Centre dedocumentation
scientifique

Automatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 63 - 76 Titre : Automatic canola mapping using time series of Sentinel 2 images Type de document : Article/Communication Auteurs : Davoud Ashourloo, Auteur ; Hamid Salehi Shahrabi, Auteur ; Mohsen Azadbakht, Auteur ; Hossein Aghighi, Auteur ; Hamed Nematollahi, Auteur ; Abbas Alimohammadi, Auteur ; Ali Akbar Matkan, Auteur Année de publication : 2019 Article en page(s) : pp 63 - 76 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] agriculture de précision [Termes descripteurs IGN] Brassica napus subsp. napus [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] Iran [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] Oklahoma (Etats-Unis) [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] série temporelle Résumé : (Auteur) Different techniques utilized for mapping various crops are mainly based on using training dataset. But, due to difficulties of access to a well-represented training data, development of automatic methods for detection of crops is an important need which has not been considered as it deserves. Therefore, main objective of present study was to propose a new automatic method for canola (Brassica napus L.) mapping based on Sentinel 2 satellite time series data. Time series data of three study sites in Iran (Moghan, Gorgan, Qazvin) and one site in USA: (Oklahoma), were used. Then, spectral reflectance values of canola in various spectral bands were compared with those of the other crops during the growing season. NDVI, Red and Green spectral bands were successfully applied for automatic identification of canola flowering date using the threshold values. Examination of the fisher function indicated that multiplication of the near-infrared (NIR) band by the sum of red and green bands during the flowering date is an efficient index to differentiate canola from the other crops. The Kappa and overall accuracy (OA) for the four study sites were more than 0.75 and 88%, respectively. Results of this research demonstrated the potential of the proposed approach for canola mapping using time series of remotely sensed data. Numéro de notice : A2019-317 Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.08.007 date de publication en ligne : 09/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93355 [article]

Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes / Meng Zhang in Geocarto international, vol 34 n° 10 (October 2019)  

Public [article]  inGeocarto international > vol 34 n° 10 (October 2019) . - pp 1144 - 1161 Titre : Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes Type de document : Article/Communication Auteurs : Meng Zhang, Auteur ; Yongnian Zeng, Auteur ; Wei Huang, Auteur ; Songnian Li, Auteur Année de publication : 2019 Article en page(s) : pp 1144 - 1161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] Chine [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] hétérogénéité [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] paysage urbain [Termes descripteurs IGN] zone humide Résumé : (auteur) Remote sensing has been proven promising in wetland mapping. However, conventional methods in a complex and heterogeneous urban landscape usually use mono temporal Landsat TM/ETM + images, which have great uncertainty due to the spectral similarity of different land covers, and pixel-based classifications may not meet the accuracy requirement. This paper proposes an approach that combines spatiotemporal fusion and object-based image analysis, using the spatial and temporal adaptive reflectance fusion model to generate a time series of Landsat 8 OLI images on critical dates of sedge swamp and paddy rice, and the time series of MODIS NDVI to calculate phenological parameters for identifying wetlands with an object-based method. The results of a case study indicate that different types of wetlands can be successfully identified, with 92.38%. The overall accuracy and 0.85 Kappa coefficient, and 85% and 90% for the user’s accuracies of sedge swamp and paddy respectively. Numéro de notice : A2019-302 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1474275 date de publication en ligne : 17/05/2018 En ligne : https://doi.org/10.1080/10106049.2018.1474275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93222 [article]

A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520 Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Afrique australe [Termes descripteurs IGN] bois [Termes descripteurs IGN] extraction de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image Ikonos [Termes descripteurs IGN] image Landsat-SWIR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] plante herbacée [Termes descripteurs IGN] savane [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019071	SL	Revue	Centre de documentation	Revues en salle	Disponible

Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols / Sen Cao in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 132 - 145 Titre : Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols Type de document : Article/Communication Auteurs : Sen Cao, Auteur ; Brad Danielson, Auteur ; Shari Clare, Auteur Année de publication : 2019 Article en page(s) : pp 132 - 145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] bande infrarouge [Termes descripteurs IGN] bande rouge [Termes descripteurs IGN] capteur multibande [Termes descripteurs IGN] drone [Termes descripteurs IGN] étalonnage radiométrique [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] test de performance Résumé : (Auteur) The main objective of this study was to develop and test a framework that can be used by Unmanned Aerial Systems (UAS) operators with varying technical backgrounds to estimate the accuracy and reliability of multispectral (visible and Near-Infrared or NIR) sensor measurements. We evaluated the performance of two multispectral sensors – the MicaSense RedEdge and the Airinov MultiSpec 4C – in both a laboratory and field setting. In the laboratory, we measured the reflectance of a number of reference target materials using each UAS sensor, and compared the values to those measured using a calibrated spectrometer. We found a strong linear relationship between the measurements made by the MicaSense RedEdge and the spectrometer, while the relationship was much weaker for the Airinov MultiSpec 4C, particularly in the longer wavelength bands (red-edge and NIR). A sub-set of the target materials were selected as ground reference targets for three field calibration exercises. In field calibration assessment No. 1, imagery was collected using each UAS sensor and reflectance values were extracted from pixels covering the ground reference targets. The extracted values were compared to the reflectance values acquired in the laboratory, and both UAS sensors were found to over-estimate reflectance, with lower accuracy in red-edge and NIR bands. Field calibration assessment No. 2 involved a calculation of Normalized Difference Vegetation Index (NDVI) values at field control points using both UAS sensors, and we found a strong linear relationship between the NDVI values and measurements made by a hand-held NDVI sensor, suggesting that the calculation of a normalized band ratio (i.e., NDVI) effectively reduces the reflectance measurement inaccuracy that we observed previously. Field calibration assessment No. 3 included image acquisition of ground reference targets using the MicaSense RedEdge sensor over seventeen sequential field surveys. Results revealed measurement variability over time, suggesting that daily differences in solar illumination and atmospheric conditions may influence derived reflectance values. In light of these results, we propose simplified procedures that can be adopted by UAS operators to periodically assess the radiometric fidelity of their multispectral sensors. Numéro de notice : A2019-226 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.016 date de publication en ligne : 29/01/2019 En ligne : https://doi.org/ Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92445 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019031	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2019033	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2019032	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Assessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 1 (January 2019) . - pp 43 - 54 Titre : Assessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data Type de document : Article/Communication Auteurs : Long Wang, Auteur ; Binbin He, Auteur ; Xiaojing Bai, Auteur ; Minfeng Xing, Auteur Année de publication : 2019 Article en page(s) : pp 43 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Enhanced vegetation index [Termes descripteurs IGN] étalonnage de modèle [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] Iowa (Etats-Unis) [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] modèle de rétrodiffusion [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] série temporelle Résumé : (auteur) Soil moisture is an important state variable of the land surface ecosystem. In this paper, the water cloud model (WCM) and advanced integral equation model (AIEM) are coupled to retrieve soil moisture using time series Sentinel-1A data and moderate resolution imaging spectroradiometer (MODIS) data. Normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR), are cross-combined to initialize the calibrated model. The calibration results show the following: (1) Vegetation parameters have a great influence on model calibration; and (2) The combination of (NDVI, LAI) is recommended to calibrate the coupled model, the RMSE, R2 is 0.739 dB, and 0.716 for the observed and estimated backscattering coefficients. The soil moisture inversion results show that: (1) the accuracy of model calibration and soil moisture inversion are inconsistent; and (2) The normalized vegetation parameters, such as NDVI, EVI and FPAR, are suitable for WCM to describe vegetation characteristics, and NDVI is the optimum. When V2 is the NDVI, the average bias, MAE, RMSE, ubRMSE and R2 are –0.007 m3/m3, 0.074 m3/m3, 0.087 m³/m³, 0.087 m3/m3 and 0.750, respectively. Numéro de notice : A2019-029 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.1.43 date de publication en ligne : 01/01/2019 En ligne : https://doi.org/10.14358/PERS.85.1.43 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91965 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019011	SL	Revue	Centre de documentation	Revues en salle	Disponible

Individual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

Permalink

A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index / Huanhuan Yuan in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Permalink

Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Permalink

Drought sensitiveness on forest growth in peninsular Spain and the Balearic Islands / Marina Peña-Gallardo in Forests, vol 9 n° 9 (September 2018)  

Permalink

Effects of a large-scale late spring frost on a beech (Fagus sylvatica L.) dominated Mediterranean mountain forest derived from the spatio-temporal variations of NDVI / Angelo Nolè in Annals of Forest Science [en ligne], vol 75 n° 3 (September 2018)  

Permalink

An improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Permalink

Intra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Permalink

Mapping rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)  

Permalink

Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)  

Permalink

A comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere / Qing Chang in Geocarto international, vol 33 n° 1 (January 2018)  

Permalink