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Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

Author

Listed:
  • Alemayehu Midekisa
  • Felix Holl
  • David J Savory
  • Ricardo Andrade-Pacheco
  • Peter W Gething
  • Adam Bennett
  • Hugh J W Sturrock

Abstract

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Suggested Citation

  • Alemayehu Midekisa & Felix Holl & David J Savory & Ricardo Andrade-Pacheco & Peter W Gething & Adam Bennett & Hugh J W Sturrock, 2017. "Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-15, September.
    • Handle: RePEc:plo:pone00:0184926
    DOI: 10.1371/journal.pone.0184926
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    References listed on IDEAS

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    1. Roger A. Pielke & Andy Pitman & Dev Niyogi & Rezaul Mahmood & Clive McAlpine & Faisal Hossain & Kees Klein Goldewijk & Udaysankar Nair & Richard Betts & Souleymane Fall & Markus Reichstein & Pavel Kab, 2011. "Land use/land cover changes and climate: modeling analysis and observational evidence," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(6), pages 828-850, November.
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    Cited by:

    1. Wubeshet Damtea & Dongyeob Kim & Sangjun Im, 2020. "Spatiotemporal Analysis of Land Cover Changes in the Chemoga Basin, Ethiopia, Using Landsat and Google Earth Images," Sustainability, MDPI, vol. 12(9), pages 1-14, April.
    2. Daniel Aja & Michael K. Miyittah & Donatus Bapentire Angnuureng, 2022. "Quantifying Mangrove Extent Using a Combination of Optical and Radar Images in a Wetland Complex, Western Region, Ghana," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    3. Ricardo Andrade-Pacheco & David J Savory & Alemayehu Midekisa & Peter W Gething & Hugh J W Sturrock & Adam Bennett, 2019. "Household electricity access in Africa (2000–2013): Closing information gaps with model-based geostatistics," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-14, May.
    4. Lopes, Catarina & Leite, Ana & Vasconcelos, Maria José, 2019. "Open-access cloud resources contribute to mainstream REDD+: The case of Mozambique," Land Use Policy, Elsevier, vol. 82(C), pages 48-60.
    5. Pankaj Bajracharya & Selima Sultana, 2020. "Rank-size Distribution of Cities and Municipalities in Bangladesh," Sustainability, MDPI, vol. 12(11), pages 1-26, June.
    6. Motuma Shiferaw Regasa & Michael Nones & Dereje Adeba, 2021. "A Review on Land Use and Land Cover Change in Ethiopian Basins," Land, MDPI, vol. 10(6), pages 1-18, June.
    7. Miaomiao Ma & Youfeng Zou & Wenzhi Zhang & Chunhui Chen, 2022. "Landscape Pattern Consistency Assessment of 10 m Land Cover Products in Different Ecological Zoning Contexts of Sichuan Province, China," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    8. Kotapati Narayana Loukika & Venkata Reddy Keesara & Venkataramana Sridhar, 2021. "Analysis of Land Use and Land Cover Using Machine Learning Algorithms on Google Earth Engine for Munneru River Basin, India," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
    9. Chasia, Stanley & Olang, Luke O. & Sitoki, Lewis, 2023. "Modelling of land-use/cover change trajectories in a transboundary catchment of the Sio-Malaba-Malakisi Region in East Africa using the CLUE-s model," Ecological Modelling, Elsevier, vol. 476(C).
    10. Zofia Kuzevicova & Diana Bobikova & Stefan Kuzevic & Samer Khouri, 2021. "Changes in the Country and Their Impact on Topographic Data of Agricultural Land—A Case Study of Slovakia," Land, MDPI, vol. 10(11), pages 1-22, November.
    11. Wakjira Takala Dibaba & Tamene Adugna Demissie & Konrad Miegel, 2020. "Drivers and Implications of Land Use/Land Cover Dynamics in Finchaa Catchment, Northwestern Ethiopia," Land, MDPI, vol. 9(4), pages 1-20, April.

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