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Yahaya I, Xu R, Zhou J, Jiang S, Su B, Huang J, Cheng J, Dong Z, Jiang T. Projected patterns of land uses in Africa under a warming climate. Sci Rep 2024; 14:12315. [PMID: 38811602 PMCID: PMC11136982 DOI: 10.1038/s41598-024-61035-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/30/2024] [Indexed: 05/31/2024] Open
Abstract
Land-use change is a direct driver of biodiversity loss, projection and future land use change often consider a topical issue in response to climate change. Yet few studies have projected land-use changes over Africa, owing to large uncertainties. We project changes in land-use and land-use transfer under future climate for three specified time periods: 2021-2040, 2041-2060, and 2081-2100, and compares the performance of various scenarios using observational land-use data for the year 2020 and projected land-use under seven Shared Socioeconomic Pathways Scenarios (SSP): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5 from 2015 to 2100 in Africa. The observational land-use types for the year 2020 depict a change and show linear relationship between observational and simulated land-use with a strong correlation of 0.89 (P < 0.01) over Africa. Relative to the reference period (1995-2014), for (2021-2040), (2041-2060), (2081-2100), barren land and forest land are projected to decrease by an average of (6%, 11%, 16%), (9%, 19%, 38%) respectively, while, crop land, grassland and urban land area are projected to increase by (36%, 58%, and 105%), (4%, 7% and 11%), and (139%, 275% and 450%) respectively. Results show a substantial variations of land use transfer between scenarios with major from barren land to crop land, for the whole future period (2015-2100). Although SSP4-3.4 project the least transfer. Population and GDP show a relationship with cropland and barren land. The greatest conversion of barren land to crop land could endanger biodiversity and have negative effects on how well the African continent's ecosystem's function.
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Affiliation(s)
- Ibrahim Yahaya
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
- Department of Geography, Gombe State University, P.M.B, 127, Gombe, Gombe State, Nigeria
| | - Runhong Xu
- School of Geographical Science, Qinghai Normal University, Xining, 810008, China
| | - Jian Zhou
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Shan Jiang
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Buda Su
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Jinlong Huang
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Jing Cheng
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhibo Dong
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Tong Jiang
- Research Institute of Climatic and Environmental Governance, Institute for Disaster Risk Management/School of Geographical Science Nanjing, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
- School of Geographical Science, Jiangsu Second Normal University, Nanjing, 210013, China.
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Liu P, Liu C, Li Q. Effects of landscape pattern on land surface temperature in Nanchang, China. Sci Rep 2024; 14:3832. [PMID: 38361044 PMCID: PMC10869699 DOI: 10.1038/s41598-024-54046-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/08/2024] [Indexed: 02/17/2024] Open
Abstract
The composition and configuration of landscapes are critical important to design effective approaches to mitigate urban thermal environment in the urbanization process. In this research, land use maps and land surface temperature (LST) retrieval were derived in Nanchang city of central China based on product datasets and the thermal infrared band of Landsat. The results showed that the thermal environment of Nanchang had become worse over the past two decades, that is, the proportion of area of the extremely low temperature zone (ELTZ) decreased from 4.39 to 0.77% from 2001 to 2020, and that of medium temperature zone (MTZ) reduced by 20%, whereas those of the high temperature zone (HTZ) and the extremely high temperature zone (EHTZ) increased sharply after 2001, and by 2020, the area ratio increased by 11% and 7.16%, respectively. The agricultural land (AL) area decreased from 68.44 to 49.69%, was gradually replaced by construction land (CL). The CL occupied the largest proportion in EHTZ, HTZ and slight high temperature zone (SHTZ); water landscape (WL) and green land (GL) occupied the largest proportion in ELTZ, low temperature zone (LTZ); and AL occupied the largest proportion in SHTZ, MTZ, and slight low temperature zone (SLTZ). Landscape configuration also obviously impacted on LST. The model fitting was well (R = 0.87) between land use area and LST by multiple regression analysis. The significant correlation between LST and six landscape pattern indices of CL (p < 0.01) indicated that the larger percent (PLANT, R = 0.78) and the more concentrate (LPI, R = 0.73) of CL implied the higher LST, while the more fragment (NP, R = - 0.45), dispersed and complex shape (R = - 0.35) were benefit to relieve LST. Contrastively, the larger percent and the more concentrated and complex shape distribution of AL, GL and WL, the lower LST (p < 0.01). In addition, LST had closely correlation with landscape level indices such as aggregation degree (AI, R = 0.44) and diversity (SHDI, R = - 0.60) (p < 0.01).
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Affiliation(s)
- Pinyi Liu
- School of Landscape and Art, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Chunqing Liu
- School of Landscape and Art, Jiangxi Agricultural University, Nanchang, 330045, China.
- Jiangxi Rural Culture Development Research Center, Nanchang, 330045, China.
| | - Qingjie Li
- School of Landscape and Art, Jiangxi Agricultural University, Nanchang, 330045, China
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