Geographies (Oct 2022)

Techniques of Geoprocessing via Cloud in Google Earth Engine Applied to Vegetation Cover and Land Use and Occupation in the Brazilian Semiarid Region

  • Jhon Lennon Bezerra da Silva,
  • Daiana Caroline Refati,
  • Ricardo da Cunha Correia Lima,
  • Ailton Alves de Carvalho,
  • Maria Beatriz Ferreira,
  • Héliton Pandorfi,
  • Marcos Vinícius da Silva

DOI
https://doi.org/10.3390/geographies2040036
Journal volume & issue
Vol. 2, no. 4
pp. 593 – 608

Abstract

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Thematic maps of land cover and use can assist in the environmental monitoring of semiarid regions, mainly due to the advent of climate change, such as drought, and pressures from anthropic activities, such as the advance of urban areas. The use of geotechnologies is key for its effectiveness and low operating cost. The objective was to evaluate and understand the spatiotemporal dynamics of the loss and gain of land cover and use in a region of the Brazilian semiarid region, and identify annual trends from changing conditions over 36 years (1985 to 2020), using cloud remote sensing techniques in Google Earth Engine (GEE). Thematic maps of land cover and land use from MapBiomas Brazil were used, evaluated by Mann–Kendall trend analysis. The Normalized Difference Vegetation Index (NDVI) was also determined from the digital processing of about 800 orbital images (1985 to 2020) from the Landsat series of satellites. The trend analysis for land cover and use detected, over time, the loss of forest areas and water bodies, followed by the advance of exposed soil areas and urban infrastructure. The modification of native vegetation directly influences water availability, and agricultural activities increase the pressure on water resources, mainly in periods of severe drought. The NDVI detected that the period from 2013 to 2020 was most affected by climatic variability conditions, with extremely low average values. Thematic maps of land cover and use and biophysical indices are essential indicators to mitigate environmental impacts in the Brazilian semiarid region.

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