Long term performance of the High Output Maximum Efficiency Resonator (HOMER) laser for NASA׳s Global Ecosystem Dynamics Investigation (GEDI) lidar

Stysley, Paul R.; Coyle, D. Barry; Kay, Richard B.; Frederickson, Robert; Poulios, Demetrios; Cory, Ken; Clarke, Greg B.

doi:10.1016/j.optlastec.2014.11.001

Cited by 40 publications

(26 citation statements)

References 7 publications

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“…A number of new EO technologies are planned, including laser-based instruments (Global Ecosystem Dynamics Investigation, GEDI − 3D-LiDAR, NASA, launch in 2019, Fig. 7a), which will enable the 3D quantification of vegetation such as volume, stand structure, biomass with a 1 m resolution (Stysley et al, 2015). A combination of FLEX and GEDI LiDAR will fill the gaps in the missing functional and structural information, enabling a more accurate modelling and understanding of climate change and its effects on ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives

Lausch

Bannehr

Beckmann

et al. 2016

Ecological Indicators

147

145

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Section: Introductionmentioning

confidence: 99%

Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives

Lausch

Bannehr

Beckmann

et al. 2016

Ecological Indicators

147

145

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“…The Global Ecosystem Dynamics Investigation (GEDI)-3D-LiDAR of NASA, which is scheduled for 2019, will provide measurements of 3D vegetation structures which can be used to model vertical stand structure, biomass, disturbance and recovery on a regional to a global scale. Although a footprint size of 25 m will not enable the high resolution mapping that we are familiar with from small footprint LiDAR, the scientific objectives of the mission include modelling finer scale structure [133]. A combination of Landsat, EnMAP, FLEX, HySPIRI and GEDI LiDAR will combine structural and spectral information and improve the modelling, prediction and understanding of FH [134][135][136][137][138][139].…”

Section: Light Detection and Ranging (Lidar)mentioning

confidence: 99%

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

et al. 2017

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Stress in forest ecosystems (FES) occurs as a result of land-use intensification, disturbances, resource limitations or unsustainable management, causing changes in forest health (FH) at various scales from the local to the global scale. Reactions to such stress depend on the phylogeny of forest species or communities and the characteristics of their impacting drivers and processes. There are many approaches to monitor indicators of FH using in-situ forest inventory and experimental studies, but they are generally limited to sample points or small areas, as well as being time-and labour-intensive. Long-term monitoring based on forest inventories provides valuable information about changes and trends of FH. However, abrupt short-term changes cannot sufficiently be assessed through in-situ forest inventories as they usually have repetition periods of multiple years. Furthermore, numerous FH indicators monitored in in-situ surveys are based on expert judgement. Remote sensing (RS) technologies offer means to monitor FH indicators in an effective, repetitive and comparative way. This paper reviews techniques that are currently used for monitoring, including close-range RS, airborne and satellite approaches. The implementation of optical, RADAR and LiDAR RS-techniques to assess spectral traits/spectral trait variations (ST/STV) is described in detail. We found that ST/STV can be used to record indicators of FH based on RS. Therefore, the ST/STV approach provides a framework to develop a standardized monitoring concept for FH indicators using RS techniques that is applicable to future monitoring programs. It is only through linking in-situ and RS approaches that we will be able to improve our understanding of the relationship between stressors, and the associated spectral responses in order to develop robust FH indicators.

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“…The diversity of algorithms used to interpret remote sensing data will continue to improve in the future, especially in terms of capturing spatial variability from forest degradation or small-scale disturbances. Integrating ecosystem models with a new generation of data from the European Space Agency Biomass Mission [Le Toan et al, 2011] or the NASA GEDI Mission [Stysley et al, 2015] will help in providing improved estimates of global biomass, as well as other ecosystem variables. 2013-SyG-610028 IMBALANCE.…”

Section: Geophysical Research Lettersmentioning

confidence: 99%

Assimilating satellite‐based canopy height within an ecosystem model to estimate aboveground forest biomass

Joetzjer

Pillet

Ciais

et al. 2017

Geophysical Research Letters

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Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high‐resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE‐CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE‐CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

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Long term performance of the High Output Maximum Efficiency Resonator (HOMER) laser for NASA׳s Global Ecosystem Dynamics Investigation (GEDI) lidar

Cited by 40 publications

References 7 publications

Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives

Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

Assimilating satellite‐based canopy height within an ecosystem model to estimate aboveground forest biomass

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