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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Samples and 4-class predictions of agroforest-forest frontiers mapping in Peru

Research datakeyboard_double_arrow_right Dataset 17 Oct 2024 English Publisher:Zenodo
Authors: wanting, yang;

doi: 10.5281/zenodo.13946752 , 10.5281/zenodo.13946751

Samples and 4-class predictions of agroforest-forest frontiers mapping in Peru

Abstract

This is a database for the study of agroforest-forest frontiers mapping conducted by Wanting Yang, etc. The data contained in the repository includes two parts. 1. the training samples(polygons and rectagle_roi) annotated with Google Earth as reference. We used Google Earth Pro to make the date of Google Earth imagery match with PlanetScope imagery. 2. the prediction from the 4-class model. Users can visualize the data with QGIS or other GIS software.

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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!
0
Average
Average
Average