Descripteur


Etendre la recherche sur niveau(x) vers le bas
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)
![]()
[article]
Titre : A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery Type de document : Article/Communication Auteurs : Lucas Prado Osco, Auteur ; Mauro Dos Santos de Arruda, Auteur ; Diogo Nunes Gonçalves, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] apprentissage profond
[Termes descripteurs IGN] carte agricole
[Termes descripteurs IGN] Citrus sinensis
[Termes descripteurs IGN] classification par réseau neuronal convolutif
[Termes descripteurs IGN] comptage
[Termes descripteurs IGN] cultures
[Termes descripteurs IGN] détection d'objet
[Termes descripteurs IGN] extraction de la végétation
[Termes descripteurs IGN] gestion durable
[Termes descripteurs IGN] image captée par drone
[Termes descripteurs IGN] maïs (céréale)
[Termes descripteurs IGN] rendement agricoleRésumé : (auteur) Accurately mapping croplands is an important prerequisite for precision farming since it assists in field management, yield-prediction, and environmental management. Crops are sensitive to planting patterns and some have a limited capacity to compensate for gaps within a row. Optical imaging with sensors mounted on Unmanned Aerial Vehicles (UAV) is a cost-effective option for capturing images covering croplands nowadays. However, visual inspection of such images can be a challenging and biased task, specifically for detecting plants and rows on a one-step basis. Thus, developing an architecture capable of simultaneously extracting plant individually and plantation-rows from UAV-images is yet an important demand to support the management of agricultural systems. In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its plants considering highly-dense plantation configurations. The experimental setup was evaluated in (a) a cornfield (Zea mays L.) with different growth stages (i.e. recently planted and mature plants) and in a (b) Citrus orchard (Citrus Sinensis Pera). Both datasets characterize different plant density scenarios, in different locations, with different types of crops, and from different sensors and dates. This scheme was used to prove the robustness of the proposed approach, allowing a broader discussion of the method. A two-branch architecture was implemented in our CNN method, where the information obtained within the plantation-row is updated into the plant detection branch and retro-feed to the row branch; which are then refined by a Multi-Stage Refinement method. In the corn plantation datasets (with both growth phases – young and mature), our approach returned a mean absolute error (MAE) of 6.224 plants per image patch, a mean relative error (MRE) of 0.1038, precision and recall values of 0.856, and 0.905, respectively, and an F-measure equal to 0.876. These results were superior to the results from other deep networks (HRNet, Faster R-CNN, and RetinaNet) evaluated with the same task and dataset. For the plantation-row detection, our approach returned precision, recall, and F-measure scores of 0.913, 0.941, and 0.925, respectively. To test the robustness of our model with a different type of agriculture, we performed the same task in the citrus orchard dataset. It returned an MAE equal to 1.409 citrus-trees per patch, MRE of 0.0615, precision of 0.922, recall of 0.911, and F-measure of 0.965. For the citrus plantation-row detection, our approach resulted in precision, recall, and F-measure scores equal to 0.965, 0.970, and 0.964, respectively. The proposed method achieved state-of-the-art performance for counting and geolocating plants and plant-rows in UAV images from different types of crops. The method proposed here may be applied to future decision-making models and could contribute to the sustainable management of agricultural systems. Numéro de notice : A2021-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.024 date de publication en ligne : 13/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97171
in ISPRS Journal of photogrammetry and remote sensing > Vol 174 (April 2021) . - pp 1 - 17[article]Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm / Mehrdad Bijandi in Transactions in GIS, Vol 25 n° 1 (February 2021)
![]()
[article]
Titre : Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm Type de document : Article/Communication Auteurs : Mehrdad Bijandi, Auteur ; Mohammad Karimi, Auteur ; Bahman Farhadi Bansouleh, Auteur ; Wim van der Knaap, Auteur Année de publication : 2021 Article en page(s) : pp 551 - 574 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] données topographiques
[Termes descripteurs IGN] irrigation
[Termes descripteurs IGN] optimisation par colonie de fourmis
[Termes descripteurs IGN] parcelle agricole
[Termes descripteurs IGN] planification
[Termes descripteurs IGN] remembrement agricole
[Termes descripteurs IGN] surface cultivée
[Termes descripteurs IGN] utilisation du solRésumé : (Auteur) In the process of agricultural land consolidation, the land parcels are optimally redesigned and rearranged in such a way that the dimensions of the resulting parcels are proportional to agricultural criteria such as irrigation discharge, soil texture, and cropping pattern. Besides these criteria, spatial factors like slope, road accessibility, volume of earthwork, and geometrical factors such as size and shape of parcels are also included in the design process of agricultural land partitioning. In this study, a land partitioning model was proposed using a multi‐objective artificial bee colony algorithm (MOABC‐LP) taking into consideration the mentioned factors. Initially, a feasible dimension range of parcels in a block was calculated based on irrigation efficiency. Two partitioning layouts were defined according to the topography and geometry of blocks. The proposed method was applied to a real study area and the results suggest that the land partitioning plan obtained by the MOABC‐LP model, in comparison with a designer's plan, not only makes the shape and size of parcels more compatible with the topographical and agricultural conditions of each block, but also reduces their cut‐and‐fill ratio. Numéro de notice : A2021-210 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12702 date de publication en ligne : 27/10/2020 En ligne : https://doi.org/10.1111/tgis.12702 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97159
in Transactions in GIS > Vol 25 n° 1 (February 2021) . - pp 551 - 574[article]Is Xylella fastidiosa a serious threat to European forests? / Marie-Laure Desprez-Loustau in Forestry, an international journal of forest research, vol 94 n° 1 (January 2021)
![]()
[article]
Titre : Is Xylella fastidiosa a serious threat to European forests? Type de document : Article/Communication Auteurs : Marie-Laure Desprez-Loustau, Auteur ; Yialmaz Balci, Auteur ; Daniele Cornara, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Acer pseudoplatanus
[Termes descripteurs IGN] Amérique du nord
[Termes descripteurs IGN] dépérissement
[Termes descripteurs IGN] écosystème forestier
[Termes descripteurs IGN] Europe (géographie politique)
[Termes descripteurs IGN] Italie
[Termes descripteurs IGN] maladie bactérienne
[Termes descripteurs IGN] Olea europaea
[Termes descripteurs IGN] Quercus (genre)
[Termes descripteurs IGN] Ulmus (genre)
[Termes descripteurs IGN] viticulture
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The recent emergence of Olive Quick Decline Syndrome in Italy, caused by Xylella fastidiosa, has drawn attention to the risks posed by this vector-borne bacterium to important crops in Europe (especially fruit trees and grapevine). Comparatively very little is known on actual and potential impacts of this pathogen in forests, in the native (North American) and introduced (European) regions, respectively. The present review aims to address important questions related to the threat posed by X. fastidiosa to European forests, such as the following: What are the symptoms, hosts and impact of bacterial leaf scorch caused by X. fastidiosa on trees in North America? Which forest tree species have been found infected in the introduction area in Europe? How does X. fastidiosa cause disease in susceptible hosts? Are there any X. fastidiosa genotypes (subspecies and sequence types) specifically associated with forest trees? How is X. fastidiosa transmitted? What are the known and potential vectors for forest trees? How does vector ecology affect disease? Is the distribution of X. fastidiosa, especially the strains associated with trees, restricted by climatic factors? Is disease risk for trees different in forest ecosystems as compared with urban settings? We conclude by pointing to important knowledge gaps related to all these questions and strongly advocate for more research about the Xylella-forest pathosystems, in both North America and Europe. Numéro de notice : A2021-072 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpaa029 date de publication en ligne : 06/08/2020 En ligne : https://doi.org/10.1093/forestry/cpaa029 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96805
in Forestry, an international journal of forest research > vol 94 n° 1 (January 2021) . - pp 1 - 17[article]Norway Spruce Seedlings from an Eastern Baltic Provenance Show Tolerance to Simulated Drought / Roberts Matisons in Forests, vol 12 n° 1 (January 2021)
![]()
[article]
Titre : Norway Spruce Seedlings from an Eastern Baltic Provenance Show Tolerance to Simulated Drought Type de document : Article/Communication Auteurs : Roberts Matisons, Auteur ; Oskars Krišāns, Auteur ; Aris Jansons, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 82 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] adaptation (biologie)
[Termes descripteurs IGN] analyse de sensibilité
[Termes descripteurs IGN] chlorophylle
[Termes descripteurs IGN] état du sol
[Termes descripteurs IGN] irrigation
[Termes descripteurs IGN] Lettonie
[Termes descripteurs IGN] photosynthèse
[Termes descripteurs IGN] Picea abies
[Termes descripteurs IGN] sécheresse
[Termes descripteurs IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) In Northern Europe, an increase in heterogeneity of summer precipitation regime will subject forests to water deficit and drought. This is particularly topical for Norway spruce (Picea abies Karst.), which is a drought sensitive, yet economically important species. Nevertheless, local populations still might be highly plastic and tolerant, supporting their commercial application. Accordingly, the tolerance of Norway spruce seedlings from an Eastern Baltic provenance (western part of Latvia) to artificial drought according to soil type was assessed in a shelter experiment. To simulate drought, seedlings were subjected to reduced amounts (0%, 25%, 50%, 75%, and 100%) of naturally occurring precipitation (irrigation intensity). Three soil types (oligotrophic mineral, mesotrophic mineral, and peat) were tested. Seedling height, chlorophyll a concentration, and fluorescence parameters were measured. Both growth and photochemical reactions were affected by the irrigation intensity, the effect of which experienced an interacted with soil type, implying complex controls of drought sensitivity. Seedlings were more sensitive to irrigation intensity on mesotrophic mineral soil, as suggested by growth and photosynthetic activity. However, the responses were nonlinear, as the highest performance (growth and fluorescence parameters) of seedlings occurred in response to intermediate drought. On peat soil, which had the highest water-bearing capacity, an inverse response to irrigation intensity was observed. In general, fluorescence parameters were more sensitive and showed more immediate reaction to soil water deficit than concentration of chlorophyll on mesotrophic mineral and peat soils, while the latter was a better indicator of seedling performance on oligotrophic soil. This indicated considerable plastic acclimation and hence tolerance of seedlings from the local Norway spruce population to drought, though drought sensitivity is age-dependent. Numéro de notice : A2021-145 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12010082 date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.3390/f12010082 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97048
in Forests > vol 12 n° 1 (January 2021) . - n° 82[article]Monitoring of wheat crops using the backscattering coefficient and the interferometric coherence derived from Sentinel-1 in semi-arid areas / Nadia Ouaadi in Remote sensing of environment, Vol 251 (15 December 2020)
![]()
[article]
Titre : Monitoring of wheat crops using the backscattering coefficient and the interferometric coherence derived from Sentinel-1 in semi-arid areas Type de document : Article/Communication Auteurs : Nadia Ouaadi, Auteur ; Lionel Jarlan, Auteur ; Jamal Ezzahar, Auteur ; Mehrez Zribi, Auteur ; Saïd Khabba, Auteur ; Elhoussaine Bouras, Auteur ; Safa Bousbih, Auteur ; Pierre-Louis Frison , Auteur
Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 112050 Note générale : bibliographie
This work was conducted within the frame of the International Joint Laboratory TREMA (https://www.lmi-trema.ma/). The authors wish to thank the projects: Rise-H2020-ACCWA (grant agreement no: 823965) and ERANETMED03-62 CHAAMS for partly funding the experiments.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] bande C
[Termes descripteurs IGN] blé (céréale)
[Termes descripteurs IGN] coefficient de rétrodiffusion
[Termes descripteurs IGN] cultures
[Termes descripteurs IGN] données polarimétriques
[Termes descripteurs IGN] évapotranspiration
[Termes descripteurs IGN] humidité du sol
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] image Sentinel-SAR
[Termes descripteurs IGN] Maroc
[Termes descripteurs IGN] polarisation
[Termes descripteurs IGN] surveillance agricole
[Termes descripteurs IGN] teneur en eau de la végétation
[Termes descripteurs IGN] zone semi-arideRésumé : (auteur) Radar data at C-band has shown great potential for the monitoring of soil and canopy hydric conditions of wheat crops. In this study, the C-band Sentinel-1 time series including the backscattering coefficients σ0 at VV and VH polarization, the polarization ratio (PR) and the interferometric coherence ρ are first analyzed with the support of experimental data gathered on three plots of irrigated winter wheat located in the Haouz plain in the center of Morocco covering five growing seasons. The results showed that ρ and PR are tightly related to the canopy development. ρ is also sensitive to soil preparation. By contrast, σ0 was found to be widely linked to changes in surface soil moisture (SSM) during the first growth stages when Leaf Area Index remains moderate ( Numéro de notice : A2020-337 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2020.112050 date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.1016/j.rse.2020.112050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96939
in Remote sensing of environment > Vol 251 (15 December 2020) . - n° 112050[article]Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])
PermalinkAdaptation de l'irrigation au changement climatique dans l'Union européenne : les actions engagées par les États membres pour économiser l'eau / Claire Serra-Wittling in Sciences, eaux & territoires, n° 34 (novembre 2020)
PermalinkAn integration of bioclimatic, soil, and topographic indicators for viticulture suitability using multi-criteria evaluation: a case study in the Western slopes of Jabal Al Arab—Syria / Karam Alsafadi in Geocarto international, vol 35 n° 13 ([01/10/2020])
PermalinkComparative analysis of index and chemometric techniques-based assessment of leaf area index (LAI) in wheat through field spectroradiometer, Landsat-8, Sentinel-2 and Hyperion bands / Bappa Das in Geocarto international, vol 35 n° 13 ([01/10/2020])
PermalinkAnalysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization / Ning Liu in Remote sensing, vol 12 n° 17 (September 2020)
PermalinkDetecting abandoned farmland using harmonic analysis and machine learning / Heeyeun Yoon in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
PermalinkMapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery / Kasper Johansen in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
PermalinkCounting of grapevine berries in images via semantic segmentation using convolutional neural networks / Laura Zabawa in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
PermalinkDiscriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data / Sugandh Chauhan in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
PermalinkProfitability of growing Scots pine on cutaway peatlands / Lasse Aro in Silva fennica, vol 54 n° 3 (June 2020)
Permalink