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Results for “vegetation response”

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

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

Xue, Yongkang↗
NASA NTRS2017

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feed backs of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of above ground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to year variation in plant growth.

Zhang, Zhen↗
NASA NTRS1979

Multisensor analysis of hydrologic features in the Wind River Range, Wyoming with emphasis on the SEASAT SAR

The author has identified the following significant results. Analysis of imagery obtained over west-central Wyoming indicates that Seasat SAR has capability for hydrologic mapping. Both the L-Band (Seasat) and the X-Band (aircraft) SAR imagery were useful for observing drainage detail. Streams have bright signatures on the SAR imagery because the riparian vegetation produces a rough surface and thus high radar returns. Lakes appear relatively bright on the Seasat image presumably in response to surface ripples and waves induced by wind action. SAR imagery did not reveal snow at either the 23.5 cm (L-Band) or 2.8 cm (X-Band) wavelengths. Comparing Seasat and X-Band aircraft SAR imagery to LANDSAT RBV imagery, U-2 photography, and topographic maps of the Wind River Range, it appears that the SAR data do not seem to provide as much hydrologic information as do the other sensors in the visible and near infrared portions of the spectrum.

Foster, J. L.↗
NASA NTRS1986

Department of Geology/NASA-GSFC geobotanical investigation

Geobotanical mapping in the southern Appalachians and soil metal associated changes in vegatation spectral responses in the reflective and emissive portions of the electromagnetic spectrum (EMS) is studied. It is determined whether deciduous forest vegetation reflection and emission characteristics show detectable changes that can be related to residual soil characteristics. Analyses of such related characteristics enhances the ability to discriminate underlying lithologies as well as variances within lithologies associated with natural heavy metal occurences. An understanding is developed of the factors which contribute to the differing spectral signatures of various lithology/soil types. A combination of field data and remote spectral analysis is studied.

Source record↗
NASA NTRS2004

Rice: Characterizing the Environmental Response of a Gibberellic Acid-Deficient Rice for Use as a Model Crop

Rice (Oryza sativa L.) is a useful model crop plant. Rice was the first crop plant to have its complete genome sequenced. Unfortunately, even semi-dwarf rice cultivars are 60 to 90 an tail, and large plant populations cannot be grown in the confined volumes of greenhouses and growth chambers. We recently identified an extremely short (20 em tall) rice line, which is an ideal model for larger rice cultivars. We called this line "Super Dwarf rice." Here we report the response of Super Dwarf to temperature, photoperiod, photosynthetic photon flux (PPF), and factors that can affect time to head emergence. Vegetative biomass increased 6% per degree Celsius, with increasing temperature from 27 to 31 C. Seed yield decreased by 2% per degree Celsius rise in temperature, and as a result, harvest index decreased from 60 to 54%. The time to heading increased by 2 d for every hour above a 12-h photoperiod. Yield increased with increasing PPF up to the highest level tested at 1800 micro-mol/sq m/s (12-h photoperiod; 77.8 mol/sq m/d). Yield efficiency (grams per mole of photons) increased to 900 micro-mol/sq m/s and then slightly decreased at 1800 micro-mol/sq m/s . Heading was delayed by addition of gibberellic acid 3 (GA,) to the root zone but was hastened under mild N stress. Overall, short stature, high yield, high harvest index, and no extraordinary environmental requirements make Super Dwarf rice an excellent model plant for yield studies in controlled environments.

Frantz, Jonathan M.↗
NASA NTRS2017

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.

SERVIR↗
NASA NTRS1983

Directional radiometric measurements of row-crop temperatures

The variability of directional sensor response for a cotton row crop in Phoenix, Arizona was measured for various solar zenith angles. The geometric structure of the canopy was described with regard to height, width, spacing, and shape of rows. In addition, radiometric temperature data were collected on four scene components: sunlit and shaded vegetation and sunlit and shaded soil. These data were used to test the predictions and assumptions of a modified version of the row crop model of Jackson et al. (1979), which predicts the thermal infrared response of a sensor as a function of sensor view angle, component temperature, and geometrical structure of the canopy. The field data showed sensor response differentials as great as 16.2 C when going from a zenith view angle of 0 deg to one of 80 deg normal to the row direction. The rms deviation between the predicted and measured sensor response for all measurement periods and view angles was 0.96 C.

Kimes, D. S.↗
NASA NTRSDate not supplied

The NASA Disasters Response Coordination System’s (DRCS) Response to the 2024 Hurricane Season

The National Aeronautics and Space Administration (NASA) Disasters Response Coordination System (DRCS) leverages the best available science and expertise to aid federal, state, local, and non-governmental organization (NGO) partners in addressing identified needs during a disaster response. During the 2024 hurricane season, the DRCS activated for seven hurricanes/tropical storms, providing openly available geospatial data through NASA’s Disasters Mapping Portal. Hurricanes Helene and Milton were major hurricanes that impacted the southeastern United States within weeks of one another. Impacts from Helene and Milton to the region included inland flooding, record coastal storm surge, over a thousand landslides, and regional power and telecommunications outages. In response to Helene and Milton, DRCS provided actionable information and products to stakeholders, including Synthetic Aperture Radar (SAR) analysis for landslide and flood detection, Black Marble nighttime lights products for assessing power outages, and Normalized Difference Vegetation Index (NDVI) analysis for post-event vegetation change detection. NASA deployed an Uninhibited Aerial Vehicle SAR (UAVSAR) instrument to collect data on flood extent, providing crucial information on affected communities. Additionally, astronauts aboard the International Space Station (ISS) collected hand-held photography along the paths of Hurricane Helene and Milton to aid in response efforts. Here, we summarize the DRCS responses to Helene and Milton, in particular highlighting the information and products that were provided by the DRCS and how they were utilized by partners to address immediate response needs.

Earth observations↗
NASA NTRS1978

Analytical techniques for the study of some parameters of multispectral scanner systems for remote sensing

The author has identified the following significant results. The concept of average mutual information in the received spectral random process about the spectral scene was developed. Techniques amenable to implementation on a digital computer were also developed to make the required average mutual information calculations. These techniques required identification of models for the spectral response process of scenes. Stochastic modeling techniques were adapted for use. These techniques were demonstrated on empirical data from wheat and vegetation scenes.

Wiswell, E. R.↗
NASA NTRS1987

Analysis of forest and forest clearings in Amazonia with Landsat and Shuttle Imaging Radar-A data

Landsat and Shuttle Imaging Radar-A L band (23.5 cm wavelength) data from 1981 were used to analyze areas of intact tropical forest and areas recently cleared from forest for agriculture and pasture in Mato Grosso, Brazil. Portions of SIR-A Data Takes #24C and #31 film were digitized using a microdensitometer. Landsat MSS data of July 1981 were also examined. The digital values from SIR-A DT 31 were compared with the normalized difference vegetation index values (NDVI) from the Landsat data for the same sites. Contrary to expectations some cleared areas had brighter radar responses than surrounding forest. The explanation seems to be that a recently cleared forest (cut and burned during the dry season) is texturally very rough as the exposed standing and fallen boles and woody litter may function as effective corner or dihedral reflectors. Combining radar data with NDVI data may help to assess the relative age of forest clearings and determine differences in both woody and green leaf biomass of primary and secondary tropical forests.

Stone, Thomas A.↗
NASA NTRS1992

Effects of management and topography on the radiometric response of a tallgrass prairie

Bidirectional reflectance measurements are obtained for grazed, burned ungrazed, and unburned ungrazed tallgrass prairie in eastern Kansas. Observations are also made on experimental plots where vegetation height and biomass were manipulated by mowing. While productivity of grazed or mowed sites was either equal to or greater than that on ungrazed or unmowed sites, individual or cumulative normalized difference vegetation index values tended to be positively correlated with biomass, not productivity.

Turner, C. L.↗
NASA NTRS1993

Predicting LANDSAT MSS endmember signatures from corresponding higher resolution TM fraction images

The approach to predicting Landsat Multispectral Scanner System (MSS) endmember signatures from fraction images derived from high resolution Landsat Thematic Mapper (TM) data is presented. The purpose, conducted in the Mogi-Guacu study site located in Sao Paulo State, Brazil, was to determine if information derived from a mixture model applied to higher resolution TM data could serve as ground truth for the lower resolution MSS sensor. The Constrained Least Squares (CLS) method was used to generate vegetation, soil, and shade fraction images from the TM data. The resulting images were then used to estimate the endmember spectral response for MSS data by regressing each MSS spectral channel against the corresponding proportion values estimated for the same resolution cells from the TM mixture model. The evaluation of the predicted signatures was performed by comparing the corresponding fraction images derived from both the MSS and TM data acquired on 14 Sep. 1986. The techniques serves as a potential tool for integrating information in global studies where remote sensors with different spectral and spatial resolutions were used.

Shimabukuro, Yosio E.↗
NASA NTRS1994

Remote sensing for hurricane Andrew impact assessment

Stennis Space Center personnel flew a Learjet equipped with instrumentation designed to acquire imagery in many spectral bands into areas most damaged by Hurricane Andrew. The calibrated airborne multispectral scanner (CAMS), a NASA-developed sensor, and a Zeiss camera acquired images of these areas. The information derived from the imagery was used to assist Florida officials in assessing the devastation caused by the hurricane. The imagery provided the relief teams with an assessment of the debris covering roads and highways so cleanup plans could be prioritized. The imagery also mapped the level of damage in residential and commercial areas of southern Florida and provided maps of beaches and land cover for determination of beach loss and vegetation damage, particularly the mangrove population. Stennis Space Center personnel demonstrated the ability to respond quickly and the value of such response in an emergency situation. The digital imagery from the CAMS can be processed, analyzed, and developed into products for field crews faster than conventional photography. The resulting information is versatile and allows for rapid updating and editing. Stennis Space Center and state officials worked diligently to compile information to complete analyses of the hurricane's impact.

Davis, Bruce A.↗
NASA NTRS2020

Widespread Mangrove Damage Resulting from the 2017 Atlantic Mega Hurricane Season

Comprised of 17 named tropical storms, 6 of which were major hurricanes, the 2017 Atlantic hurricane season ranked as one of the most damaging and costly hurricane seasons on record. In addition to socio-economic impacts, many previous studies have shown that important coastal ecosystems like mangroves are shaped by severe storms. However, little is known about how the cumulative effects of storms over entire hurricane seasons affect mangroves across large regions. We used satellite imagery from the entire Caribbean and Gulf of Mexico region to show that 2017 resulted in disproportionate mangrove damage compared to baseline responses over the previous 8 years. Specifically, we observed 30 times more mangrove damage, via a reduction in the normalized difference vegetation index (NDVI), during 2017 compared to any of the eight previous hurricane seasons, and most (72%) of this damage persisted throughout the 7 month post-hurricane season period as indicated by no NDVI recovery. Furthermore, wind speed, rainfall, and canopy height data showed that mangrove damage primarily resulted from high maximum wind speeds, but flooding (cumulative rainfall), previous storm history, and mangrove structure (canopy height) were also important predictors of damage. While mangroves are known to be resilient to hurricane impacts, our results suggest that increasingly frequent mega-hurricane seasons in the Caribbean region will dramatically alter mangrove disturbance dynamics.

Temilola Elisabeth Fatoyinbo Agueh↗
NASA NTRS2021

Modeling Snow Ablation over the Western United States Mountains: Patterns and Controlling Factors

When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.

Snow↗
NASA NTRS1991

Transient water stress in a vegetation canopy - Simulations and measurements

Consideration is given to observational and modeling evidence of transient water stress, the effects of the transpiration plateau on the canopy radiometric temperature, and the factors responsible for the onset of the transpiration plateau, such as soil moisture. Attention is also given to the point at which the transient stress can be detected by remote measurement of surface temperature.

Carlson, Toby N.↗
NASA NTRS1988

An approach for detecting post-launch spectral changes in satellite multispectral sensors

An approach for testing whether or not post-launch changes have occurred in sensor spectral responses is described. The approach uses field measurements of ground targets having differing spectral reflectance properties as well as calculations based on the original spectral response characteristics. As an example, a shift in band location was modeled and evaluated through the simulation of signals from soil and vegetation targets in the spectral bands of five satellite systems.

Suits, G. H.↗
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗