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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Land Use and Land Cover 2019 of Ribaue Mountains (Mount Ribaue and Mount M'paluwe) in Mozambique

Authors: Montfort, Frédérique; Grinand, Clovis;

Land Use and Land Cover 2019 of Ribaue Mountains (Mount Ribaue and Mount M'paluwe) in Mozambique

Abstract

This repository includes the land use and land cover map of the Ribaue Mountains and surroundings (Ribaue district, Nampula province, Mozambique), using remote sensing. The Ribaue massif is a series of granite inselbergs in northern Mozambique near the town of Ribaue in Nampula Province. The main area of the massif is made up of the Serra de Ribaue to the west and the Serra de M'paluwe to the east. The inselbergs rise from a relatively flat landscape at ca 500-600 m altitude up to 1675 m on Monte M'paluwe. They form part of a belt of granite rock outcrops, inselbergs and mountains, running NE-SW across Nampula and Zambezia provinces and including Mt Inago (1804 m) and Mt Namuli (2419 m) to the southwest of the Ribaue massif. This belt is considered as a center of endemism. Overall the site supports 15 nationally endemic plant taxa (plants that only occur in Mozambique), 11 near-endemics (plants that are restricted to Mozambique and neighbouring countries) and 10 taxa that are threatened with extinction on the Global IUCN Red List. Steeply sloping granite rock outcrops, mid-altitude moist forest and miombo woodland are the dominant habitat types at the Ribaue massif. The site also includes smaller areas of gallery forest, marsh, seasonal stream gullies, seepage on granite rock, and shaded granite cliffs. The methodology used in this study is based on a classical approach of remote sensing: satellite image collection (cloud-free and shadow free Sentinel 2, 10 m resolution, two season), identification of land use typology (based on field campains), delineation of training plots, supervised classification of land use using a machine learning algorithm (Random Forest) and finally, calculation of land occupation statistics. The methodology and statistics are presented in the report included in the repository.

Keywords

Sentinel 2, Sky Island, Moist forest, Land Use and Land Cover, Mozambique, Random forest

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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