Contributors: Raúl Roberto poppiel, Jose Alexandre Dematte, Marilusa Pinto Coelho Lacerda, José Lucas Safanelli, Rodnei Rizzo, Manuel Pereira de Oliveira junior, Jean Jesus Novais
... Maps of clay, silt and sand contents (g kg-1) predicted at 0-20 cm, 20-60 cm and 60-100 cm depths intervals (3D) obtained by random forest regression in Google Earth Engine. Gridded soil information covers Midwest Brazil, from 12° S to 20° S and from 45° W to 54° W, and is available with 250m resolution. The maps were cross-validated and had Coefficient of Determination ranging from 0.64 to 0.85 at all depth intervals.
Contributors: Francisco BELTRAN
... Supplemental data for paper manuscript "Indirect determination of shear wave velocity in slow formations from full-wave sonic logging", submitted to the Journal of Rock Mechanics and Geotechnical Engineering. Data includes three ASCII files: a sample full-wave sonic log, a FORTRAN code for processing the sonic log, and an ABAQUS/Standard input file used to determine the functional dependency of Poisson's ratio on the shape of the wave packets. The data is intended to be used together with the paper. The data could be used for an independent review of the methodology proposed in the paper as well as a starting point for further research in the generalization of the proposed method to different borehole geometries and sonic probe designs.
Contributors: Phil Symonds
... These data were used to quantify the impacts of air pollution policies on population health and health inequalities within a microsimulation model, MicroEnv . They provide a basis for comparing results from similar models and allow researchers to integrate additional model components.  P. Symonds, E. Hutchinson, A. Ibbetson, J. Taylor, J. Milner, Z. Chalabi, M. Davies, P. Wilkinson, MicroEnv: A microsimulation model for quantifying the impacts of environmental policies on population health and health inequalities, Science of The Total Environment, Volume 697, (2019) 134105, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2019.134105.
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Contributors: Qiankun Liu, Jingang Jiang, Changwei Jing, Zhong Liu, Jiaguo Qi
... In this paper, a new, alternative, multi-scale, multi-pollution source waste load allocation (WLA) system was developed, with a goal to produce optimal, fair quota allocations at multiple scales. The new WLA system integrates multi-constrained environmental Gini coefficients (EGCs) and Delphi-analytic hierarchy process (Delphi-AHP) optimization models to achieve the stated goal. This dataset consists of the raw data and the source code of models (The multi-constrained environmental Gini coefficients and Delphi-analytic hierarchy process optimization models). The source code of the multi-constrained EGCs and Delphi-AHP models was used to run the program in MATLAB environment to allocate waste load reduction quotas at both the regional scale and the site-specific scale with multiple pollution sources. The raw data mainly consists of the following two parts: (1) The shp files of various geographic information data, which was used to depicture the administrative divisions, pollution source distribution, geographical characteristics and patterns of Xian-jiang watershed; (2) The basic data includes the statistical yearbook data of villages and towns in Ningbo city, the various indicator data using to calculate the weights at criteria level and decision-making level, the contribution coefficients, and the EGC values of the three pollutants. On the basis of these data, a new, alternative, multi-scale, multi-sector optimal WLA framework was developed. The new scheme provides decision-makers critical information (i.e., the best compromise solutions of WLA) and practical guidance as they address the related water pollution control. The results, in comparison with existing practices by the local governments, suggested that the pollution discharge quota at regional scale is much fairer than the existing WLA and, even have some environmental economic benefits at pollutant source scale after optimal WLA. Some important conclusions had been found: 1) Reductions and proportions of pollutants at regional scale are significantly associated with the region’s actual socioeconomic development modes. 2）There are certain characteristics that high-reduced pollution sources tend to share (which are listed in the article). The sources with the above features should be the top priorities in the reduction of removals. 3）Most previous studies reported primarily on the WLA of removals among point sources pollution. Conversely, we found that the industrial pollution source should be the last option for reduction from an environmental-economic benefit perspective. Instead, the often overlooked types, such as agricultural non-point source and domestic sources, deserve more attention, especially in extensive rural areas.
Contributors: Ryan Watkins
... Version 1.0, September 9, 2019 Purpose: Created as part of a project funded by NASA’S Lunar Data Analysis Program (LDAP), the purpose of this dataset is to provide locations and diameters of boulders around small, young impact craters on the Moon. These boulder counts were conducted as part of a study aimed at determining regolith production rates and assessing landing site hazards, as discussed in the associated publications. Researchers are encouraged to read the publications and data description document to understand how the data was acquired and used. This database contains boulder distributions around small (< 1 km), young (< 200 Ma) lunar impact craters located near spacecraft landing sites. The most up-to-date database contains boulder diameters and coordinates for counts around Surveyor (Apollo 12), Cone (Apollo 14), North Ray (Apollo 16), South Ray (Apollo 16), Camelot (Apollo 17), and Zi Wei (Chang’e-3) craters. Boulders were manually identified and measured on Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images (Robinson et al., 2010) at scales of ~0.5-2 m/pixel. LROC NAC images allow for boulders ~1-2m in size and larger to be identified and measured. The tools for measuring boulders were CraterTools (Kneissl et al., 2011) and Crater Helper Tools (Nava, 2011), both developed for the ArcMap GIS platform. These boulder distributions are being used to understand boulder degradation rates on the lunar surface, and to assess landing site hazards for future surface missions to the Moon. This dataset is being archived in Mendeley Data and at the Planetary Data System (PDS) Cartography and Imaging Node for use in future boulder distribution and landing hazard studies. Future boulder counts and any refinements to existing measurements will be uploaded into subsequent versions of this dataset here and at the PDS IMG Annex: https://astrogeology.usgs.gov/search/map/Moon/Research/Regolith/lunar_boulder_data_bundle
Data for: MAPPING CHARACTERISTICS OF AT-RISK POPULATION TO DISASTERS IN THE CONTEXT OF BRAZILIAN EARLY WARNING SYSTEM
Contributors: Regina Célia dos Santos Alvalá, Mariane Assis Dias, Silvia Saito, Claudio Stenrer, Cayo Franco, Pilar Amadeu, Julia Ribeiro, Rodrigo Santana, Carlos Nobre
... This dataset includes 6.437 polygons of BATER from 825 brazilian municipalites with landslides and hydrological risk areas that was used to characterize the at-risk population in this present article. Also is available the data dictionary that describes the variables about the residents and households. This datased was produced in 2018 by CEMADEN and IBGE, as detailed in the article. It is available for everyone in the link: https://www.ibge.gov.br/apps/populacaoareasderisco/
Data for: Landscape structural analysis of the Lençóis Maranhenses National Park: Implications for conservation
Contributors: Yuri Teixeira Amaral, Larissa Barreto, Edyane Moraes dos Santos, MILTON RIBEIRO
... Matadata of final mapping and landscape analysis of Lençóis Maranhenses National Park.
Contributors: Tongtong Wang, Yuankun Luo, Zhilin Tao, Weijie Chen, Xin Gu
... The zip file contains project files, screenshots of research results, chart data, experimental data, simulation data, and grid independence verification data.
Contributors: Olanrewaju Lawal
... Exposure capture factors which could be manifested in the magnitude and intensity of long-term changes in climate (Intergovernmental Panel on Climate Change, 2007) and in this context factors with impact on agricultural production. Temperature and rainfall were used to capture the extent to which Maize is exposed to climate change. Data was sourced from the Centre for Environmental Data Analysis (CRU TS release 4), with data extracted for 1941 - 2015. The data were processed within R (Version 3.4.2), within this environment the mean (temperature and rainfall) for northern and southern parts of the country were computed. The growing season for Maize in the north spans from May to September while in the south it starts from March and ends in August (FAO, 2018). Furthermore, long (1941 – 2015) and short (1961 – 2015) term averages for the respective growing season were computed for each of the regions. Following the computation of the long and short-term averages, exposure was computed as the ratio of the long-term to the short-term averages. With exposure index for rainfall and temperature computed separately, the two were added to get the combined exposure index. A high value indicates high exposure to climate variability. In this dataset, the exposure index is presented in raster format (Geotiff) to allow for easy processing across GIS software. In addition, the boundaries of the northern and the southern regions were also included as shapefiles.
Contributors: Jacqueline Zadelaar
... Are Individual Differences Quantitative Or Qualitative? An Integrated Behavioral And Fmri Mimic Approach. Authors: Jacqueline N. Zadelaar, Wouter D. Weeda, Lourens J. Waldorp, Anna C. K. Van Duijvenvoordee, N. E. Blankenstein, Hilde M. Huizenga In cognitive neuroscience there is a growing interest in individual differences. We propose the Multiple Indicators Multiple Causes (MIMIC) model of combined behavioral and fMRI data to determine whether such differences are quantitative or qualitative in nature. A simulation study revealed the MIMIC model to have adequate power for this goal, and parameter recovery to be satisfactory. The MIMIC model was illustrated with a re-analysis of Van Duijvenvoorde et al. (2016) and Blankenstein et al. (2018) decision making data. This showed individual differences in Van Duijvenvoorde et al. (2016) to originate in qualitative differences in decision strategies. Parameters indicated some individuals to use an expected value decision strategy, while others used a loss minimizing strategy, distinguished by individual differences in vmPFC activity. Individual differences in Blankenstein et al. (2018) were explained by quantitative differences in risk aversion. Parameters showed that more risk averse individuals preferred safe over risky choices, as predicted by heightened vmPFC activity. We advocate using the MIMIC model to empirically determine, rather than assume, the nature of individual differences in combined behavioral and fMRI datasets.