Maya Forest Water Resources: Using NASA Earth Observations to Map Forested Inundation in the Maya Forest
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Reasonable and effective use of renewable resources can reduce dependence on traditional fossil-based energy sources and reduce carbon emissions. This study mapped the spatial potentials of renewable resources (i.e., solar radiation, precipitation, wind, and geothermal resources) in China. The results showed that China's most abundant renewable resources are located in the southwestern regions, which are significantly different from the spatial distribution patterns of population and economic development. Four southwestern provinces (Tibet, Qinghai, Sichuan, and Yunnan) make up only 7% of the national gross domestic product (GDP) and 30% of the national land area but possess 58% of the renewable resources. Furthermore, we found a weak to moderate degree of negative correlation between the emergy density of renewable resources and GDP per capita on the administrative levels of the prefecture-level cities for the whole country and in its eastern, central, and western regions. This means that the socioeconomically underdeveloped Midwest has more abundant renewable resources. A distributed energy-economic system may help to bridge the regional gaps of renewable sources in China. These findings can support policy decisions for the better development and use of renewable resources in China.
Remote aerial sensing and automatic mapping for forest resources information system
Digital computer processing of airborne multispectral data, discussing automatic recognition and mapping of terrain distribution, Earth Resources Technology Satellite data channel efficiency, etc
Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP).Resource Prospector is a lunar mission to investigate strategic knowledge gaps (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith Environment Science and Oxygen Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis.
Imagery from U-2 flight or Skylab is used to produce maps of Arizona for resource management and land use. Color photography and thermal mapping techniques are described for studying vegetation growth, natural resources, flood plains, soil erosion, and heat loss from buildings.
The author has identified the following significant results. Significant correspondence codes relating ERTS imagery to ground truth from vegetation and geology maps have been established. The use of color equidensity and color composite methods for selecting zones of equal densitometric value on ERTS imagery was perfected. Primary interest of temporal color composite is stressed. A chain of transfer operations from ERTS imagery to the automatic mapping of natural resources was developed.
Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.
The use of NASA high altitude aerial photography of south eastern Arizona to develop a natural resources information system for Federal lands is discussed. The data are to be used by local, State, and Federal agencies in connection with geologic mapping projects, water resources investigations, and land use studies to determine the alignment of a proposed major aqueduct. In addition, the data are used to confirm land ownership boundaries, detect changes in land use, and legislative reappointment mapping. Other applications include mapping vegetive cover, evaluation of changes in wildlife habitat, location of deer kills, and as a base for recording telemetry data from radio-collared big game animals.
The author has identified the following significant results. The images can be positioned in an absolute reference system (geographical coordinates or polar stereographic coordinates) by means of their marginal indicators. By digital analysis of LANDSAT data and geometric positioning of pixels in UTM projection, accuracy was achieved for corrected MSS information which could be used for updating maps at scale 1:200,000 or smaller. Results show that adjustment of the UTM grid was better obtained by a first order, or even second order, algorithm of geometric correction. Digital analysis of LANDSAT data from the Madrid area showed that this line of study was promising for automatic classification of data applied to thematic cartography and soils identification.
The application of ERTS-1 imagery for providing information on agriculture, forestry, and rangeland resources is described. The use of the ERTS-1 system for stratification and sampling estimates of relatively small areas is discussed. Examples of maps to improve resource definition for land use planning, resource allocation, and resource development are provided. Inventories of various crops, as determined by photointerpretation of ERTS imagery are submitted in tabular form.
The author has identified the following significant results. Methods of detecting ice and for distinguishing between ice and clouds are discussed, and examples of ERTS-1 data showing ice distributions in northern Hudson Bay, M'Clure Strait, the eastern Beaufort Sea, and the Greenland Sea are presented. The results of the initial analysis of ERTS-1 data indicate that the locations of ice edges and ice concentrations can be accurately mapped, and that considerable information on ice type can be derived through use of the various spectral bands. Ice features as small as 80 to 100 m width can be mapped.
Papers are presented on remote sensing applications in resource monitoring and management, data classification and modeling procedures, and the use of remote sensing techniques in developing nations. The subjects of land use/land cover, soil mapping, crop identification, mapping of geological resources, renewable resource analysis, and oceanographic applications are discussed. Papers from Argentina, Bolivia, Brazil, Costa Rica, the Syrian Arab Republic, the People's Republic of China, the Phillipines, Italy, Upper Volta and the United States are included.
The presentation is divided into three parts. Part I is an overview of early expeditions to the High Arctic, and their political consequences at the time. The focus then shifts to the Geological Survey of Canada s mapping program in the North (Operation Franklin), and to the Polar Continental Shelf Project (PCSP), a unique organization that resides within the Government of Canada s Department of Natural Resources, and supports mapping projects and science investigations. PCSP is highlighted throughout the presentation so a description of mandate, budgets, and support infrastructure is warranted. In Part II, the presenter describes the planning required in advance of scientific deployments carried out in the Canadian High Arctic from the perspective of government and university investigators. Field operations and challenges encountered while leading arctic field teams in fly camps are also described in this part of the presentation, with particular emphasis on the 2008 field season. Part III is a summary of preliminary results obtained from a Polar Survey questionnaire sent out to members of the Arctic research community in anticipation of the workshop. The last part of the talk is an update on the analog program at the Canadian Space Agency, specifically, the Canadian Analog Research Network (CARN) and current activities related to Analog missions, 2009-2010.
INTRODUCTION The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) implements a computational model that aims to quantify spaceflight medical risk by utilizing probabilistic techniques to simulate critical event incidence and outcomes over thousands of simulated mission trials. The goal of MEDPRAT is to characterize mission medical risk and provide insight into medical resource utilization. In order to analyze the medical resource space, treatment must be mapped from each simulated condition, and resources consumed as a result of this treatment must be tracked throughout the course of the mission. A new MEDPRAT feature, ‘treatment clusters’, provide a more sophisticated method of defining the structure and interaction between resources, more closely mimicking the way treatment is carried out clinically. METHODS Treatment clusters expand on the two existing treatment groupings (combination and alternate) adding a new grouping: bundled treatment. Treatment clusters may be combined to any depth, giving users the ability to specify complex treatment trees whose behavior is governed by several user-specified parameters. This approach emphasizes reusability, as treatment clusters, once defined, can be used to create more complex treatment trees or applied to many conditions. By configuring parameters for contribution, efficacy, necessity, primacy, and equivalence, resource relationships and dependencies can be more accurately represented, thereby allowing users to build capabilities with desired treatment properties, for example an intravenous capability for conditions such as anaphylaxis, acute radiation syndrome, etc. MEDPRAT v1.0 remains backward compatible with existing treatment structures, giving users the ability to define new treatment clusters as evidence becomes available, without having to recode their existing treatment databases. In addition to facilitating the representation of more complex treatment options, by pairing treatment clusters with the internal optimization routine, the MEDPRAT set selector, medical resources can be identified as organized in bundles, where appropriate, so that optimized resource sets include groups of highly-dependent resources only when all resources of the group are together. For example, it would be wasteful to include ultrasound gel but not an ultrasound machine, since the gel provides no benefit as a treatment without the ultrasound machine. With treatment clusters, the user may require that both resources are available to provide any benefit as treatment, so that if one resource is optimized out of the set, the other resource will be optimized out as well. RESULTS AND CONCLUSIONS We will report on MEDPRAT treatment clusters used in a bundling study under the IMPACT project of the ExMC element. We will discuss an example of a complex treatment tree. Through the implementation of this feature MEDPRAT enables treatment to be defined and applied in a way that is more representative of the real world, providing more accurate insight into mission medical risk and the medical resource space.
In 2017, NASA initiated the Artemis program to send astronauts back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface. While much of NASA’s plans for the Artemis program currently focus on the Human Lunar Return and the ability for astronauts to explore the lunar surface for limited durations each year, the longer-term vision for the Artemis program is to enable sustained human exploration and commercial operations in cis-lunar space and the lunar surface. An important aspect of achieving this long-term vision, is to better understand and characterize the resources on the Moon and Mars and learn how to extract and use these resources. Known as In Situ Resource Utilization (ISRU), the identification, mapping, extraction, and processing of space resources has the potential to greatly reduce the cost and risk of human exploration. These are achieved by reducing what needs to be delivered from Earth and the dependency on these supplies, lowering costs through commercial operations, and expanding infrastructure for safer and more capable exploration and surface operations. To guide development of ISRU technologies and systems on the ground and demonstrate these capabilities on the Moon and Mars, the NASA Space Technology Mission Directorate (STMD) created and released the ISRU Envisioned Future Priorities (EFP) strategic plan in 2022 and updated it in 2023. While lunar ISRU technology development had already started, these publicly released strategic plans have been used to guide and prioritize technology development, and assess the progress in achieving the vision. Since the release of the ISRU EFP, there have been several significant activities/events that have occurred with respect to human lunar exploration, surface infrastructure, and ISRU. One was the release of the Artemis Architecture Definition Document Revision 1 that included ISRU as a sub-architecture. The second was the release of several STMD solicitations including the Announcement of Collaborative Opportunities (ACO) and Tipping Point (TP). The third was the release of a Request for Information for the Lunar Infrastructure Foundational Technology-1 (LIFT-1) mission with the primary objective of extracting oxygen from lunar regolith. The fourth was the release of STMD technology and capability Shortfalls, and the review, ranking by numerous stakeholders and individuals, and subsequent prioritization of the Shortfalls that will be utilized in future solicitation and development plans. This paper will provide an overview and status of on-going technology and system development activities, an update of ISRU into the Artemis campaign, an update on ISRU-related mission, and the impacts of the Shortfall prioritization.
In 2017, NASA initiated the Artemis program to send astronauts back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface. While much of NASA’s plans for the Artemis program currently focus on the Human Lunar Return and the ability for astronauts to explore the lunar surface for limited durations each year, the longer-term vision for the Artemis program is to enable sustained human exploration and commercial operations in cis-lunar space and the lunar surface. An important aspect of achieving this long-term vision, is to better understand and characterize the resources on the Moon and Mars and learn how to extract and use these resources. Known as In Situ Resource Utilization (ISRU), the identification, mapping, extraction, and processing of space resources has the potential to greatly reduce the cost and risk of human exploration. These are achieved by reducing what needs to be delivered from Earth and the dependency on these supplies, lowering costs through commercial operations, and expanding infrastructure for safer and more capable exploration and surface operations. To guide development of ISRU technologies and systems on the ground and demonstrate these capabilities on the Moon and Mars, the NASA Space Technology Mission Directorate (STMD) created and released the ISRU Envisioned Future Priorities (EFP) strategic plan in 2022 and updated it in 2023. While lunar ISRU technology development had already started, these publicly released strategic plans have been used to guide and prioritize technology development, and assess the progress in achieving the vision. Since the release of the ISRU EFP, there have been several significant activities/events that have occurred with respect to human lunar exploration, surface infrastructure, and ISRU. This presentation will provide an overview and status of on-going technology and system development activities, an update of ISRU into the Artemis campaign, an update on ISRU-related activities.
oarse-grained reconfigurable arrays (CGRAs) are a promising solution to enable energy-efficient acceleration of applications from different domains. By leveraging reconfiguration at the functional level, they can adapt to significantly different computational patterns. Existing CGRA mapping approaches extract instruction-level parallelism, exploit loop-pipelining opportunities, guarantee the data dependency, and target high throughput of a given loop. However, the recurrence data-dependency in the DFG and the mismatch between required and available computing/communication resources complicate the mapping, and might lead to significant unbalances in the utilization of the CGRA's tiles. This results in wasted power for tiles with low utilization. Applying dynamic voltage and frequency scaling (DVFS) can potentially solve this challenge and improve energy efficiency by adjusting voltage and frequency of different tiles independently. CGRAs have also been successful in accelerating data-dependent streaming applications. However, in these applications, the execution time of each kernel in the pipeline might dynamically vary depending on the characteristics of the input. This also leads to under-utilization of resources for the dynamically changing kernels that do not limit the application throughput. DVFS can also improve energy efficiency for these applications by dynamically changing the voltage and frequency levels of tiles that host non performance-constraining kernels. This paper proposes ICEDTEA -- an integrated DVFS-aware framework to map applications on CGRAs that support power islands. ICEDTEA proposes a CGRA architecture supporting DVFS islands at varying granularity (from a single tile to a group of tiles) and the related DVFS-aware compilation and mapping toolchain. ICEDTEA is the first work that introduces DVFS support for spatio-temporal CGRAs at power-island levels. The experimental evaluation shows that ICEDTEA improves average utilization by 2.3$\times$ and energy-efficiency by 1.32$\times$ over a conventional CGRA. With streaming applications, ICEDTEA improves energy efficiency by 1.12$\times$ over a state-of-the-art CGRA that introduces partial dynamic reconfiguration to adapt to variations in kernels' throughput.