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Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece / Stavroula Dimitriadou in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)
[article]
Titre : Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece Type de document : Article/Communication Auteurs : Stavroula Dimitriadou, Auteur ; Konstantinos G. Nikolakopoulos, Auteur Année de publication : 2021 Article en page(s) : n° 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ArcMap
[Termes IGN] changement climatique
[Termes IGN] climat méditerranéen
[Termes IGN] évapotranspiration
[Termes IGN] Grèce
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de Monteith
[Termes IGN] système d'information géographique
[Termes IGN] température
[Termes IGN] utilisation du sol
[Termes IGN] variation saisonnièreRésumé : (auteur) The present study develops ArcMap models to implement the following three methods: FAO-56 Penman–Monteith (FAO PM), Hargreaves–Samani (HS) and Hansen, with the former used as a reference. Moreover, three models implementing statistical indices (RMSD, MB, NMB) are also created. The purpose is threefold, as follows: to investigate the variability in the daily mean reference evapotranspiration (ETo) for the Decembers and Augusts during 2016–2019, over Peloponnese, Greece. Furthermore, to investigate the agreement between the methods’ ETo estimates, and examine the former along with MODIS ET (daily) averaged products. The study area is a complex Mediterranean area. Meteorological data from sixty-two stations under the National Observatory of Athens (NOA), and MODIS Terra LST products, have been employed. FAO PM is found sensitive to wind speed and depicts interactions among climate parameters (T, evaporative demand and water availability) in the frame of climate change. The years 2016–2019 are four of the warmest since the preindustrial era. Hargreaves–Samani’s estimations for the Decembers of 2016–2019 were almost identical to MODIS ET, despite their different physical meaning. However, for the Augusts there are considerable discrepancies between the methods’ and MODIS’s estimates, attributed to the higher evaporative demand in the summertime. The GIS models are accurate, reliable, time-saving, and adjustable to any study area. Numéro de notice : A2021-522 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060390 Date de publication en ligne : 05/06/2021 En ligne : https://doi.org/10.3390/ijgi10060390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97959
in ISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 390[article]The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)
[article]
Titre : The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries Type de document : Article/Communication Auteurs : Nagihan Aslan, Auteur ; Dilek Koc-San, Auteur Année de publication : 2021 Article en page(s) : n° 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image proche infrarouge
[Termes IGN] Normalized Difference Built-up Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] occupation du sol
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] température au sol
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (auteur) The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period. Numéro de notice : A2021-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060416 Date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.3390/ijgi10060416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97936
in ISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 416[article]Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery / Mahmoud Salah in Applied geomatics, vol 13 n° 2 (June 2021)
[article]
Titre : Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery Type de document : Article/Communication Auteurs : Mahmoud Salah, Auteur Année de publication : 2021 Article en page(s) : pp 261 - 275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement d'histogramme
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] Egypte
[Termes IGN] géoréférencement
[Termes IGN] image à très haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image multitemporelle
[Termes IGN] incertitude des données
[Termes IGN] méthode robuste
[Termes IGN] modèle de Markov caché
[Termes IGN] occupation du sol
[Termes IGN] réseau neuronal artificiel
[Termes IGN] utilisation du solRésumé : (auteur) Robust approaches for image change detection (ICD) are essential for a range of large-scale applications. However, the uncertainties involved in such approaches have not been fully addressed. To investigate this problem, this paper proposes a new approach for change detection from multi-temporal very high resolution (VHR) satellite imagery based on uncertainty detection and management. First, two GeoEye-1 images of Giza urban area (Egypt), acquired in 2009 and 2019, have been geographically co-registered and their histograms have been matched. Second, a set of feature attributes have been generated from the co-registered images. Third, the support vector machine (SVM) algorithm has been adopted to classify the data into four classes: building, tree, road, and ground. In this regard, the co-registered images along with the generated attributes have been applied as input data for the SVM to calculate the probability of each pixel belonging to each class. After that, the probability images for both epochs have been compared to model the uncertainty of changes. The uncertainty places are then evaluated to estimate their likelihood of being change or no change. Finally, the obtained results have been compared with manually digitized change detection map. Compared with using the widely used post-classification comparison (PCC) approach, the results suggest that (1) the proposed method has improved the overall accuracy of change detection by 13%; (2) the class-accuracies have been improved by 35.63%; and (3) the achieved accuracies for the proposed approach are less variable. Whereas the standard deviation (SD) of the accuracies obtained for the proposed approach is 6.80, the SD of those obtained for the PCC approach is 35.50. Numéro de notice : A2021-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00346-z Date de publication en ligne : 28/10/2020 En ligne : https://doi.org/10.1007/s12518-020-00346-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97737
in Applied geomatics > vol 13 n° 2 (June 2021) . - pp 261 - 275[article]Electrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])
[article]
Titre : Electrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed Type de document : Article/Communication Auteurs : H.S. Virupaksha, Auteur ; K.N. Lokesh, Auteur Année de publication : 2021 Article en page(s) : pp 888 - 902 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] aquifère
[Termes IGN] bassin hydrographique
[Termes IGN] carte des pentes
[Termes IGN] carte hydrogéologique
[Termes IGN] eau souterraine
[Termes IGN] géomorphologie locale
[Termes IGN] Karnataka (Inde)
[Termes IGN] lithologie
[Termes IGN] occupation du sol
[Termes IGN] potentiel hydrogène
[Termes IGN] précipitation
[Termes IGN] résistivité
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) Electrical resistivity method and RS & GIS techniques are very much useful in identification of potential aquifer zones for exploitation, management and recharge of groundwater. Vertical Electrical Soundings are conducted at 35 locations in Gurpur watershed using Schlumberger array. The thematic layers like porosity, transmissivity and hydraulic conductivity are prepared using electrical resistivity data. Total of 13 thematic layers are used for vector integration and identification of Groundwater Potential Zones (GWPZ). The numerical weights and ranks are assigned to the themes based on their relationship with groundwater. The findings shows that the depth to bedrock varies from 9.1 to 44.4 m and most of the mid land and low land region shows moderate to high depths of about 25–44 m. The GWPZ are classified into five classes namely, Very Good (≈21.02 km2), Good (≈231.35 km2), Moderate (≈420.76 km2), Poor (≈185.05 km2) and Very Poor (≈19.56 km2). The Good and Moderate categories cover ≈75% of total area. Numéro de notice : A2021-483 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1624986 Date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1624986 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97442
in Geocarto international > vol 36 n° 8 [01/05/2021] . - pp 888 - 902[article]Integrating a forward feature selection algorithm, random forest, and cellular automata to extrapolate urban growth in the Tehran-Karaj region of Iran / Hossein Shafizadeh-Moghadam in Computers, Environment and Urban Systems, vol 87 (May 2021)
[article]
Titre : Integrating a forward feature selection algorithm, random forest, and cellular automata to extrapolate urban growth in the Tehran-Karaj region of Iran Type de document : Article/Communication Auteurs : Hossein Shafizadeh-Moghadam, Auteur ; Masoud Minaei, Auteur ; Robert Gilmore Pontius Jr, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101595 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] croissance urbaine
[Termes IGN] extrapolation
[Termes IGN] image Landsat
[Termes IGN] modèle de simulation
[Termes IGN] occupation du sol
[Termes IGN] Téhéran
[Termes IGN] utilisation du solRésumé : (auteur) This paper couples a Forward Feature Selection algorithm with Random Forest (FFS-RF) to create a transition index map, which then guides the spatial allocation for the extrapolation of urban growth using a Cellular Automata model. We used Landsat imagery to generate land cover maps at the years 1998, 2008, and 2018 for the Tehran-Karaj Region (TKR) in Iran. The FFS-RF considered the independent variables of slope, altitude, and distances from urban, crop, greenery, barren, and roads. The FFS-RF revealed temporal non-stationary of drivers from 1998–2008 to 2008–2018. The FFS-RF detected that altitude and distance from greenery were the most important drivers of urban growth during 1998–2008, then distances from crop and barren were the most important drivers during 2008–2018. We used the Total Operating Characteristic to evaluate the transition index maps. Validation during 2008–2018 showed that FFS-RF produced a transition index map that had predictive power no better than an allocation of urban growth near existing urban. Simulation to 2060 extrapolated that Tehran, Karaj, and their adjacent cities will interconnect spatially to form a gigantic city-region. Numéro de notice : A2021-274 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101595 Date de publication en ligne : 16/02/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101595 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97357
in Computers, Environment and Urban Systems > vol 87 (May 2021) . - n° 101595[article]Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future / Tamás Gál in Computers, Environment and Urban Systems, vol 87 (May 2021)PermalinkA Voronoi-based method for land-use optimization using semidefinite programming and gradient descent algorithm / Vorapong Suppakitpaisarn in International journal of geographical information science IJGIS, vol 35 n° 5 (May 2021)PermalinkA user-driven process for INSPIRE-compliant land use database: example from Wallonia, Belgium / Benjamin Beaumont in Annals of GIS, vol 27 n° 2 (April 2021)PermalinkAggregating land-use polygons considering line features as separating map elements / Sven Gedicke in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)PermalinkAssessing land use–land cover change and soil erosion potential using a combined approach through remote sensing, RUSLE and random forest algorithm / Siddhartho Shekhar Paul in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkAttribution of the Australian bushfire risk to anthropogenic climate change / Geert Jan Van Oldenborgh in Natural Hazards and Earth System Sciences, vol 21 n° 3 (March 2021)PermalinkSuitability assessment of urban land use in Dalian, China using PNN and GIS / Ziqian Kang in Natural Hazards, vol 106 n° 1 (March 2021)PermalinkAgricultural 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)PermalinkGeographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling / Stefanos Georganos in Geocarto international, vol 36 n° 2 ([01/02/2021])PermalinkLand cover harmonization using Latent Dirichlet Allocation / Zhan Li in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkMapping seasonal agricultural land use types using deep learning on Sentinel-2 image time series / Misganu Debella-Gilo in Remote sensing, Vol 13 n° 2 (January-2 2021)PermalinkApports des méthodes d'apprentissage profond pour la reconnaissance automatique des modes d'occupation des sols et d'objets par télédétection en milieu tropical / Guillaume Rousset (2021)PermalinkPermalinkChange detection of land use and land cover, using landsat-8 and sentinel-2A images / Mohammed Abdulmohsen Alhedyan (2021)PermalinkDevelopment and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors / Marta Sapena Moll (2021)PermalinkEvaluation of Sentinel-1 & 2 time series for the identification and characterization of ecological continuities, from wooded to crop-dominated landscapes / Audrey Mercier (2021)PermalinkPermalinkGeovisualization of artificial land use in European cities in 2006, with urban scaling laws / Axel Pecheric (2021)PermalinkPermalinkPermalink