Cost Analysis in a Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single mission-type support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multi-mission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature service-oriented, multi-mission control centers to streamline or refine their cost analysis process

Field and data analysis studies related to the atmospheric environment

This report summarizes work on a broad array of projects including: (1) applications of meteorological and/or oceanographic satellites; (2) improvement of the current set of NASA/USAF lightning related launch commit criteria rules; (3) the design, building, testing and deployment of a set of cylindrical field mills for aircraft use; (4) the study of marginal electrification storm conditions in relationship to the current launch commit rules for the space shuttle and various other launch vehicles using an instrumented aircraft; (5) support of the DC-8 and ER-2 lightning instrument package as part of both the Tropical Ocean - Global Atmospheric/Coupled Ocean-Atmospheric Response Experiment and the Convection and Moisture Experiment; (6) design of electronic circuitry and microprocessor firmware for the NASA Advanced Ground Based Field Mill; (7) design and testing of electronic and computer instrumentation for atmospheric electricity measurements; (8) simulating observations from a lightning imaging sensor on the Tropical Rainfall Measuring satellite; and (9) supporting scientific visualization and the development of computer software tools

Realising the full potential of citizen science monitoring programs

Citizen science is on the rise. Aided by the internet, the popularity and scope of citizen science appears almost limitless. For citizens the motivation is to contribute to "real" science, public information and conservation. For scientists, citizen science offers a way to collect information that would otherwise not be affordable. The longest running and largest of these citizen science programs are broad-scale bird monitoring projects. There are two basic types of protocols possible: (a) cross-sectional schemes such as Atlases - collections of surveys of many species contributed by volunteers over a set period of time, and (b) longitudinal schemes such as Breeding Bird Surveys (BBS) - on-going stratified monitoring of sites that require more coordination. We review recent applications of these citizen science programs to determine their influence in the scientific literature. We use return-on-investment thinking to identify the minimum investment needed for different citizen science programs, and the point at which investing more in citizen science programs has diminishing benefits. Atlas and BBS datasets are used to achieve different objectives, with more knowledge-focused applications for Atlases compared with more management applications for BBS. Estimates of volunteer investment in these datasets show that compared to cross-sectional schemes, longitudinal schemes are more cost-effective, with increased BBS investment correlated with more applications, which have higher impact in the scientific literature, as measured by citation rates. This is most likely because BBS focus on measuring change, allowing the impact of management and policy to be quantified. To ensure both types of data are used to their full potential we recommend the following: elements of BBS protocols (fixed sites, long-term monitoring) are incorporated into Atlases; regional coordinators are in place to maintain data quality; communication between researchers and the organisations coordinating volunteer monitoring is enhanced, with monitoring targeted to meet specific needs and objectives; application of data to under-explored objectives is encouraged, and data are made freely and easily accessible. (C) 2013 Elsevier Ltd. All rights reserved

Opportunistic citizen science data of animal species produce reliable estimates of distribution trends if analysed with occupancy models

Many publications documenting large-scale trends in the distribution of species make use of opportunistic citizen data, that is, observations of species collected without standardized field protocol and without explicit sampling design. It is a challenge to achieve reliable estimates of distribution trends from them, because opportunistic citizen science data may suffer from changes in field efforts over time (observation bias), from incomplete and selective recording by observers (reporting bias) and from geographical bias. These, in addition to detection bias, may lead to spurious trends. We investigated whether occupancy models can correct for the observation, reporting and detection biases in opportunistic data. Occupancy models use detection/nondetection data and yield estimates of the percentage of occupied sites (occupancy) per year. These models take the imperfect detection of species into account. By correcting for detection bias, they may simultaneously correct for observation and reporting bias as well. We compared trends in occupancy (or distribution) of butterfly and dragonfly species derived from opportunistic data with those derived from standardized monitoring data. All data came from the same grid squares and years, in order to avoid any geographical bias in this comparison. Distribution trends in opportunistic and monitoring data were well-matched. Strong trends observed in monitoring data were rarely missed in opportunistic data. Synthesis and applications. Opportunistic data can be used for monitoring purposes if occupancy models are used for analysis. Occupancy models are able to control for the common biases encountered with opportunistic data, enabling species trends to be monitored for species groups and regions where it is not feasible to collect standardized data on a large scale. Opportunistic data may thus become an important source of information to track distribution trends in many groups of species

[United States Soil Survey Report]

Text describes the area, climate, agricultural history and statistics, soil-survey methods and definitions, soils and crops, land uses and agricultural methods, irrigation, and morphology and genesis of soils of Brown and Mills Counties, Texas

Environmental and socio-economic factors shaping the geography of floristic collections in China

AimEffort in collecting biodiversity information often varies strongly in space and may be driven by environmental, cultural and socio-economic factors. Understanding the constraints on collecting effort is crucial for identifying potential bias in distributional databases and for making future surveys more efficient. Here we test six competing hypotheses on drivers of geographical variation in collecting effort and identify the main factors shaping the geography of floristic collections in China. LocationChina. MethodsWe used the most comprehensive database of Chinese vascular plant distributions including 4,338,516 county-level occurrences derived from herbarium specimens and literature sources. Explanatory variables were assembled representing six different hypotheses: accessibility, human population density, the botanist effect', mountains, water availability and conservation priority. Ordinary least-squares models with eigenvector-based spatial filters were applied to investigate their effects on spatial patterns of two different facets of collecting effort, i.e. collection density and inventory incompleteness. ResultsAll hypotheses except accessibility and human population density received significant support. Elevational range was the strongest predictor with a positive effect on collection density. Inventory incompleteness in turn was best predicted by human population density, but unexpectedly showed a positive effect. In contrast to previous studies, collecting effort was only weakly and negatively related to road density. Counties with herbaria had significantly higher collecting effort, and the presence of herbaria had weakly positive effects on neighbouring counties. Main conclusionsOur results indicate that China's mountains are most intensively and completely collected, whereas densely populated areas are surprisingly under-sampled. Because densely populated areas are more seriously threatened by land-use change, our results show a need to increase biological collections in those areas for conservation assessment and monitoring. More generally, our study suggests that collecting effort and its environmental and socio-economic constraints have a strong region-specific component influenced by cultural context and by different botanical traditions

The effects of soil eutrophication propagate to higher trophic levels

Conservation Biolog