Lunar Orbiter photo site accuracy analysis. Part 2 - Supporting data Final report
Input data for analysis of improved photo location calculations
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Input data for analysis of improved photo location calculations
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Solid waste disposal were studied in Volusia County to protect the water supply in the area. Highlands in this County are of limited areal extent and, most significantly, the sand hills and ridges are in areas where recharge of the Floridan aquifer occurs. This study proves that well drained soils meeting the current State requirements are of limited areal extent. These areas should not be utilized as sanitary landfill sites! Rather, it is recommended that the Tomoka Farm Road site into the adjacent wetlands be extended. The County site on Rima Ridge recommended by Greenleaf-Telesca as the primary waste burial site in the County should be re-evaluated because of potential danger to the Daytona Beach water supply.
X-ray single-crystal diffraction studies, supplemented by electron microprobe analyses of core pigeonites and rim augites from rocks 12031, 15085, 15475, and 15495, have been used to suggest cooling rates for these and other Apollo 12 and 15 rocks studied by similar methods. The extent of subsolidus phase separation of pyroxenes is used as a measure of the cooling rate. The results were interpreted in terms of model cooling histories of a lava flow whose thickness was estimated from the absolute cooling rates obtained by cooling rate experiments and by temperature-time variation through an extrusive flow computed by employing simplified theory of Jaeger. All available data on the exsolution and cation distributions of pyroxenes from Apollo 12 and 15 samples at present are consistent with the hypothesis that these rocks were derived from the top and interior of lava flows with thicknesses of 4-10 m. A process for exsolution of augite from a host pigeonite on (100) has been related to its low-calcium content.
The use of satellites for mobile radio service in non-urban areas of the United States in the years from 1985 to 2000 was investigated. Several satellite concepts are considered: a system with single-beam coverage of the fifty United States and Puerto Rico, and multi-beam satellites with greater capacity. All of the needed functions and services identified in the market study are provided by the satellite systems, including nationwide radio access to vehicles without knowledge of vehicle location wideband data transmission from remote sites, two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The costs of providing the services are within acceptable limits, and the desired returns to the system investors are attractive. The criteria by which the Federal Communication judges the competing demands for public radio spectrum are reviewed with comments on how the criteria might apply to the consideration of land mobile satellites. Institutional arrangements for operating a mobile satellite system are based on the present institutional arrangements in which the services are offered to the end users through wireline and radio common carriers, with direct access by large private and government users.
Economical archival and retrieval of image data is becoming increasingly important considering the unprecedented data volumes expected from the Earth Observing System (EOS) instruments. For cost effective browsing the image data (possibly from remote site), and retrieving the original image data from the data archive, we suggest an integrated image browse and data archive system employing incremental transmission. We produce our browse image data with the JPEG/DCT lossy compression approach. Image residual data is then obtained by taking the pixel by pixel differences between the original data and the browse image data. We then code the residual data with a form of variable length coding called diagonal coding. In our experiments, the JPEG/DCT is used at different quality factors (Q) to generate the browse and residual data. The algorithm has been tested on band 4 of two Thematic mapper (TM) data sets. The best overall compression ratios (of about 1.7) were obtained when a quality factor of Q=50 was used to produce browse data at a compression ratio of 10 to 11. At this quality factor the browse image data has virtually no visible distortions for the images tested.
Our primary objectives during the last year have been to develop a helicopter-borne radar system for measuring microwave backscatter from vegetation and to use this system to study the characteristics of backscatter from the boreal forest. Our research is aimed at refining the current microwave models and using these improvements for more accurate interpretation of SAR data. SAR data are very useful for monitoring the boreal forest region because of the microwave signal's ability to penetrate clouds and to see at night. Meeting these objectives involves several stages of development. The first stage is the design and implementation of a frequency-modulated continuous-wave (FM-CW) radar system with the capability of measuring backscatter at three frequencies and four polarizations at each frequency. These requirements necessitate a twelve-channel radar system. Using three frequencies is advantageous because it allows us to look at different parts of the canopy. For instance, the lower frequency signal penetrates deeper into the canopy and allows us to see the ground while the high frequency signal is scattered more by the leaves and needles and typically does not penetrate to the floor of the forest. We designed the radar starting with the antenna system. We then developed the intermediate frequency (IF) and radio frequency (RF) sections of the radar. Also, the need to collect data from twelve channels during each flight line presented a complex data acquisition problem that we solved by using a high-speed data acquisition board. After construction, the radar was tested at the lab. We performed extensive testing of the IF and RF systems of the radar during this time. Once we were satisfied with the operation of the radar it was shipped to Canada for use in the second intensive field campaign (IFC-2) from July 16 - August 8, 1994. During IFC-2, we collected backscatter data over the experimental sites in the southern study area (SSA). Additionally, we used a ground-based step-frequency radar to measure the reflection coefficient of the forest floor at the old jack pine (OJP) and young jack pine (YJP) sites. The ground-based radar data have been processed and a frew examples are included in this report. we are currently processing the helicopter-borne radar data.
Presentation to be presented during the Site-Directed Research and Development (SDRD) program FY 2021 review meeting (Webex), September 22–23, 2021.
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Analysis of Global Positioning System (GPS) data from two sites separated by horizontal distance of only approximately 2.2 m yielded phase residuals exhibiting a systematic elevation angle dependence. One of the two GPS antennas was mounted on an approximately 1 m high concrete pillar, and the other was mounted on a standard wooden tripod. We performed elevation angle cutoff tests with these data, and established that the vertical coordinate of site position was sensitive to the minimum elevation angle (elevation cutoff) of the data analyzed. For example, the vertical coordinate of site position changed by 9.7 plus or minus 0.8 mm when the minimum elevation angle was increased from 10 to 25. We performed simulations based on a simple (ray tracing) multipath model with a single horizontal reflector, and demonstrated that the elevation angle cutoff test results and the pattern of the residual versus elevation angle could be qualitatively reproduced if the reflector were located 0.1-0.2 m beneath the antenna phase center. We therefore, hypothesized that the source of the elevation-angle-dependent error were multipath reflections and scattering and that the horizontal surface of the pillar, located a distance of approximately 0.2 m beneath the antenna phase center, was the primary reflector. We tested this hypothesis by placing microwave absorbing material between the antenna and the pillar in a number of configurations and analyzed the changes in apparent position of the antenna. The results indicate that (1) the horizontal surface of the pillar is indeed the main reflector, (2) both the concrete and the metal plate embedded in the pillar are significant reflectors, and (3) the reflection can be reduced to a great degree by the use of microwave absorbing materials. These results have significant implications for the accuracy of global GPS geodetic tracking networks which use pillar-antenna configuration identical or similar to the one used here (at the Westford WFRD GPS site).
Among the potential reasons for enhanced warming rates in many high elevation regions is the nonlinear relationship between surface downward longwave radiation (DLR) and specific humidity (q). In this study we use ground-based observations at two neighboring high elevation sites in Southwestern Colorado that have different local topography and are 1.3 kilometers apart horizontally and 348 meters vertically. We examine the spatial consistency of the sensitivities (partial derivatives) of DLR with respect to changes in q, and the sensitivities are obtained from the Jacobian matrix of a neural network analysis. Although the relationship between DLR and q is the same at both sites, the sensitivities are higher when q is smaller, which occurs more frequently at the higher elevation site. There is a distinct hourly distribution in the sensitivities at both sites especially for high sensitivity cases, although the range is greater at the lower elevation site. The hourly distribution of the sensitivities relates to that of q. Under clear skies during daytime, q is similar between the two sites, however under cloudy skies or at night, it is not. This means that the DLR-q sensitivities are similar at the two sites during daytime but not at night, and care must be exercised when using data from one site to infer the impact of water vapor feedbacks at another site, particularly at night. Our analysis suggests that care should be exercised when using the lapse rate adjustment to infill high frequency data in a complex topographical region, particularly when one of the stations is subject to cold air pooling as found here.
Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099
A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.
The East Tennessee Technology Park (ETTP) Biological Monitoring and Abatement Program (BMAP) consists of three tasks that reflect different but complementary approaches to evaluating the ecological integrity of waters near ETTP. These tasks include (1) bioaccumulation monitoring of fish and clams, (2) benthic macroinvertebrate species richness and density monitoring, and (3) fish community monitoring. The sampling and analysis requirements for the ETTP BMAP in calendar year 2024, covering in part both FY 2024 and FY 2025, are outlined in the respective FY sampling and analysis plans (UCOR 2023, 2024). Sampled water bodies and locations for the ETTP BMAP are shown in Figures 1 and 2. This ETTP BMAP report presents the CY 2024 results and provides context with results from previous years. The report also includes Oak Ridge National Laboratory (ORNL)–generated biological monitoring data collected for other US Department of Energy programs, including the UCOR Water Resources Restoration Program (WRRP) off-site fish bioaccumulation data (UCOR 2023) and select Y-12 National Security Complex (Y-12) BMAP fish bioaccumulation data. Historical data collected for the ETTP BMAP and other programs in the nearby Poplar Creek and Clinch River are provided where appropriate. This progress report provides an update on the biological monitoring activities supporting the ETTP UCOR Environmental Compliance organization, which sponsors the ETTP BMAP. In addition to this internal reporting, ETTP BMAP results are provided in the annual remediation effectiveness reports and the annual site environmental reports, both of which are publicly available. BMAP data are also available to the public via the Oak Ridge Environmental Information System (https://ucor.com/oak-ridge-environmental-information-system-oreis/).
The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.
The Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature (LST) has been operationally produced for a decade since the Suomi National Polar-orbiting Partnership (SNPP) launched in October 2011. A comprehensive evaluation of its accuracy and precision will be helpful for product users in climate studies and atmospheric models. In this study, the VIIRS LST is validated with ground observations from multiple high-quality radiation networks, including six stations from the Surface Radiation budget (SURFRAD) network, two stations from the Baseline Surface Radiation Network (BSRN), and 13 stations from the Atmospheric Radiation Measurement (ARM) network, to evaluate its performance over various land-cover types. The VNP21A1 LST was validated against the same ground observations as a reference. The results yield a close agreement between the SNPP VIIRS LST and ground LSTs with a bias of -0.4 K and a RMSE of 1.96 K over six SURFRAD sites; a bias of -0.2 K and a RMSE of 1.93 K over two BSRN sites; and a bias of -0.1 K and a RMSE of 1.7 K over the 13 ARM sites. The time series of the LST errors over individual sites indicate seasonal cycles. The data anomaly over the BSRN site in Cabauw and the SURFRAD site in Desert Rock is revealed and discussed in this study. In addition, a method using Landsat-8 data is applied to quantify the heterogeneity level of each ground station and the results provide promising insights. The validation results demonstrate the maturity of the JPSS VIIRS LST products and their readiness for various application studies.