Impact of land cover changes on carbon stock trends in Kenya for spatial implementation of REDD+ policy

Research output: Contribution to journalArticlepeer-review

Abstract

Terrestrial carbon stock estimates information has significant importance in planning decisions for global warming and climate change mitigation. This study aimed to estimate and analyze carbon stock changes in Kenya as consequence of land cover change (LCC) using free open data to provide affordable and timely information. Using Random Forest (RF) decision trees, the land cover for 2028 was modelled based on 2004 and 2016 land cover under a Business as Usual (BAU) and an alternative Reducing of Emissions from Forest Degradation and Deforestation (REDD+) scenarios. The InVEST carbon model was used for estimation and valuation of carbon stock between 2004 and 2028. Results show a 16% decline in carbon stock with a loss of 21 billion US$ under the BAU scenario. On a regional scale, results show a gradual decline in carbon stock in the Coastal and Central regions while other regions exhibited mixed results. This trend can be reversed by the implementation of a REDD + scenario with a possible increase of 1.6% between 2016 and 2028, translating to a gain of 1 billion US$. This study contributes to the understanding of spatiotemporal carbon stock changes under different scenarios for effective spatial planning aiming to a balanced natural resource utilization.

Original languageEnglish
Article number102479
Pages (from-to)1-12
Number of pages12
JournalApplied Geography
Volume133
Early online date3 Jun 2021
DOIs
Publication statusPublished - 1 Aug 2021

Keywords

  • Ecosystems services
  • InVEST carbon model
  • Land cover changes modelling
  • Random forest decision trees
  • REDD+

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