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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Industrial and Smallholder Oil Palm Plantation Expansion in Indonesia from 2001 to 2019

Authors: Gaveau, David; Salim, Mohammad Agus; Husnayaen; Manurung, Timer;

Industrial and Smallholder Oil Palm Plantation Expansion in Indonesia from 2001 to 2019

Abstract

The dataset contains wall-to-wall maps of the annual expansion of industrial and smallholder oil palm plantations from 2001 to 2019 generated from interpretation of annual LANDSAT composites, SPOT-6 and UAV imagery. We define an oil palm plantation as an area of land planted with oil palm trees (Elaeis guineensis Jacq.). Industrial plantations are intensively managed large-scale, typically covering several thousand hectares of land, plantations owned by companies. They exhibit distinctive linear boundaries while harvesting trails are laid out in grids on level land or follow contours on hilly terrain. Smallholder plantations are typically smaller — < 25 hectares according to government definition — although wealthy individuals sometimes own several hundred hectares — and their spatial patterns are less consistent. Smallholder landscapes sometimes form a mixed mosaic with one or more other crops and types of landcover , or a large homogeneous landscape , or resemble industrial plantings though generally smaller and with less consistent structure. The datasets are in shapefile format with the following columns: Year: The year an area was converted to oil palm. This is the year an area of either Forest or Non-Forest transitioned to either industrial or smallholder oil palm. Class: The type of plantation that exists as of year 2019. Class has category: ‘IOPP’ for Industrial Oil Palm Plantation or 'Smallholder'. Gridcode: A code for the year the annual Tree Loss dataset (version 1.7) - developed at University of Maryland (Hansen et al. 2013) - recorded a loss, and whether this is loss of trees in the forest or loss of non-forested trees. This column can be ignored. 1xx : Year forest loss detected, where xx represents the last 2 digits of the year (from 2001 to 2019) when the loss happened. For example, 105 indicates forest loss in 2005. 300 : Non-forest since 2000. 3xx : Year tree (non-forest) loss detected, where xx represents the last 2 digits of the year (from 2001 to 2019) when the loss happened. For example, 305 indicates tree loss in 2005 in non-forest areas with trees. F2000 to F2019: The annual land cover types (Forest or Non forest) that existed before oil palm plantations replaced them. TDelay : The time delay (in number of years) beween the year an area lost its forest cover and the year it was developed as a plantation. If Tdelay = 0, the area was developed as a plantation in the same calendar year that it lost forest cover, or the area was already not forest in 2000. CompDriven : The year an area was developed as a plantation and lost its forest cover. We reasoned that industrial plantations developed in the same year as forest clearance are likely to be responsible for that clearance, hence the term Company-driven deforestation. If CompDriven = 0 the area lost its forest cover several years (at one year) before it was developed as a plantation. Region: The name of the region considered (Sumatra, Kalimantan, Java, Sulawesi, Maluku and Papua) AreaHA: The area in hectares

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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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