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The proposed dataset can be used to test the precision of scaling SfM reconstructed objects using camera positioning data. In addition position uncertainty data from a DJI GPS RTK in X,Y and Z is added, so the propagation of uncertainty from the positioning sensor to the calculated scale can be calculated. The camera positions are also given with any uncertainty, so other types of position uncertainty can be used to test how the system will react with different uncertainty inputs. Images from two objects are given - an angel statue and a wind turbine blade. Images are taken in a semi-circle pattern around the object and a total of 19 images are taken from each object. The positions of the images are given in a separate file, while all the images contain EXIF data with the used camera parameters. All images are captured using Canon 5Ds DSLR camera. More information on how the scale and scale uncertainty can be calculated are present in the referenced paper.
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Here are the results in a paper entitled "Characterization of the 2008 phreatomagmatic eruption of Okmok from ArcticDEM and InSAR: deposition, erosion, and deformation" submitted to JGR Solid Earth in 2020. The main revision compared to version 1: This revision does not use one DEM (acquired on 15 May 2016) that was partly contaminated by clouds in the north flank of Ahmanilix. This revision mostly improves the result of the elevation change rate (rate.tif), but it also slightly changes the elevation change data and its corresponding uncertainties. It includes the 2-m resolution surface elevation change of the 2008 Okmok eruption (Fig. 3a in the paper) and the 2-m resolution post-eruptive elevation change rate map (Fig. 4), as well as the corresponding uncertainties (Fig. S3). It also includes the boundary of the proximal deposit field classified using a minimum elevation increase of 2 m, the boundary of large slope failure, and the shorelines of two lakes (Fig. 3a and S5) at different acquisition times. The GeoTIFF files can be viewed in free and open-source software QGIS, in Google Earth, or by Matlab using code https://github.com/ihowat/setsm_postprocessing/blob/master/readGeotiff.m. The shapefiles can be viewed in QGIS. Google Earth may not show some of the shapefiles well.
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The folder contains the files for the replication of the main results in our paper.
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Data for solitary wave interactions with array of structures
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MATLAB code for ellipsoid fitting : using binarized image MATLAB code for measuring SPO : measuring aspect ratio and grain size (length of major axis); Sorted SPO direction data with aspect ratio and grain size SPO data of BK-1 sample (fault gouge) : Trend - Plunge format data (appearent and restored) Binarized image of BK-1 sample
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Raw data and analysis scripts
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This dataset includes the yearly decomposed concentrations of four spatial components ("long-range", "mid-range", "neighborhood", "near-source") for PM2.5 and NO2, from year-2000 to year-2015. The concentrations are at the census block level. The unit of concentrations is ug/m3 for both pollutants. Block is identified by variable "block_fip"; the longitude and latitude of each block centroid are indicated by "longitude" and "latitude". Names of concentration variables follow the pattern as "COMPONENT_YEAR". "COMPONENT" represents four spatial components; "YEAR" represents the last two digits of year-2000 to year-2015. For example, "long-range_00" represents the "long-range" component concentrations for the year-2000.
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The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. A series of 42 river function indicators were used to characterize divergent aspects of river ecosystems while also serving to consolidate the dimensionality of these complex systems into a manageable number of measures. These indicators were developed from a comprehensive literature review of the environmental impacts of hydropower and are associated with six main categories of impacts to river systems: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. The three tools comprising the DSP toolkit and associated data include: 1) Science-Based Questionnaire (SBQ): A series of structured survey-style 140 questions for understanding impacts of dams on river ecosystems were developed through a global literature review. A spreadsheet program was developed to summarize the results of questions into evidence of dam impacts on the 42 ecological indicators. Output is provided in tabular and graphical/chart formats. 2) Environmental Envelope Model (EEM): The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. A dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns were compiled and combined with data on ecological indicators measured at those sites. The data were used to develop models predicting impacts of dams on ecological indicators. A total of 247 envelopes and weighting factors, representing the individual effect of each variable on each ecological indicator, were developed in a spreadsheet program. 3) River Function Linkage Assessment Tool (RFLAT): The purpose of RFLAT is to examine causal relationships amongst indicators. Based on literature review, a node and edge dataset was developed representing causal relationships (“edges”) between ecological indicators (“nodes)”. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks.
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The excel data and the original data (uncropped, unmodified images) for figures .
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LF--Pumping frequency HF--Probing frequency Fs--Sample Frequency All the sample length is 1M points the probing amplitude is 10Vpp the pumping amplitude is 3N except for the data of Figure 7
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