Search NASA⌕ Search

SEARCH · Search NASA

Results for “vegetation canopy”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Evaluation of the photochemical reflectance index in AVIRIS imagery

In this paper, we evaluate the potential for extracting the 'photochemical reflectance index' (PRI; previously called the 'physiological reflectance index') from AVIRIS data. This index, which is derived from narrow-band reflectance at 531 and 570 nm, has proven to be a useful indicator of photosynthetic function at the leaf and canopy scales. At the leaf level, PRI varies with photosynthetic capacity, radiation-use efficiency, and vegetation type (unpublished data). This finding is consistent with the hypothesis that vegetation types exhibiting chronically reduced photosynthesis during periods of stress (e.g. drought-tolerant evergreens) invest proportionally more in photoprotective processes than vegetation with high photosynthetic capacity (e.g. crops or deciduous perennials). Vertical transects in tropical and boreal forest canopies have indicated declines in PRI associated with downregulation of photosynthesis at the canopy tops under sunny, dry midday conditions (unpublished data). This reduced PRI in upper canopy levels provides a further basis for examining this signal with the 'view from above' afforded by aircraft overflights. Although many factors could confound interpretation of a subtle physiological signal at the landscape scale, we conducted a preliminary examination of PRI extracted from existing, AVIRIS imagery of Stanford University's Jasper Ridge Biological Preserve obtained on the June 2nd, 1992, overflight. The goal was to use the hyperspectral capabilities of AVIRIS to evaluate the potential of this index for obtaining useful physiological data at the landscape scale. The expectation based on leaf- and canopy-level studies was that regions containing vegetation of reduced photosynthetic capacity (e.g. chaparral or evergreen woodland) would exhibit lower PRI values than regions of high capacity (e.g. deciduous woodland).

Gamon, John A.↗
DOE OSTI2026

Land-Surface Temperature Transitions at the Bankhead National Forest (LASTT-BNF) Field Campaign Report

Land surface types that are common in the Southeast United States (e.g., forests, agriculture, urban) can play key roles in the regulation of surface-atmosphere energy exchange and boundary-layer evolution in the region (Hinkle et al. 2024). Heterogeneity in these land-surface types and associated emissivities can drive strong transitions in land surface temperature (LST), which is an important component of the surface energy balance. Within the forested canopy surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s field deployment at the Bankhead National Forest (BNF) in Alabama main site (M1) (Kuang et al. 2026), the different components of the vegetation and ground surface can create strong gradients in surface temperature that can influence the canopy thermal environment and vegetative function (e.g., stress, transpiration), both of which can have important, yet poorly characterized, controls on lower atmospheric processes (e.g., thermal turbulence, secondary circulations).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

The Spectral Invariant Approximation Within Canopy Radiative Transfer to Support the Use of the EPIC/DSCOVR Oxygen B-band for Monitoring Vegetation

EPIC (Earth Polychromatic Imaging Camera) is a 10-channel spectroradiometer onboard DSCOVR (Deep Space Climate Observatory) spacecraft. In addition to the near-infrared (NIR, 780 nm) and the 'red' (680 nm) channels, EPIC also has the O2 A-band (764+/-0.2 nm) and B-band (687.75+/-0.2 nm). The EPIC Normalized Difference Vegetation Index (NDVI) is defined as the difference between NIR and 'red' channels normalized to their sum. However, the use of the O2 B-band instead of the 'red' channel mitigates the effect of atmosphere on remote sensing of surface reflectance because O2 reduces contribution from the radiation scattered by the atmosphere. Applying the radiative transfer theory and the spectral invariant approximation to EPIC observations, the paper provides supportive arguments for using the O2 band instead of the red channel for monitoring vegetation dynamics. Our results suggest that the use of the O2 B-band enhances the sensitivity of the top-of-atmosphere NDVI to the presence of vegetation.

Alexander Marshak↗
NASA NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

Hurricane Maria, a Category 4 storm, 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 (100–800 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 13.5% 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 (2017–2018) followed by rapid height gain > 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 height changes larger than ± 1 m in either period. Canopy layers < 10 m tall accounted for most increases in canopy height and fractional cover between 2018 and 2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage and highlight the diversity of ecosystem impacts from heterogeneous spatial patterns and vertical stratification of forest regrowth following a major disturbance event.

forest structure↗
NASA NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

Hurricane Maria, a Category 4 storm, 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 (100–800 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 13.5% 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 (2017–2018) followed by rapid height gain > 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 height changes larger than ± 1 m in either period. Canopy layers < 10 m tall accounted for most increases in canopy height and fractional cover between 2018 and 2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage and highlight the diversity of ecosystem impacts from heterogeneous spatial patterns and vertical stratification of forest regrowth following a major disturbance event.

forest structure↗
DOE OSTI2021

Canopy damage and recovery following Hurricane Maria using multitemporal lidar data, Mar/2017 - Mar/2020, Puerto Rico

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, 2017-2018) followed by rapid height gain (>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 <10 m accounted for most increases in canopy height and fractional cover between 2018-2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage. Included in the attached zip file are four TIF and four KML files.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model

Satellite observations for the Arctic and boreal region may contain information of vegetation, soil, snow, snowmelt, and/or other surface water bodies. We investigated the impacts of vegetation, soil, snow and surface water on empirical vegetation/snow indices on a tundra ecosystem area located around Utqiaġvik (formerly Barrow) of Alaska with the Moderate Resolution Imaging Spectrometer (MODIS) images in 2001–2014. Empirical vegetation indices, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), the index of near infrared of vegetation (NIRv), and modified EVI (EVI2), have been used to monitor vegetation. Normalized difference snow index (NDSI) has been widely applied to monitor snow. The vegetation cover fraction (VGCF), the soil cover fraction (SOILCF), the snow cover fraction (SNOWCF), the surface water body cover fraction (WaterBodyCF), the fractional absorption of photosynthetically active radiation (PAR) by vegetation chlorophyll (fAPARchl), the fractional absorption of PAR by non-chlorophyll components of the vegetation (fAPARnon-chl), and the fractional absorption of PAR by the entire canopy (fAPARcanopy) are retrieved with the MODIS images and a coupled Leaf-Vegetation-Soil-Snow-Surface water body radiative transfer model, LVS3. The vegetation indices (NDVI, EVI, EVI2 and NIRv) differ from VGCF, fAPARchl, fAPARnon-chl, and fAPARcanopy. In addition to vegetation, we find that soil, snow and surface water also have impacts on vegetation indices NDVI, EVI (EVI2), and NIRv. Presence of snow makes lower the observed values of NDVI, EVI2 and NIRv. After snowmelt is gone, the vegetation indices (NDVI, EVI, EVI2 and NIRv) linearly decrease with SOILCF and WaterBodyCF, and WaterBodyCF has stronger impacts on these vegetation indices than SOILCF. The relationship between EVI and snow is complicated. NDSI non-linearly increases with SNOWCF, but linearly increases with sum of SNOWCF and WaterBodyCF (sum = 0.5893 × NDSI +0.4342, R2 = 0.976). NDSI linearly decreases with VGCF, and the relationship between NDSI and SOILCF is complex. Retrievals of VGCF, fAPARchl, fAPARnon-chl and fAPARcanopy with the LVS3 model provide alternatives for vegetation monitoring and ecological modeling.

Qingyuan Zhang↗
NASA NTRS1991

Analysis of field measurements of carbon dioxide and water vapor fluxes

Analysis of the field measurements of carbon dioxide and water vapor fluxes is discussed. These data were examined in conjunction with reflectance obtained from helicopter mounted Modular Multiband Radiometer. These measurements are representative of the canopy scale (10 to 100 m)(exp 2) and provide a good basis for investigating the hypotheses/relationship potentially useful in remote sensing applications. All the micrometeorological data collected during FIFE-89 were processed and fluxes of CO2, water vapor, and sensible heat were calculated. Soil CO2 fluxes were also estimated. Employing these soil CO2 flux values, in conjunction with micrometeorological measurements, canopy photosynthesis is being estimated. A biochemical model of leaf photosynthesis was adapted to the prairie vegetation. The modeled leaf photosynthesis rates were scaled up to the canopy level. This model and a multiplicative stomatal conductance model are also used to calculate canopy conductance.

Verma, Shashi B.↗
DOE OSTI2025

Using satellite data to assess Hurricane Helene’s impact on vegetation by land use in the CSRA

Many regions within Georgia, South Carolina, and North Carolina experienced record-breaking rainfall and catastrophic winds due to Hurricane Helene. Helene made landfall on Florida’s big bend on September 26 th , 2024, as a category 4 hurricane, and tracked northward through Georgia and the southern Appalachian Mountains before dissipating on September 29 th , 2024. One significant impact of the hurricane was severe damage to tree canopies across the southeastern United States. This study utilizes satellite-based remotely sensed data provided by the National Aeronautical and Space Administration (NASA) to examine the resilience of these tree canopies following the hurricane. Specifically, the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Cover Type, Soil Moisture Active Passive (SMAP), and the Global Precipitation Measurement (GPM) mission datasets were employed to study the tree canopy’s response to such events in the Central Savannah River Area (CSRA). A significant increase was observed in the LAI in November of 2024. This increase in LAI was likely influenced by warmer-than-average temperatures throughout October of 2024, along with a second record-breaking rainfall event in the CSRA on November 6th, 2024. The LAI increase was then broken down into land cover type to understand which areas contributed most. The complex nature and resilience of trees became evident, offering opportunities for further exploration and application in urban planning, emergency response, and environmental management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Ecosystem-Level Energy and Water Budgets Are Resilient to Canopy Mortality in Sparse Semiarid Biomes

Climate-driven woody vegetation mortality is a defining feature of semiarid biomes that drives fundamental changes in ecosystem structure. However, the observed impacts of woody mortality on ecosystem-scale energy and water budgets and the responses of surviving vegetation are highly variable among studies in water-limited environments. A previous girdling manipulation experiment in a piñon-juniper woodland suggested that although ecosystem-scale evapotranspiration was not altered by large-scale piñon mortality, soil water content decreased and the surviving juniper experienced greater water stress than juniper in an undisturbed woodland. Here we experimentally explored to what extent mortality-induced changes in energy balance components can explain these results. We compared energy fluxes measured above two adjacent piñon-juniper woodlands where piñon girdling was implemented at one site and the other subsequently experienced large-scale natural piñon mortality. We found that the mortality-induced decrease in canopy area was not sufficient to alter surface reflectance, roughness, and partitioning between energy budget components at both sites. A radiative transfer model estimated that because of the sparse premortality canopy, surface reflectance is more sensitive to a large increase in understory leaf area than further loss of crown area. Increased water stress in the remaining juniper following both mortality events can be explained by an increase in radiation on the ground that promoted higher soil temperature and evaporation. We found similar responses of ecosystem and tree-level functions to both girdling and natural mortality. This suggests that girdling is an appropriate approach to explore the impact of tree mortality on ecosystem structure, function, and energy balance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Is There Ecological Information in Optical Polarization Data?

Optical linear polarization? In remote sensing it's due to specular reflection. The first surface that incident light encounters - a smooth water surface or the waxy first surface of a leaf's cuticle, if it's even somewhat smooth (i.e. shiny) - will specularly reflect and linearly polarize the incident light. We provide three examples of the types of ecological information contained in remotely sensed optical linear polarization measurements. Remove the surface reflection to better see the interior. The linearly polarized light reflected by leaf surfaces contains no information about cellular pigments, metabolites, or water contained in the leaf interiors of a plant canopy, because it never enters the leaf interior to interact with them. Thus, for purposes of remotely sensing the leaf interiors of a plant canopy, the linearly polarized light should be subtracted from the total reflected light, because including it would add noise to the measurement. In particular 'minus specular' vegetation indices should allow improved monitoring of a plant canopy's physiological processes. Estimate plant development stage and yield. Wheat and sorghum grain heads, following emergence, rapidly extend upward and very quickly tower over nearby leaves, partially blocking our view of the sunlight reflected by those leaf surfaces. The resulting decrease in the amount of surface reflected and polarized sunlight, if monitored over time, potentially allows per-field estimates of the dates of the heading and flowering development stages to be interleaved with weather data in models, which is key to better estimating per-field grain yield. Similar polarization changes may occur in other grasses, such as oats, barley, corn and rice, each a crop so widely grown that it potentially affects climate at the regional scale. Wetlands Mapping. The sunlight specularly reflected by surface waters is blindingly bright, spectrally flat and polarized - all of which telegraphs that the ground area is inundated. Inundated soils exchange methane with the atmosphere; non-inundated soils, carbon dioxide. Aquatic plants growing through the water surface pipe the soil-produced methane via the stomata to the atmosphere, enhancing exchanges rates by factors of 10-20 compared to ebullition (bubbling) or diffusion through the water column to the atmosphere. Thus, mapping wetland areas into three community types - inundated areas with emergent vegetation, open water and uplands - provides potentially key information to water, carbon and energy budgets at landscape to global scales.

Water↗
DOE OSTI2025

Normalized Solar-Induced Fluorescence Responds Earlier Than Vegetation Indices to the 2019 North China Plain Drought

Recently, solar-induced chlorophyll fluorescence (SIF) from satellites has shown potential for evaluating vegetation status and stress responses. Fluorescence quantum yield ($Φ_F$) is essentially linked to vegetation stress. However, the complex physiological and structural responses of SIF and $Φ_F$ to drought need further study. This study normalized SIF as SIFn to account for angular variations and fluctuations in photosynthetically active radiation (PAR), aiming for more accurate drought monitoring. SIFn anomalies were compared to historical baselines (2019–2021 averages) of vegetation indices (VIs), raw SIF, and $Φ_F$ during a 2019 drought in the North China Plain (NCP). Here, the results show SIFn provides an effective method for drought monitoring, showing the earliest decline compared to raw SIF, VIs, and $Φ_F$. In the first two weeks of drought, SIFn decreased by 8.2%, 7.0%, 12.5%, and 8.2% across the four NCP subdivisions. SIFn outperformed other indicators, proving sensitive to early drought detection. SIFn was also examined for tracking drought alleviation by rainfall. The uncertainty under different viewing geometries was quantified. SIFn anomalies showed a strong correlation with rainfall anomalies (R: 0.45 ~ 0.52) and meteorological factors like PAR (R: 0.80 ~ 0.84) and relative humidity (R:0.52 ~ 0.54). The correlation of near-infrared reflectance (NIRv) and $Φ_F$ anomalies with SIF was weak during drought onset (R: 0.16 ~ 0.32) but strong at the end (R: 0.83 ~ 0.87). These suggest both canopy structure (mainly characterized by NIRv) and vegetation chlorophyll ($Φ_F$) are impacted by drought and influence SIF at different stages.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

BOREAS TE-5 Diurnal CO2 Canopy Profile Data

The BOREAS TE-5 team collected several data sets to investigate the vegetation-atmosphere CO2 and H2O exchange processes. These data were collected to provide detailed information within the canopy during times when TE-05 sampled canopy CO2 for carbon and oxygen isotope analysis. These measurements were made in both the NSA and SSA at the OJP, OBS, UBS, and OA sites from 25-May1994 to 08-Sep1994. CO2 profile data were not collected at SSA-OA during the first IFC. The data are available 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).

Hall, Forrest G.↗
NASA NTRS1999

Simple Forest Canopy Thermal Exitance Model

We describe a model to calculate brightness temperature and surface energy balance for a forest canopy system. The model is an extension of an earlier vegetation only model by inclusion of a simple soil layer. The root mean square error in brightness temperature for a dense forest canopy was 2.5 C. Surface energy balance predictions were also in good agreement. The corresponding root mean square errors for net radiation, latent, and sensible heat were 38.9, 30.7, and 41.4 W/sq m respectively.

Smith J. A.↗
NASA NTRS1992

Remote sensing of solar radiation absorbed and reflected by vegetated land surfaces

1D and 3D radiative-transfer models have been used to investigate the problem of remotely sensed determination of vegetated land surface-absorbed and reflected solar radiation. Calculations were conducted for various illumination conditions to determine surface albedo, soil- and canopy-absorbed photosynthetically active and nonactive radiation, and normalized difference vegetation index. Simple predictive models are developed on the basis of the relationships among these parameters.

Myneni, Ranga B.↗
NASA NTRS1978

Some observations about LANDSAT digital analysis

Several hypotheses concerning LANDSAT data are analyzed. These hypotheses are: (1) LANDSAT does not discriminate vegetation types, but mostly sees chlorophyl and canopy cover. (2) A majority of the features in the ground scene possess linearly proportional amounts of color from each spectral band. (3) The data are continuous and as a result there is no true separability of ground scene features in the data, but some features possess an excess of color in a particular band pair. (4) There are relatively few features present in the spectral data, and these do not correspond to the conventional definitions that are used. (5) Aside from seasonal effects, in a distributional sense all LANDSAT data are essentially the same. The only difference is the way the data are spatially arranged in the image.

Jayroe, R. R., Jr.↗
NASA NTRS1980

Multispectral Resource Sampler (MRS): Proof of concept. Study on bidirectional reflectance. A simulation analysis of bidirectional reflectance properties and their effects on scene radiance. Implications for the MRS

A study was performed to evaluate the geometrical implication of a Multispectral Resource Sampler; a pointable sensor. Several vegetative targets representative of natural and agricultural canopies were considered in two wavelength bands. All combinations of Sun and view angles between 5 and 85 degrees zenith for a range of azimuths were simulated to examine geometrical dependance arising from seasonal as well as latitudinal variation. The effects of three different atmospheres corresponding to clear, medium and heavy haze conditions are included. An extensive model data base was generated to provide investigators with means for possible further study of atmospheric correction procedures and sensor design questions.

Smith, J. A.↗
NASA NTRS1984

Biogeochemical cycling and remote sensing

The present investigation is concerned with the role of remote sensing in the analysis of biochemical cycling. A general review is provided of the interest of NASA in biochemical cycling, taking into account an assessment of the state and dynamics of the pools and fluxes of four major elements (carbon, nitrogen, phosphorus, sulfur), an understanding of the coupling and interaction of the biosphere and the atmosphere, and an understanding of the biosphere and the oceans. Attention is given to biogeochemical cycling science issues, the potential remote sensing role, the vegetation type, aspects of vegetation structure, the leaf area index, the canopy height, functional relationships, environmental and soil variables, questions of experimental design, sampling sites and ground data, and radiometric data and analysis.

Peterson, D. L.↗