Data · dataset · 2025
A dataset of aboveground biomass carbon density in forests in Southeast China (2002-2017)
Listed in ScienceDB
The research used satellite observations from MODIS and SMOS to estimate aboveground carbon density changes in southern China from 2002 to 2017.
Description
A static benchmark map of carbon density for 2015 was used to train a machine learning algorithm applied to annual MODIS imagery to estimate carbon density changes. SMOS low-frequency passive microwave data at 25 kmx 25 km resolution was used to independently assess biomass changes and soil moisture trends from 2010-2017.
The carbon density dataset covers southern China at 500 m x 500 m spatial resolution from 2002-2017. It was validated against independent tree cover data at 30 m and 5.6 km resolutions. Quality control involved comparing to high-resolution 2 m satellite imagery and forestry data.
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The dataset quantifies the carbon sequestration impact of different forest management strategies like afforestation, harvesting, and natural regrowth. It demonstrates southern China's forests offset 33% of regional fossil fuel emissions, with implications for climate change mitigation.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00001.01523 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Forestry sciences 72% · Satellite remote sensing 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00001.01523 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3007 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:remote-sensing | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |