دورية أكاديمية
Very high resolution land use and land cover mapping using pleiades-1 stereo imagery and machine learning
| العنوان: | Very high resolution land use and land cover mapping using pleiades-1 stereo imagery and machine learning |
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| المؤلفون: | James, D., Collin, Antoine, Mury, A., Costa, S. |
| المساهمون: | École Pratique des Hautes Études (EPHE), Université Paris Sciences et Lettres (PSL), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École Pratique des Hautes Études (EPHE), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN) |
| المصدر: | ISSN: 1682-1750. |
| بيانات النشر: | HAL CCSD Copernicus GmbH (Copernicus Publications) |
| سنة النشر: | 2020 |
| المجموعة: | Archive Ouverte de l'Université Rennes (HAL) |
| مصطلحات موضوعية: | Pleiades-1, VHR, multispectral, DSM, classification, LULC, [SDE.MCG]Environmental Sciences/Global Changes, [SDE.ES]Environmental Sciences/Environment and Society, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SHS.GEO]Humanities and Social Sciences/Geography, [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph], [STAT.ME]Statistics [stat]/Methodology [stat.ME], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDE.IE]Environmental Sciences/Environmental Engineering, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing |
| الوصف: | International audience ; Anthropocene is featured with increasing human population and global changes that strongly affect landscapes at an unprecedented pace. As a flagship, the coastal fringe is subject to an accelerated conversion of natural areas into agricultural ones, in turn, into urban ones, generating hazardous soil artificialization. Very high resolution (VHR) technologies such as airborne LiDAR or UAV imageries are good assets to model the topography and classify the land use/land cover (LULC), helping local management. Even if their spatial resolution suits with the management scale, their extent covers a few km2, making large-scale monitoring complex and time-consuming. VHR spaceborne imagery has a great potential to address this spatial challenge given its regional acquisition. This research proposes to evaluate the capabilities of a Pleiades-1 stereo-satellite multispectral imagery (blue, green, red, BGR, and near-infrared, NIR) to both model the surface topography and classify LULC. Horizontal and vertical accuracies of the photogrammetry-driven digital surface model (DSM) attain 0.53 m and 0.65 m, respectively. Nine LULC generic classes are studied using the maximum likelihood (ML) and support vector machine (SVM) algorithms. The classification accuracy of the basic BGR (reaching 84.64 % and 76.13 % with ML and SVM, respectively) is improved by the DSM contribution (5.49 % and 2.91 % for ML and SVM, respectively), and the NIR contribution (6.78 % and 3.89 % for ML and SVM, respectively). The gain of the DSM-NIR combination totals 8.91 % and 8.40 % for ML and SVM, respectively, making the ML-based full combination the best performance (93.55 %). |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | hal-03378889; https://hal.science/hal-03378889Test; https://hal.science/hal-03378889/documentTest; https://hal.science/hal-03378889/file/isprs-archives-XLIII-B2-2020-675-2020.pdfTest |
| DOI: | 10.5194/isprs-archives-XLIII-B2-2020-675-2020 |
| الإتاحة: | https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-675-2020Test https://hal.science/hal-03378889Test https://hal.science/hal-03378889/documentTest https://hal.science/hal-03378889/file/isprs-archives-XLIII-B2-2020-675-2020.pdfTest |
| حقوق: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.90DF45B4 |
| قاعدة البيانات: | BASE |
| DOI: | 10.5194/isprs-archives-XLIII-B2-2020-675-2020 |
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