The effect of reef morphology on coral recruitment at multiple spatial scales.

Coral reefs are in decline worldwide, making it increasingly important to promote coral recruitment in new or degraded habitat. Coral reef morphology-the structural form of reef substrate-affects many aspects of reef function, yet the effect of reef morphology on coral recruitment is not well understood. We used structure-from-motion photogrammetry and airborne remote sensing to measure reef morphology (rugosity, curvature, slope, and fractal dimension) across a broad continuum of spatial scales and evaluated the effect of morphology on coral recruitment in three broadcast-spawning genera. We also measured the effect of other environmental and biotic factors such as fish density, adult coral cover, hydrodynamic larval import, and depth on coral recruitment. All variables combined explained 72% of coral recruitment in the study region. Coarse reef rugosity and curvature mapped at ≥2 m spatial resolution-such as large colonies, knolls, and boulders-were positively correlated with coral recruitment, explaining 22% of variation in recruitment. Morphology mapped at finer scales (≤32 cm resolution) was not significant. Hydrodynamic larval import was also positively related to coral recruitment in Porites and Montipora spp., and grazer fish density was linked to significantly lower recruitment in all genera. In addition, grazer density, reef morphology, and hydrodynamic import had differential effects on coral genera, reflecting genus-specific life history traits, and model performance was lower in gonochoric species. Overall, coral reef morphology is a key indicator of recruitment potential that can be detected by remote sensing, allowing potential larval sinks to be identified and factored into restoration actions.

Increased methane emissions from oil and gas following the Soviet Union's collapse.

Global atmospheric methane concentrations rose by 10 to 15 ppb/y in the 1980s before abruptly slowing to 2 to 8 ppb/y in the early 1990s. This period in the 1990s is known as the "methane slowdown" and has been attributed in part to the collapse of the former Soviet Union (USSR) in December 1991, which may have decreased the methane emissions from oil and gas operations. Here, we develop a methane plume detection system based on probabilistic deep learning and human-labeled training data. We use this method to detect methane plumes from Landsat 5 satellite observations over Turkmenistan from 1986 to 2011. We focus on Turkmenistan because economic data suggest it could account for half of the decline in oil and gas emissions from the former USSR. We find an increase in both the frequency of methane plume detections and the magnitude of methane emissions following the collapse of the USSR. We estimate a national loss rate from oil and gas infrastructure in Turkmenistan of more than 10% at times, which suggests the socioeconomic turmoil led to a lack of oversight and widespread infrastructure failure in the oil and gas sector. Our finding of increased oil and gas methane emissions from Turkmenistan following the USSR's collapse casts doubt on the long-standing hypothesis regarding the methane slowdown, begging the question: "what drove the 1992 methane slowdown?"

Quantifying NOx point sources with Landsat and Sentinel-2 satellite observations of NO2 plumes.

We show that the Landsat and Sentinel-2 satellites can detect NO2 plumes from large point sources at 10 to 60 m pixel resolution in their blue and ultrablue bands. We use the resulting NO2 plume imagery to quantify nitrogen oxides (NOx) emission rates for several power plants in Saudi Arabia and the United States, including a 13-y analysis of 132 Landsat plumes from Riyadh power plant 9 from 2009 through 2021. NO2 in the plumes initially increases with distance from the source, likely reflecting recovery from ozone titration. The fine pixel resolutions of Landsat and Sentinel-2 enable separation of individual point sources and stacks, including in urban background, and the long records enable examination of multidecadal emission trends. Our inferred NOx emission rates are consistent with previous estimates to within a precision of about 30%. Sources down to ~500 kg h-1 can be detected over bright, quasi-homogeneous surfaces. The 2009 to 2021 data for Riyadh power plant 9 show a strong summer peak in emissions, consistent with increased power demand for air conditioning, and a marginal slow decrease following the introduction of Saudi Arabia's Ambient Air Standard 2012.

Urban effects on local cloud patterns.

Urbanization extensively modifies surface roughness and properties, impacting regional climate and hydrological cycles. Urban effects on temperature and precipitation have drawn considerable attention. These associated physical processes are also closely linked to clouds' formation and dynamics. Cloud is one of the critical components in regulating urban hydrometeorological cycles but remains less understood in urban-atmospheric systems. We analyzed satellite-derived cloud patterns spanning two decades over 447 US cities and quantified the urban-influenced cloud patterns diurnally and seasonally. The systematic assessment suggests that most cities experience enhanced daytime cloud cover in both summer and winter; nocturnal cloud enhancement prevails in summer by 5.8%, while there is modest cloud suppression in winter nights. Statistically linking the cloud patterns with city properties, geographic locations, and climate backgrounds, we found that larger city size and stronger surface heating are primarily responsible for summer local cloud enhancement diurnally. Moisture and energy background control the urban cloud cover anomalies seasonally. Under strong mesoscale circulations induced by terrains and land-water contrasts, urban clouds exhibit considerable nighttime enhancement during warm seasons, which is relevant to strong urban surface heating interacting with these circulations, but other local and climate impacts remain complicated and inconclusive. Our research unveils extensive urban influences on local cloud patterns, but the effects are diverse depending on time, location, and city properties. The comprehensive observational study on urban-cloud interactions calls for more in-depth research on urban cloud life cycles and their radiative and hydrologic implications under the urban warming context.

Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure.

We demonstrate geostationary satellite monitoring of large transient methane point sources with the US Geostationary Operational Environmental Satellites (GOES). GOES provides continuous 5- to 10-min coverage of the Americas at 1 to 2 km nadir pixel resolution in two shortwave infrared spectral bands from which large methane plumes can be retrieved. We track the full evolution of an extreme methane release from the El Encino-La Laguna natural gas pipeline in Durango, Mexico on 12 May 2019. The release lasted 3 h at a variable rate of 260 to 550 metric tons of methane per hour and totaled 1,130 to 1,380 metric tons. We report several other detections of transient point sources from oil/gas infrastructure, from which we infer a detection limit of 10 to 100 t h-1. Our results show that extreme releases of methane can last less than an hour, as from deliberate venting, and would thus be difficult to identify and quantify with low-Earth orbit satellites.

Melt rates in the kilometer-size grounding zone of Petermann Glacier, Greenland, before and during a retreat.

Warming of the ocean waters surrounding Greenland plays a major role in driving glacier retreat and the contribution of glaciers to sea level rise. The melt rate at the junction of the ocean with grounded ice-or grounding line-is, however, not well known. Here, we employ a time series of satellite radar interferometry data from the German TanDEM-X mission, the Italian COSMO-SkyMed constellation, and the Finnish ICEYE constellation to document the grounding line migration and basal melt rates of Petermann Glacier, a major marine-based glacier of Northwest Greenland. We find that the grounding line migrates at tidal frequencies over a kilometer-wide (2 to 6 km) grounding zone, which is one order of magnitude larger than expected for grounding lines on a rigid bed. The highest ice shelf melt rates are recorded within the grounding zone with values from 60 ± 13 to 80 ± 15 m/y along laterally confined channels. As the grounding line retreated by 3.8 km in 2016 to 2022, it carved a cavity about 204 m in height where melt rates increased from 40 ± 11 m/y in 2016 to 2019 to 60 ± 15 m/y in 2020 to 2021. In 2022, the cavity remained open during the entire tidal cycle. Such high melt rates concentrated in kilometer-wide grounding zones contrast with the traditional plume model of grounding line melt which predicts zero melt. High rates of simulated basal melting in grounded glacier ice in numerical models will increase the glacier sensitivity to ocean warming and potentially double projections of sea level rise.

The weekly cycle of photosynthesis in Europe reveals the negative impact of particulate pollution on ecosystem productivity.

Aerosols can affect photosynthesis through radiative perturbations such as scattering and absorbing solar radiation. This biophysical impact has been widely studied using field measurements, but the sign and magnitude at continental scales remain uncertain. Solar-induced fluorescence (SIF), emitted by chlorophyll, strongly correlates with photosynthesis. With recent advancements in Earth observation satellites, we leverage SIF observations from the Tropospheric Monitoring Instrument (TROPOMI) with unprecedented spatial resolution and near-daily global coverage, to investigate the impact of aerosols on photosynthesis. Our analysis reveals that on weekends when there is more plant-available sunlight due to less particulate pollution, 64% of regions across Europe show increased SIF, indicating more photosynthesis. Moreover, we find a widespread negative relationship between SIF and aerosol loading across Europe. This suggests the possible reduction in photosynthesis as aerosol levels increase, particularly in ecosystems limited by light availability. By considering two plausible scenarios of improved air quality-reducing aerosol levels to the weekly minimum 3-d values and levels observed during the COVID-19 period-we estimate a potential of 41 to 50 Mt net additional annual CO2 uptake by terrestrial ecosystems in Europe. This work assesses human impacts on photosynthesis via aerosol pollution at continental scales using satellite observations. Our results highlight i) the use of spatiotemporal variations in satellite SIF to estimate the human impacts on photosynthesis and ii) the potential of reducing particulate pollution to enhance ecosystem productivity.

Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts.

Intact tropical rainforests have been exposed to severe droughts in recent decades, which may threaten their integrity, their ability to sequester carbon, and their capacity to provide shelter for biodiversity. However, their response to droughts remains uncertain due to limited high-quality, long-term observations covering extensive areas. Here, we examined how the upper canopy of intact tropical rainforests has responded to drought events globally and during the past 3 decades. By developing a long pantropical time series (1992 to 2018) of monthly radar satellite observations, we show that repeated droughts caused a sustained decline in radar signal in 93%, 84%, and 88% of intact tropical rainforests in the Americas, Africa, and Asia, respectively. Sudden decreases in radar signal were detected around the 1997-1998, 2005, 2010, and 2015 droughts in tropical Americas; 1999-2000, 2004-2005, 2010-2011, and 2015 droughts in tropical Africa; and 1997-1998, 2006, and 2015 droughts in tropical Asia. Rainforests showed similar low resistance (the ability to maintain predrought condition when drought occurs) to severe droughts across continents, but American rainforests consistently showed the lowest resilience (the ability to return to predrought condition after the drought event). Moreover, while the resistance of intact tropical rainforests to drought is decreasing, albeit weakly in tropical Africa and Asia, forest resilience has not increased significantly. Our results therefore suggest the capacity of intact rainforests to withstand future droughts is limited. This has negative implications for climate change mitigation through forest-based climate solutions and the associated pledges made by countries under the Paris Agreement.

Boat encounter with the 2019 Java bioluminescent milky sea: Views from on-deck confirm satellite detection.

"Milky seas" are massive swaths of uniformly and steadily glowing ocean seen at night. The phenomenon is thought to be caused by luminous bacteria, but details of milky sea composition, structure, cause, and implications in nature remain largely uncertain. Between late July and early September 2019, specialized low-light satellite sensors detected a possible bioluminescent milky sea south of Java, Indonesia, spanning >100,000 km2. Upon learning of these findings, crew members of the yacht Ganesha reached out to confirm and share details of their personal encounter with this same event. Here, we document Ganesha's experience as recalled by the crew, compare their course to satellite data, and assess their photography of this milky sea.

Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover.

Monitoring the status of species is crucial for biodiversity conservation and sustainable resource management in tropical forests, but conventional in situ monitoring methods are impractical over large scales. Scientists have resorted to two potentially complementary approaches: local ecological knowledge (LEK) and remote sensing. To gauge the potential of combining LEK and remote sensing for assessing species status at landscape scales, a large-scale assessment of the reliability of both measures is critical but hampered by the lack of ground-level data. We conducted a landscape-scale assessment of LEK and remote sensing, using a survey of over 900 communities (a near census in our study area) and nearly 4,000 households in 235 randomly selected communities in the Peruvian Amazon-the largest LEK survey as yet undertaken in tropical forests. The survey collected LEK data on the presence of 20 indicator species from both community leaders/elders and randomly sampled households. We assessed LEK and remotely sensed land cover-forest cover and nonmain channel open water-as proxies for species habitat, across species (game, fish, and timber), over time (current and historical), and by indigeneity (Indigenous peoples and mestizos). Overall, LEK and remotely sensed land cover corroborate each other well. Concordance is highest for the current status of game species reported by sampled households, as is the concordance of historical LEK from Indigenous community leaders/elders. The results point to the promise of combining LEK and remote sensing in monitoring the status of species in data-poor tropical forests.

Prevalence and drivers of abrupt vegetation shifts in global drylands.

The constant provision of plant productivity is integral to supporting the liability of ecosystems and human wellbeing in global drylands. Drylands are paradigmatic examples of systems prone to experiencing abrupt changes in their functioning. Indeed, space-for-time substitution approaches suggest that abrupt changes in plant productivity are widespread, but this evidence is less clear using observational time series or experimental data at a large scale. Studying the prevalence and, most importantly, the unknown drivers of abrupt (rather than gradual) dynamical patterns in drylands may help to unveil hotspots of current and future dynamical instabilities in drylands. Using a 20-y global satellite-derived temporal assessment of dryland Normalized Difference Vegetation Index (NDVI), we show that 50% of all dryland ecosystems exhibiting gains or losses of NDVI are characterized by abrupt positive/negative temporal dynamics. We further show that abrupt changes are more common among negative than positive NDVI trends and can be found in global regions suffering recent droughts, particularly around critical aridity thresholds. Positive abrupt dynamics are found most in ecosystems with low seasonal variability or high aridity. Our work unveils the high importance of climate variability on triggering abrupt shifts in vegetation and it provides missing evidence of increasing abruptness in systems intensively managed by humans, with low soil organic carbon contents, or around specific aridity thresholds. These results highlight that abrupt changes in dryland dynamics are very common, especially for productivity losses, pinpoint global hotspots of dryland vulnerability, and identify drivers that could be targeted for effective dryland management.

Regime shifts, trends, and variability of lake productivity at a global scale.

Lakes are often described as sentinels of global change. Phenomena like lake eutrophication, algal blooms, or reorganization in community composition belong to the most studied ecosystem regime shifts. However, although regime shifts have been well documented in several lakes, a global assessment of the prevalence of regime shifts is still missing, and, more in general, of the factors altering stability in lake status, is missing. Here, we provide a first global assessment of regime shifts and stability in the productivity of 1,015 lakes worldwide using trophic state index (TSI) time series derived from satellite imagery. We find that 12.8% of the lakes studied show regime shifts whose signatures are compatible with tipping points, while the number of detected regime shifts from low to high TSI has increased over time. Although our results suggest an overall stable picture for global lake dynamics, the limited instability signatures do not mean that lakes are insensitive to global change. Modeling the interaction between lake climatic, geophysical, and socioeconomic features and their stability properties, we find that the probability of a lake experiencing a tipping point increases with human population density in its catchment, while it decreases as the gross domestic product of that population increases. Our results show how quantifying lake productivity dynamics at a global scale highlights socioeconomic inequalities in conserving natural environments.

Living fast, dying young: Anthropogenic habitat modification influences the fitness and life history traits of a cooperative breeder.

Anthropogenic habitat modification can indirectly effect reproduction and survival in social species by changing the group structure and social interactions. We assessed the impact of habitat modification on the fitness and life history traits of a cooperative breeder, the Arabian babbler (Argya squamiceps). We collected spatial, reproductive and social data on 572 individuals belonging to 21 social groups over 6 years and combined it with remote sensing to characterize group territories in an arid landscape. In modified resource-rich habitats, groups bred more and had greater productivity, but individuals lived shorter lives than in natural habitats. Habitat modification favoured a faster pace-of-life with lower dispersal and dominance acquisition ages, which might be driven by higher mortality providing opportunities for the dominant breeding positions. Thus, habitat modification might indirectly impact fitness through changes in social structures. This study shows that trade-offs in novel anthropogenic opportunities might offset survival costs by increased productivity.

Effect of the Photoexcitation Wavelength and Polarization on the Generated Heat by a Nd-Doped Microspinner at the Microscale.

Thermal control at small scales is critical for studying temperature-dependent biological systems and microfluidic processes. Concerning this, optical trapping provides a contactless method to remotely study microsized heating sources. This work introduces a birefringent luminescent microparticle of NaLuF4:Nd3+ as a local heater in a liquid system. When optically trapped with a circularly polarized laser beam, the microparticle rotates and heating is induced through multiphonon relaxation of the Nd3+ ions. The temperature increment in the surrounding medium is investigated, reaching a maximum heating of ≈5 °C within a 30 µm radius around the static particle under 51 mW laser excitation at 790 nm. Surprisingly, this study reveals that the particle's rotation minimally affects the temperature distribution, contrary to the intuitive expectation of liquid stirring. The influence of the microparticle rotation on the reduction of heating transfer is analyzed. Numerical simulations confirm that the thermal distribution remains consistent regardless of spinning. Instead, the orientation-dependence of the luminescence process emerges as a key factor responsible for the reduction in heating. The anisotropy in particle absorption and the lag between the orientation of the particle and the laser polarization angle contribute to this effect. Therefore, caution must be exercised when employing spinning polarization-dependent luminescent particles for microscale thermal analysis using rotation dynamics.

Unraveling the drivers and impacts of leaf phenological diversity in a subtropical forest: A fine-scale analysis using PlanetScope CubeSats.

Leaf phenology variations within plant communities shape community assemblages and influence ecosystem properties and services. However, questions remain regarding quantification, drivers, and productivity impacts of intra-site leaf phenological diversity. With a 50-ha subtropical forest plot in China's Heishiding Provincial Nature Reserve (part of the global ForestGEO network) as a testbed, we gathered a unique dataset combining ground-derived abiotic (topography, soil) and biotic (taxonomic diversity, functional diversity, functional traits) factors. We investigated drivers underlying leaf phenological diversity extracted from high-resolution PlanetScope data, and its influence on aboveground biomass (AGB) using structural equation modeling (SEM). Our results reveal considerable fine-scale leaf phenological diversity across the subtropical forest landscape. This diversity is directly and indirectly influenced by abiotic and biotic factors (e.g. slope, soil, traits, taxonomic diversity; r2 = 0.43). While a notable bivariate relationship between AGB and leaf phenological diversity was identified (r = -0.24, P < 0.05), this relationship did not hold in SEM analysis after considering interactions with other biotic and abiotic factors (P > 0.05). These findings unveil the underlying mechanism regulating intra-site leaf phenological diversity. While leaf phenology is known to be associated with ecosystem properties, our findings confirm that AGB is primarily influenced by functional trait composition and taxonomic diversity rather than leaf phenological diversity.

Inside-out: Synergising leaf biochemical traits with stomatal-regulated water fluxes to enhance transpiration modelling during abiotic stress.

As the global climate continues to change, plants will increasingly experience abiotic stress(es). Stomata on leaf surfaces are the gatekeepers to plant interiors, regulating gaseous exchanges that are crucial for both photosynthesis and outward water release. To optimise future crop productivity, accurate modelling of how stomata govern plant-environment interactions will be crucial. Here, we synergise optical and thermal imaging data to improve modelled transpiration estimates during water and/or nutrient stress (where leaf N is reduced). By utilising hyperspectral data and partial least squares regression analysis of six plant traits and fluxes in wheat (Triticum aestivum), we develop a new spectral vegetation index; the Combined Nitrogen and Drought Index (CNDI), which can be used to detect both water stress and/or nitrogen deficiency. Upon full stomatal closure during drought, CNDI shows a strong relationship with leaf water content (r2 = 0.70), with confounding changes in leaf biochemistry. By incorporating CNDI transformed with a sigmoid function into thermal-based transpiration modelling, we have increased the accuracy of modelling water fluxes during abiotic stress. These findings demonstrate the potential of using combined optical and thermal remote sensing-based modelling approaches to dynamically model water fluxes to improve both agricultural water usage and yields.

Alternative method for determining leaf CO2 assimilation without gas exchange measurements: Performance, comparison and sensitivity analysis.

We present an alternative method to determine leaf CO2 assimilation rate (An ), eliminating the need for gas exchange measurements in proximal and remote sensing. This method combines the Farquhar-von Caemmerer-Berry photosynthesis model with mechanistic light reaction (MLR) theory and leaf energy balance (EB) analysis. The MLR theory estimates the actual electron transport rate (J) by leveraging chlorophyll fluorescence via pulse amplitude-modulated fluorometry for proximal sensing or sun-induced chlorophyll fluorescence measurements for remote sensing, along with spectral reflectance. The EB equation is used to directly estimate stomatal conductance from leaf temperature. In wheat and soybean, the MLR-EB model successfully estimated An variations, including midday depression, under various environmental and phenological conditions. Sensitivity analysis revealed that the leaf boundary layer conductance (gb ) played an equal, if not more, crucial role compared to the variables for J. This was primarily caused by the indirect influence of gb through the EB equation rather than its direct impact on convective CO2 exchange on the leaf. Although the MLR-EB model requires an accurate estimation of gb , it can potentially reduce uncertainties and enhance applicability in photosynthesis assessment when gas exchange measurements are unavailable.

Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas.

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi-arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long-term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate-ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi-arid biomes for the assessment of climate-ecosystem interactions that contribute to abrupt shifts.

Shortening fire return interval predisposes west-central Canadian boreal peatlands to more rapid vegetation growth and transition to forest cover.

Climate change in northern latitudes is increasing the vulnerability of peatlands and the riparian transition zones between peatlands and upland forests (referred to as ecotones) to greater frequency of wildland fires. We examined early post-fire vegetation regeneration following the 2011 Utikuma complex fire (central Alberta, Canada). This study examined 779 peatlands and adjacent ecotones, covering an area of ~182 km2 . Based on the known regional fire history, peatlands that burned in 2011 were stratified into either long return interval (LRI) fire regimes of >80 years (i.e., no recorded prior fire history) or short fire return interval (SRI) of 55 years (i.e., within the boundary of a documented severe fire in 1956). Data from six multitemporal airborne lidar surveys were used to quantify trajectories of vegetation change for 8 years prior to and 8 years following the 2011 fire. To date, no studies have quantified the impacts of post-fire regeneration following short versus long return interval fires across this broad range of peatlands with variable environmental and post-fire successional trajectories. We found that SRI peatlands demonstrated more rapid vascular and shrub growth rates, especially in peatland centers, than LRI peatlands. Bogs and fens burned in 1956, and with little vascular vegetation (classified as "open peatlands") prior to the 2011 fire, experienced the greatest changes. These peatlands tended to transition to vascular/shrub forms following the SRI fire, while open LRI peatlands were not significantly different from pre-fire conditions. The results of this study suggest the emergence of a positive feedback, where areas experiencing SRI fires in southern boreal peatlands are expected to transition to forested vegetation forms. Along fen edges and within bog centers, SRI fires are expected to reduce local peatland groundwater moisture-holding capacity and promote favorable conditions for increased fire frequency and severity in the future.

Pixel walking along the boreal forest-Arctic tundra ecotone: Large scale ground-truthing of satellite-derived greenness (NDVI).

In this Technical Advance, we describe a novel method to improve ecological interpretation of remotely sensed vegetation greenness measurements that involved sampling 24,395 Landsat pixels (30 m) across 639 km of Alaska's central Brooks Range. The method goes well beyond the spatial scale of traditional plot-based sampling and thereby more thoroughly relates ground-based observations to satellite measurements. Our example dataset illustrates that, along the boreal-Arctic boundary, vegetation with the greatest Landsat Normalized Difference Vegetation Index (NDVI) is taller than 1 m, woody, and deciduous; whereas vegetation with lower NDVI tends to be shorter, evergreen, or non-woody. The field methods and associated analyses advance efforts to inform satellite data with ground-based vegetation observations using field samples collected at spatial scales that closely match the resolution of remotely sensed imagery.