Global Maps of Agricultural Expansion Potential at a 300 m Resolution
The global expansion of agricultural land is a leading driver of climate change and biodiversity loss. However, the spatial resolution of current global land change models is relatively coarse, which limits environmental impact assessments. To address this issue, we developed global maps representin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/12/3/579 |
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| author | Mirza Čengić Zoran J. N. Steinmann Pierre Defourny Jonathan C. Doelman Céline Lamarche Elke Stehfest Aafke M. Schipper Mark A. J. Huijbregts |
| author_facet | Mirza Čengić Zoran J. N. Steinmann Pierre Defourny Jonathan C. Doelman Céline Lamarche Elke Stehfest Aafke M. Schipper Mark A. J. Huijbregts |
| author_sort | Mirza Čengić |
| collection | DOAJ |
| description | The global expansion of agricultural land is a leading driver of climate change and biodiversity loss. However, the spatial resolution of current global land change models is relatively coarse, which limits environmental impact assessments. To address this issue, we developed global maps representing the potential for conversion into agricultural land at a resolution of 10 arc-seconds (approximately 300 m at the equator). We created the maps using artificial neural network (ANN) models relating locations of recent past conversions (2007–2020) into one of three cropland categories (cropland only, mosaics with >50% crops, and mosaics with <50% crops) to various predictor variables reflecting topography, climate, soil, and accessibility. Cross-validation of the models indicated good performance with area under the curve (AUC) values of 0.88–0.93. Hindcasting of the models from 1992 to 2006 revealed a similar high performance (AUC of 0.83–0.91), indicating that our maps provide representative estimates of current agricultural conversion potential provided that the drivers underlying agricultural expansion patterns remain the same. Our maps can be used to downscale projections of global land change models to more fine-grained patterns of future agricultural expansion, which is an asset for global environmental assessments. |
| first_indexed | 2024-03-11T06:18:32Z |
| format | Article |
| id | doaj.art-c3d0603fc723470295112f70f8fcd37c |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-11T06:18:32Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-c3d0603fc723470295112f70f8fcd37c2023-11-17T12:06:28ZengMDPI AGLand2073-445X2023-02-0112357910.3390/land12030579Global Maps of Agricultural Expansion Potential at a 300 m ResolutionMirza Čengić0Zoran J. N. Steinmann1Pierre Defourny2Jonathan C. Doelman3Céline Lamarche4Elke Stehfest5Aafke M. Schipper6Mark A. J. Huijbregts7Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, 6525 XZ Nijmegen, The NetherlandsDepartment of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, 6525 XZ Nijmegen, The NetherlandsEarth and Life Institute, Environmental Sciences, Université Catholique de Louvain, 1348 Louvain-la-Neuve, BelgiumPBL Netherlands Environmental Assessment Agency, 2500 GH The Hague, The NetherlandsEarth and Life Institute, Environmental Sciences, Université Catholique de Louvain, 1348 Louvain-la-Neuve, BelgiumPBL Netherlands Environmental Assessment Agency, 2500 GH The Hague, The NetherlandsDepartment of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, 6525 XZ Nijmegen, The NetherlandsDepartment of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, 6525 XZ Nijmegen, The NetherlandsThe global expansion of agricultural land is a leading driver of climate change and biodiversity loss. However, the spatial resolution of current global land change models is relatively coarse, which limits environmental impact assessments. To address this issue, we developed global maps representing the potential for conversion into agricultural land at a resolution of 10 arc-seconds (approximately 300 m at the equator). We created the maps using artificial neural network (ANN) models relating locations of recent past conversions (2007–2020) into one of three cropland categories (cropland only, mosaics with >50% crops, and mosaics with <50% crops) to various predictor variables reflecting topography, climate, soil, and accessibility. Cross-validation of the models indicated good performance with area under the curve (AUC) values of 0.88–0.93. Hindcasting of the models from 1992 to 2006 revealed a similar high performance (AUC of 0.83–0.91), indicating that our maps provide representative estimates of current agricultural conversion potential provided that the drivers underlying agricultural expansion patterns remain the same. Our maps can be used to downscale projections of global land change models to more fine-grained patterns of future agricultural expansion, which is an asset for global environmental assessments.https://www.mdpi.com/2073-445X/12/3/579agriculturecroplandland-cover changedeforestationintegrated assessment modelsGLOBIO |
| spellingShingle | Mirza Čengić Zoran J. N. Steinmann Pierre Defourny Jonathan C. Doelman Céline Lamarche Elke Stehfest Aafke M. Schipper Mark A. J. Huijbregts Global Maps of Agricultural Expansion Potential at a 300 m Resolution Land agriculture cropland land-cover change deforestation integrated assessment models GLOBIO |
| title | Global Maps of Agricultural Expansion Potential at a 300 m Resolution |
| title_full | Global Maps of Agricultural Expansion Potential at a 300 m Resolution |
| title_fullStr | Global Maps of Agricultural Expansion Potential at a 300 m Resolution |
| title_full_unstemmed | Global Maps of Agricultural Expansion Potential at a 300 m Resolution |
| title_short | Global Maps of Agricultural Expansion Potential at a 300 m Resolution |
| title_sort | global maps of agricultural expansion potential at a 300 m resolution |
| topic | agriculture cropland land-cover change deforestation integrated assessment models GLOBIO |
| url | https://www.mdpi.com/2073-445X/12/3/579 |
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