Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2

The UN SDG15 'Life on Land,' aims to promote the sustainable management and use of terrestrial ecosystems, with sub-indicator SDG15.1.2 quantifying the proportion of Key Biodiversity Areas (KBAs) covered by protected areas. However, progress on SDG15.1.2 remains unclear, complicating the prioritization of ecosystems with high conservation potential. Here, we propose an innovative framework that utilizes Big Earth Data (BED) to quantify SDG15.1.2 across five mainland Southeast Asian (MSA) countries. This framework employs the Integrative Multidimensional Biodiversity Index (iMBI) to map KBAs, enabling the derivation of SDG15.1.2 by overlaying KBA maps with protected areas. The results indicate that Cambodia (87.3%) and Thailand (63.9%) have relatively high SDG15.1.2, while Myanmar (13%), Vietnam (23.3%), and Laos (25.1%) exhibit considerably lower values, resulting in a regional average of 29.1% for the MSA. While there was a slight upward trend in SDG15.1.2 from 2000 to 2020, the rate of increase remains insufficient to achieve comprehensive legal protection for the majority of KBAs by 2030. Furthermore, we identified areas with high conservation potential that remain unprotected, providing insights for improving SDG15.1.2. Although the MSA serves as a case study, the proposed framework is adaptable to other regions, facilitating consistent and spatially explicit global tracking of UN SDG15.1.2.

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Publication Details

Journal
International Journal of Digital Earth
Published
2025-05-25
DOI
https://doi.org/10.1080/17538947.2025.2506186
Citations
3
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
20.17

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article

Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2

Yuhe Zhao, Xuanlong Ma, Kedi Liu, Wenjuan Li et al.
3 citations
International Journal of Digital Earth
Geographic Information Systems Studies
20.17
article

Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2

Yuhe Zhao, Xuanlong Ma, Kedi Liu, Wenjuan Li, Zhengyang Zhang
article en
3 citations

Abstract

The UN SDG15 'Life on Land,' aims to promote the sustainable management and use of terrestrial ecosystems, with sub-indicator SDG15.1.2 quantifying the proportion of Key Biodiversity Areas (KBAs) covered by protected areas. However, progress on SDG15.1.2 remains unclear, complicating the prioritization of ecosystems with high conservation potential. Here, we propose an innovative framework that utilizes Big Earth Data (BED) to quantify SDG15.1.2 across five mainland Southeast Asian (MSA) countries. This framework employs the Integrative Multidimensional Biodiversity Index (iMBI) to map KBAs, enabling the derivation of SDG15.1.2 by overlaying KBA maps with protected areas. The results indicate that Cambodia (87.3%) and Thailand (63.9%) have relatively high SDG15.1.2, while Myanmar (13%), Vietnam (23.3%), and Laos (25.1%) exhibit considerably lower values, resulting in a regional average of 29.1% for the MSA. While there was a slight upward trend in SDG15.1.2 from 2000 to 2020, the rate of increase remains insufficient to achieve comprehensive legal protection for the majority of KBAs by 2030. Furthermore, we identified areas with high conservation potential that remain unprotected, providing insights for improving SDG15.1.2. Although the MSA serves as a case study, the proposed framework is adaptable to other regions, facilitating consistent and spatially explicit global tracking of UN SDG15.1.2.

International Journal of Digital EarthVol. 18(1)
Beijing Normal University (CN), Beijing Institute of Big Data Research (CN), Chinese Academy of Agricultural Sciences (CN), Institute for Sustainable Development (ET), Sanya University (CN), State Key Laboratory of Remote Sensing Science (CN), Lanzhou University (CN)
International Development Research Centre, Natural Science Foundation of Gansu Province
Climate action
Openalex Percentile: Top 1%
Geographic Information Systems Studies
20.17
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