Persistent Identifier
|
doi:10.23708/U6WTLE |
Publication Date
|
2023-06-01 |
Title
| Land use land cover high resolution map (10 m) for the area of Tori-Bossito, Benin, 2010-2011 |
Author
| Moiroux, Nicolas (UMR MIVEGEC - IRD, CNRS, Univ.Montpellier - France) - ORCID: 0000-0001-6755-6167
Bio-Bangana, Sahabi (Université d'Agriculture de Kétou - Benin) - ORCID: 0000-0003-0059-4075 |
Point of Contact
|
Use email button above to contact.
Moiroux, Nicolas (UMR MIVEGEC - IRD, CNRS, Univ.Montpellier - France) |
Description
| This dataset is a high spatial resolution Land Use / Land Cover (LULC) map of the region of Tori-Bossito, southern Benin. Its spatial resolution is 10 m. It was produced in 2011 and made available for a wide range of uses.
It has been produced to study the environmental determinants of the presence and abundance of three malaria mosquito species.
It contains 14 land cover classes: Freshwater, Herbswamp, Aquatic grassland, Coco tree, Eucalyptus tree, Thicket, Palm tree, Savanna, Teak tree, Pineapple, Degraded riparian forest, Degraded surfaces, Rain-fed agriculture, Forest.
The method used to generate the map involved a supervised object-based image classification using mono- and multi-spectral SPOT 5 satellite products from 2010, ground-truth data (> 200 plots) acquired by fieldwork (2010-2011), and nearest-neighbor classifier. The classification accuracy was 98%.
In addition to the LULC georeferenced raster data, we propose the following files in this release:
- the raster attribute table, as an .ods (libreoffice) file, including names and definitions of the land cover classes in both English and French ;
- a QGIS layer style file (.qml) for visualizing the raster in QGIS ;
- two color map files (.clr) (English and French) to be used in a variety of GIS software.
- the map as a .png miniature image ;
- representative pictures of the land cover classes ;
The methodology used to generate the data was detailed in french in Moiroux 2012 (https://theses.hal.science/tel-00812118, p. 79-85 ) and in English, in a more concise way in Moiroux et al. 2013 ( https://doi.org/10.1186/1756-3305-6-71). (2023-05-23) |
Subject
| Agricultural Sciences; Computer and Information Science; Earth and Environmental Sciences; Medicine, Health and Life Sciences |
Keyword
| land use
land cover
vegetation
agriculture
wetland |
Scientific Theme
| Cartography (NumeriSud) https://uri.ird.fr/so/kos/tnu/128 |
Related Publication
| Moiroux, N., Bio-Bangana, A.S., Djènontin, A., Chandre, F., Corbel, V., Guis, H. (2013) "Modelling the risk of being bitten by malaria vectors in a vector control area in southern Benin, west Africa", Parasites & Vectors. Springer Science and Business Media LLC. doi: 10.1186/1756-3305-6-71 https://doi.org/10.1186/1756-3305-6-71
Nicolas Moiroux. Modélisation du risque d'exposition aux moustiques vecteurs de Plasmodium spp. dans un contexte de lutte anti-vectorielle.. Ecologie, Environnement. Université Montpellier II - Sciences et Techniques du Languedoc, 2012. Français. ⟨NNT : ⟩. ⟨tel-00812118⟩ url: https://theses.hal.science/tel-00812118
Moiroux, N., Djènontin, A., Bio-Bangana, A.S., Chandre, F., Corbel, V., Guis, H. (2014) "Spatio-temporal analysis of abundances of three malaria vector species in southern Benin using zero-truncated models", Parasites & Vectors. Springer Science and Business Media LLC. doi: 10.1186/1756-3305-7-103 https://doi.org/10.1186/1756-3305-7-103 |
Language
| English; French |
Producer
| Moiroux, Nicolas (UMR MIVEGEC - IRD, CNRS, Univ.Montpellier - France) |
Production Location
| Cotonou, Benin |
Contributor
| Data Collector : Moiroux, Nicolas
Data Collector : Bio-Bangana, Sahabi
Supervisor : Guis, Hélène |
Funding Information
| CNES: ISIS (412)
Ministère Francais des Affaires Etrangères: FSP REFS (2022-6) |
Depositor
| Moiroux, Nicolas (UMR MIVEGEC - IRD, CNRS, Univ.Montpellier - France) |
Deposit Date
| 2023-05-23 |
Date of Collection
| Start Date: 2010-01-01 ; End Date: 2010-01-31
Start Date: 2011-03-01 ; End Date: 2011-03-31 |
Software
| ArcGis, Version: 9
eCognition, Version: 4
QGIS, Version: 3 |
Data Source
| SPOT5 scene ID 50643371001201018472T SPOT5 scene ID 50643371001201018502J |