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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Extraction of Airport Features from High Resolution Satellite Imagery for Design and Risk Assessment

The LPA Group, consisting of 17 offices located throughout the eastern and central United States is an architectural, engineering and planning firm specializing in the development of Airports, Roads and Bridges. The primary focus of this ARC project is concerned with assisting their aviation specialists who work in the areas of Airport Planning, Airfield Design, Landside Design, Terminal Building Planning and design, and various other construction services. The LPA Group wanted to test the utility of high-resolution commercial satellite imagery for the purpose of extracting airport elevation features in the glide path areas surrounding the Columbia Metropolitan Airport. By incorporating remote sensing techniques into their airport planning process, LPA wanted to investigate whether or not it is possible to save time and money while achieving the equivalent accuracy as traditional planning methods. The Affiliate Research Center (ARC) at the University of South Carolina investigated the use of remotely sensed imagery for the extraction of feature elevations in the glide path zone. A stereo pair of IKONOS panchromatic satellite images, which has a spatial resolution of 1 x 1 m, was used to determine elevations of aviation obstructions such as buildings, trees, towers and fence-lines. A validation dataset was provided by the LPA Group to assess the accuracy of the measurements derived from the IKONOS imagery. The initial goal of this project was to test the utility of IKONOS imagery in feature extraction using ERDAS Stereo Analyst. This goal was never achieved due to problems with ERDAS software support of the IKONOS sensor model and the unavailability of imperative sensor model information from Space Imaging. The obstacles encountered in this project pertaining to ERDAS Stereo Analyst and IKONOS imagery will be reviewed in more detail later in this report. As a result of the technical difficulties with Stereo Analyst, ERDAS OrthoBASE was used to derive aviation obstruction measurements for this project. After collecting ancillary data such as GPS locations, South Carolina Geodetic Survey and Aero Dynamics ground survey points to set up the OrthoBASE Block File, measurements were taken of the various glide path obstructions and compared to the validation dataset. This process yielded the following conclusions: The IKONOS stereo model in conjunction with Imagine OrthoBASE can provide The LPA Group with a fast and cost efficient method for assessing aviation obstructions. Also, by creating our own stereo model we achieved any accuracy better currently available commercial products.

Robinson, Chris↗
NASA NTRS2013

Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX)

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0deg (nadir) to 70deg off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR's operational stereo product uses this capability to retrieve cloud heights and winds for every satellite orbit, yielding global coverage every nine days. The MISR INteractive eXplorer (MINX) visualization and analysis tool complements the operational stereo product by providing users the ability to retrieve heights and winds locally for detailed studies of smoke, dust and volcanic ash plumes, as well as clouds, at higher spatial resolution and with greater precision than is possible with the operational product or with other space-based, passive, remote sensing instruments. This ability to investigate plume geometry and dynamics is becoming increasingly important as climate and air quality studies require greater knowledge about the injection of aerosols and the location of clouds within the atmosphere. MINX incorporates features that allow users to customize their stereo retrievals for optimum results under varying aerosol and underlying surface conditions. This paper discusses the stereo retrieval algorithms and retrieval options in MINX, and provides appropriate examples to explain how the program can be used to achieve the best results.

MISR↗
NASA NTRS2001

Internal Consistency of the NVAP Water Vapor Dataset

The NVAP (NASA Water Vapor Project) dataset is a global dataset at 1 x 1 degree spatial resolution consisting of daily, pentad, and monthly atmospheric precipitable water (PW) products. The analysis blends measurements from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS), the Special Sensor Microwave/Imager (SSM/I), and radiosonde observations into a daily collage of PW. The original dataset consisted of five years of data from 1988 to 1992. Recent updates have added three additional years (1993-1995) and incorporated procedural and algorithm changes from the original methodology. Since each of the PW sources (TOVS, SSM/I, and radiosonde) do not provide global coverage, each of these sources compliment one another by providing spatial coverage over regions and during times where the other is not available. For this type of spatial and temporal blending to be successful, each of the source components should have similar or compatible accuracies. If this is not the case, regional and time varying biases may be manifested in the NVAP dataset. This study examines the consistency of the NVAP source data by comparing daily collocated TOVS and SSM/I PW retrievals with collocated radiosonde PW observations. The daily PW intercomparisons are performed over the time period of the dataset and for various regions.

Suggs, Ronnie J.↗
NASA NTRS1991

Case Studies of Water Vapor and Surface Liquid Water from AVIRIS Data Measured Over Denver, CO and Death Valley, CA

High spatial resolution column atmospheric water vapor amounts and equivalent liquid water thicknesses of surface targets are retrieved from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The retrievals are made using a nonlinear least squares curve fitting technique. Two case studies from AVIRIS data acquired over Denver-Platteville area, Colorado and over Death Valley, California are presented. The column water vapor values derived from AVIRIS data over the Denver-Platteville area are compared with those obtained from radiosondes, ground level upward-looking microwave radiometers, and geostationary satellite measurements. The column water vapor image shows spatial variation patterns related to the passage of a weather front system. The column water vapor amounts derived from AVIRIS data over Death Valley decrease with increasing surface elevation. The derived liquid water image clearly shows surface drainage patterns.

Gao, B.-C.↗
NASA NTRS2010

Spectroscopic Observation of the Stardust Re-Entry in the Near UV with SLIT: Deduction of Surface Temperatures and Plasma Radiation

Thermal radiation of the heat-shield and the emission of the post-shock layer around the Stardust capsule, during its re-entry, were detected by a NASA-led observation campaign aboard NASA's DC-8 airborne observatory involving teams from several nations. The German SLIT experiment used a conventional spectrometer, in a Czerny-Turner configuration (300 mm focal length and a 600 lines/mm grating), fed by fiber optics, to cover a wavelength range from 324 nm to 456 nm with a pixel resolution of 0.08 nm. The reentering spacecraft was tracked m uansuinaglly a camera with a view angle of 20 degrees, and light from the capsule was collected using a small mirror telescope with a view angle of only 0.45 degrees. Data were gathered with a measurement frequency of 5 Hz in a 30-second time interval around the point of maximum heating until the capsule left the field of view. The emission of CN (as a major ablation product), N2(+) and different atoms were monitored successfully during that time. Due to the nature of the experimental set up, spatial resolution of the radiation field was not possible. Therefore, all measured values represent an integration of radiation from the visible part of the glowing heat shield, and from the plasma in the post-shock region. Further, due to challenges in tracking not every spectrum gathered contained data. The measured spectra can be split up into two parts: (i) continuum spectra which represent a superposition of the heat shield radiation and the continuum radiation of potential dust particles in the plasma, and (ii) line spectra from the plasma in the shock layer. Planck temperatures (interpreted as the surface temperatures of the Stardust heat shield) were determined assuming either a constant surface temperature, or a temperature distribution deduced from numerical simulation. The constant surface temperatures are in good agreement with numerical simulations, but the peak values at the stagnation point are significantly lower than those in the numerical simulation if a temperature distribution over the surface is assumed. Emission bands of CN and N2(+) were tracked along the visible trajectory and compared to a spectral simulation with satisfying agreement. Values for the integrated radiation of the transitions of interest for these species were extracted from this comparison.

Winter, Michael W.↗
NASA NTRS2011

Global Night-Time Lights for Observing Human Activity

We present a concept for a small satellite mission to make systematic, global observations of night-time lights with spatial resolution suitable for discerning the extent, type and density of human settlements. The observations will also allow better understanding of fine scale fossil fuel CO2 emission distribution. The NASA Earth Science Decadal Survey recommends more focus on direct observations of human influence on the Earth system. The most dramatic and compelling observations of human presence on the Earth are the night light observations taken by the Defence Meteorological System Program (DMSP) Operational Linescan System (OLS). Beyond delineating the footprint of human presence, night light data, when assembled and evaluated with complementary data sets, can determine the fine scale spatial distribution of global fossil fuel CO2 emissions. Understanding fossil fuel carbon emissions is critical to understanding the entire carbon cycle, and especially the carbon exchange between terrestrial and oceanic systems.

Hipskind, Stephen R.↗
NASA NTRS1984

The Structure of the Uranian Rings and the Search for Rings Around Neptune

The nine narrow rings of Uranus, presently the only confirmed features of this system, have been observed with the diffraction-limited resolution (3.5 km) of ground-based occultations since their discovery in 1977. These data have been used to establish an orbit model, from which the five Keplerian orbit parameters for each ring, the pole of the mean ring plane, and the gravitational harmonic coefficients J sub 2 and J sub 4 have been determined. The rings are typically a few kilometers wide with eccentricities of about 0.001 and inclinations of a few hundredths of a degree, although a few have no measurable eccentricity or inclination. Interesting Voyager investigations would include probing the structure of the rings at higher spatial resolution, searching for new rings in the system (including inter-ring material), locating the postulated shepherd satellites, and searching for satellites inside the orbit of Miranda that might have dynamical influence on the rings. The high precision (approx 2 km) of the ring orbits might prove useful for spacecraft navigation. For Neptune, occultation searches have revealed no rings to a limit of a few hundreths optical depth, within a few hundred kilometers from the top of the planet's atmosphere (for equatorial rings).

Elliot, J. L.↗
NASA NTRS1989

Rocket measurements of electron density irregularities during MAC/SINE

Four Super Arcas rockets were launched at the Andoya Rocket Range, Norway, as part of the MAC/SINE campaign to measure electron density irregularities with high spatial resolution in the cold summer polar mesosphere. They were launched as part of two salvos: the turbulent/gravity wave salvo (3 rockets) and the EISCAT/SOUSY radar salvo (one rocket). In both salvos meteorological rockets, measuring temperature and winds, were also launched and the SOUSY radar, located near the launch site, measured mesospheric turbulence. Electron density irregularities and strong gradients were measured by the rocket probes in the region of most intense backscatter observed by the radar. The electron density profiles (8 to 4 on ascent and 4 on descent) show very different characteristics in the peak scattering region and show marked spatial and temporal variability. These data are intercompared and discussed.

Ulwick, J. C.↗
NASA NTRS1992

Computation of high resolution unsteady airloads using a constant vorticity contour free wake model

Recent work in the study of helicopter aerodynamic loading for acoustics applications has involved research on the development of an exceptionally efficient simulation of the velocity field induced by the rotor's vortex wake. This paper summarizes the work to date on the development of this analysis, which builds on the refined constant vorticity contour (CVC) free wake model recently developed for application to the study of vibratory loading. The particular focus of this paper is on demonstrations of a reconstruction approach that efficiently computes both the flow fields and airloads induced by CVC wakes on lifting rotor blades. Results of recent calculations on both main rotor and tail rotors are presented. These calculations show that by employing flow field reconstruction it is possible to apply the CVC wake analysis with temporal and spatial resolution suitable for acoustics applications while reducing the computation time required by one to two orders of magnitude relative to the direct calculations used in traditional methods.

Quackenbush, T. R.↗
NASA NTRS1989

Radio wavelength observations of the L134N molecular core

A detailed study of the L134N dense molecular core through radio astronomical observations of spectral lines at millimeter and centimeter wavelengths is presented. The prototypical dark cloud was chosen for the following reasons: it is a nearby cloud at a distance of 160 pc, and thus radio observations have high spatial resolution; it resides out of the galactic disk, providing unobscured viewing along the line of sight; and it is known to be a rich source of molecular emission. The absence af any embedded infrared sources leads to the assumption that L134N is either in a stage of evolution prior to star formation or is a cloud in which internal support will prohibit a star from forming. A spectral line survey of 24 molecular transitions at up to seven positions in the L134N core, and observations of molecular emission from C18O, CSm, H13CO+, SO, NH3, and C3H2 are reviewed. Results indicate different spatial distributions for each species which may be attributed to variations in the excitation conditions for each transition or chemical abundance variations within the cloud core. Observational techniques and results are presented.

Swade, Daryl A.↗
NASA NTRS2012

Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..

Brown, Molly E.↗
NASA NTRS2012

Measuring the Surface Temperature of the Cryosphere using Remote Sensing

A general description of the remote sensing of cryosphere surface temperatures from satellites will be provided. This will give historical information on surface-temperature measurements from space. There will also be a detailed description of measuring the surface temperature of the Greenland Ice Sheet using Moderate-Resolution Imaging Spectroradiometer (MODIS) data which will be the focus of the presentation. Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate data record, trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the MODIS IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now freely available to download at 6.25-km spatial resolution on a polar stereographic grid. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends of the duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. The consistency of this IST record, with temperature and melt records from other sources will be discussed.

Hall, Dorothy K.↗
NASA NTRS2006

Pattern-Recognition Processor Using Holographic Photopolymer

proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square-law detector for the purpose of holographic recording of interference fringes. A typical state-of-the-art CCD has a pixel-pitch limited resolution of about 100 lines/mm. In contrast, the holographic photopolymer to be used in the proposed JTOC offers a resolution > 2,000 lines/mm. In addition to being disadvantageous in itself, the low resolution of the CCD causes overlap of a DC term and the desired correlation term in the output image. This overlap severely limits the correlation signal-to-noise ratio. The two-stage nature of the process limits the achievable throughput rate. A further limit is imposed by the low frame rate (typical video rates) of low- and medium-cost commercial CCDs.

Chao, Tien-Hsin↗
NASA NTRS1990

Summary of results and conclusions based on analysis of volume imaging and high spectral resolution lidar data acquired during FIRE phase 1, part 1

The collection of long term global statistics on cloud cover may be most easily accomplished with satellite based observations; however, measurements derived from passive satellite retrieval methods must be calibrated and verified by in situ or ground based remote sensor observations. Verification is not straight forward, however, because the highly variable nature of cloud altitude, morphology, and optical characteristics complicates the scaling of point measurements to satellite footprint sized areas. This is particularly evident for cirrus clouds which may be organized on horizontal scales of 10's of meters to 8 km or more, and have optical depths ranging from less than .003 to greater than 3. Cirrus clouds can strongly influence earths' radiative balance, but, because they are often transmissive, cirrus clouds are difficult to detect and characterize from satellite measurements. Because of its precise ranging capabilities, spatial resolution and sensitivity, lidar observations have played an important role in the detection, depiction, and characterization of cirrus clouds. Some of the characteristics of cirrus clouds are summarized which observed the High Spectral Resolution and Volume Imaging Lidars during the phase 1 IFO and ETO periods.

Grund, Christian J.↗
NASA NTRS1994

Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations: 1. North polar region

We present the first maps of the apparent thermal inertia and albedo of the north polar region of Mars. The observations used to create these maps were acquired by the infrared thermal mapper (IRTM) instruments on the two Viking orbiters over a 50-day period in 1978 during the Martian early northern summer season. The maps cover the region from 60 deg N to the north pole at a spatial resolution of 1/2 deg of latitude. The analysis and interpretation of these maps is aided by the results of a one-dimensional radiative convective model, which is used to calculate diurnal variations in surface and atmospheric temperatures, and brightness temperatures at the top of the atmospphere for a wide range of assumptions concerning aerosol optical properties and aerosol optical depths. The results of these calculations show that the effects of the Martian atmosphere on remote determinations of surface thermal inertia are more significant than have been indicated in previous studies. The maps of apparent thermal inertia and albedo show a great deal of spatial structure that is well correlated with surface features.

Paige, David A.↗
NASA NTRS2010

Mimas: Preliminary Evidence For Amorphous Water Ice from VIMS

We have conducted a statistical clustering analysis (1,2) on a mosaic of VIMS data cubes obtained on February 13, 2010, for Saturn s satellite Mimas. Seven VIMS cubes were geometrically projected and re-sampled to a common spatial resolution. The clustering technique consists of a partitioning algorithm coupled to a criterion that prevents sub-optimal solutions and tests for the influence of random noise in the measurements. The clustering technique is agnostic about the meaning of the clusters, and scientific interpretation requires their a posteriori evaluation. The preliminary results yielded five clusters, demonstrating that spectral variability across Mimas surface is statistically significant. The ratios of the means calculated for each of the clusters show structure within the 1.6- micron water ice band, as well as the shape and the central wavelength of the strong ice band at 2 micron, that map spatially in patterns apparently related to the topography of Mimas, in particular certain regions in and around Herschel crater. The mean spectra of the five clusters, show similarities with laboratory spectra of amorphous and crystalline H2O ice (3) that are suggestive of the presence of an amorphous ice component in certain regions of Mimas, notably on the central peak of Herschel, on the crater floor, and in faults surrounding the crater. This may represent a mixture of both ice phases, or perhaps a layer of amorphous ice on a base of crystalline ice. Another possible occurrence of amorphous ice appears southwest of Herschel, close to the south pole.

Cruikshank, Dale P.↗
NASA NTRS2016

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

climate projection↗
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗