques des cultures intermédiaires / Gaétan Pique (2021)  

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Diagnostics of Plant Diseases / Dmitry Kurouski (2021)  

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