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 p...

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Main Authors: Yuhe Zhao, Xuanlong Ma, Zhengyang Zhang, Kedi Liu, Wenjuan Li
Format: Article
Language:English
Published: Taylor & Francis Group 2025-08-01
Series:International Journal of Digital Earth
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2506186
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author Yuhe Zhao
Xuanlong Ma
Zhengyang Zhang
Kedi Liu
Wenjuan Li
author_facet Yuhe Zhao
Xuanlong Ma
Zhengyang Zhang
Kedi Liu
Wenjuan Li
author_sort Yuhe Zhao
collection DOAJ
description 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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spelling doaj-art-e54d7c039b0c4e0589fce493fa7654552025-08-25T11:25:10ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2506186Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2Yuhe Zhao0Xuanlong Ma1Zhengyang Zhang2Kedi Liu3Wenjuan Li4International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, People’s Republic of ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, People’s Republic of ChinaState Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, People’s Republic of ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, People’s Republic of ChinaState Key Laboratory of Efficient Utilization of Arable Land in China, Key Laboratory of Agricultural Remote Sensing (AGRIRS) Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of ChinaThe 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.https://www.tandfonline.com/doi/10.1080/17538947.2025.2506186Sustainable development goalsterrestrial biodiversityBig Earth Datamainland Southeast Asiaconservation planning
spellingShingle Yuhe Zhao
Xuanlong Ma
Zhengyang Zhang
Kedi Liu
Wenjuan Li
Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
International Journal of Digital Earth
Sustainable development goals
terrestrial biodiversity
Big Earth Data
mainland Southeast Asia
conservation planning
title Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
title_full Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
title_fullStr Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
title_full_unstemmed Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
title_short Leveraging big Earth data for spatially explicit tracking of the progress on UN SDG15.1.2
title_sort leveraging big earth data for spatially explicit tracking of the progress on un sdg15 1 2
topic Sustainable development goals
terrestrial biodiversity
Big Earth Data
mainland Southeast Asia
conservation planning
url https://www.tandfonline.com/doi/10.1080/17538947.2025.2506186
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