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Abstract

In environmental research, remote sensing techniques are mostly based on orbital data, which is characterized by limited acquisition and spectral and spatial resolutions. Orbital remote sensing bears devoted sensor systems for CO2 monitoring, even though carbon observations are performed with natural resources systems, supported by spectral models as CO2Flux adapted to multispectral imagery. Here, this adaptation on Landsat-8, Sentinel-2 and PlanetScope were compared to hyperspectral response of AisaFENIX, based on the same ROI on southern Amazon surveys. From it, analysis of variance was applied to statistically compare indices results among imagery systems and different land uses in the ROI. Our results suggest the data variability along a heterogeneous scene in evergreen forest biome are similar among imagery systems. Furthermore, research applications using CO2Flux directly using Sentinel-2 data will be enforceable, especially on LULC similar to bare soil.

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Institutions
  • 1 Universidade do Estado de Mato Grosso
  • 2 Universidade do Estado de Mato Grosso - UNEMAT
  • 3 Universidade Federal de Mato Grosso do Sul
  • 4 Universidade Estadual de Maringá
  • 5 Louisiana State University
  • 6 Universidade Federal de Mato Grosso
  • 7 University of South Alabama
  • 8 Universidade Federal de Alagoas
  • 9 Universidade Estadual Paulista “Júlio de Mesquita Filho”
Track
  • 41. Sustainability and Environment
Keywords
carbon dynamics
hyperspectral imagery
Orbital remote sensing
Brazilian Amazon
CO2flux