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Discover SEA Peatland through our interactive mapping tool. It contain publicly available dataset that easy to use for everyone. Get more in-depth information about peatland.

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Peatland Extent

Gumbricht et al (2017)

An expert system model for mapping tropical wetland and peatland reveals South America  the largest contributor

This study estimate wetland development and extracted peat forming wetland for peatland map. The wetland development is gathered by calculate water balance, differentiate seasonal/permanent wet and its hydrogeomorphology. 

Xu et al (2017)

PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis

The dataset is results of multiple scientific studies and geospatial information combine. Taking into consideration the relevance of identifying peatland from other land cover types, finest spatial resolution, and most updated data. In the case of Indonesia, the data source originates from Ritung et al. (2011), the old Indonesia government official map. For Malaysia, the data is derived from Wetland International (2010).

Protected Area

UNEP- WCMC and IUCN

World Database on Protected Areas

A global database encompassing both marine and terrestrial protected areas. It is a collaborative project between the UN Environment Programme and the International Union for Conservation of Nature (IUCN). The data undergoes monthly updates.

Global Forest Watch (GFW)

Sarawak Protected Areas

On the GFW website, it is explained tha the boundaries for Protected Areas rely on maps provided by the Sarawak Forestry Department (SFD). These maps delineate Protected Areas in Sarawak, categorizing them as National Parks, Wildlife Sanctuaries, and Nature Reserves. Some of these areas are officially gazetted, while others remain ungazetted and are classified as 'proposed.'

Forest Loss

Hansen et al (2013)

High-Resolution Global Maps of 21st-Century Forest Cover Change

The dataset consists of tree cover in year 2000, tree loss, and tree gain. The tree loss layer is updated annually, the newest is for 2022. Here forest loss define as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. The data were generated using multispectral satellite imagery from the Landsat 5 (TM), the Landsat 7 (ETM+), and the Landsat 8 OLI

Global Trends of Forest Loss Due to Fire From 2001 to 2019

its 30-meter resolution satellite map forest loss due to fire vs. other disturbance drivers. the study aligned the mapped forest loss areas with reference data obtained through an unbiased sampling method. the code 4, indicating a high level of certainty regarding forest loss due to fires, corresponds to the sample-based estimate minus its standard error

Oil Palm Plantation

Descals et al (2021)

High resolution global industrial and smallholder oil palm map for 2019

This dataset provides a 10-meter resolution global map distinguishing between industrial-scale and smallholder oil palm plantations, based on Sentinel-1 and Sentinel-2 imagery. The temporal coverage focuses on the year 2019, capturing the distribution of plantations worldwide. Using advanced machine learning classification, this spatially explicit dataset supports the analysis of oil palm expansion, its environmental impacts, and land-use change patterns.

Global Forest Watch (GFW)

Spatial Database of Planted Trees 2.0 (including oil palm, rubber, and other species)

it's a compilation of plantation data by Global Forest Watch (GFW) from a wide range of countries and sources, including national governments, non-governmental organizations, and independent researchers. The dataset provides detailed information on both planted forests and agricultural tree crops, such as oil palm, rubber, coffee, coconut, cocoa, and other orchard species. The majority of data anchored around 2020.

Canal Density

Dadap et al (2021)

Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions

The dataset covers peatland areas in Sumatra, Borneo, and Peninsular Malaysia, and was developed using manually digitized drainage canals based on high-resolution satellite imagery dated on 2015–2019. The study found that drainage canals are present in 65% of Southeast Asia’s peatlands, significantly increasing carbon emissions through peat oxidation and subsidence. These canals are a major driver of peatland degradation, underscoring the urgent need for restoration and rewetting efforts.

Green House Gases

Harris et al (2021)

Global maps of twenty-first century forest carbon fluxes

This study provides high-resolution 30 m scale, of emissions, removals, and net carbon balance data from 2001 - 2019. The analysis shows that global forests acted as a net carbon sink, absorbing ~7.6 ± 4.9 Gt CO₂e per year, despite significant emissions from deforestation and degradation. 

© 2024 Southeast Asia Peatland Team

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