Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Svetlana Saarela

Biographic Data

ID8002610
NAMESvetlana Saarela
GIVEN NAMESSvetlana
FAMILY NAMESaarela
SIGNATURESAARELA S
AFFILIATIONSNorwegian University of Life Sciences
ORCID0000-0002-9044-7249
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Estimating aboveground biomass density using hybrid statistical inference with Gedi lidar data and Paraguay’s national forest inventory

    Open Access•Eric L Bullock, SEAN P HEALEY et al.•ARTICLE•Environmental Research Letters•2023

    Forests are widely recognized as critical to combating climate change due to their ability to sequester and store carbon in the form of biomass. In recent years, the combined use of data from ground-based forest inventories and remotely sensed data from light detection and ranging (lidar) has proven useful for large-scale assessment of forest biomass, but airborne lidar is expensive and data acquisition is infeasible for many countries. By contra…

  • Gedi launches a new era of biomass inference from space

    Open Access•Ralph Dubayah, John Armston et al.•ARTICLE•Environmental Research Letters•2022

    Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO 2 . The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a novel, theoretical sampling design that explicitl…

  • Statistical properties of hybrid estimators proposed for Gedi—Nasa’s global ecosystem dynamics investigation

    Open Access•Paul L Patterson, SEAN P HEALEY et al.•ARTICLE•Environmental Research Letters•2019

    NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission will collect waveform lidar data at a dense sample of ∼25 m footprints along ground tracks paralleling the orbit of the International Space Station (ISS). GEDI’s primary science deliverable will be a 1 km grid of estimated mean aboveground biomass density (Mg ha −1 ), covering the latitudes overflown by ISS (51.6 °S to 51.6 °N). One option for using the sample of waveforms contained wi…

No prominent works on this page.

  • Statistical properties of hybrid estimators proposed for Gedi—Nasa’s global ecosystem dynamics investigation

    Open Access•Paul L Patterson, SEAN P HEALEY et al.•ARTICLE•Environmental Research Letters•2019

    NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission will collect waveform lidar data at a dense sample of ∼25 m footprints along ground tracks paralleling the orbit of the International Space Station (ISS). GEDI’s primary science deliverable will be a 1 km grid of estimated mean aboveground biomass density (Mg ha −1 ), covering the latitudes overflown by ISS (51.6 °S to 51.6 °N). One option for using the sample of waveforms contained wi…

  • Gedi launches a new era of biomass inference from space

    Open Access•Ralph Dubayah, John Armston et al.•ARTICLE•Environmental Research Letters•2022

    Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO 2 . The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a novel, theoretical sampling design that explicitl…

  • Estimating aboveground biomass density using hybrid statistical inference with Gedi lidar data and Paraguay’s national forest inventory

    Open Access•Eric L Bullock, SEAN P HEALEY et al.•ARTICLE•Environmental Research Letters•2023

    Forests are widely recognized as critical to combating climate change due to their ability to sequester and store carbon in the form of biomass. In recent years, the combined use of data from ground-based forest inventories and remotely sensed data from light detection and ranging (lidar) has proven useful for large-scale assessment of forest biomass, but airborne lidar is expensive and data acquisition is infeasible for many countries. By contra…

Environmental Science (3 works) · Geography (3 works) · Remote Sensing and LiDAR Applications (3 works) · Remote Sensing in Agriculture (3 works) · Biomass (ecology (2 works) · Computer Science (2 works) · Ecology (2 works) · Estimator (2 works) · Forest ecology and management (2 works) · Lidar (2 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae