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A fully-automated approach to land cover mapping with airborne LiDAR and high resolution multispectral imagery in a forested suburban landscape / Jason R. Parent in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)
[article]
Titre : A fully-automated approach to land cover mapping with airborne LiDAR and high resolution multispectral imagery in a forested suburban landscape Type de document : Article/Communication Auteurs : Jason R. Parent, Auteur ; John C. Volin, Auteur ; Daniel L. Civco, Auteur Année de publication : 2015 Article en page(s) : pp 18 - 29 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification automatique
[Termes IGN] classification pixellaire
[Termes IGN] Connecticut (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] forêt ripicole
[Termes IGN] image multibande
[Termes IGN] PinophytaRésumé : (auteur) Information on land cover is essential for guiding land management decisions and supporting landscape-level ecological research. In recent years, airborne light detection and ranging (LiDAR) and high resolution aerial imagery have become more readily available in many areas. These data have great potential to enable the generation of land cover at a fine scale and across large areas by leveraging 3-dimensional structure and multispectral information. LiDAR and other high resolution datasets must be processed in relatively small subsets due to their large volumes; however, conventional classification techniques cannot be fully automated and thus are unlikely to be feasible options when processing large high-resolution datasets. In this paper, we propose a fully automated rule-based algorithm to develop a 1 m resolution land cover classification from LiDAR data and multispectral imagery.
The algorithm we propose uses a series of pixel- and object-based rules to identify eight vegetated and non-vegetated land cover features (deciduous and coniferous tall vegetation, medium vegetation, low vegetation, water, riparian wetlands, buildings, low impervious cover). The rules leverage both structural and spectral properties including height, LiDAR return characteristics, brightness in visible and near-infrared wavelengths, and normalized difference vegetation index (NDVI). Pixel-based properties were used initially to classify each land cover class while minimizing omission error; a series of object-based tests were then used to remove errors of commission. These tests used conservative thresholds, based on diverse test areas, to help avoid over-fitting the algorithm to the test areas.
The accuracy assessment of the classification results included a stratified random sample of 3198 validation points distributed across 30 1 × 1 km tiles in eastern Connecticut, USA. The sample tiles were selected in a stratified random manner from locations representing the full range of rural to urban landscapes in eastern Connecticut. The overall land cover accuracy was 93% with accuracies exceeding 90% for deciduous trees, low vegetation, water, buildings, and low impervious cover. Slight confusion occurred between coniferous and deciduous trees; major confusion occurred between water and riparian wetlands; and moderate confusion occurred between medium vegetation and other vegetation classes. The algorithm was robust for the forested suburban landscape of eastern Connecticut, which is typical for much of the northeastern U.S., and the algorithm shows promise for applications in similar landscapes with similar datasets. Further research is needed to test the applicability of the algorithm to more diverse landscapes as well as with different LiDAR and multispectral datasets.Numéro de notice : A2015-698 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78334
in ISPRS Journal of photogrammetry and remote sensing > vol 104 (June 2015) . - pp 18 - 29[article]Building a hybrid land cover map with crowdsourcing and geographically weighted regression / Linda M. See in ISPRS Journal of photogrammetry and remote sensing, vol 103 (May 2015)
[article]
Titre : Building a hybrid land cover map with crowdsourcing and geographically weighted regression Type de document : Article/Communication Auteurs : Linda M. See, Auteur ; Dmitry Schepaschenko, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 48 - 56 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] image à moyenne résolution
[Termes IGN] image Envisat-MERIS
[Termes IGN] intégration de données
[Termes IGN] production participative
[Termes IGN] régression géographiquement pondéréeRésumé : (auteur) Land cover is of fundamental importance to many environmental applications and serves as critical baseline information for many large scale models e.g. in developing future scenarios of land use and climate change. Although there is an ongoing movement towards the development of higher resolution global land cover maps, medium resolution land cover products (e.g. GLC2000 and MODIS) are still very useful for modelling and assessment purposes. However, the current land cover products are not accurate enough for many applications so we need to develop approaches that can take existing land covers maps and produce a better overall product in a hybrid approach. This paper uses geographically weighted regression (GWR) and crowdsourced validation data from Geo-Wiki to create two hybrid global land cover maps that use medium resolution land cover products as an input. Two different methods were used: (a) the GWR was used to determine the best land cover product at each location; (b) the GWR was only used to determine the best land cover at those locations where all three land cover maps disagree, using the agreement of the land cover maps to determine land cover at the other cells. The results show that the hybrid land cover map developed using the first method resulted in a lower overall disagreement than the individual global land cover maps. The hybrid map produced by the second method was also better when compared to the GLC2000 and GlobCover but worse or similar in performance to the MODIS land cover product depending upon the metrics considered. The reason for this may be due to the use of the GLC2000 in the development of GlobCover, which may have resulted in areas where both maps agree with one another but not with MODIS, and where MODIS may in fact better represent land cover in those situations. These results serve to demonstrate that spatial analysis methods can be used to improve medium resolution global land cover information with existing products. Numéro de notice : A2015-696 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78331
in ISPRS Journal of photogrammetry and remote sensing > vol 103 (May 2015) . - pp 48 - 56[article]Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil / Dan-Xia Song in ISPRS Journal of photogrammetry and remote sensing, vol 103 (May 2015)
[article]
Titre : Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil Type de document : Article/Communication Auteurs : Dan-Xia Song, Auteur ; Chengquan Huang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 81 - 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] Brésil
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte forestière
[Termes IGN] détection de changement
[Termes IGN] Etats-Unis
[Termes IGN] forêt tropicale
[Termes IGN] image Corona
[Termes IGN] image LandsatRésumé : (auteur) Land-cover change detection using satellite remote sensing is largely confined to the era of Landsat satellites, from 1972 to present. However, the Corona, Argon, and Lanyard intelligence satellites operated by the U.S. government between 1960 and 1972 have the potential to provide an important extension of the long-term record of Earth’s land surface. Recently declassified, the archive of images recorded by these satellites contains hundreds of thousands of photographs, many of which have very high ground resolution- 6–9 ft (1.8–2.7 m) even by today’s standards. This paper demonstrates methods for extending the span of forest-cover change analysis from the Landsat-5 and -7 era (1984 to present) to the previous era covered by the Corona archive in two study areas: one area covered predominantly by urban and sub-urban land uses in the eastern US and another area by tropical forest in central Brazil. We describe co-registration of Corona and Landsat images, extraction of texture features from Corona images, classification of Corona and Landsat images, and post-classification change detection based on the resulting thematic dataset. Second-order polynomial transformation of Corona images yielded geometric accuracy relative to Landsat-7 of 18.24 m for the urban area and 29.35 m for the tropical forest study area, generally deemed adequate for pixel-based change detection at Landsat resolution. Classification accuracies were approximately 95% and 96% for forest/non-forest discrimination for the temperate urban and tropical forest study areas, respectively. Texture within 7 × 7- to 9 × 9-pixel (∼13.0–16.5 m) neighborhoods and within 11 × 11-pixel (∼30 m) neighborhoods were the most informative metrics for forest classification in Corona images in the temperate and tropical study areas, respectively. The trajectory of change from the 1960s to 2000s differed between the two study areas: the average annual forest loss rate in the urban area doubled from 0.68% to 1.9% from the 1960s to the mid-1980s and then decreased during the following decade. In contrast, deforestation in the Brazilian study area continued at a slightly increased pace between the 1960s and 1990s at annual loss rate of 0.62–0.79% and quickly slowed down afterward. This study demonstrates the strong potential of declassified Corona images for detecting historical forest changes in these study regions and suggests increased utility for retrieving a wide range of land cover histories around the world. Numéro de notice : A2015-697 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.09.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.09.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78333
in ISPRS Journal of photogrammetry and remote sensing > vol 103 (May 2015) . - pp 81 - 92[article]Improved land cover mapping using aerial photographs and satellite images / Katalin Varga in Open geosciences, vol 7 n° 1 (January 2015)
[article]
Titre : Improved land cover mapping using aerial photographs and satellite images Type de document : Article/Communication Auteurs : Katalin Varga, Auteur ; Szilárd Szabó, Auteur ; Gergely Szabó, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 15 - 26 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] couvert végétal
[Termes IGN] image aérienne
[Termes IGN] image Landsat
[Termes IGN] MNS SRTM
[Termes IGN] précision de la classification
[Termes IGN] variation saisonnièreRésumé : (auteur) Manual Land Cover Mapping using aerial photographs provides sufficient level of resolution for detailed vegetation or land cover maps. However, in some cases it is not possible to achieve the desired information over large areas, for example from historical data where the quality and amount of available images is definitely lower than from modern data. The use of automated and semi automated methods offers the means to identify the vegetation cover using remotely sensed data. In this paper automated methods were tested on aerial photographs and satellite images to extract better and more reliable information about vegetation cover. These testswere performed by using automated analysis of LANDSAT7 images (with and without the surface model of the Shuttle Radar Topography Mission (SRTM)) and two temporally similar aerial photographs. The spectral bands were analyzed with supervised (maximum likelihood) methods. In conclusion, the SRTM and the combination of two temporally similar aerial photographs from earlier years were useful in separating the vegetation cover on a floodplain area. In addition the different date of the vegetation season also gave reliable information about the land cover. High quality information about old and present vegetation on a large area is an essential prerequisites ensuring the conservation of ecosystems. Numéro de notice : A2015-435 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1515/geo-2015-0002 En ligne : https://doi.org/10.1515/geo-2015-0002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77035
in Open geosciences > vol 7 n° 1 (January 2015) . - pp 15 - 26[article]Méthode de cartographie de la consommation de sol agricole dans le Grand Genève / Marie-Laure Halle (2015)
Titre : Méthode de cartographie de la consommation de sol agricole dans le Grand Genève Type de document : Mémoire Auteurs : Marie-Laure Halle, Auteur Editeur : Strasbourg : Institut National des Sciences Appliquées INSA Strasbourg Année de publication : 2015 Importance : 66 p. Format : 21 x 30 cm Note générale : Bibliographie
Mémoire de fin d'études INSA StrasbourgLangues : Français (fre) Descripteur : [Termes IGN] agglomération
[Termes IGN] analyse des besoins
[Termes IGN] analyse diachronique
[Termes IGN] base de données localisées
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte transfrontalière
[Termes IGN] cartographie urbaine
[Termes IGN] collecte de données
[Termes IGN] état de l'art
[Termes IGN] Genève
[Termes IGN] harmonisation des données
[Termes IGN] outil d'aide à la décision
[Termes IGN] prototype
[Termes IGN] surface cultivée
[Termes IGN] urbanisme
[Termes IGN] utilisation du sol
[Termes IGN] zone (aménagement du territoire)
[Vedettes matières IGN] GéovisualisationIndex. décimale : INSAS Mémoires d'ingénieur de l'INSA Strasbourg - Topographie, ex ENSAIS Résumé : (Auteur) Le grand Genève est une agglomération très dynamique, un de ses enjeux principaux est de limiter la consommation de sol agricole. Le projet consiste en la mise au point d'un outil cartographique transfrontalier. Les questions à résoudre relatives aux données ont été : leur disponibilité variable selon les territoires, l'accès aux sources, leur actualisation, leur harmonisation, leur traitement. Les deux prototypes développés sur un périmètre test, permettent un suivi annuel de la consommation du sol agricole, ainsi qu'un suivi de l'évolution décennale de l'utilisation des sols. Ils s'accompagnent de recommandations pour l'extension et la pérennisation des méthodes sur l'ensemble du Grand Genève. Enfin une proposition de vulgarisation de ces outils techniques permettra une meilleure communication. Numéro de notice : 22485 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Mémoire ingénieur INSAS Organisme de stage : Le Grand Genève Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80731 Documents numériques
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22485_Méthode de cartographie de la consommation de sol agricole dans le Grand Genève_Halle.pdfAdobe Acrobat PDF Sub-pixel-scale land cover map updating by integrating change detection and sub-pixel mapping / Xiaodong Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 1 (January 2015)PermalinkL’infographie comme support pour comprendre / Laurie Gobled in Cahiers de l'Institut d'aménagement et d'urbanisme de la région Île-de-France, n° 169 (juin 2014)PermalinkAssessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkAn entropy-based multispectral image classification algorithm / Di Long in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)PermalinkUne base nationale pour quels objectifs ? / Thierry Touzet in Cahiers de l'Institut d'aménagement et d'urbanisme de la région Île-de-France, n° 168 (décembre 2013)PermalinkA combined object- and pixel-based image analysis framework for urban land cover classification of VHR imagery / Bahram Salehi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)PermalinkMapping and assessing of urban impervious areas using multiple endmember spectral mixture analysis: a case study in the city of Tampa, Florida / Fenqing Weng in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkModeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkA data mining approach for evaluation of optimal time-series of MODIS data for land cover mapping at a regional level / Fuqun Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)PermalinkAnalysing spatio-temporal footprints of urbanization on environment of Surat city using satellite-derived bio-physical parameters / Richa Sharma in Geocarto international, vol 28 n° 5-6 (August - October 2013)PermalinkModelling the impacts of civil war on land use and land cover change within Kono District, Sierra Leone: a socio-geospatial approach / Sigismond A. Wilson in Geocarto international, vol 28 n° 5-6 (August - October 2013)PermalinkAn object-based system for Lidar data fusion and feature extraction / Jarlath P. M. O'Neil-Dunne in Geocarto international, vol 28 n° 3-4 (June - July 2013)PermalinkImproving representation of land-use maps derived from object-oriented image classification / Wenxiu Gao in Transactions in GIS, vol 17 n° 3 (June 2013)PermalinkOrganiser la topographie pour répondre aux nouvelles exigences réglementaires / Henri Pornon in Géomatique expert, n° 92 (01/06/2013)PermalinkAssessing reference dataset representativeness through confidence metrics based on information density / Giorgos Mountrakis in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkObject-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)PermalinkSpectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region / George P. Petropoulos in Geocarto international, vol 28 n° 1-2 (February - May 2013)PermalinkAnalyse par télédétection des paysages agraires des villages de Barani, Sampieri et Orodara (Burkina Faso) / Marius Yao (2013)PermalinkContribution à la mise en place d'un SIG fédérateur des données géographiques pour l'aménagement et les infrastructures / Mustapha Mimouni (2013)PermalinkUpdating land-cover maps by classification of image time series : A novel change-detection-driven transfer learning approach / Begüm Demir in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)Permalink