IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5458-d807200.html
   My bibliography  Save this article

CO 2 Flux Model Assessment and Comparison between an Airborne Hyperspectral Sensor and Orbital Multispectral Imagery in Southern Amazonia

Author

Listed:
  • João Lucas Della-Silva

    (Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Amazônia Legal (BIONORTE), State University of Mato Grosso (UNEMAT), Sinop 78555-000, Mato Grosso, Brazil)

  • Carlos Antonio da Silva Junior

    (Department of Geography, State University of Mato Grosso (UNEMAT), Sinop 78555-000, Mato Grosso, Brazil)

  • Mendelson Lima

    (Department of Biology, State University of Mato Grosso (UNEMAT), Alta Floresta 78580-000, Mato Grosso, Brazil)

  • Paulo Eduardo Teodoro

    (Department of Agronomy, Federal University of Mato Grosso do Sul (UFMS), Chapadão do Sul 79560-000, Mato Grosso do Sul, Brazil)

  • Marcos Rafael Nanni

    (Department of Agronomy, State University of Maringá (UEM), Maringá 87030-120, Paraná, Brazil)

  • Luciano Shozo Shiratsuchi

    (AgCenter, School of Plant, Environmental and Soil Sciences, Louisiana State University (LSU), Baton Rouge, LA 70808, USA)

  • Larissa Pereira Ribeiro Teodoro

    (Department of Agronomy, Federal University of Mato Grosso do Sul (UFMS), Chapadão do Sul 79560-000, Mato Grosso do Sul, Brazil)

  • Guilherme Fernando Capristo-Silva

    (Postgraduate Program in Agronomy, Federal University of Mato Grosso (UFMT), Sinop 78555-000, Mato Grosso, Brazil)

  • Fabio Henrique Rojo Baio

    (Department of Agronomy, Federal University of Mato Grosso do Sul (UFMS), Chapadão do Sul 79560-000, Mato Grosso do Sul, Brazil)

  • Gabriel de Oliveira

    (Department of Earth Sciences, University of South Alabama, Mobile, AL 36688, USA)

  • José Francisco de Oliveira-Júnior

    (Institute of Atmospheric Sciences, Federal University of Alagoas (UFAL), Maceió 57072-970, Alagoas, Brazil)

  • Fernando Saragosa Rossi

    (Department of Agronomy, State University of São Paulo (UNESP), Jaboticabal 14884-900, São Paulo, Brazil)

Abstract

In environmental research, remote sensing techniques are mostly based on orbital data, which are characterized by limited acquisition and often poor spectral and spatial resolutions in relation to suborbital sensors. This reflects on carbon patterns, where orbital remote sensing bears devoted sensor systems for CO 2 monitoring, even though carbon observations are performed with natural resources systems, such as Landsat, supported by spectral models such as CO 2 Flux adapted to multispectral imagery. Based on the considerations above, we have compared the CO 2 Flux model by using four different imagery systems (Landsat 8, PlanetScope, Sentinel-2, and AisaFenix) in the northern part of the state of Mato Grosso, southern Brazilian Amazonia. The study area covers three different land uses, which are primary tropical forest, bare soil, and pasture. After the atmospheric correction and radiometric calibration, the scenes were resampled to 30 m of spatial resolution, seeking for a parametrized comparison of CO 2 Flux, as well as NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index). The results obtained here suggest that PlanetScope, MSI/Sentinel-2, OLI/Landsat-8, and AisaFENIX can be similarly scaled, that is, the data variability along a heterogeneous scene in evergreen tropical forest is similar. We highlight that the spatial-temporal dynamics of rainfall seasonality relation to CO 2 emission and uptake should be assessed in future research. Our results provide a better understanding on how the merge and/or combination of different airborne and orbital datasets that can provide reliable estimates of carbon emission and absorption within different terrestrial ecosystems in southern Amazonia.

Suggested Citation

  • João Lucas Della-Silva & Carlos Antonio da Silva Junior & Mendelson Lima & Paulo Eduardo Teodoro & Marcos Rafael Nanni & Luciano Shozo Shiratsuchi & Larissa Pereira Ribeiro Teodoro & Guilherme Fernand, 2022. "CO 2 Flux Model Assessment and Comparison between an Airborne Hyperspectral Sensor and Orbital Multispectral Imagery in Southern Amazonia," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5458-:d:807200
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5458/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5458/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Yun & Guerschman, Juan P & Cheng, Zhibo & Guo, Longzhu, 2019. "Remote sensing for vegetation monitoring in carbon capture storage regions: A review," Applied Energy, Elsevier, vol. 240(C), pages 312-326.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Quanfeng Li & Wei Liu & Guoming Du & Bonoua Faye & Huanyuan Wang & Yunkai Li & Lu Wang & Shijin Qu, 2022. "Spatiotemporal Evolution of Crop Planting Structure in the Black Soil Region of Northeast China: A Case Study in Hailun County," Land, MDPI, vol. 11(6), pages 1-14, May.
    2. Sara Yasemi & Yasin Khalili & Ali Sanati & Mohammadreza Bagheri, 2023. "Carbon Capture and Storage: Application in the Oil and Gas Industry," Sustainability, MDPI, vol. 15(19), pages 1-32, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5458-:d:807200. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.