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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Correlation between aircraft MSS and LIDAR remotely sensed data on a forested wetland in South Carolina

Wetlands in a portion of the Savannah River swamp forest, the Steel Creek Delta, were mapped using April 26, 1985 high-resolution aircraft multispectral scanner (MSS) data. Due to the complex spectral characteristics of the wetland vegetation, it was necessary to implement several techniques in the classification of the MSS imagery of the Steel Creek Delta. In particular, when performing unsupervised classification, an iterative cluster busting technique was used which simplified the cluster labeling process. In addition to the MSS data, light detecting and ranging (LIDAR) data were acquired by National Aeronautics and Space Administration (NASA) personnel along two flightlines over the Steel Creek Delta. These data were registered with the wetland classification map and correlated. Statistical analyses demonstrated that the laser derived canopy height information was significantly correlated with the Steel Creek Delta wetland classes encountered along the profiling transect of the LIDAR data.

Jensen, John R.↗
NASA NTRS1988

Estimating forest biomass and volume using airborne laser data

An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.

Nelson, Ross↗
NASA NTRS1987

Correlation between aircraft MSS and LIDAR remotely sensed data on a forested wetland in South Carolina

Wetlands in a portion of the Savannah River swamp forest, the Steel Creek Delta, were mapped using April 26, 1985 high-resolution aircraft multispectral scanner (MSS) data. Due to the complex spectral characteristics of the wetland vegetation, it was necessary to implement several techniques in the classification of the MSS imagery of the Steel Creek Delta. In particular, when performing unsupervised classification, an iterative cluster busting technique was used which simplified the cluster labeling process. In addition to the MSS data, light detecting and ranging (LIDAR) data were acquired by National Aeronautics and Space Administration (NASA) personnel along two flightlines over the Steel Creek Delta. These data were registered with the wetland classification map and correlated. Statistical analyses demonstrated that the laser derived canopy height information was significantly correlated with the Steel Creek Delta wetland classes encountered along the profiling transect of the LIDAR data.

Jensen, John R.↗
NASA NTRS1991

Discrete random media techniques for microwave modeling of vegetated terrain

Microwave remote sensing models of vegetated terrain are investigated. The problem is to determine canopy characteristics such as biomass, canopy height, and the moisture of the underlying soil. The report describes a discrete scatter model which has been employed to model backscatter in the active (radar) case and to model brightness temperature in the passive (radiometric) case. The acquisition of ground truth data is discussed, as well as the comparison of theory and experiment. The overall conclusion of the work has been that the discrete scatter model in conjunction with efficient scatter algorithms and the distorted Born approximation is a most appropriate methodology to use for modeling purposes in the microwave region.

Lang, Roger H.↗
NASA NTRS1992

Measurement of surface physical properties and radiation balance for KUREX-91 study

Biophysical properties and radiation balance components were measured at the Streletskaya Steppe Reserve of the Russian Republic in July 1991. Steppe vegetation parameters characterized include leaf area index (LAI), leaf angle distribution, mean tilt angle, canopy height, leaf spectral properties, leaf water potential, fraction of absorbed photosynthetically active radiation (APAR), and incoming and outgoing shortwave and longwave radiation. Research results, biophysical parameters, radiation balance estimates, and sun-view geometry effects on estimating APAR are discussed. Incoming and outgoing radiation streams are estimated using bidirectional spectral reflectances and bidirectional thermal emittances. Good agreement between measured and modeled estimates of the radiation balance were obtained.

Walter-Shea, Elizabeth A.↗
NASA NTRS1990

Land surface parameterization for regional surface heat transfer in hilly grassland

Radiometrically obtained surface temperature data and wind and temperature data from the atmospheric boundary layer are analyzed to determine the regional surface-heat flux. Monin-Obukhov similarity theory is employed to analyze the wind speed and the relationship between the surface potential temperature and the potential temperature. The radiometric scalar roughness is considered and found to be related to solar elevation and canopy height, although the regional sensible heat flux derived by the similarity theory analysis agrees with measured flux values.

Sugita, Michiaki↗
NASA NTRS1992

Closed Ecological Life Support Systems (CELSS) Test Facility

The CELSS Test Facility (CTF) is being developed for installation on Space Station Freedom (SSF) in August 1999. It is designed to conduct experiments that will determine the effects of microgravity on the productivity of higher (crop) plants. The CTF will occupy two standard SSF racks and will accommodate approximately one square meter of growing area and a canopy height of 80 cm. The growth volume will be isolated from the external environment, allowing stringent control of environmental conditions. Temperature, humidity, oxygen, carbon dioxide, and light levels will all be closely controlled to prescribed set points and monitored. This level of environmental control is needed to prevent stress and allow accurate assessment of microgravity effect (10-3 to 10-6 x g). Photosynthetic rates and respiration rates, calculated through continuous recording of gas concentrations, transpiration, and total and edible biomass produced will be measured. Toxic byproducts will be monitored and scrubbed. Transpiration water will be collected within the chamber and recycled into the nutrient solution. A wide variety of crop plants, e.g., wheat, soy beans, lettuce, potatoes, can be accommodated and various nutrient delivery systems and light delivery systems will be available. In the course of its development, the CTF will exploit fully, and contribute importantly, to the state-of-art in closed system technology and plant physiology.

Macelroy, Robert D.↗
NASA NTRS2002

Application of Reconfigurable Computing Technology to Multi-KiloHertz Micro-Laser Altimeter (MMLA) Data Processing

The Multi-KiloHertz Micro-Laser Altimeter (MMLA) is an aircraft based instrument developed by NASA Goddard Space Flight Center with several potential spaceflight applications. This presentation describes how reconfigurable computing technology was employed to perform MMLA signal extraction in real-time under realistic operating constraints. The MMLA is a "single-photon-counting" airborne laser altimeter that is used to measure land surface features such as topography and vegetation canopy height. This instrument has to date flown a number of times aboard the NASA P3 aircraft acquiring data at a number of sites in the Mid-Atlantic region. This instrument pulses a relatively low-powered laser at a very high rate (10 kHz) and then measures the time-of-flight of discrete returns from the target surface. The instrument then bins these measurements into a two-dimensional array (vertical height vs. horizontal ground track) and selects the most likely signal path through the array. Return data that does not correspond to the selected signal path are classified as noise returns and are then discarded. The MMLA signal extraction algorithm is very compute intensive in that a score must be computed for every possible path through the two dimensional array in order to select the most likely signal path. Given a typical array size with 50 x 6, up to 33 arrays must be processed per second. And for each of these arrays, roughly 12,000 individual paths must be scored. Furthermore, the number of paths increases exponentially with the horizontal size of the array, and linearly with the vertical size. Yet, increasing the horizontal and vertical sizes of the array offer science advantages such as improved range, resolution, and noise rejection. Due to the volume of return data and the compute intensive signal extraction algorithm, the existing PC-based MMLA data system has been unable to perform signal extraction in real-time unless the array is limited in size to one column, This limits the ability of the MMLA to operate in environments with sparse signal returns and a high number of noise return. However, under an IR&D project, an FPGA-based, reconfigurable computing data system has been developed that has been demonstrated to perform real-time signal extraction under realistic operating constraints. This reconfigurable data system is based on the commercially available Firebird Board from Annapolis Microsystems. This PCI board consists of a Xilinx Virtex 2000E FPGA along with 36 MB of SRAM arranged in five separately addressable banks. This board is housed in a rackmount PC with dual 850MHz Pentium processors running the Windows 2000 operating system. This data system performs all signal extraction in hardware on the Firebird, but also runs the existing "software based" signal extraction in tandem for comparison purposes. Using a relatively small amount of the Virtex XCV2000E resources, the reconfigurable data system has demonstrated to improve performance improvement over the existing software based data system by an order of magnitude. Performance could be further improved by employing parallelism. Ground testing and a preliminary engineering test flight aboard the NASA P3 has been performed, during which the reconfigurable data system has been demonstrated to match the results of the existing data system.

Powell, Wesley↗
NASA NTRS2005

NASA Tech Briefs, October 2005

Topics covered include: Insect-Inspired Optical-Flow Navigation Sensors; Chemical Sensors Based on Optical Ring Resonators; A Broad-Band Phase-Contrast Wave-Front Sensor; Progress in Insect-Inspired Optical Navigation Sensors; Portable Airborne Laser System Measures Forest-Canopy Height; Deployable Wide-Aperture Array Antennas; Faster Evolution of More Multifunctional Logic Circuits; Video-Camera-Based Position-Measuring System; N-Type delta Doping of High-Purity Silicon Imaging Arrays; Avionics System Architecture Tool; Updated Chemical Kinetics and Sensitivity Analysis Code; Predicting Flutter and Forced Response in Turbomachinery; Upgrades of Two Computer Codes for Analysis of Turbomachinery; Program Facilitates CMMI Appraisals; Grid Visualization Tool; Program Computes Sound Pressures at Rocket Launches; Solar-System Ephemeris Toolbox; Data-Acquisition Software for PSP/TSP Wind-Tunnel Cameras; Corrosion-Prevention Capabilities of a Water-Borne, Silicone-Based, Primerless Coating; Sol-Gel Process for Making Pt-Ru Fuel-Cell Catalysts; Making Activated Carbon for Storing Gas; System Regulates the Water Contents of Fuel-Cell Streams; Five-Axis, Three-Magnetic-Bearing Dynamic Spin Rig; Modifications of Fabrication of Vibratory Microgyroscopes; Chamber for Growing and Observing Fungi; Electroporation System for Sterilizing Water; Thermoelectric Air/Soil Energy-Harvesting Device; Flexible Metal-Fabric Radiators; Actuated Hybrid Mirror Telescope; Optical Design of an Optical Communications Terminal; Algorithm for Identifying Erroneous Rain-Gauge Readings; Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads; Lightweight Thermal Insulation for a Liquid-Oxygen Tank; Stellar Gyroscope for Determining Attitude of a Spacecraft; and Lifting Mechanism for the Mars Explorer Rover.

Source record↗
NASA NTRS2011

The ICESat-2 Mission: Concept, Pre-Launch Activities, and Opportunities

Ice sheet and sea level changes have been explicitly identified as a priority in the President's Climate Change Science Program, the Arctic Climate Impact Assessment, the 4th Assessment Report of the IPee and other national and international policy documents. Following recommendations from the National Research Council for an ICESat follow-on mission, the ICESat-2 mission is now under development for launch in early 2016. The primary aims of the ICESat-2 mission are to continue measurements of sea-ice thickness change, and ice sheet elevation changes at scales from outlet glaciers to the entire ice sheet as established by ICES at. In contrast to ICES at, ICESat-2 will employ a 6-beam micro-pulse laser photon-counting approach. The current concept uses a high repetition rate (10 kHz; equivalent to 70 cm on the ground) low-power laser in conjunction with single-photon sensitive detectors to measure range using approximately 532nm (green) light. The concept will enable the generation of seasonal maps of ice sheet elevation of Greenland and Antarctica, monthly maps of sea ice thickness of the polar ocean, a dense map of land elevation (2 km track spacing at the equator after two years) enabling the determination of canopy height, as well as ocean heights. While the mission has been optimized for cryospheric science and vast amount of high precision elevation measurements taken over land and over the ocean as well as of the atmosphere will provide scientists with a wealth of opportunities to explore the utility of ICESat-2. Those will range from the retrieval of cloud properties, to river stages, to snow cover, to land use changes and more. The presentation will review the measurement concept and physical principles of ICESat-2, current and planned activities to assess instrument performance and develop geophysical algorithms, as well as potential opportunities outside the main objectives of ICESat-2.

Markus, Thorsten↗
NASA NTRS2011

First Assessments of ICESat-2 Performance Using Aircraft Data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) Is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in early 2016, ICESat-2 will use a high repetition rate (approximately 10 kHz), small footprint (10m diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise ranges to the earth's surface. Operating in the green (approximately 532nm), the six beams of ICESat-2 will provide improved spatial coverage compared with ICESat while the differences in transmit energy among the beams provide a large dynamic range. In order to evaluate models of predicted ICESat-2 performance, and provide ICESat-2-like data for algorithm development an airborne ICESat-2 simulator was developed and first flown in 2010, this simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) has now had three deployments in the western US, and will be deployed to the polar regions in spring of 2012. MABEL uses a similar measurement strategy to what will be used on ICESat-2. MABEL collects more spatially-dense data than ICESat-2 (approximately 2-cm along track) with a smaller 2m diameter footprint in 16 green channels and an additional 8 channels in the infrared. The comparison between frequencies allows for analysis of possible penetration of green energy into water or snow. We present MABEL data collected over deserts, forests, ocean water, lakes. snow covered mountains, and saft flats, provide examples of how these data are being used to develop algorithms that derive geophysical products from ICESat 2 and assess expected performances.

Neumann, Tom↗
NASA NTRS2012

First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard. Several of the flights were coincident in time and space with NASA's Operation IceBridge, which provides an independent data set for validation. MABEL also collected data along CryoSat track 10482 in north central Greenland approximately one month after CryoSat passed overhead.

Neumann, Thomas↗
NASA NTRS2011

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Uninhabited Aerial Vehicle Synthetic Aperture Rada↗
NASA NTRS2013

Thermal Performance of ATLAS Laser Thermal Control System Demonstration Unit

The second Ice, Cloud, and Land Elevation Satellite mission currently planned by National Aeronautics and Space Administration will measure global ice topography and canopy height using the Advanced Topographic Laser Altimeter System {ATLAS). The ATLAS comprises two lasers; but only one will be used at a time. Each laser will generate between 125 watts and 250 watts of heat, and each laser has its own optimal operating temperature that must be maintained within plus or minus 1 degree Centigrade accuracy by the Laser Thermal Control System (LTCS) consisting of a constant conductance heat pipe (CCHP), a loop heat pipe (LHP) and a radiator. The heat generated by the laser is acquired by the CCHP and transferred to the LHP, which delivers the heat to the radiator for ultimate rejection. The radiator can be exposed to temperatures between minus 71 degrees Centigrade and minus 93 degrees Centigrade. The two lasers can have different operating temperatures varying between plus 15 degrees Centigrade and plus 30 degrees Centigrade, and their operating temperatures are not known while the LTCS is being designed and built. Major challenges of the LTCS include: 1) A single thermal control system must maintain the ATLAS at 15 degrees Centigrade with 250 watts heat load and minus 71 degrees Centigrade radiator sink temperature, and maintain the ATLAS at plus 30 degrees Centigrade with 125 watts heat load and minus 93 degrees Centigrade radiator sink temperature. Furthermore, the LTCS must be qualification tested to maintain the ATLAS between plus 10 degrees Centigrade and plus 35 degrees Centigrade. 2) The LTCS must be shut down to ensure that the ATLAS can be maintained above its lowest desirable temperature of minus 2 degrees Centigrade during the survival mode. No software control algorithm for LTCS can be activated during survival and only thermostats can be used. 3) The radiator must be kept above minus 65 degrees Centigrade to prevent ammonia from freezing using no more than 135 watts of heater power. 4) The LHP reservoir control heater power is limited to 15 watts with a 70 percent duty cycle. 5) The voltage of the power supply can vary between 26 volts direct current and 34 volts direct current during the spacecraft lifetime. A design analysis shows that a single LTCS can satisfy these requirements. However, shutdown of· the LHP is particularly challenging and the shutdown heater must be wired in series with two reservoir thermostats and two CCHP thermostats at different set points. An LTCS demonstration unit has been tested to verify these performance characteristics experimentally prior to proceeding to the final LTCS design and fabrication. Test results showed that the LHP shutdown scheme would be able to shut down the LHP as designed and the reservoir control heater can maintain the ATLAS mass simulator within the plus or minus 1 degrees Centigrade accuracy under various combinations of the heat load, sink temperature, and power supply voltage.

Ku, Jentung↗
NASA NTRS2015

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗
NASA NTRS2014

The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.

LiDAR↗
NASA NTRS2019

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗
NASA NTRS2020

A Multi-scaled Analysis of Forest Structure using Individual-Based Modeling in a Costa Rican Rainforest

Consideration of scale is essential when examining structural relationships in forests. In this study, we present a parameterization of the FORMIND individual-based forest model for old growth Atlantic lowland rainforest in La Selva, Costa Rica. Results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest within 2.3% of aboveground biomass values, based on comparisons with CARBONO inventory plot data. The Costa Rica FORMIND simulation was then used to investigate the relationship between canopy height and aboveground biomass (AGB), leaf area index (LAI) and gross primary productivity (GPP) at different spatial scales (20 × 20 m, 60 × 60 m, 100mx100m). The relationship between aboveground biomass and height is of particular importance toward the calibration of various remote sensing products including lidar and radar, whereas the LAI and GPP relationships are understudied in this context. We found that the relationship between all three variables and height varies considerably: the relationship is stronger at finer scales and weaker at coarser resolution. However, in all three comparisons, RMSE also decreased as scales coarsened, with the largest difference shown between 100 m and 10 m resolutions in relating AGB to Lorey's height (R^2 decreased by 0.3; RMSE decreased by 114.5 Mg/ha). This suggests that a trade-off between accuracy and precision exists, and further highlights the importance of spatial scale in determining the relatability of forest structure variables.

A.H.Armstrong↗