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Hans-Erik Andersen

Biographic Data

ID10494156
NAMEHans-Erik Andersen
GIVEN NAMESHans-Erik
FAMILY NAMEAndersen
SIGNATUREANDERSEN H
ORCID0000-0002-5546-9522
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS0
WORKS AS AUTHOR6
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2017
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Toward spatio-temporal models to support national-scale forest carbon monitoring and reporting

    Open Access•Elliot S Shannon, Andrew O Finley et al.•ARTICLE•Environmental Research Letters•2024

    National forest inventory (NFI) programs provide vital information on forest parameters’ status, trend, and change. Most NFI designs and estimation methods are tailored to estimate status over large areas but are not well suited to estimate trend and change, especially over small spatial areas and/or over short time periods (e.g. annual estimates). Fine-scale space-time indexed estimates are critical to a variety of environmental, ecological, and…

  • Characterizing and communicating uncertainty

    Open Access•Robert E Kennedy, Sylvia Serbin et al.•ARTICLE•Environmental Research Letters•2024

    Navigating uncertainty is a critical challenge in all fields of science, especially when translating knowledge into real-world policies or management decisions. However, the wide variance in concepts and definitions of uncertainty across scientific fields hinders effective communication. As a microcosm of diverse fields within Earth Science, NASA’s Carbon Monitoring System (CMS) provides a useful crucible in which to identify cross-cutting concep…

  • Lidar-derived estimates of boreal shrub biomass in Southcentral Alaska

    Open Access•Kaili A Martin, Roman Dial et al.•ARTICLE•Environmental Research Letters•2024

    Despite widespread observations of shrub proliferation and expansion (shrubification), few studies quantify shrub biomass at the regional scale. Here we describe and implement a two-part modeling approach to estimate and map tall shrub (diameter at root collar > 2.5 cm) expected aboveground biomass, or E[SHB], across a 16.6 million ha boreal region where shrubification occurs in wetlands and subalpine ecosystems. Using n = 384 field plots nested …

  • 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…

  • Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

    Open Access•Ram K Deo, Grant M Domke et al.•ARTICLE•Environmental Research Letters•2018

    Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. T…

  • Patterns of canopy and surface layer consumption in a boreal forest fire from repeat airborne lidar

    Open Access•Michael Alonzo, Douglas C Morton et al.•ARTICLE•Environmental Research Letters•2017

    Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pr…

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  • Patterns of canopy and surface layer consumption in a boreal forest fire from repeat airborne lidar

    Open Access•Michael Alonzo, Douglas C Morton et al.•ARTICLE•Environmental Research Letters•2017

    Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pr…

  • Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

    Open Access•Ram K Deo, Grant M Domke et al.•ARTICLE•Environmental Research Letters•2018

    Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. T…

  • 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…

  • Toward spatio-temporal models to support national-scale forest carbon monitoring and reporting

    Open Access•Elliot S Shannon, Andrew O Finley et al.•ARTICLE•Environmental Research Letters•2024

    National forest inventory (NFI) programs provide vital information on forest parameters’ status, trend, and change. Most NFI designs and estimation methods are tailored to estimate status over large areas but are not well suited to estimate trend and change, especially over small spatial areas and/or over short time periods (e.g. annual estimates). Fine-scale space-time indexed estimates are critical to a variety of environmental, ecological, and…

  • Characterizing and communicating uncertainty

    Open Access•Robert E Kennedy, Sylvia Serbin et al.•ARTICLE•Environmental Research Letters•2024

    Navigating uncertainty is a critical challenge in all fields of science, especially when translating knowledge into real-world policies or management decisions. However, the wide variance in concepts and definitions of uncertainty across scientific fields hinders effective communication. As a microcosm of diverse fields within Earth Science, NASA’s Carbon Monitoring System (CMS) provides a useful crucible in which to identify cross-cutting concep…

  • Lidar-derived estimates of boreal shrub biomass in Southcentral Alaska

    Open Access•Kaili A Martin, Roman Dial et al.•ARTICLE•Environmental Research Letters•2024

    Despite widespread observations of shrub proliferation and expansion (shrubification), few studies quantify shrub biomass at the regional scale. Here we describe and implement a two-part modeling approach to estimate and map tall shrub (diameter at root collar > 2.5 cm) expected aboveground biomass, or E[SHB], across a 16.6 million ha boreal region where shrubification occurs in wetlands and subalpine ecosystems. Using n = 384 field plots nested …

Environmental Science (6 works) · Geography (5 works) · Remote Sensing and LiDAR Applications (5 works) · Computer Science (4 works) · Ecology (4 works) · Geology (4 works) · Remote sensing (4 works) · Lidar (3 works) · Mathematics (3 works) · Physical geography (3 works)

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