A GIS-based methodology for sustainable farming planning: Assessment of land use/cover changes and carbon dynamics at farm level

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Abstract

The assessment of carbon dynamics as a climate-regulation ecosystem service (ES) by modeling of scenarios on land use and land cover (LULC) changes is widely used in environmental conservation studies to support public policies. However, ES studies at local scales that address the subject from the perspective of farm property are rare. In this paper, we performed the quantification, valuation, and mapping of carbon storage and sequestration of observed (2007–2017) and future LULC (2027) sustainable scenarios at a cattle ranch in Serra da Mantiqueira, in Southeastern Brazil. The aim was to understand how different LULC changes affect the provision of ES and contribute to economic opportunities to the farming sector. Under a GIS-approach, we used remote sensing techniques for LULC mapping, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) for scenario building and carbon assessment, as well as the Sis software suite for forest growth and production simulation. All scenarios contributed to increasing carbon storage and sequestration and provided profitable economic opportunities. The introduction of Eucalyptus trees in livestock and agricultural production systems is an alternative for diversification and income increase, contributing to the balance of greenhouse gases (GHG) from livestock activity and adding value to production. These results are useful to support land use planning and management for both environmental conservation policies and sustainable farming production.
Original languageEnglish
Article number105788
Pages (from-to)1-17
Number of pages17
JournalLand Use Policy
Volume111
Issue numberDecember
Early online date5 Oct 2021
DOIs
Publication statusPublished - 1 Dec 2021

Keywords

  • Carbon storage and sequestration
  • Geographic information system (GIS)
  • Land use planning
  • Land use land cover change (LULCC)
  • Sustainable agriculture
  • Tropical forest

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