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In situ calibration of light sensors for long-term monitoring of vegetation / Hongxiao Jin 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 3405 - 3416 Titre : In situ calibration of light sensors for long-term monitoring of vegetation Type de document : Article/Communication Auteurs : Hongxiao Jin, Auteur ; Lars Eklundh, Auteur Année de publication : 2015 Article en page(s) : pp 3405 - 3416 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] capteur terrestre [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] photosynthèse [Termes IGN] propagation d'erreur [Termes IGN] surveillance forestière Résumé : (Auteur) Light sensors are increasingly used to monitor vegetation growing status by measuring reflectance or transmittance in multispectral or photosynthetically active radiation (PAR) bands. The measurements are then used to estimate vegetation indices or the fraction of absorbed PAR (FPAR) in a continuous and long-term manner and to serve as inputs to environmental monitoring and calibration/validation data for satellite remote sensing. However, light-sensor calibration is often overlooked or not properly attended to, which leads to difficulties when comparing the measurement results across sites and through time. In this paper, we investigate a practical and accurate user-level in situ calibration method in daylight. The calibration of a sensor pair is made for measuring either bihemispherical reflectance or hemispherical-conical reflectance, which are the two most common ground-based spectral measurements. Procedures and considerations are suggested for user calibration. We also provide a method for calibrating and measuring a single-sensor reflectance-derived Normalized Difference Vegetation Index (NDVI) from red and near-infrared bands. The calibration error propagation is analyzed, and the induced uncertainties in vegetation reflectance and in the NDVI are evaluated. The analysis and field measurements show that the NDVI estimated from a user calibration factor can be as accurate as, or even more accurate than, the manufacturer's calibration. The in situ calibration described here remedies the situation where reflectance for large field-of-view sensors cannot be always estimated from the manufacturer's calibration. The method developed in this paper may help improve the reliability of long-term field spectral measurements and contributes to the near-surface remote sensing of vegetation. Numéro de notice : A2015-275 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2375381 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2375381 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76388 [article]

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Discovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)  

Public [article]  inTransactions in GIS > vol 16 n° 3 (June 2012) . - pp 411 - 429 Titre : Discovering spatial patterns in origin-destination mobility data Type de document : Article/Communication Auteurs : D. Guo, Auteur ; Hongxiao Jin, Auteur ; C. Andris, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 411 - 429 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] analyse spatiale [Termes IGN] base de données d'objets mobiles [Termes IGN] cartographie des flux [Termes IGN] distribution spatiale [Termes IGN] données spatiotemporelles [Termes IGN] Kouangtoung (Chine) [Termes IGN] mobilité urbaine [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] origine - destination [Termes IGN] positionnement par GPS [Termes IGN] trajectographie par GPS [Termes IGN] transport urbain [Termes IGN] véhicule automobile Résumé : (Auteur) Mobility and spatial interaction data have become increasingly available due to the wide adoption of location-aware technologies. Examples of mobility data include human daily activities, vehicle trajectories, and animal movements, among others. In this article, we focus on a special type of mobility data, i.e. origin-destination pairs, and present a new approach to the discovery and understanding of spatio-temporal patterns in the movements. Specifically, to extract information from complex connections among a large number of point locations, the approach involves two steps: (1) spatial clustering of massive GPS points to recognize potentially meaningful places; and (2) extraction and mapping of the flow measures of clusters to understand the spatial distribution and temporal trends of movements. We present a case study with a large dataset of taxi trajectories in Shenzhen, China to demonstrate and evaluate the methodology. The contribution of the research is two-fold. First, it presents a new methodology for detecting location patterns and spatial structures embedded in origin-destination movements. Second, the approach is scalable to large data sets and can summarize massive data to facilitate pattern extraction and understanding. Numéro de notice : A2012-282 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01344.x Date de publication en ligne : 28/05/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01344.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31728 [article]