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DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗

NASA NTRS1999

Automated Planning for a Deep Space Communications Station

This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. Me described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication services. To perform this task, the Automated Scheduling and Planning Environment (ASPEN) has been applied to automatically produce antenna trucking plans that are tailored to support a set of input goals. In this paper, we describe the antenna automation problem, the ASPEN planning and scheduling system, how ASPEN is used to generate antenna track plans, the results of several technology demonstrations, and future work utilizing dynamic planning technology.

Estlin, Tara↗

NASA NTRS2023

Invasion in the Niger Delta: Remote Sensing of Mangrove Conversion to Invasive Nypa fruticans from 2015-2020

Invasive species are a leading threat to biodiversity worldwide. Nypa palm ( Nypa fruticans ) has emerged as the predominant invasive species in the Niger Delta region of Nigeria. While endemic mangroves have high rates of carbon sequestration, stabilize coastlines, and protect biodiversity, Nypa does not provide these services outside its native region of Southeast Asia. Oil exploration and urbanization in this region also exacerbates mangrove loss and Nypa spread. As Nypa is difficult to distinguish from endemic mangrove species in remotely sensed data, estimates of mangrove and ecosystem services losses in Nigeria are highly uncertain. Here, we analyze multisensor satellite data with machine learning to quantify the rapid expansion of Nypa from 2015-2020 in Nigeria. Using Landsat imagery and random forest classification, we quantify total potential Nypa extent in Nigeria in 2019. We then produced a Nypa extent map using iterative combinations of Sentinel-1 SAR, Sentinel-2 MSI, and ALOS PALSAR. Random forest classifications using SAR data from ALOS and Sentinel-1 were best suited for mapping Nypa extent with similar accuracies (78% and 75% respectively). Based on data availability and accuracy, we focused our change analysis on Sentinel-1 SAR. Our results show ~28,000 ha of mangroves were converted to Nypa in Nigeria by 2020 and covered a larger extent than endemic mangroves, compounding the effect of the existing degradation and deforestation in the region. We also compared forest height and complexity estimates from GEDI (Global Ecosystem Dynamics Investigation) LiDAR to further distinguish between endemic mangroves and Nypa in three dimensions. Nypa structural variability, measured by top-of-canopy height, vegetation cover, plant area index, and foliage height diversity, was lower than that of mangroves. At current rates of Nypa expansion, the entire area of study would be invaded by Nypa by 2028, with potentially detrimental consequences to the ecosystem services provided by mangroves.

GEE↗

DOE OSTI2022

Space and Time Dynamics of Transpiration in the East River Watershed: Biotic and Abiotic Controls

Alpine forests have important impacts on water resources by affecting how much of the precipitation that falls on a watershed is routed to streamflow or returned to the atmosphere as transpiration – so-called “green water”. In many of the high-altitude watersheds that supply critical water resources to the western US, it remains a challenge to predict how much water forests will utilize limiting the ability to predict both short and long term information on downstream water resources. The uncertainty emerges because transpiration varies between tree species, across landscapes and over time in ways that cannot readily be predicted from physically-based models for evaporation. In this project, we utilized a technique called sap flux to measure the rate of water use for three common species of fir, spruce and aspen distributed across a hillslope in the East River Watershed from 2019-2021. We also made ~weekly measurements of the concentration of stable isotopic tracers in transpiration to understand not only how much water was being used but whether it originated from summer rain or snowmelt. Firstly, our results show that the species tend to use similar amounts of total water but they achieve this similar cumulative water flux both by using water at different times of the year and by using different water sources. This shows the importance of including species-level information into models used to make seasonal streamflow predictions. Secondly, our results show that trees lower on the hillslope use older waters all through the summer whereas trees higher on the hillslope rely more heavily on recent summer rain. This means trees lower on the hillslope are less sensitive to year-to-year changes in summer climate. Lastly, we found that sites with dense forest stands displayed the largest amounts of year-to-year changes in transpiration and thus these high localized spots in the watershed are the primary drivers of changes in “green water” use. The results provide an unprecedented spatial and temporal picture of forest water use that confirms a number of fundamental hypotheses on hillslope ecohydrology that had not previously been tested against observations. Predictions of streamflow that will benefit from this work are highly valuable for agriculture management, flood control and ecological restoration efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Linked nitrogen and carbon dynamics reveal distinct pools and patterns in a deep, weathered bedrock rhizosphere

Nitrogen is one of the most limiting nutrients to forest productivity worldwide. Recently, it has been established that diverse ecosystems source a substantial fraction of their water from weathered bedrock, leading to questions about whether root-driven nitrogen cycling extends into weathered bedrock as well. In this study, we specifically examined nitrogen dynamics using specialized instrumentation distributed across a 16 m weathered bedrock vadose zone (WBVZ) underlying an old growth forest in northern California where the rhizosphere—composed of plant roots and their associated microbiome—extends meters into rock. We documented total dissolved nitrogen (TDN), dissolved organic carbon (DOC), inorganic nitrogen (ammonium and nitrate), and CO 2 and O 2 gases every 1.5 m to 16 m depth for 2 y. We found that TDN concentrations increased with depth, were an order of magnitude greater at 15 m than in the upper 30 cm, and that the majority of TDN throughout the weathered bedrock vadose zone was organic. We also found that TDN concentrations are influenced by depth, season, and interannual precipitation patterns. Carbon isotope composition of the DOC suggests that dissolved organic matter in the WBVZ is primarily derived from plant sources, and not the nitrogen-rich bedrock. We conclude that nitrogen dynamics in the WBVZ may be driven, in part, by an active rhizosphere, meters below the base of soil, and we argue that weathered bedrock horizons may play a key role in C-N cycling in ecosystems with deep-rooted plants.

Science & Technology - Other Topics↗

DOE OSTI2023

Topography and canopy cover influence soil organic carbon composition and distribution across a forested hillslope in the discontinuous permafrost zone

Abstract Topography and canopy cover influence ground temperature in warming permafrost landscapes, yet soil temperature heterogeneity introduced by mesotopographic slope positions, microtopographic differences in vegetation cover, and the subsequent impact of contrasting temperature conditions on soil organic carbon (SOC) dynamics are understudied. Buffering of permafrost‐affected soils against warming air temperatures in boreal forests can reflect surface soil characteristics (e.g., thickness of organic material) as well as the degree and type of canopy cover (e.g., open cover vs. closed cover). Both landscape and soil properties interact to determine meso‐ and microscale heterogeneity of ground warming. We sampled a hillslope catena transect in a discontinuous permafrost zone near Fairbanks, Alaska, to test the small‐scale (1 to 3 m) impacts of slope position and cover type on soil organic matter composition. Mineral active layer samples were collected from backslope, low backslope, and footslope positions at depths spanning 19 to 60 cm. We examined soil mineralogical composition, soil moisture, total carbon and nitrogen content, and organic mat thickness in conjunction with an assessment of SOC composition using Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS). Soils in the footslope position had a higher relative contribution of lignin‐like compounds, whereas backslope soils had more aliphatic and condensed aromatic compounds as determined using FT‐ICR‐MS. The effect of open versus closed tree canopy cover varied with the slope position. On the backslope, we found higher oxidation of molecules under open cover than closed cover, indicating an effect of warmer soil temperature on decomposition. Little to no effect of the canopy was observed in soils at the footslope position, which we attributed, in part, to the strong impact of soil moisture content in SOC dynamics in the water‐gathering footslope position. The thin organic mat under open cover on the backslope position may have contributed to differences in soil temperature and thus SOC oxidation under open and closed canopies. Here, the thinner organic mat did not appear to buffer the underlying soil against warm season air temperatures and thus increased SOC decomposition as indicated by the higher oxidation of SOC molecules and a lower contribution of simple molecules under open cover than the closed canopy sites. Our findings suggest that the role of canopy cover in SOC dynamics varies as a function of landscape position and soil properties, namely, organic mat thickness and soil moisture. Condition‐specific heterogeneity of SOC composition under open and closed canopy cover highlights the protective effect of canopy cover for soils on backslope positions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Seasonal trends in leaf-level photosynthetic capacity and water use efficiency in a North American Eastern deciduous forest and their impact on canopy-scale gas exchange

Vegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems. Here, we investigated seasonal patterns in leaf-level physiological, hydraulic, and anatomical properties, including the seasonal progress of the stomatal slope parameter (g 1 ; inversely proportional to WUE) and the maximum carboxylation rate (V cmax ). V cmax and g 1 were seasonally variable; however, their patterns were not temporally synchronized. g 1 generally showed an increasing trend until late in the season, while V cmax peaked during the midsummer months. Seasonal progression of V cmax was primarily driven by changes in leaf structural, and anatomical characteristics, while seasonal changes in g 1 were most strongly related to changes in V cmax and leaf hydraulics. Using a seasonally variable V cmax and g 1 to parameterize a canopy-scale gas exchange model increased seasonally aggregated A and E by 3% and 16%, respectively.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Preliminary analysis of ERS-1 SAR for forest ecosystem studies

An image obtained by the C-band VV-polarized ERS-1 SAR is examined with respect to potential land applications. A scene obtained near noon on August 15, 1991, along the U.S.-Canadian border near Sault Ste. Marie is calibrated relative to an array of trihedral corner reflectors and active radar calibrators distributed across the swath. Extensive contemporaneous ground observations of forest stands are used to predict the radar backscattering coefficient sigma at the time of the SAR overpass using a first-order vector radiative transfer model. These predictions generally agree with the calibrated ERS-1 data to within 1 dB. It is demonstrated that the dynamic range of sigma is sufficient to perform limited discrimination of various forest and grassland communities even for a single-date observation. Furthermore, retrieval of near-surface soil moisture is feasible for grass-covered soils when plant biomass is less than 1 tonne/ha.

Dobson, M. G.↗

DOE OSTI2020

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

Effects of Topography on Tropical Forest Structure Depend on Climate Context

Topography affects abiotic conditions which can influence the structure, function, and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine-scale topographic heterogeneity but we have a limited understanding of how We merged high-resolution (1 sq. meter) data on topography and canopy height derived from airborne lidar with ground-based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning ca. 800 to 3,500 mm yr(exp -1). Ground-based data included species composition, estimated above-ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource-use strategies and a trade-off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography climate is related to metrics of forest structure (i.e., canopy height and AGB), as well as taxonomic and functional alpha- and beta-diversity. Fine-scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine-scale topography influenced functional composition but had only weak or non-significant effects on taxonomic and functional alpha- and beta-diversity. For instance, community-weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis: The effects of fine-scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Tropical dry forest↗

DOE OSTI2021

Consequences of Altered Root Nutrient Uptake for Soil Carbon Stabilization (Final Report)

Objectives: The primary objectives of this project are to improve our understanding of tropical forest belowground processes, and to increase representation of this biome in ecosystem-scale and global C cycle models. Belowground dynamics present a major source of uncertainty inhibiting our ability to predict C cycle responses to climate change. Representation of tropical forests in these models is particularly lacking, even though these ecosystems hold >25% of terrestrial C stocks. While the majority of humid tropical forests exist on relatively infertile soils (i.e. poor in rock-derived nutrients), enormous gradients in soil nutrient availability exist at landscape-scales due to shifts in geology and soil order. Soil fertility is likely to greatly influence how tropical soil C storage will respond to the declines in precipitation predicted for the tropics. In particular, root dynamics vary across soil fertility gradients, with roots representing the major input of C to subsurface soils. Root characteristics related to soil fertility include biomass, turnover, C exudates, tissue chemistry, and nutrient uptake rates, with each of these likely sensitive to changes in moisture. The proposed project will fully integrate field research with an existing ecosystem model to assess potential effects of drying on belowground tropical C dynamics across a range of soil fertilities. Project Description:. This project will identify key linkages among soil fertility, root nutrient uptake, root dynamics, and soil C storage. The hypothesized framework for understanding these linkages is: Tropical rainforest roots in relatively fertile soils have lesser root biomass, faster turnover, fewer exudates, and improved root tissue quality relative to infertile sites, all resulting from increased root nutrient uptake. Ultimately, these root characteristics in fertile soils promote proportionally greater long-term soil C storage in organo-mineral associations. Specifically, lower root exudates and improved root tissue quality in fertile soils reduce microbial respiration of extant soil C (i.e. “priming) and increase microbial C use efficiency, leading to sorption of protein-rich microbial and plant organic matter on soil mineral surfaces. However, the larger pools of mineral-associated C in fertile tropical soils are more vulnerable to decreased rainfall than smaller C pools in infertile soils, in part because of the lesser root biomass, faster turnover, and softer, more labile root tissues. Also, the shallower lateral rooting structures typical in fertile soils experience greater desiccation and death than deeper roots in infertile sites, with little short-term adaptation to drying.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Improving collaborations between empiricists and modelers to advance grassland community dynamics in ecosystem models

Climate change, increasing atmospheric CO 2 , and land use change have altered biogeochemical and hydrologic cycles world-wide, with grassland systems being particularly vulnerable to resulting vegetation shifts (Komatsu et al., 2019). Therefore, incorporating plant community dynamics into ecosystem models is critical for accurate forecasting of ecosystem responses to global change (Levine, 2016). Process-based ecosystem models, which simulate the biogeochemical transfers of mass and energy among biota, the subsurface, and atmosphere, require representation of dynamic composition of organisms within ecosystems. For example, these models simulate leaf and plant-level characteristics, such as electron transport rate and allometry of carbon (C) allocation, to predict how net primary productivity and other ecosystem processes respond to abiotic drivers. These models are particularly useful in scaling from organismal to ecosystem levels but are still underdeveloped in their ability to capture community change, especially in grassland ecosystems. To represent compositional changes, these models must simulate competition, mortality, establishment, and reproduction of plant populations within communities. Yet, current ecosystem modeling approaches to forecast plant community change have derived from studies of forested systems and are either too coarse to capture fine-scale community dynamics (e.g. dynamic global vegetation models (DGVMs)) or too complex to be used at large spatial scales (e.g. forest gap models).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

Large-scale product of forest height using a new approach from spaceborne repeat-pass SAR interferometry and LIDAR

Spaceborne SAR interferometry (InSAR) has the potential of mapping the forest height on a global scale and a monthly/weekly basis under all weather conditions, which can improve our understanding of the global carbon dynamics. In previous work, repeatpass SAR interferometry from spaceborne sensors is utilized to create large-scale forest height maps (that are particularly interested for large-scale ecological research) based on a newly developed approach. This paper thus serves as a summary paper and also sheds light on the future directions with improved results. In particular, it will be shown that repeat-pass SAR interferometry is able to create a large-scale forest height mosaic product with RMSE 4 m for forest stands on the order of 20 hectares through using the past spaceborne repeat-pass InSAR observations (i.e. JAXA’s ALOS-1 and ALOS-2) combined with sparse airborne lidar training samples over the forested areas in New England, US. Moreover, the results and performance of this approach can be remarkably improved with several enhancement techniques that can be easily satisfied with use of future spaceborne repeat-pass InSAR and lidar missions (e.g. NASA-ISRO’s NISAR and NASA’s GEDI). The methodology described in this paper can be considered as a complimentary tool to the existing PolInSAR technique and also serves as an observing prototype for the future spaceborne missions of repeatpass InSAR in fusion with lidar (e.g. NISAR and GEDI).

Treuhaft, Robert↗

NASA NTRS2008

Relating a Spectral Index from MODIS and Tower-based Measurements to Ecosystem Light Use Efficiency for a Fluxnet-Canada Coniferous Forest

As part of the North American Carbon Program effort to quantify the terrestrial carbon budget of North America, we have been examining the possibility of retrieving ecosystem light use efficiency (LUE, the carbon sequestered per unit photosynthetically active radiation) directly from satellite observations. Our novel approach has been to compare LUE derived from tower fluxes with LUE estimated using spectral indices computed from MODIS satellite observations over forests in the Fluxnet-Canada Research Network, using the MODIS narrow ocean bands acquired over land. We matched carbon flux data collected around the time of the MODIS mid-day overpass for over one hundred relatively clear days in five years (2001-2006) from a mature Douglas fir forest in British Columbia. We also examined hyperspectral reflectance data collected diurnally from the tower in conjunction with the eddy correlation fluxes and meteorological measurements made throughout the 2006 growing season at this site. The tower-based flux data provided an opportunity to examine diurnal and seasonal LUE processes and their relationship to spectral indices at the scale of the forest stand. We evaluated LUE in conjunction with the Photochemical Reflectance Index (PRI), a normalized difference spectral index that uses 531 nm and a reference band to capture responses to high light induced stress afforded by the xanthophyll cycle. Canopy structure information, retrieved from airborne laser scanning radar (LiDAR) observations, was used to partition the forest canopy into sunlit and shaded fractions throughout the day, on numerous days during 2006. At each observation period throughout a day, the PRI was examined for the sunlit, shaded, and intermediate canopy segments defined by their instantaneous position relative to the solar principal plane (SPP). The sunlit sector was associated with the illumination "hotspot" (the reflectance backscatter maximum), the shaded sector with the "cold or dark spot" (the reflectance forward scatter minimum), while the intermediate, mixed sunlit/shade sector was located in the cross-plane to the SPP. The PRI indices clearly captured the differences in leaf groups, with sunlit foliage exhibiting the lowest values on sunny days throughout the 2006 season. When tower-based canopy-level LUE was recalculated to estimate foliage-based values (LUE(sub foilage) for the three foliage groups under their incident light environments, a strong linear relationship for PRI:LUE(sub foilage) was demonstrated (0.6 less than or equal to r(sup 2) less than or equal to 0.8, n=822, P<0.0001). The MODIS data represent relatively large areas when acquired at nadir (approx.1 sq km) or at variable off-nadir view angles (greater than or equal to 1 sq km) looking forward or aft. Nevertheless, a similar relationship between MODIS PRI and tower-based LUE was obtained from satellite observations (r(sup 2) = 0.76, n=105, P= 0.026) when the azimuth offsets from the SPP for off-nadir observations were considered. At this relatively high latitude of 50 degrees, the MODIS directional observations were offset from the SPP by approximately 50 degrees, but still represented backscatter or forward scatter sectors of the bidirectional reflectance distribution function (BRDF). The backscatter observations sampled the sunlit forest and provided lower PRI values, in general, than the forward scatter observations from the shaded forest. Since the hotspot and darkspot were not typically directly observed, the dynamic range for MODIS PRI was less than that observed in the SPP at the canopy level; therefore, MODIS PRI values were more similar to those observed in sifu in the BRDF cross-plane. While not ideal in terms of spatial resolution or optimal viewing configuration, the MODIS observations nevertheless provide a means to monitor forest under stress using narrow spectral band indices and off-nadir observations. This research has stimulated several spin-off studies for remote sensinf LUE, and demonstrates the importance of the connection between ecosystem structure and physiological function.

Middleton, Elizabeth M.↗

NASA NTRS2015

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI↗