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At least 325 records · Page 18

Enhanced crop discrimination using the mid-IR (1.55-1.75 microns)

Improvements in crop discrimination can be realized by using mid-IR bands (1.55 -1.75 and 2.08 -2.35 microns) which are sensitive to canopy moisture content. Analyses of data from two growing seasons in Webster County, Iowa clearly indicate that corn and soybeans are highly separable in the mid-IR from early season through harvest. This contrasts sharply with visible and near-IR bands where corn and soybeans are confused throughout much of the growing season. The mid-IR temporal reflectance behavior appears to result from differences between C4 monocot and C3 dicot internal leaf structure. If this hypothesis holds, mid-IR observations should improve discrimination in other instances where similar differences in internal leaf structure are present.

Ungar, S. G.↗

Radar and Lidar Radar DEM

Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

remote sensing↗

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S R Neigh↗

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S. R. Neigh↗

Space Station Freedom cupola definition

Following the realization that adequate Space Station Freedom viewing could not be achieved without breaking the plane of the modules, a conceptual design phase for the development of a cupola progressed from the idea of a small, bubble-type canopy to a much larger, two crewmember cupola. The evolving cupola conceptual designs were each evaluated against the requirements for providing a large field-of-view, a complete proximity control workstation with flexible and relocatable restraints, and sufficient volume for two, 95th percentile crewmembers to operate while still maintaining reasonable weight and size restrictions. As the SS Freedom program Preliminary Design Review draws closer, the cupola development phase shifts toward evaluation of viewing and operational capability. The appropriate balance of viewing, structures and operations must be achieved before the program can place confidence in a cupola design providing SS Freedom with a direct viewing workstation capable of supporting the great variety of tasks projected for the life of the station.

Weaver, Laurie A.↗

Observations of lightning in convective supercells within tropical storms and hurricanes

Cloud-to-ground (CG) lightning observations from land-based lightning detection networks now allow monitoring this component of the electrical structure of tropical storms and hurricanes within a few hundred kilometers of the United States coastline. Several case studies confirm the long-held opinion that lightning is rather common within the outer rainbands. The general absence of CG lightning within the interior of mature tropical cyclones is also apparent. On the other hand, bursts of CG lightning near the circulation center of developing storms appear to precede periods of further deepening. The CG events are associated with convective supercells, whose anvil canopies can often obscure much of the underlying storm. Near-eyewall CG bursts preceding periods of intensification were noted in Hurricanes Diana (1984) and Florence (1988). A detailed case study of the 1987 unnamed tropical storm that struck the Texas-Louisiana coastline reveals that lightning was associated with two large supercells. These supercells appeared to be the trigger for the development of a closed circulation that formed several hours after the apparent low pressure center made landfall. Further studies of lightning may provide additional insight into the role of convective supercells in tropical storm intensification. It may also provide a useful diagnostic of impending deepening.

Lyons, Walter A.↗

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

Research into parachute performance continues to be a source of significant investment from the National Aeronautics and Space Administration to mitigate risks and to enable a variety of exploration missions, including landing on Mars as well as returning to Earth. The cost of flight tests to certify any changes to the current state-of-the-art parachute designs limits the development of next generation parachute systems. Fluid-structure interaction simulations could help accelerate this process once validated. The Launch, Ascent, and Vehicle Aerodynamics team is developing the capability to perform such fluid-structure interaction simulations by coupling a higher-order Cartesian immersed boundary computational fluid dynamics solver with adaptive mesh refinement to a finite element structural dynamics solver in space and time. We continue the effort to validate this tool with the Advanced Supersonic Parachute Inflation Research Experiments SR03 flight test featuring a strengthened parachute akin to the Mars 2020 mission that landed the Perseverance rover on Mars, and a higher freestream dynamic pressure prior to inflation. The effect of the flow conditions’ angle of attack and of the initial parachute shape are quantified. The impact of relaxing modeling assumptions with regards to radial stiffeners on the parachute canopy is also investigated. Results demonstrate improvements in agreement with the pull force recorded during the SR03 flight test as the initial conditions of the flow and parachute are brought closer to those experienced in flight, and further improved when the radial stiffener modeling assumptions are relaxed.

ESM↗

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

Research into parachute performance continues to be a source of significant investment from the National Aeronautics and Space Administration to mitigate risks and to enable a variety of exploration missions, including landing on Mars as well as returning to Earth. The cost of flight tests to certify any changes to the current state-of-the-art parachute designs limits the development of next generation parachute systems. Fluid-structure interaction simulations could help accelerate this process once validated. The Launch, Ascent, and Vehicle Aerodynamics team is developing the capability to perform such fluid-structure interaction simulations by coupling a higher-order Cartesian immersed boundary computational fluid dynamics solver with adaptive mesh refinement to a finite element structural dynamics solver in space and time. We continue the effort to validate this tool with the Advanced Supersonic Parachute Inflation Research Experiments SR03 flight test featuring a strengthened parachute akin to the Mars 2020 mission that landed the Perseverance rover on Mars, and a higher freestream dynamic pressure prior to inflation. The effect of the flow conditions’ angle of attack and of the initial parachute shape are quantified. The impact of relaxing modeling assumptions with regards to radial stiffeners on the parachute canopy is also investigated. Results demonstrate improvements in agreement with the pull force recorded during the SR03 flight test as the initial conditions of the flow and parachute are brought closer to those experienced in flight, and further improved when the radial stiffener modeling assumptions are relaxed.

ESM↗

Determining successional stage of temperate coniferous forests with Landsat satellite data

Thematic Mapper (TM) digital imagery was used to map forest successional stages and to evaluate spectral differences between old-growth and mature forests in the central Cascade Range of Oregon. Relative sun incidence values were incorporated into the successional stage classification to compensate for topographic induced variation. Relative sun incidence improved the classification accuracy of young successional stages, but did not improve the classification accuracy of older, closed canopy forest classes or overall accuracy. TM bands 1, 2, and 4; the normalized difference vegetation index (NDVI); and TM 4/3, 4/5, and 4/7 band ratio values for old-growth forests were found to be significantly lower than the values of mature forests (P less than or equal to 0.010). Wetness and the TM 4/5 and 4/7 band ratios all had low correlations to relative sun incidence (r(exp 2) less than or equal to 0.16). The TM 4/5 band ratio was named the 'structural index' (SI) because of its ability to distinguish between mature and old-growth forests and its simplicity.

Fiorella, Maria↗

Structure of the St. Francois Mountains and surrounding lead belt, S. E. Missouri: Inferences from thermal IR and other data sets

Day-IR, day-visible, and night-IR image data sets were analyzed. All three images were contrast enhanced, using a linear stretch. The night-IR image was destriped using a box-car filtering approach. Apparent thermal inertia images were generated from the data. The enhanced data and the apparent thermal inertia image were also registered and overlayed onto shaded relief images depicting topography and onto a colored version of the Missouri geologic map. The combination of the apparent thermal inertial image and the shaded relief map proved to have the greatest discriminability in terms of portraying linear features. The reason seems to be that the vegetation canopy on the Ozark Plateau is different topography, tend to emphasize subtle topographic effects.

Arvidson, R. E.↗

Low Density Supersonic Decelerator Parachute Decelerator System

The Low Density Supersonic Decelerator Project has undertaken the task of developing and testing a large supersonic ringsail parachute. The parachute under development is intended to provide mission planners more options for parachutes larger than the Mars Science Laboratory's 21.5m parachute. During its development, this new parachute will be taken through a series of tests in order to bring the parachute to a TRL-6 readiness level and make the technology available for future Mars missions. This effort is primarily focused on two tests, a subsonic structural verification test done at sea level atmospheric conditions and a supersonic flight behind a blunt body in low-density atmospheric conditions. The preferred method of deploying a parachute behind a decelerating blunt body robotic spacecraft in a supersonic flow-field is via mortar deployment. Due to the configuration constraints in the design of the test vehicle used in the supersonic testing it is not possible to perform a mortar deployment. As a result of this limitation an alternative deployment process using a ballute as a pilot is being developed. The intent in this alternate approach is to preserve the requisite features of a mortar deployment during canopy extraction in a supersonic flow. Doing so will allow future Mars missions to either choose to mortar deploy or pilot deploy the parachute that is being developed.

Low Density Supersonic Decelerator (LDSD)↗

Water cycles in closed ecological systems: effects of atmospheric pressure

In bioregenerative life support systems that use plants to generate food and oxygen, the largest mass flux between the plants and their surrounding environment will be water. This water cycle is a consequence of the continuous change of state (evaporation-condensation) from liquid to gas through the process of transpiration and the need to transfer heat (cool) and dehumidify the plant growth chamber. Evapotranspiration rates for full plant canopies can range from ~1 to 10 L m-2 d-1 (~1 to 10 mm m-2 d-1), with the rates depending primarily on the vapor pressure deficit (VPD) between the leaves and the air inside the plant growth chamber. VPD in turn is dependent on the air temperature, leaf temperature, and current value of relative humidity (RH). Concepts for developing closed plant growth systems, such as greenhouses for Mars, have been discussed for many years and the feasibility of such systems will depend on the overall system costs and reliability. One approach for reducing system costs would be to reduce the operating pressure within the greenhouse to reduce structural mass and gas leakage. But managing plant growth environments at low pressures (e.g., controlling humidity and heat exchange) may be difficult, and the effects of low-pressure environments on plant growth and system water cycling need further study. We present experimental evidence to show that water saturation pressures in air under isothermal conditions are only slightly affected by total pressure, but the overall water flux from evaporating surfaces can increase as pressure decreases. Mathematical models describing these observations are presented, along with discussion of the importance for considering "water cycles" in closed bioregenerative life support systems.

NASA Center KSC↗

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗

Canopy reflectance modelling of semiarid vegetation

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Franklin, Janet↗

CO and the Temperature Structure of the Solar Atmosphere

The surface layers of the Sun provide a crucial boundary condition for many of the processes that occur in the deep interior. The stratification of the outer solar atmosphere once was thought to be well understood. However, studies of thermally sensitive molecular absorptions in the infrared revealed puzzling anomalies. Strong lines of the CO fundamental vibration-rotation bands near 5 microns showed very cool temperatures at the extreme limb, and remarkable off-limb emissions extending well into the supposedly hot chromosphere. The conflicting pictures of the photosphere/chromosphere interface, from the widely separated wavelength regimes, has raised suspicions that those "layers" of the atmosphere are much more inhomogeneous than previously suspected. One proposal is that the low chromosphere is dominated by cool gas--the "COmosphere," if you will--which is threaded by a network of persistent small-scale hot magnetic filaments and occasionally disrupted by localized acoustic disturbances. The COmosphere is capped by the merged fields of the network elements in the chromospheric "canopy." I will describe the evidence in favor of that model, including recent work at the NSO McMath-Pierce telescope (including use of the new "Phoenix" spectrometer) and translimb far-UV spectroscopy by SOHO/SUMER.

Ayres, Thomas R.↗

Mapping invasive alien species in grassland ecosystems using airborne imaging spectroscopy and remotely observable vegetation functional traits

Lespedeza cuneata (sericea lespedeza; hereafter “sericea”) is an invasive species brought to the U.S. from East Asia in the 1890s to be used as forage. However, it has now become a growing ecological and economic threat in grasslands of several states in the U.S. southern Great Plains including Oklahoma, Kansas, Missouri, and Nebraska. Here, we demonstrate the capability of airborne imaging spectroscopy to map sericea in a large natural grassland within the Tallgrass Prairie Preserve, the largest protected tallgrass prairie in the world, located in northeastern Oklahoma. Through this research, we investigated which remotely observable vegetation functional traits (referring to biochemical, physiological, and structural traits) contribute to distinguishing sericea from cooccurring native species and whether we can detect sericea remotely through quantifying these functional traits using imaging spectroscopic data (also known as hyperspectral data). To achieve these objectives, full-range airborne hyperspectral data with spatial resolution of 1 m were collected from the study area in August 2020. In addition, a total of 12 vegetation functional traits were measured through field sampling for model development. We first identified functional traits that contributed to separating sericea from other species, and then used them in a classification model to detect sericea in our study site. We found total carotenoids (sum of neoxanthin, violaxanthin, antheraxanthin, zeaxanthin, and lutein), chlorophyll a + b (sum of chlorophyll a and chlorophyll b), total nitrogen, canopy height, potassium, and magnesium as the main functional traits contributing to the detection of sericea; an overall classification accuracy of approximately 94% was reported. However, the proposed approach overestimated sericea cover in species-rich plant communities. Overall, our findings demonstrated an essential role for airborne remote sensing in 1) direct mapping of invasive plants and 2) quantifying functional traits associated with success strategies of invasive species. Eventually, experiments like ours can aid in developing large-scale and science-driven management practices to both identify the current extent, and to control the spread of invasive species in grasslands and similar short-stature environments. This will not only improve management practices but will have major societal and economic benefits.

Hamed Gholizadeh↗

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.

Brazilian Amazon↗

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗