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Hurricane Maria (Category 4) snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100 to 800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥1 m in canopy height (mean = −7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13% of the study area had canopy heights ≤2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss (1 m, 2018-2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no structural changes >|1| m in either period. Canopy layers MANUSCRIPT HIGHLIGHTSHurricane Maria gave forests a haircut by toppling trees and shearing branches.Regrowth after Maria was patchy, with equal areas of height gain and no change.3-D measures of forest recovery after hurricanes can improve ecosystem models.

The hemlock woolly adelgid (HWA; Adelges tsugae) is an invasive insect infestation that is spreading into the forests of the northeastern United States, driven by the warmer winter temperatures associated with climate change. The initial stages of this disturbance are difficult to detect with passive optical remote sensing, since the insect often causes its host species, eastern hemlock trees (Tsuga canadensis), to defoliate in the midstory and understory before showing impacts in the overstory. New active remote sensing technologies—such as the recently launched NASA Global Ecosystem Dynamics Investigation (GEDI) spaceborne lidar—can address this limitation by penetrating canopy gaps and recording lower canopy structural changes. This study explores new opportunities for monitoring the HWA infestation with airborne lidar scanning (ALS) and GEDI spaceborne lidar data. GEDI waveforms were simulated using airborne lidar datasets from an HWA-infested forest plot at the Harvard Forest ForestGEO site in central Massachusetts. Two airborne lidar instruments, the NASA G-LiHT and the NEON AOP, overflew the site in 2012 and 2016. GEDI waveforms were simulated from each airborne lidar dataset, and the change in waveform metrics from 2012 to 2016 was compared to field-derived hemlock mortality at the ForestGEO site. Hemlock plots were shown to be undergoing dynamic changes as a result of the HWA infestation, losing substantial plant area in the middle canopy, while still growing in the upper canopy. Changes in midstory plant area (PAI 11–12 m above ground) and overall canopy permeability (indicated by RH10) accounted for 60% of the variation in hemlock mortality in a logistic regression model. The robustness of these structure-condition relationships held even when simulated waveforms were treated as real GEDI data with added noise and sparse spatial coverage. These results show promise for future disturbance monitoring studies with ALS and GEDI lidar data.

Considering the trajectories of pulses from terrestrial laser scanners (TLS) can provide refined models of occlusion and improve the assessment of observation quality in forests and other ecosystems. By considering the space traversed by light detection and ranging (lidar) pulses, we can separate empty regions of an ecosystem sample from unobserved regions of an ecosystem sample. We apply this method of TLS observation quality assessment, and analyze Compact Biomass Lidar 2 (CBL2) TLS observations of a single tree and of a deciduous forest stand. We show the contribution of information from each TLS scan to be inconsistent and the combination of multiple scans to have diminishing returns for new information, without guaranteeing complete coverage of a sample. We quantitatively investigate the effects of imposing information quality requirements on TLS sampling, for example, requiring minimum numbers of observations in each region or requiring regions to be observed from a minimum number of independent scans. We show empirically that rigid, predefined TLS sampling schemes, even with hypothetically dense coverage, cannot guarantee successful samples in geometrically complex systems such as forests. Through these methods, we lay the groundwork for on-the-fly assessment of observation quality according to several modeling-relevant metrics which enhance TLS ecosystem assessment. We also establish the value of flexible deployment options for TLS instruments, including the ability to deploy at a variety of heights.

Airborne lidar can observe saltmarshes on a regional scale, targeting phenological and tidal states to provide the information to more effectively utilize frequent multispectral satellite observations to monitor change. Airborne lidar observations from NASA Goddard Lidar Hyperspectral and Thermal (G-LiHT) of a well-studied region of saltmarsh (Plum Island, Massachusetts, United States) were acquired in multiple years (2014, 2015 and 2016). These airborne lidar data provide characterizations of important saltmarsh components, as well as specifications for effective surveys. The invasive Phragmites australis was observed to increase in extent from 8374 m2 in 2014, to 8882 m2 in 2015 (+6.1%), and again to 13,819 m2 in 2016 (+55.6%). Validation with terrestrial lidar supported this increase, but suggested the total extent was still underestimated. Estimates of Spartina alterniflora extent from airborne lidar were within 7% of those from terrestrial lidar, but overestimation of height of Spartina alterniflora was found to occur at the edges of creeks (+83.9%). Capturing algae was found to require observations within &plusmn, 15&deg, of nadir, and capturing creek structure required observations within &plusmn, 10&deg, of nadir. In addition, 90.33% of creeks and ditches were successfully captured in the airborne lidar data (8206.3 m out of 9084.3 m found in aerial imagery).

Solar induced fluorescence (SIF) is an ecological variable of interest to remote sensing retrievals, as it is directly related to vegetation composition and condition. FIREFLY (fluorescence imaging of red and far-red light yield) is a high performance spectrometer for estimating SIF. FIREFLY was flown in conjunction with NASA Goddard&rsquo, s lidar, hyperspectral, and thermal (G-LiHT) instrument package in 2017, as a technology demonstration for airborne retrievals of SIF. Attributes of FIREFLY relevant to SIF retrieval, including detector response and linearity, full-width at half maximum (FWHM), stray light, dark current, and shot noise were characterized with a combination of observations from Goddard&rsquo, s laser for absolute measurement of radiance calibration facility, an integrating sphere, controlled acquisitions of known targets, in-flight acquisitions, and forward modelling. FWHM, stray light, and dark current were found to be of acceptable magnitude, and characterized to within acceptable limits for SIF retrieval. FIREFLY observations were found to represent oxygen absorption features, along with a large number of solar absorption features. Shot noise was acceptable for direct SIF retrievals at native resolution, but indirect SIF retrievals from absorption features would require spatial aggregation, or repeated observations of targets.

FIREFLY (Fluorescence Imaging of REd and Far-red Light Yield) is a compact, fine-resolution imaging spectrometer that was designed and assembled by Headwall Photonics (Fitchburg, MA, USA) in collaboration with NASA scientists for airborne measurements of Solar-Induced Fluorescence (SIF). FIREFLY is integrated into the next generation of NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager (G-LiHT; www.gliht.nasa.gov), providing a complete system for measuring, interpreting and scaling SIF emissions. Characterization of FIREFLY was performed here to evaluate its performance and suitability for retrieving SIF.

Radiometric calibration of the Dual-Wavelength Echidna(®) Lidar (DWEL), a full-waveform terrestrial laser scanner with two simultaneously-pulsing infrared lasers at 1064 nm and 1548 nm, provides accurate dual-wavelength apparent reflectance (ρ(app)), a physically-defined value that is related to the radiative and structural characteristics of scanned targets and independent of range and instrument optics and electronics. The errors of ρ(app) are 8.1% for 1064 nm and 6.4% for 1548 nm. A sensitivity analysis shows that ρ(app) error is dominated by range errors at near ranges, but by lidar intensity errors at far ranges. Our semi-empirical model for radiometric calibration combines a generalized logistic function to explicitly model telescopic effects due to defocusing of return signals at near range with a negative exponential function to model the fall-off of return intensity with range. Accurate values of ρ(app) from the radiometric calibration improve the quantification of vegetation structure, facilitate the comparison and coupling of lidar datasets from different instruments, campaigns or wavelengths and advance the utilization of bi- and multi-spectral information added to 3D scans by novel spectral lidars.

A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations. publishedVersion

Contemporary terrestrial laser scanning (TLS) is being used widely in forest ecology applications to examine ecosystem properties at increasing spatial and temporal scales. Harvard Forest (HF) in Petersham, MA, USA, is a long-term ecological research (LTER) site, a National Ecological Observatory Network (NEON) location and contains a 35 ha plot which is part of Smithsonian Institution's Forest Global Earth Observatory (ForestGEO). The combination of long-term field plots, eddy flux towers and the detailed past historical records has made HF very appealing for a variety of remote sensing studies. Terrestrial laser scanners, including three pioneering research instruments: the Echidna Validation Instrument, the Dual-Wavelength Echidna Lidar and the Compact Biomass Lidar, have already been used both independently and in conjunction with airborne laser scanning data and forest census data to characterize forest dynamics. TLS approaches include three-dimensional reconstructions of a plot over time, establishing the impact of ice storm damage on forest canopy structure, and characterizing eastern hemlock ( Tsuga canadensis ) canopy health affected by an invasive insect, the hemlock woolly adelgid ( Adelges tsugae ). Efforts such as those deployed at HF are demonstrating the power of TLS as a tool for monitoring ecological dynamics, identifying emerging forest health issues, measuring forest biomass and capturing ecological data relevant to other disciplines. This paper highlights various aspects of the ForestGEO plot that are important to current TLS work, the potential for exchange between forest ecology and TLS, and emphasizes the strength of combining TLS data with long-term ecological field data to create emerging opportunities for scientific study.

Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. Destructive AGB measurements, although accurate, are time consuming and are not easily undertaken on a repeat basis or over large areas. Structure-from-Motion (SfM) photogrammetry and Terrestrial Laser Scanning (TLS) are two technologies that have the potential to yield precise 3D structural measurements of vegetation quite rapidly. Recent advances have led to the successful application of TLS and SfM in woody biomass estimation, but application in natural grassland systems remains largely untested. The potential of these techniques for AGB estimation is examined considering 11 grass plots with a range of biomass in South Dakota, USA. Volume metrics extracted from the TLS and SfM 3D point clouds, and also conventional disc pasture meter settling heights, were compared to destructively harvested AGB total (grass and litter) and AGB grass plot measurements. Although the disc pasture meter was the most rapid method, it was less effective in AGB estimation (AGBgrass r2 = 0.42, AGBtotal r2 = 0.32) than the TLS (AGBgrass r2 = 0.46, AGBtotal r2 = 0.57) or SfM (AGBgrass r2 = 0.54, AGBtotal r2 = 0.72) which both demonstrated their utility for rapid AGB estimation of grass systems.

Terrestrial laser scanning combining both near-infrared (NIR) and shortwave-infrared (SWIR) wavelengths can readily distinguish broad leaves from trunks, branches, and ground surfaces. Merging data from the 1548 nm SWIR laser in the Dual-Wavelength Echidna® Lidar (DWEL) instrument in engineering trials with data from the 1064 nm NIR laser in the Echidna® Validation Instrument (EVI), we imaged a deciduous forest scene at the Harvard Forest, Petersham, Massachusetts, and showed that trunks are about twice as bright as leaves at 1548 nm, while they have about equal brightness at 1064 nm. The reduced return of leaves in the SWIR is also evident in merged point clouds constructed from the two laser scans. This distinctive difference between leaf and trunk reflectance in the two wavelengths validates the principle of effective discrimination of leaves from other targets using the new dual-wavelength instrument.

This study presents a three-dimensional (3-D) forest reconstruction methodology using the new and emerging science of terrestrial full-waveform lidar scanning, which can provide rapid and efficient measurements of canopy structure. A 3-D forest reconstruction provides a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). It enables the study of the detailed structure study with respect to the canopy (foliage or branch/trunk), as well as the generation of a digital elevation model (DEM) and a canopy height model (CHM) at the stand level. Leaf area index (LAI) and Foliage area volume density profile directly estimated from voxelized 3-D reconstruction agree with measurements from field and airborne instrument. A 3-D forest reconstruction allows virtual direct representation of forest structure, and provides consistent and reliable validation data sources for airborne or spaceborne data.

The Nighttime Light (NTL) observed from the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) has shown a strong relationship with socio-economic and environmental variables. The long-term NTL measurements have been used as a primary data source to monitor the temporal dynamics of human activities. Characterizing the uncertainties in NTL is crucial for time series analysis. Here we analyzed the uncertainties due to moon-view geometry, vegetation, snow, surface Bidirectional Reflectance Distribution Function (BRDF)/albedo, and aerosol.