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This work presents a Non-Ionizing Radiation (NIR) measurement campaign and proposes a specific measurement method for trajectography radars. This kind of radar has a high gain narrow beam antenna and emits a high power signal. Power density measurements from a C-band trajectography radar are carried out using bench equipment and a directional receiving antenna, instead of the commonly used isotropic probe. The measured power density levels are assessed for compliance test via comparison with the occupational and general public exposure limit levels of both the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Brazilian National Telecommunication Agency (Anatel). The limit for the occupational public is respected everywhere, evidencing the safe operation of the studied radar. However, the limit for the general public is exceeded at a point next to the radar's antenna, showing that preventive measures are needed.

Three SAR-derived observations of dark surface patches along the Northeastern Brazilian coastline by the end of 2019 were misreported in the Brazilian media as oil spill-related. Unfortunately, these observations were misled by false positives or look-alikes. Therefore, this paper aims to technically evaluate these look-alike classes by analyzing image attributes found to be helpful to the identification of ocean targets, including oil spills, rain cells, biofilms, and low wind conditions. We use image augmentation to extend our dataset size and create the probability density function curves. The processing includes image segmentation, optimal attribute extraction, and classification with random forest classifiers. Our results contrast with the open-source oil spill detection system and patch classifier methodology called "RIOSS." Analysis of the feature probability density functions based on optimal attributes is promising since we could capture most of the false positive targets in the three SAR-reported images in 2019. The only exception was the biofilm slick observed on October 28th, where the RIOSS mistakenly classified this organic patch as a low wind region with oil spots. This pitfall is acceptable at this project stage since we had only five biogenic film samples to train the algorithm.

The estimation of the vertical components of built-up areas from free Digital Elevation Model (DEM) global data filtered by multi-scale convolutional, morphological and textural transforms are generalized at the spatial resolution of 250 meters using linear least-squares regression techniques. Six test cases were selected: Hong Kong, London, New York, San Francisco, Sao Paulo, and Toronto. Five global DEM and two DEM composites are evaluated in terms of 60 combinations of linear, morphological and textural filtering and different generalization techniques. Four generalized vertical components estimates of built-up areas are introduced: the Average Gross Building Height (AGBH), the Average Net Building Height (ANBH), the Standard Deviation of Gross Building Height (SGBH), and the Standard Deviation of Net Building Height (SNBH). The study shows that the best estimation of the net GVC of built-up areas given by the ANBH and SNBH, always contains a greater error than their corresponding gross GVC estimation given by the AGBH and SGBH, both in terms of mean and standard deviation. Among the sources evaluated in this study, the best DEM source for estimating the GVC of built-up areas with univariate linear regression techniques is a composite of the 1-arcsec Shuttle Radar Topography Mission (SRTM30) and the Advanced Land Observing Satellite (ALOS) World 3D-30 m (AW3D30) using the union operator (CMP_SRTM30-AW3D30_U). A multivariate linear model was developed using 16 satellite features extracted from the CMP_SRTM30-AW3D30_U enriched by other land cover sources, to estimate the gross GVC. A RMSE of 2.40 m and 3.25 m was obtained for the AGBH and the SGBH, respectively. A similar multivariate linear model was developed to estimate the net GVC. A RMSE of 6.63 m and 4.38 m was obtained for the ANBH and the SNBH, respectively. The main limiting factors on the use of the available global DEMs for estimating the GVC of built-up areas are two. First, the horizontal resolution of these sources (circa 30 and 90 meters) corresponds to a sampling size that is larger than the expected average horizontal size of built-up structures as detected from nadir-angle Earth Observation (EO) data, producing more reliable estimates for gross vertical components than for net vertical component of built-up areas. Second, post-production processing targeting Digital Terrain Model specifications may purposely filter out the information on the vertical component of built-up areas that are contained in the global DEMs. Under the limitations of the study presented here, these results show a potential for using global DEM sources in order to derive statistically generalized parameters describing the vertical characteristics of built-up areas, at the scale of 250x250 meters. However, estimates need to be evaluated in terms of the specific requirements of target applications such as spatial population modelling, urban morphology, climate studies and so on., Competing Interests: The authors have declared that no competing interests exist.

The unsuitable construction of unpaved roads has been causing problems related to the formation of erosive processes, sediments in watersheds, bogs, flooding, and holes. Presuming that the areas where flow accumulation intersects unpaved roads represent risk points, our objectives are (1) to develop a qualitative method based on the GIS software management tool (FlowAccRoad) for the identification of the intersection points between flow accumulation and roads and (2) to verify the discrepancy between the points of intersection produced by digital elevation models (DEM) accounting for different spatial resolutions. In the GIS environment, we used the Shuttle Radar Topography Mission (SRTM) and Goiania (GOI) digital elevation models for the modeling of flow accumulation and vectorization of the unpaved roads, both of which are based on the Bandeira Stream Watershed in Goiania, Goiás, Brazil. This highlights that 54 points of intersection between the flow accumulation and unpaved roads present problems related to erosive processes and quagmires, among others. The FlowAccRoad method identified the principal critical points observed in the field, using both the DEM of 30.4 m of spatial resolution (SRTM) and also of 4.8 m of spatial resolution (GOI). From the FlowAccRoad method, we observed that 91% of the risk points identified through the GOI DEM were located less than 20 m from valid points in the field by using GPS. Analyzing the SRTM DEM, only 45% of the critical risk points identified by the method were located less than 20 m from valid points in the field.

In forensic geophysical research, using controlled experiments assists forensic search practitioners in identifying optimal technique(s) and equipment configuration(s) in different burial scenarios. The objective of the research is to observe the geophysical response to different types of buried wrappings, taking into consideration the influence that the presence or absence of a decomposing body (pig carcass) in a lateritic soil in central-western Brazil can have. In this article, the GPR results are presented after a 15day burial period during the rainy season, and the results of Electrical resistivity tomography (ERT) after a burial period of 6 months during the dry season. The controlled site was built in the research area of the University of Brasília, in a region with soil, typical of the Brazilian savannah. 14 simulated clandestine graves of murder victims were constructed, in which seven pig carcasses were wrapped or covered by: soil (backfill), a plastic bag, a bed sheet, cement block, construction debris, a wooden coffin and hydrated lime, respectively a further seven burials, presenting only the wrappings acted as comparison (control burial). During the GPR survey a 400MHz frequency antenna was used. The resistivity surveys were carried out before and after the burial of the targets with dipole-dipole and Wenner-Schlumberger array configurations, with different spacing of electrodes (1.00 and 0.50m). The comparison between the various scenarios with and without pig carcasses revealed that good reflection events occurred mainly due to the wrappings and that pig carcasses attenuated the GPR signal. Electrical resistivity results showed that the Wenner-Schlumberger array presents a better resolution of the lateral boundaries of the burials, and the dipole-dipole array presents a better sensitivity to heterogeneity of the buried materials. The burials with the pig carcasses wrapped in the various materials presented better resistivity contrasts as opposed to the control burials., (Copyright © 2018 Elsevier B.V. All rights reserved.)