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This is the AmeriFlux version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in a red pine forest (canopy height: 15 - 21.6 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is the northwestern most tower in the 10 x 10km study domain. It is located in a red pine forest (canopy height ~25m). There is a regrowing/trap layer consisting of broadleaf aspen and other deciduous vegetation.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFk SW1 Aspen-2 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFk SW1 Aspen-2 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: immediate vicinity - 10m; greater area - 24.4 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFL SW2 Aspen-3 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFL SW2 Aspen-3 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (25m Rohn) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: 15 - 19.2 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFm SW3 Hardwood-2 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFm SW3 Hardwood-2 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen and maple forest (canopy height: 15 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFq SE3 Aspen-4 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFq SE3 Aspen-4 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: 10 - 14.3 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in a red pine forest (canopy height: 15 - 21.6 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFi NE3 Hardwood-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFi NE3 Hardwood-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the northeastern quadrant of the 10 x 10km study domain. It is located in a mixed hardwood forest (canopy height: 18 - 20m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFj NE4 Maple-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFj NE4 Maple-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the northeastern quadrant of the 10 x 10km study domain. It is located in a maple forest (canopy height: 18 - 20m). Some conifers mixed in, more conifers to the NNW.
The BOREAS TE-5 team collected measurements in the NSA and SSA on gas exchange, gas composition, and tree growth. This data set contains measurements of the concentration and stable carbon (C-13/C-12 and oxygen (O-18/O-16) isotope ratios of atmospheric CO2 in air samples collected at different heights within forest canopies. The data were collected to determine the influence of photosynthesis and respiration by the forest ecosystems on the concentration and stable isotope ratio of atmospheric CO2 These measurements were collected at the SSA during each 1994 IFC at OJP, OBS, and OA sites. Measurements were also collected at the NSA during each 1994 IFC at the OJP, T6R5S TE UBS, and T2Q6A TE OA sites. The stable isotope ratios are expressed using standard delta notation and in units of per mil. The isotope ratios are expressed relative to the international standard, PDB, for both carbon and oxygen samples. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
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.
NASA's Global Ecosystem Dynamics Investigation (GEDI) instrument was launched Dec. 5, 2018, and installed on the International Space Station 419 km from Earth. The GEDI is a Light Detection and Ranging (LIDAR) instrument; measuring the time of flight of transmitted laser beams to the Earth and back to determine altitude for geospatial mapping of forest canopy heights. The need for very dense cross track sampling for slope measurements of canopy height is accomplished by using three individual laser transmitter systems, where each beam is split into two beams by a birefringent crystal. Furthermore, one transmitter is equipped with a diffractive optical element splitting the two beams into four, for a total of 8 beams. The beams are reflected off of the features and imaged by an 800 mm diameter Receiver Telescope Assembly, composed of a Ritchey-Chretien telescope, a refractive aft optics assembly and focal plane array which collects and focuses the light from the 8 probe beams into the 8 science fibers, each with a field of view on the Earth subtending 300 mu rad. The dense cross-track sampling mandated a custom designed dual-fiber interface. The science fibers had to be aligned to the nominal, projected laser spots. The alignment was highly dependent on optimization and co-positioning of the fibers pair-wise due to mechanical constraints. This paper presents the end-to-end alignment and metrology of the full optical system from transmitter elements through receiver telescope, aft-optics, focal plane and receiver fibers performed at NASA Goddard Space Flight Center.[GRAPHICS]
Spaceborne SAR interferometry (InSAR) has the potential ofdetecting forest change on a global scale with fine (meter-level)spatial resolution as well as on a monthly/weekly basis under allweather conditions. This is significant to characterize the land usechange and its impact on climate change. In this paper, bothsingle-pass and repeat-pass SAR interferometry from spacebornesensors are combined in order to detect and quantify (withNormalized RMSE 30%) forest disturbance at a large scale(dozens of kilometers) however with a fine spatial resolution (<1 hectare) based on two newly developed approaches. The singlepassInSAR approach is not only able to detect forest disturbancebut also capable of characterizing meter (or even sub-meter)level change of forest phase-center (mean) height due to forestgrowth and/or degradation. The methodology described in thispaper can be considered as complimentary tools and thus can becombined with the existing PolInSAR technique (that has beenwidely used for retrieving forest height from single-pass SARinterferometry). These methods are extensively validated with thepast and current spaceborne single-pass and repeat-pass InSARmissions (i.e. JAXA’s ALOS-1, ALOS-2 and DLR’s TanDEM-X)over subtropical forests in Australia as well as tropical forestsin Brazil. Such techniques also serve as observing prototypes forthe fusion of the future spaceborne InSAR missions (such asNASA-ISRO’s NISAR and DLR’s TanDEM-L).
Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled leaf temperature distributions based on canopy temperature measurements from one of the warmest days in a 2 year dry season record indicated that 87% of leaves in the warmest burned forest patches exceeded the temperature threshold where respiration surpasses photosynthesis, compared to approximately 72%–74% in intact and logged forests, respectively, in the same time period. After controlling for environmental factors, burned forests were predicted to be 2.6 °C warmer on average [1.39 °C–3.96 °C, 95% credible interval] than intact forests across a 5–40 m canopy height range. Burned forests showed modest thermal recovery over time, with temperatures decreasing by approximately 1.2 °C over a 30 year recovery period. In contrast, logged forests showed minimal thermal differences from intact forests (−0.353 on average, [−1.125–0.274, 95% credible interval]) and negligible change (0.15 °C) over the same timeframe. While the absolute probabilities of exceeding damaging thermal thresholds remain low across all forest types under current climate conditions, the probability of leaves exceeding temperatures that cause permanent leaf damage was ten times higher in burned forests, with implications for the future of burned forest regeneration in water-limited regions of the Amazon basin. In particular, the combination of higher mean temperatures, greater temperature variability, and more frequent exposure to damaging thermal thresholds implies that burned tropical forests will experience substantially higher mortality rates and slower biomass recovery compared to intact and selectively logged forests, especially in water-limited regions where trees cannot rely on evaporative cooling to moderate canopy temperatures.
A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included.
Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MtB Mt Bigelow. This is the FLUXNET version of the carbon flux data for the site US-MtB Mt Bigelow produced by applying the standard ONEFlux (1F) software. Site Description - Western slope of Mt. Bigelow; 29 km NE of Tucson, AZ, USA; Mixed evergreen conifer forest; Average canopy height = 10 m; Summer monsoon; 30-m tower installed in 2002; Secondary forest re-established in the 1930s