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Assessment of the Thematic Accuracy of Land Cover Maps
NASA Astrophysics Data System (ADS)
Höhle, J.
2015-08-01
Several land cover maps are generated from aerial imagery and assessed by different approaches. The test site is an urban area in Europe for which six classes (`building', `hedge and bush', `grass', `road and parking lot', `tree', `wall and car port') had to be derived. Two classification methods were applied (`Decision Tree' and `Support Vector Machine') using only two attributes (height above ground and normalized difference vegetation index) which both are derived from the images. The assessment of the thematic accuracy applied a stratified design and was based on accuracy measures such as user's and producer's accuracy, and kappa coefficient. In addition, confidence intervals were computed for several accuracy measures. The achieved accuracies and confidence intervals are thoroughly analysed and recommendations are derived from the gained experiences. Reliable reference values are obtained using stereovision, false-colour image pairs, and positioning to the checkpoints with 3D coordinates. The influence of the training areas on the results is studied. Cross validation has been tested with a few reference points in order to derive approximate accuracy measures. The two classification methods perform equally for five classes. Trees are classified with a much better accuracy and a smaller confidence interval by means of the decision tree method. Buildings are classified by both methods with an accuracy of 99% (95% CI: 95%-100%) using independent 3D checkpoints. The average width of the confidence interval of six classes was 14% of the user's accuracy.
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United States Offshore Wind Resource Assessment
NASA Astrophysics Data System (ADS)
Schwartz, M.; Haymes, S.; Heimiller, D.
2008-12-01
The utilization of the offshore wind resource will be necessary if the United States is to meet the goal of having 20% of its electricity generated by wind power because many of the electrical load centers in the country are located along the coastlines. The United States Department of Energy, through its National Renewable Energy Laboratory (NREL), has supported an ongoing project to assess the wind resource for the offshore regions of the contiguous United States including the Great Lakes. Final offshore maps with a horizontal resolution of 200 meters (m) have been completed for Texas, Louisiana, Georgia, northern New England, and the Great Lakes. The ocean wind resource maps extend from the coastline to 50 nautical miles (nm) offshore. The Great Lake maps show the resource for all of the individual lakes. These maps depict the wind resource at 50 m above the water as classes of wind power density. Class 1 represents the lowest available wind resource, while Class 7 is the highest resource. Areas with Class 5 and higher wind resource can be economical for offshore project development. As offshore wind turbine technology improves, areas with Class 4 and higher resource should become economically viable. The wind resource maps are generated using output from a modified numerical weather prediction model combined with a wind flow model. The preliminary modeling is performed by AWS Truewind under subcontract to NREL. The preliminary model estimates are sent to NREL to be validated. NREL validates the preliminary estimates by comparing 50 m model data to available measurements that are extrapolated to 50 m. The validation results are used to modify the preliminary map and produce the final resource map. The sources of offshore wind measurement data include buoys, automated stations, lighthouses, and satellite- derived ocean wind speed data. The wind electric potential is represented as Megawatts (MW) of potential installed capacity and is based on the square kilometers (sq. km) of Class 5 and higher wind resource found in a specific region. NREL uses a factor of 5 MW of installed capacity per sq. km of "windy water" for its raw electric potential calculations. NREL uses Geographic Information System data to break down the offshore wind potential by state, water depth, and distance from shore. The wind potential estimates are based on the updated maps, and on previous offshore resource information for regions where new maps are not available. The estimates are updated as new maps are completed. For example, the updated Texas offshore map shows almost 3000 sq. km of Class 5 resource within 10 nm of shore and nearly 2000 sq. km of Class 5 resource or 10,000 MW of potential installed capacity in water depths of less than 30 m. NREL plans to develop exclusion criteria to further refine the offshore wind potential
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Mapping urban revitalization: using GIS spatial analysis to evaluate a new housing policy.
PubMed
Perkins, Douglas D; Larsen, Courtney; Brown, Barbara B
2009-01-01
This longitudinal, multimethod study uses geographical information system (GIS) software to evaluate the community-wide impact of a neighborhood revitalization project. Unsystematic visual examination and analysis of GIS maps are offered as a complementary tool to quantitative analysis and one that is much more compelling, meaningful, and effective in presentation to community and nonscientific professional audiences. The centerpiece of the intervention was the development of a new, middle-class housing subdivision in an area that was declining physically and economically. This represents three major urban/housing policy directions: (1) the emphasis on home ownership for working-class families, (2) the deconcentration of poverty through development of mixed-income neighborhoods, and (3) the clean up and redevelopment of contaminated, former industrial brownfields. Resident survey responses, objective environmental assessment observations, and building permit data were collected, geocoded at the address level, and aggregated to the block level on 60 street blocks in the older neighborhoods surrounding the new housing in two waves: during site clearing and housing construction (Time 1: 1993-95) and three years post-completion (Time 2: 1998-99). Variables mapped include (a) Time 1-2 change in self-reported home repairs and improvements, (b) change in the assessed physical condition of yards and exteriors of 925 individual residential properties, (c) change in residents' home pride, and (d) a city archive of building permits at Time 2. Physical conditions improved overall in the neighborhood, but spatial analysis of the maps suggest that the spillover effects, if any, of the new housing were geographically limited and included unintended negative psychological consequences. Results argue for greater use of GIS and the street block level in community research and of psychological and behavioral variables in planning research and decisions.
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Winter wheat mapping combining variations before and after estimated heading dates
NASA Astrophysics Data System (ADS)
Qiu, Bingwen; Luo, Yuhan; Tang, Zhenghong; Chen, Chongcheng; Lu, Difei; Huang, Hongyu; Chen, Yunzhi; Chen, Nan; Xu, Weiming
2017-01-01
Accurate and updated information on winter wheat distribution is vital for food security. The intra-class variability of the temporal profiles of vegetation indices presents substantial challenges to current time series-based approaches. This study developed a new method to identify winter wheat over large regions through a transformation and metric-based approach. First, the trend surfaces were established to identify key phenological parameters of winter wheat based on altitude and latitude with references to crop calendar data from the agro-meteorological stations. Second, two phenology-based indicators were developed based on the EVI2 differences between estimated heading and seedling/harvesting dates and the change amplitudes. These two phenology-based indicators revealed variations during the estimated early and late growth stages. Finally, winter wheat data were extracted based on these two metrics. The winter wheat mapping method was applied to China based on the 250 m 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) time series datasets. Accuracy was validated with field survey data, agricultural census data, and Landsat-interpreted results in test regions. When evaluated with 653 field survey sites and Landsat image interpreted data, the overall accuracy of MODIS-derived images in 2012-2013 was 92.19% and 88.86%, respectively. The MODIS-derived winter wheat areas accounted for over 82% of the variability at the municipal level when compared with agricultural census data. The winter wheat mapping method developed in this study demonstrates great adaptability to intra-class variability of the vegetation temporal profiles and has great potential for further applications to broader regions and other types of agricultural crop mapping.
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Do Science and Technology Teachers and Pre-Service Primary Teachers Have Different Thoughts about Concept Maps in Science and Technology Lessons?
ERIC Educational Resources Information Center
Karakuyu, Yunus
2011-01-01
The purpose of this study is to determine the thoughts of primary science and technology teachers, primary class teachers, pre-service primary class teachers and pre-service primary science and technology teachers' about concept maps. This scale applied the use of basic and random method on the chosen 125 4th and 5th grade primary class teachers…
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The Cosmology Large Angular Scale Surveyor
NASA Technical Reports Server (NTRS)
Harrington, Kathleen; Marriage, Tobias; Ali, Aamir; Appel, John; Bennett, Charles; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe; 
2016-01-01
The Cosmology Large Angular Scale Surveyor (CLASS) is a four telescope array designed to characterize relic primordial gravitational waves from inflation and the optical depth to reionization through a measurement of the polarized cosmic microwave background (CMB) on the largest angular scales. The frequencies of the four CLASS telescopes, one at 38 GHz, two at 93 GHz, and one dichroic system at 145217 GHz, are chosen to avoid spectral regions of high atmospheric emission and span the minimum of the polarized Galactic foregrounds: synchrotron emission at lower frequencies and dust emission at higher frequencies. Low-noise transition edge sensor detectors and a rapid front-end polarization modulator provide a unique combination of high sensitivity, stability, and control of systematics. The CLASS site, at 5200 m in the Chilean Atacama desert, allows for daily mapping of up to 70% of the sky and enables the characterization of CMB polarization at the largest angular scales. Using this combination of a broad frequency range, large sky coverage, control over systematics, and high sensitivity, CLASS will observe the reionization and recombination peaks of the CMB E- and B-mode power spectra. CLASS will make a cosmic variance limited measurement of the optical depth to reionization and will measure or place upper limits on the tensor-to-scalar ratio, r, down to a level of 0.01 (95% C.L.).
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Making large class basic histology lectures more interactive: The use of draw-along mapping techniques and associated educational activities.
PubMed
Kotzé, Sanet Henriët; Mole, Calvin Gerald
2015-01-01
At Stellenbosch University, South Africa, basic histology is taught to a combination class of almost 400 first-year medical, physiotherapy, and dietetic students. Many students often find the amount of work in basic histology lectures overwhelming and consequently loose interest. The aim was to determine if a draw-along mapping activity would focus students during large class lectures. After each lecture on three basic histology tissues, a guided draw-along mapping session covering the work from the lecture was introduced in the form of a click-advance PowerPoint presentation which was used to demonstrate the unfolding of an "ideal" map. The lecturer simultaneously drew a similar map using an overhead projector allowing the students to draw their own maps on blank sheets of paper along with the lecturer. Students remained attentive during the activity and many participated in answering informal questions posed by the lecturer as the map-making session progressed. After the last session, students completed an anonymous, voluntary questionnaire (response rate of 78%). The majority of students found the draw-along maps useful (94%) and believed that its use should be continued in the future (93%). A significant increase (P < 0.001) was found in the test results of student cohorts who were given the current intervention compared to cohorts from previous years who were given mind maps as handouts only or had no intervention. The use of the draw-along mapping sessions were successful in focusing students during large class lectures while also providing them with a useful tool for their studies. © 2015 American Association of Anatomists.
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Mapping of land cover in northern California with simulated hyperspectral satellite imagery
NASA Astrophysics Data System (ADS)
Clark, Matthew L.; Kilham, Nina E.
2016-09-01
Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands, woodlands and mixed forests from the classification. This 12-class map had significantly improved accuracy of 85.1% (Kappa 0.83) and most classes had over 70% producer and user accuracies. Finally, we summarized important metrics from the multi-temporal Random Forests to infer the underlying chemical and structural properties that best discriminated our land-cover classes across seasons.
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Coastal Ecosystem Assessment, Development and Creation of a Policy Tool using Unmanned Aerial Vehicles (UAVs) for: A Case Study of Western Puerto Rico Coastal Region
NASA Astrophysics Data System (ADS)
Munoz Barreto, J.; Pillich, J.; Aponte Bermúdez, L. D.; Torres Pagan, G.
2017-12-01
This project utilizes low-cost Unmanned Aerial Vehicles (UAVs) based systems for different applications, such as low-altitude (high resolution) aerial photogrammetry for aerial analysis of vegetation, reconstruction of beach topography and mapping coastal erosion to understand, and estimated ecosystem values. As part of this work, five testbeds coastal sites, designated as the Caribbean Littoral Aerial Surveillance System (CLASS), were established. The sites are distributed along western Puerto Rico coastline where population and industry (tourism) are very much clustered and dense along the coast. Over the past year, rapid post-storm deployment of UAV surveying has been successfully integrated into the CLASS sites, specifically at Rincon (Puerto Rico), where coastal erosion has raised the public and government concern over the past decades. A case study is presented here where we collected aerial photos before and after the swells caused by Hurricane Mathew (October 2016). We merged the point cloud obtained from the UAV photogrammetric assessment with topo-bathymetric data, to get a complete beach topography. Using the rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for the pre-swell and post-swell events. Also, we used numerical modeling (X-Beach) to simulate the rate-of-change dynamics of the coastal zones and compare the model results to observed values (including multiple historic shoreline positions). In summary, our project has accomplished the first milestone which is the Development and Implementation of an Effective Shoreline Monitoring Program using UAVs. The activities of the monitoring program have enabled the collection of crucial data for coastal mapping along Puerto Rico's shorelines with emphasis on coastal erosion hot spots zones and ecosystem values. Our results highlight the potential of the synergy between UAVs, photogrammetry, and Geographic Information Systems to provide faster and low-cost reliable information on littoral zone changes compared with traditional techniques without losing in accuracy.
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The Cosmology Large Angular Scale Surveyor (CLASS)
NASA Technical Reports Server (NTRS)
Harrington, Kathleen; Marriange, Tobias; Aamir, Ali; Appel, John W.; Bennett, Charles L.; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe;
2016-01-01
The Cosmology Large Angular Scale Surveyor (CLASS) is a four telescope array designed to characterize relic primordial gravitational waves from in ation and the optical depth to reionization through a measurement of the polarized cosmic microwave background (CMB) on the largest angular scales. The frequencies of the four CLASS telescopes, one at 38 GHz, two at 93 GHz, and one dichroic system at 145/217 GHz, are chosen to avoid spectral regions of high atmospheric emission and span the minimum of the polarized Galactic foregrounds: synchrotron emission at lower frequencies and dust emission at higher frequencies. Low-noise transition edge sensor detectors and a rapid front-end polarization modulator provide a unique combination of high sensitivity, stability, and control of systematics. The CLASS site, at 5200 m in the Chilean Atacama desert, allows for daily mapping of up to 70% of the sky and enables the characterization of CMB polarization at the largest angular scales. Using this combination of a broad frequency range, large sky coverage, control over systematics, and high sensitivity, CLASS will observe the reionization and recombination peaks of the CMB E- and B-mode power spectra. CLASS will make a cosmic variance limited measurement of the optical depth to reionization and will measure or place upper limits on the tensor-to-scalar ratio, r, down to a level of 0.01 (95% C.L.).
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Generation of 2D Land Cover Maps for Urban Areas Using Decision Tree Classification
NASA Astrophysics Data System (ADS)
Höhle, J.
2014-09-01
A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a false-colour orthoimage. The produced 2D land cover map with six classes is then subsequently refined by using image analysis techniques. The proposed methodology is described step by step. The classification, assessment, and refinement is carried out by the open source software "R"; the generation of the dense and accurate digital surface model by the "Match-T DSM" program of the Trimble Company. A practical example of a 2D land cover map generation is carried out. Images of a multispectral medium-format aerial camera covering an urban area in Switzerland are used. The assessment of the produced land cover map is based on class-wise stratified sampling where reference values of samples are determined by means of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes "building" (99 %, 95 % CI: 95 %-100 %) and "road and parking lot" (90 %, 95 % CI: 83 %-95 %). Some other accuracy measures (overall accuracy, kappa value) and their 95 % confidence intervals are derived as well. The proposed methodology has a high potential for automation and fast processing and may be applied to other scenes and sensors.
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Annualized earthquake loss estimates for California and their sensitivity to site amplification
USGS Publications Warehouse
Chen, Rui; Jaiswal, Kishor; Bausch, D; Seligson, H; Wills, C.J.
2016-01-01
Input datasets for annualized earthquake loss (AEL) estimation for California were updated recently by the scientific community, and include the National Seismic Hazard Model (NSHM), site‐response model, and estimates of shear‐wave velocity. Additionally, the Federal Emergency Management Agency’s loss estimation tool, Hazus, was updated to include the most recent census and economic exposure data. These enhancements necessitated a revisit to our previous AEL estimates and a study of the sensitivity of AEL estimates subjected to alternate inputs for site amplification. The NSHM ground motions for a uniform site condition are modified to account for the effect of local near‐surface geology. The site conditions are approximated in three ways: (1) by VS30 (time‐averaged shear‐wave velocity in the upper 30 m) value obtained from a geology‐ and topography‐based map consisting of 15 VS30 groups, (2) by site classes categorized according to National Earthquake Hazards Reduction Program (NEHRP) site classification, and (3) by a uniform NEHRP site class D. In case 1, ground motions are amplified using the Seyhan and Stewart (2014) semiempirical nonlinear amplification model. In cases 2 and 3, ground motions are amplified using the 2014 version of the NEHRP site amplification factors, which are also based on the Seyhan and Stewart model but are approximated to facilitate their use for building code applications. Estimated AELs are presented at multiple resolutions, starting with the state level assessment and followed by detailed assessments for counties, metropolitan statistical areas (MSAs), and cities. AEL estimate at the state level is ∼$3.7 billion, 70% of which is contributed from Los Angeles–Long Beach–Santa Ana, San Francisco–Oakland–Fremont, and Riverside–San Bernardino–Ontario MSAs. The statewide AEL estimate is insensitive to alternate assumptions of site amplification. However, we note significant differences in AEL estimates among the three sensitivity cases for smaller geographic units.
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Soil property maps of Africa at 250 m resolution
NASA Astrophysics Data System (ADS)
Kempen, Bas; Hengl, Tomislav; Heuvelink, Gerard B. M.; Leenaars, Johan G. B.; Walsh, Markus G.; MacMillan, Robert A.; Mendes de Jesus, Jorge S.; Shepherd, Keith; Sila, Andrew; Desta, Lulseged T.; Tondoh, Jérôme E.
2015-04-01
Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the next decades. Protection and sustainable management of Africa's soil resources is crucial to achieve this. In this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or environmental management or policy and decision-making model. In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped, and monitored. Over the period 2008-2014, the AfSIS project has compiled two soil profile data sets (about 28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples) database -- the two data sets represent the most comprehensive soil sample database of the African continent to date. In addition a large set of high-resolution environmental data layers (covariates) was assembled. The point data were used in the AfSIS project to generate a set of maps of key soil properties for the African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Random forests modelling was used to relate the soil profile observations to a set covariates, that included global soil class and property maps, MODIS imagery and a DEM, in a 3D mapping framework. The model residuals were interpolated by 3D kriging, after which the kriging predictions were added to the random forests predictions to obtain the soil property predictions. The model predictions were validated with 5-fold cross-validation. The random forests models explained between 37% (exch. Na) and 85% (Al content) of the variation in the data. Results also show that globally predicted soil classes help improve continental scale mapping of the soil nutrients and are often among the most important predictors. We conclude that the first mapping results look promising. We used an automated modelling framework that enables re-computing the maps as new data becomes arrives, hereby gradually improving the maps. We showed that global maps of soil classes and properties produced with models that were predominantly calibrated on areas with plentiful observations can be used to improve the accuracy of predictions in regions with less plentiful data, such as Africa.
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Terrestrial Ecosystems - Topographic Moisture Potential of the Conterminous United States
USGS Publications Warehouse
Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi
2009-01-01
As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated topographic moisture potential classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe. A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Substrate moisture regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and therefore topographic moisture potential is one of the key input layers in this biophysical stratification. The method used to produce these topographic moisture potential classes was based on the derivation of ground moisture potential using a combination of computed topographic characteristics (CTI, slope, and aspect) and mapped National Wetland Inventory (NWI) boundaries. This method does not use climate or soil attributes to calculate relative topographic moisture potential since these characteristics are incorporated into the ecosystem model though other input layers. All of the topographic data used for this assessment were derived from the USGS 30-meter National Elevation Dataset (NED ) including the National Compound Topographic Index (CTI). The CTI index is a topographically derived measure of slope for a raster cell and the contributing area from upstream raster cells, and thus expresses potential for water flow to a point. In other words CTI data are 'a quantification of the position of a site in the local landscape', where the lowest values indicate ridges and the highest values indicate stream channels, lakes and ponds. These CTI values were compared to independent estimates of water accumulation by obtaining geospatial data from a number of sample locations representing two types of NWI boundaries: freshwater emergent wetlands and freshwater forested/shrub wetlands. Where these shorelines (the interface between the NWI wetlands and adjacent land) occurred, the CTI values were extracted and a histogram of their statistical distributions was calculated. Based on an evaluation of these histograms, CTI thresholds were developed to separate periodically saturated or flooded land, mesic uplands (moderately moist), and uplands. After the range of CTI values for these three different substrate moisture regimes was determined, the CTI values were grouped into three initial topographic moisture potential classes. As a final step in the generation of this national data layer, the uplands classification was subdivided into either very dry uplands or dry uplands. Very dry uplands were defined as uplands with relatively steep, south-facing slopes, and identification of this class was based on the slope and aspect datasets derived from the NED. The remaining uplands that did not meet these additional criteria were simply re-classified as dry uplands. The final National Topographic Moisture Potential dataset for the conterminous United States contains four classes: periodically saturated or flooded land (CTI = 18.5), mesic uplands (12 = 24 degrees and 91 degrees =< Aspect =< 314 degrees). This map shows a smoothed and generalized image of the four topographic moisture potential classes. Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.
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Usability Evaluation of Public Web Mapping Sites
NASA Astrophysics Data System (ADS)
Wang, C.
2014-04-01
Web mapping sites are interactive maps that are accessed via Webpages. With the rapid development of Internet and Geographic Information System (GIS) field, public web mapping sites are not foreign to people. Nowadays, people use these web mapping sites for various reasons, in that increasing maps and related map services of web mapping sites are freely available for end users. Thus, increased users of web mapping sites led to more usability studies. Usability Engineering (UE), for instance, is an approach for analyzing and improving the usability of websites through examining and evaluating an interface. In this research, UE method was employed to explore usability problems of four public web mapping sites, analyze the problems quantitatively and provide guidelines for future design based on the test results. Firstly, the development progress for usability studies were described, and simultaneously several usability evaluation methods such as Usability Engineering (UE), User-Centered Design (UCD) and Human-Computer Interaction (HCI) were generally introduced. Then the method and procedure of experiments for the usability test were presented in detail. In this usability evaluation experiment, four public web mapping sites (Google Maps, Bing maps, Mapquest, Yahoo Maps) were chosen as the testing websites. And 42 people, who having different GIS skills (test users or experts), gender (male or female), age and nationality, participated in this test to complete the several test tasks in different teams. The test comprised three parts: a pretest background information questionnaire, several test tasks for quantitative statistics and progress analysis, and a posttest questionnaire. The pretest and posttest questionnaires focused on gaining the verbal explanation of their actions qualitatively. And the design for test tasks targeted at gathering quantitative data for the errors and problems of the websites. Then, the results mainly from the test part were analyzed. The success rate from different public web mapping sites was calculated and compared, and displayed by the means of diagram. And the answers from questionnaires were also classified and organized in this part. Moreover, based on the analysis, this paper expands the discussion about the layout, map visualization, map tools, search logic and etc. Finally, this paper closed with some valuable guidelines and suggestions for the design of public web mapping sites. Also, limitations for this research stated in the end.
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A qualitative study on using concept maps in problem-based learning.
PubMed
Chan, Zenobia C Y
2017-05-01
The visual arts, including concept maps, have been shown to be effective tools for facilitating student learning. However, the use of concept maps in nursing education has been under-explored. The aim of this study was to explore how students develop concept maps and what these concept maps consist of, and their views on the use of concept maps as a learning activity in a PBL class. A qualitative approach consisting of an analysis of the contents of the concept maps and interviews with students. The study was conducted in a school of nursing in a university in Hong Kong. A total of 38 students who attended the morning session (20 students) and afternoon session (18 students) respectively of a nursing problem-based learning class. The students in both the morning and afternoon classes were allocated into four groups (4-5 students per group). Each group was asked to draw two concept maps based on a given scenario, and then to participate in a follow-up interview. Two raters individually assessed the concept maps, and then discussed their views with each other. Among the concept maps that were drawn, four were selected. Their four core features of those maps were: a) the integration of informative and artistic elements; b) the delivery of sensational messages; c) the use of images rather than words; and d) three-dimensional and movable. Both raters were concerned about how informative the presentation was, the composition of the elements, and the ease of comprehension, and appreciated the three-dimensional presentation and effective use of images. From the results of the interview, the pros and cons of using concept maps were discerned. This study demonstrated how concept maps could be implemented in a PBL class to boost the students' creativity and to motivate them to learn. This study suggests the use of concept maps as an initiative to motivate student to learn, participate actively, and nurture their creativity. To conclude, this study explored an alternative way for students to make presentations and pioneered the use of art-based concept maps to facilitate student learning. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature
NASA Astrophysics Data System (ADS)
Akay, S. S.; Sertel, E.
2016-06-01
Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.
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Evaluating Soil Health Using Remotely Sensed Evapotranspiration on the Benchmark Barnes Soils of North Dakota
NASA Astrophysics Data System (ADS)
Bohn, Meyer; Hopkins, David; Steele, Dean; Tuscherer, Sheldon
2017-04-01
The benchmark Barnes soil series is an extensive upland Hapludoll of the northern Great Plains that is both economically and ecologically vital to the region. Effects of tillage erosion coupled with wind and water erosion have degraded Barnes soil quality, but with unknown extent, distribution, or severity. Evidence of soil degradation documented for a half century warrants that the assumption of productivity be tested. Soil resilience is linked to several dynamic soil properties and National Cooperative Soil Survey initiatives are now focused on identifying those properties for benchmark soils. Quantification of soil degradation is dependent on a reliable method for broad-scale evaluation. The soil survey community is currently developing rapid and widespread soil property assessment technologies. Improvements in satellite based remote-sensing and image analysis software have stimulated the application of broad-scale resource assessment. Furthermore, these technologies have fostered refinement of land-based surface energy balance algorithms, i.e. Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) algorithm for evapotranspiration (ET) mapping. The hypothesis of this study is that ET mapping technology can differentiate soil function on extensive landscapes and identify degraded areas. A recent soil change study in eastern North Dakota resampled legacy Barnes pedons sampled prior to 1960 and found significant decreases in organic carbon. An ancillary study showed that evapotranspiration (ET) estimates from METRIC decreased with Barnes erosion class severity. An ET raster map has been developed for three eastern North Dakota counties using METRIC and Landsat 5 imagery. ET pixel candidates on major Barnes soil map units were stratified into tertiles and classified as ranked ET subdivisions. A sampling population of randomly selected points stratified by ET class and county proportion was established. Morphologic and chemical data will be recorded at each sampling site to test whether soil properties correlate to ET, thus serving as a non-biased proxy for soil health.
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Seismic hazard analysis for Jayapura city, Papua
NASA Astrophysics Data System (ADS)
Robiana, R.; Cipta, A.
2015-04-01
Jayapura city had destructive earthquake which occurred on June 25, 1976 with the maximum intensity VII MMI scale. Probabilistic methods are used to determine the earthquake hazard by considering all possible earthquakes that can occur in this region. Earthquake source models using three types of source models are subduction model; comes from the New Guinea Trench subduction zone (North Papuan Thrust), fault models; derived from fault Yapen, TareraAiduna, Wamena, Memberamo, Waipago, Jayapura, and Jayawijaya, and 7 background models to accommodate unknown earthquakes. Amplification factor using geomorphological approaches are corrected by the measurement data. This data is related to rock type and depth of soft soil. Site class in Jayapura city can be grouped into classes B, C, D and E, with the amplification between 0.5 - 6. Hazard maps are presented with a 10% probability of earthquake occurrence within a period of 500 years for the dominant periods of 0.0, 0.2, and 1.0 seconds.
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Macroinvertebrate-based assessment of biological condition at selected sites in the Eagle River watershed, Colorado, 2000-07
USGS Publications Warehouse
Zuellig, Robert E.; Bruce, James F.; Healy, Brian D.; Williams, Cory A.
2010-01-01
The U.S. Geological Survey (USGS), in cooperation with the Colorado River Water Conservation District, Eagle County, Eagle River Water and Sanitation District, Upper Eagle Regional Water Authority, Colorado Department of Transportation, City of Aurora, Town of Eagle, Town of Gypsum, Town of Minturn, Town of Vail, Vail Resorts, Colorado Springs Utilities, Denver Water, and the U.S. Department of Agriculture Forest Service (FS), compiled macroinvertebrate (73 sites, 124 samples) data previously collected in the Eagle River watershed from selected USGS and FS studies, 2000-07. These data were analyzed to assess the biological condition (that is, biologically ?degraded? or ?good?) at selected sites in the Eagle River watershed and determine if site class (for example, urban or undeveloped) described biological condition. An independently developed predictive model was applied to calculate a site-specific measure of taxonomic completeness for macroinvertebrate communities, where taxonomic completeness was expressed as the ratio of observed (O) taxa to those expected (E) to occur at each site. Macroinvertebrate communities were considered degraded at sites were O/E values were less than 0.80, indicating that at least 20 percent of expected taxa were not observed. Sites were classified into one of four classes (undeveloped, adjacent road or highway or both, mixed, urban) using a combination of riparian land-cover characteristics, examination of topographic maps and aerial imagery, screening for exceedances in water-quality standards, and best professional judgment. Analysis of variance was used to determine if site class accounted for variability in mean macroinvertebrate O/E values. Finally, macroinvertebrate taxa observed more or less frequently than expected at urban sites were indentified. This study represents the first standardized assessment of biological condition of selected sites distributed across the Eagle River watershed. Of the 73 sites evaluated, just over half (55 percent) were considered in good biological condition (O/E greater than 0.80). The remaining sites were either consistently biologically degraded (30 percent; O/E less than 0.80) or varied annually between good and degraded condition (15 percent; O/E is less than or greater than 0.80). Sites primarily affected by urbanization were among the most severely degraded (lowest O/E values) when compared to other site classes. Although most urban sites were among the most severely degraded (lowest O/E values), a few sites had nearly intact macroinvertebrate communities (O/E near 1.0). Similar observations were noted among sites classified as mixed. Thirteen macroinvertebrate taxa were indentified that occurred more or less frequently than expected at urban sites. Additionally, six other taxa were impartial (tolerant) to the same conditions. Combined, these 19 taxa provide an opportunity to enhance the interpretation of future studies in the Eagle River watershed, but will require better insight into the responses of these taxa to specific stressors. Understanding the sources of variability affecting biological condition along with why some sites expected to be degraded, but showed otherwise, will have clear implications for mitigation efforts. Integrating results of this study with field and laboratory investigations will greatly enhance the ability to identify causal factors affecting biological condition at degraded sites, the logical next step. Information generated from such integrative studies will be imperative for well targeted mitigation efforts in the Eagle River watershed.
