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At least 55 records · Page 3

Time-variable Earth's albedo model characteristics and applications to satellite sampling errors

Characteristics of the time variable Earth albedo model are described. With the cloud cover multiplying factor adjusted to produce a global annual average albedo of 30.3, the global annual average cloud cover is 45.5 percent. Global annual average sunlit cloud cover is 48.5 percent; nighttime cloud cover is 42.7 percent. Month-to-month global average albedo is almost sinusoidal with maxima in June and December and minima in April and October. Month-to-month variation of sunlit cloud cover is similar, but not in all details. The diurnal variation of global albedo is greatest from November to March; the corresponding variation of sunlit cloud cover is greatest from May to October. Annual average zonal albedos and monthly average zonal albedos are in good agreement with satellite-measured values, with notable differences in the polar regions in some months and at 15 S. The albedo of some 10 deg by 10 deg. areas of the Earth versus zenith angle are described. Satellite albedo measurement sampling effects are described in local time and in Greenwich mean time.

Bartman, F. L.↗

Monitoring vegetation recovery patterns on Mount St. Helens using thermal infrared multispectral data

The Mount St. Helens 1980 eruption offers an opportunity to study vegetation recovery rates and patterns in a perturbed ecosystem. The eruptions of Mount St. Helens created new surfaces by stripping and implacing large volumes of eroded material and depositing tephra in the blast area and on the flanks of the mountain. Areas of major disturbance are those in the blast zone that were subject to debris avalanche, pyroclastic flows, mudflows, and blowdown and scorched timber; and those outside the blast zone that received extensive tephra deposits. It was observed that during maximum daytime solar heating, surface temperatures of vegetated areas are cooler than surrounding nonvegetated areas, and that surface temperature varies with percent vegetation cover. A method of measuring the relationship between effective radiant temperature (ERT) and percent vegetation cover in the thermal infrared (8 to 12 microns) region of the electromagnetic spectrum was investigated.

Langran, Kenneth J.↗

Vega landing sites - Venera 15/16 unit analogs from Pioneer Venus reflectivity and RMS slope data

Pioneer Venus radar data on surface properties have been used to compare the Vega spacecraft landing sites with the northern 1/4 of Venus mapped by the orbiters Venera 15 and 16. The regions surrounding both landing sites possess surface reflectivity and small-scale roughness properties most similar to those of mapped volcanoes and volcanic plains regions and different surface properties than those of mapped tectonic units. Regions analogous to the Vega 1 site are relatively rare, covering 2.8 percent of the mapped surface. Vega 2 analogs are much more common and cover 22.6 percent of the surface. Neither landing site is representative of the nearby highlands of Aphrodite, but the Vega 2 landing site is similar to much of the northern plains of Venus.

Bindschadler, Duane L.↗

Methods of editing cloud and atmospheric layer affected pixels from satellite data

Plotted transects made from south Texas daytime HCMM data show the effect of subvisible cirrus (SCI) clouds in the emissive (IR) band but the effect is unnoticable in the reflective (VIS) band. The depression of satellite indicated temperatures ws greatest in the center of SCi streamers and tapered off at the edges. Pixels of uncontaminated land and water features in the HCMM test area shared identical VIS and IR digital count combinations with other pixels representing similar features. A minimum of 0.015 percent repeats of identical VIS-IR combinations are characteristic of land and water features in a scene of 30 percent cloud cover. This increases to 0.021 percent of more when the scene is clear. Pixels having shared VIS-IR combinations less than these amounts are considered to be cloud contaminated in the cluster screening method. About twenty percent of SCi was machine indistinguishable from land features in two dimensional spectral space (VIS vs IR).

Nixon, P. R.↗

Soybean canopy reflectance as influenced by cultural practices

Experiments were conducted at West Lafayette, Indiana in 1978 and 1979 to study the reflectance factor of soybean canopies as affected by differences in row width, population, planting date, cultivar and soil type. Reflectance factor data were acquired throughout the growing season with a LANDSAT-band radiometer. Agronomic data included plant height, leaf area index, development stage, total fresh and dry biomass, percent soil cover, and grain yield. The results indicate that row width, planting date, and cultivar influence the percent soil cover, leaf area index, and biomass present, which are in turn related to the multispectral reflectance. Additionally, the reflectance data were quite sensitive to the onset of senescence. Soil color and moisture were found to be important factors influencing the reflectance in single LANDSAT bands, but the near infrared/red reflectance ratio and the greeness transformation were less sensitive than the single bands to the soil background present.

Bauer, M. E.↗

Charge-coupled device imaging spectroscopy of Mars. I - Instrumentation and data reduction/analysis procedures

This paper describes the collection, reduction, and analysis of 0.4-1.0-micron Mars imaging spectroscopy data obtained during the 1988 and 1990 oppositions from Mauna Kea Observatory and provides a general outline for the acquisition and analysis of similar imaging spectroscopy data sets. The U.H. 2.24-m Wide Field Grism CCD Spectrograph was used to collect 13 3D image cubes covering 90 percent of the planet south of 50 deg N in the 0.4-0.8 micron region and covering 55 percent of the planet south of 50 deg N in the 0.5-1.0 micron region. Spectra extracted from these image cubes reveal the detailed character of the Martian near-UV to visible spectrum. Images at red wavelengths reveal the 'classical' albedo markings at 100-500 km spatial resolution while images at blue wavelengths show little surface feature contrast and are dominated by condensate clouds/hazes and polar ice.

Bell, James F., III↗

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Hall, D. K.↗

Effects of management practices on reflectance of spring wheat canopies

The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.

Daughtry, C. S. T.↗

Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay - A comparison of Landsat MSS to TM imagery

Landsat MSS and TM imagery, obtained simultaneously over Guinea Marsh, VA, as analyzed and compares for its ability to detect submerged aquatic vegetation (SAV). An unsupervised clustering algorithm was applied to each image, where the input classification parameters are defined as functions of apparent sensor noise. Class confidence and accuracy were computed for all water areas by comparing the classified images, pixel-by-pixel, to rasterized SAV distributions derived from color aerial photography. To illustrate the effect of water depth on classification error, areas of depth greater than 1.9 m were masked, and class confidence and accuracy recalculated. A single-scattering radiative-transfer model is used to illustrate how percent canopy cover and water depth affect the volume reflectance from a water column containing SAV. For a submerged canopy that is morphologically and optically similar to Zostera marina inhabiting Lower Chesapeake Bay, dense canopies may be isolated by masking optically deep water. For less dense canopies, the effect of increasing water depth is to increase the apparent percent crown cover, which may result in classification error.

Ackleson, S. G.↗

Effects of vegetation canopy structure on remotely sensed canopy temperatures

The effects of vegetation canopy structure on thermal infrared sensor response must be understood before vegetation surface temperatures of canopies with low percent ground cover can be accurately inferred. The response of a sensor is a function of vegetation geometric structure, the vertical surface temperature distribution of the canopy components, and sensor view angle. Large deviations between the nadir sensor effective radiant temperature (ERT) and vegetation ERT for a soybean canopy were observed throughout the growing season. The nadir sensor ERT of a soybean canopy with 35 percent ground cover deviated from the vegetation ERT by as much as 11 C during the mid-day. These deviations were quantitatively explained as a function of canopy structure and soil temperature. Remote sensing techniques which determine the vegetation canopy temperature(s) from the sensor response need to be studied.

Kimes, D. S.↗

MODIS Tree Cover Validation for the Circumpolar Taiga-Tundra Transition Zone

A validation of the 2005 500m MODIS vegetation continuous fields (VCF) tree cover product in the circumpolar taiga-tundra ecotone was performed using high resolution Quickbird imagery. Assessing the VCF's performance near the northern limits of the boreal forest can help quantify the accuracy of the product within this vegetation transition area. The circumpolar region was divided into longitudinal zones and validation sites were selected in areas of varying tree cover where Quickbird imagery is available in Google Earth. Each site was linked to the corresponding VCF pixel and overlaid with a regular dot grid within the VCF pixel's boundary to estimate percent tree crown cover in the area. Percent tree crown cover was estimated using Quickbird imagery for 396 sites throughout the circumpolar region and related to the VCF's estimates of canopy cover for 2000-2005. Regression results of VCF inter-annual comparisons (2000-2005) and VCF-Quickbird image-interpreted estimates indicate that: (1) Pixel-level, inter-annual comparisons of VCF estimates of percent canopy cover were linearly related (mean R(sup 2) = 0.77) and exhibited an average root mean square error (RMSE) of 10.1 % and an average root mean square difference (RMSD) of 7.3%. (2) A comparison of image-interpreted percent tree crown cover estimates based on dot counts on Quickbird color images by two different interpreters were more variable (R(sup 2) = 0.73, RMSE = 14.8%, RMSD = 18.7%) than VCF inter-annual comparisons. (3) Across the circumpolar boreal region, 2005 VCF-Quickbird comparisons were linearly related, with an R(sup 2) = 0.57, a RMSE = 13.4% and a RMSD = 21.3%, with a tendency to over-estimate areas of low percent tree cover and anomalous VCF results in Scandinavia. The relationship of the VCF estimates and ground reference indicate to potential users that the VCF's tree cover values for individual pixels, particularly those below 20% tree cover, may not be precise enough to monitor 500m pixel-level tree cover in the taiga-tundra transition zone.

Montesano, P. M.↗

Daily, 30 m Resolution NDSI Data for the East River Watershed, CO for 2000-2020

This dataset contains daily Normalized Difference Snow Index (NDSI) values at 30 m spatial resolution for the East River watershed in Colorado, USA. The temporal range of these data includes water years 2001-2020. These data were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). This model fuses low spatial and high temporal resolution data from MODIS (500 m, daily) with high spatial and low temporal resolution data from Landsat (30 m, 16 days) to create a 30m synthetic daily snow product. This product allows for the analysis of historical snow covered area trends in the East River Watershed at fine spatiotemporal resolutions where it was not available previously. This research was performed as a part of the Department of Energy’s Subsurface Biogeochemical Research Program with the primary intent of better understanding the timing and spatial patterns of water delivery to the Critical Zone in mountain watersheds. Each .zip file contains one "water year" of data (October 1 - September 30; i.e., water year 2010 starts October 1, 2010 and ends September 30, 2011). Each zip file contains the following: STARFM daily Normalized Difference Snow Index (NDSI) fusion data files in GeoTiff format with one layer for each day between Landsat data acquisition dates (i.e., for dates of Landsat acquisition, the Landsat image is included for that date). The study area is located in an area of Landsat path overlap, so Landsat dates acquisitions are every 7-9 days. Landsat NDSI files containing the high spatial (30m), low temporal (7-9 days due to Landsat path overlap) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Dates for which no Landsat data were obtained are included as NoData layers. MODIS NDSI files containing the high temporal (daily), low spatial (500m) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Please note the MODIS data were resampled to 30m pixels for input into the STARFM model. The data have a scale factor of 10,000 and a no data value of -32767. The projection of all datasets is WGS 84 (EPSG: 4326), which has a latitude/longitude based degree resolution of 0.0002694946 X 0.0002694946, and approximates to the 30 m spatial resolution mentioned above. The Layer Index files in .csv format. They contain information for each layer in the above GeoTiff files regarding the corresponding date for each layer, the fraction of pixels in the image that contain valid data (missing data is due to either cloud cover or poor data quality; these values are not percent snow cover). Dates of Landsat overpass are indicated in these files. If no Landsat data were able to be obtained due to cloud cover or lack of Landsat Tier 1 data available on Google Earth Engine, this is also noted.

EARTH SCIENCE > CRYOSPHERE > SNOW/ICE↗

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗

Parabolic features and the erosion rate on Venus

The impact cratering record on Venus consists of 919 craters covering 98 percent of the surface. These craters are remarkably well preserved, and most show pristine structures including fresh ejecta blankets. Only 35 craters (3.8 percent) have had their ejecta blankets embayed by lava and most of these occur in the Atla-Beta Regio region; an area thought to be recently active. parabolic features are associated with 66 of the 919 craters. These craters range in size from 6 to 105 km diameter. The parabolic features are thought to be the result of the deposition of fine-grained ejecta by winds in the dense venusian atmosphere. The deposits cover about 9 percent of the surface and none appear to be embayed by younger volcanic materials. However, there appears to be a paucity of these deposits in the Atla-Beta Regio region, and this may be due to the more recent volcanism in this area of Venus. Since parabolic features are probably fine-grain, wind-deposited ejecta, then all impact craters on Venus probably had these deposits at some time in the past. The older deposits have probably been either eroded or buried by eolian processes. Therefore, the present population of these features is probably associated with the most recent impact craters on the planet. Furthermore, the size/frequency distribution of craters with parabolic features is virtually identical to that of the total crater population. This suggests that there has been little loss of small parabolic features compared to large ones, otherwise there should be a significant and systematic paucity of craters with parabolic features with decreasing size compared to the total crater population. Whatever is erasing the parabolic features apparently does so uniformly regardless of the areal extent of the deposit. The lifetime of parabolic features and the eolian erosion rate on Venus can be estimated from the average age of the surface and the present population of parabolic features.

Strom, Robert G.↗

Detection and mapping of mineralized areas in the Cortez-Uinta Belt, Utah-Nevada using computer-enhanced ERTS imagery

The author has identified the following significant results. The reflectance spectra of most hydrothermally altered rocks were characterized by broad ferric iron absorption bands short of 1.1 microns and a sharper hydroxyl band near 2.2 microns; maximum reflectance occurred near 1.6 microns. Their features became more prominent as albedo increased. The MSS color ratio composite images were the most effective and practical means for detecting and mapping limonitic rocks in areas having less than about 50 percent desert brush cover and less than 25-35 percent coniferous tree cover. Limonitic altered and unaltered rocks could not be distinguished in MSS color ratio composite images.

Rowan, L. C.↗

An Energy Codes Gap Analysis Field Study in the Southwest (Final Technical Report)

The primary goal of the “An Energy Codes Gap Analysis Field Study in the Southwest” project was to improve housing through strengthened building energy code implementation in two states, Colorado and Nevada, leading to greater energy and utility bill savings for households. Colorado is a home rule state. Nevada adopts a statewide code, but cities and counties must also adopt the code, making the state function like a home rule state. To broaden the impact of the project, an additional goal was to share and amplify project experiences, findings, and lessons that can be applied in other states. To achieve these goals, the project’s key objectives were to examine how residential energy codes are implemented in partner states; to use these findings to strengthen codes implementation through enhanced education, training, and outreach; and to enhance energy code technical assistance capabilities in the two partner states. In both partner states, the project led to the creation of a quantitative baseline understanding of compliance with high-impact energy code requirements, such as foundation, wall, and ceiling R-value; window U-factor and SHGC; envelope air tightness; duct tightness; and high-efficiency lighting. It then applied this baseline information to directly inform training in geographic areas with high levels of building and construction activity. The project has placed Colorado and Nevada among 23 states across the country that have conducted a single-family residential field study based on the established U.S. Department of Energy (DOE) methodology since 2014. It has also helped each State Energy Office test models for partnership- and relationship-building among government agencies and key stakeholder groups, including the State Energy Office and relevant code administration and professional licensing agencies, building officials, designers, builders, trades and utilities. At the national level, the project helped educate and inform State and Territory Energy Offices on a replicable methodology to assess energy code construction practices, effective stakeholder engagement strategies, and tailored energy code education and training. These findings are particularly pertinent for home-rule states, such as Colorado and Nevada, which rely on local government awareness and action to advance and implement building energy codes. By raising awareness of code adoption and compliance, this project has helped to equip each partner state with data on code compliance, strategies, education, and partnership models to advance building energy codes. This in turn will have an important impact on new construction practices in Colorado and Nevada, leading to more energy efficient and affordable housing. Currently, more than 62 percent of Colorado’s population lives in one of the 55 jurisdictions that have adopted the 2021 IECC to date, while nearly 95 percent of the state's population lives in one of the 208 jurisdictions that have adopted a code at 2015 IECC levels or higher. In Nevada, the 2018 IECC was adopted by the Governor’s Office of Energy in July 2018. By July 2020, 47 percent of the adopted energy code in the state was 2018 IECC which covers 96.5 percent of Nevada’s population. The training materials funded by this project focus on the 2021 IECC and will continue to be relevant in the two states as additional jurisdictions update their building energy codes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of ERTS imagery for spectral geological mapping in diverse terranes of New York State

The author has identified the following significant results. Preliminary visual examination of film positives of thirty ERTS-1 scenes obtained over New York State and adjacent areas indicates the following: (1) sixty percent of the imagery has a cloud cover of 70-100 percent, twenty-five percent has a cloud cover of 0-30 percent, and the remainder has a cover of 40-65 percent; (2) on the useable imagery, the spectral lines which may turn out to be geologically-linked totals as follows: spectral linears, 5200 km; broadly curved lines (spectral curvilinears), 700 km; major forest boundaries, 3100 km; areas with spectral geological fabric, 3100 sgkm. In the central and northwest Adirondacks, known lineaments and faults were subtracted from the spectral linears leaving a residue which totals 160 km in the central Adirondacks and 230 km in the northwest Adirondacks. It must be emphasized that these are spectral linears which have not yet been checked out against any ground truth except geological.

Isachsen, Y. W.↗

Evaluation and interpretation of Thematic Mapper ratios in equations for estimating corn growth parameters

Reflectance and agronomic Thematic Mapper (TM) data were analyzed to determine possible data transformations for evaluating several plant parameters of corn. Three transformation forms were used: the ratio of two TM bands, logarithms of two-band ratios, and normalized differences of two bands. Normalized differences and logarithms of two-band ratios responsed similarly in the equations for estimating the plant growth parameters evaluated in this study. Two-term equations were required to obtain the maximum predictability of percent ground cover, canopy moisture content, and total wet phytomass. Standard error of estimate values were 15-26 percent lower for two-term estimates of these parameters than for one-term estimates. The terms log(TM4/TM2) and (TM4/TM5) produced the maximum predictability for leaf area and dry green leaf weight, respectively. The middle infrared bands TM5 and TM7 are essential for maximizing predictability for all measured plant parameters except leaf area index. The estimating models were evaluated over bare soil to discriminate between equations which are statistically similar. Qualitative interpretations of the resulting prediction equations are consistent with general agronomic and remote sensing theory.

Dardner, B. R.↗