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The Role of Maps in Capturing Distal Drivers of Deforestation and Degradation: A Case Study in Central Mozambique

Part of the Human-Environment Interactions book series (HUEN,volume 6)

Abstract

While remote sensing images provide unprecedented abundance of earth observation data from both optical and radar perspectives, on a satellite or airborne platform, from plot to global scale, identifying and modeling drivers of land cover and land use change remains a huge challenge. This challenge is aggravated by the merging of distal drivers, which play an increasingly important and complex role in altering local land cover and land use change. Distal drivers, in the form of global markets, NGOs, international governments, and institutions, significantly contribute to shaping the landscape of central African states—the focus of this chapter—by controlling capital, information, knowledge flow, and international development initiatives. In this chapter, I will explore the applications and constraints of Remote Sensing (RS) and Geographic Information System (GIS) in capturing distal drivers of deforestation and forest degradation in the Beira corridor, Manica, Mozambique. I investigate how this analysis fits into the conceptual and methodological framework of distal drivers. In Beira corridor, it is primarily the scarcity and uneven distribution of forest resources shaping land use competition in woodland areas. This competition is intensified by dramatic population increases, demands from remote markets, and conflicts of interest between local government and international organizations to preserve or develop certain forests and not others. Remote sensing images can capture the patterns of land use change as ‘balanced’ results of different land uses within a geographic area with time, which reflects the respective outcomes of competition between these different land use activity types. Examples explain drivers can be connected to their spatial patterns by combining regional biomass change maps derived from optical and radar remote sensing imagery, and knowledge of local deforestation and degradation processes. Moreover, we discuss the biases and uncertainties that result from processing RS images, as well as interpolating land use maps from RS images. I conclude with a brief discussion of the biases and uncertainties that may affect our perception of land use change, and how maps and their attributes themselves may feedback into land use competition.

Keywords

  • Remote sensing
  • Uncertainty
  • Land use practices
  • Governance
  • Radar

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Fig. 6.1
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Fig. 6.7

Notes

  1. 1.

    Optical imagery showed a different trend than radar imagery, which might due to the characteristics of the two sensors, differences in forest and forest loss events, time of year when the image is captured, and various other factors.

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Correspondence to Yaqing Gou .

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Gou, Y. (2016). The Role of Maps in Capturing Distal Drivers of Deforestation and Degradation: A Case Study in Central Mozambique. In: , et al. Land Use Competition. Human-Environment Interactions, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-33628-2_6

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