Using a SPATIAL INS/GNSS MEMS Unit to Detect Local Gravity Variations in Static and Mobile Experiments: First Results.

In this study, we present the feasibility of using gravity measurements made with a small inertial navigation system (INS) during in situ experiments, and also mounted on an unmanned aerial vehicle (UAV), to recover local gravity field variations. The INS operated is the SPATIAL one developed by Advanced Navigation, which has three-axis accelerometers. When the temperature bias is corrected, these types of INS are powerful enough to present the periodic signal corresponding to the solid Earth tides. There is also a clear correlation with the data measured at different altitudes by a CG5 gravimeter. However, these data were recorded on static points, so we also studied the INS in a moving platform on a UAV. Because there are a lot of vibrations recorded by the INS (wind, motor, on-board computer), the GPS and accelerometric data need to be filtered extensively. Once the data are corrected so they do not show thermal bias and low-pass filtered, we take the second derivative of the altitude (GPS) data to find the radial accelerometry of the drone and compare it to the radial accelerometry measured directly by the INS, in order to isolate the accelerometric signal that is related to the area that is being studied and the altitude. With a high enough precision, this method could be used to obtain the gravity variations due to the topography and density variations in the ground.

Signatures of Life Detected in Images of Rocks Using Neural Network Analysis Demonstrate New Potential for Searching for Biosignatures on the Surface of Mars.

Microorganisms play a role in the construction or modulation of various types of landforms. They are especially notable for forming microbially induced sedimentary structures (MISS). Such microbial structures have been considered to be among the most likely biosignatures that might be encountered on the martian surface. Twenty-nine algorithms have been tested with images taken during a laboratory experiment for testing their performance in discriminating mat cracks (MISS) from abiotic mud cracks. Among the algorithms, neural network types produced excellent predictions with similar precision of 0.99. Following that step, a convolutional neural network (CNN) approach has been tested to see whether it can conclusively detect MISS in images of rocks and sediment surfaces taken at different natural sites where present and ancient (fossil) microbial mat cracks and abiotic desiccation cracks were observed. The CNN approach showed excellent prediction of biotic and abiotic structures from the images (global precision, sensitivity, and specificity, respectively, 0.99, 0.99, and 0.97). The key areas of interest of the machine matched well with human expertise for distinguishing biotic and abiotic forms (in their geomorphological meaning). The images indicated clear differences between the abiotic and biotic situations expressed at three embedded scales: texture (size, shape, and arrangement of the grains constituting the surface of one form), form (outer shape of one form), and pattern of form arrangement (arrangement of the forms over a few square meters). The most discriminative components for biogenicity were the border of the mat cracks with their tortuous enlarged and blistered morphology more or less curved upward, sometimes with thin laminations. To apply this innovative biogeomorphological approach to the images obtained by rovers on Mars, the main physical and biological sources of variation in abiotic and biotic outcomes must now be further considered.

Time-variations of equivalent water heights'from Grace Mission and in-situ river stages in the Amazon basin / Variações temporais do equivalente à altura d'água obtidas da Missão Grace e da altura d'água in-situ nos rios da bacia Amazônica

Gravity Recovery and Climate Experiment (GRACE) mission is dedicated to measuring temporal variations of the Earth's gravity field. In this study, the Stokes coefficients made available by Groupe de Recherche en Géodésie Spatiale (GRGS) at a 10-day interval were converted into equivalent water height (EWH) for a ~4-year period in the Amazon basin (from July-2002 to May-2006). The seasonal amplitudes of EWH signal are the largest on the surface of Earth and reach ~ 1250mm at that basin's center. Error budget represents ~130 mm of EWH, including formal errors on Stokes coefficient, leakage errors (12 ~ 21 mm) and spectrum truncation (10 ~ 15 mm). Comparison between in situ river level time series measured at 233 ground-based hydrometric stations (HS) in the Amazon basin and vertically-integrated EWH derived from GRACE is carried out in this paper. Although EWH and HS measure different water bodies, in most of the cases a high correlation (up to ~80 percent) is detected between the HS series and EWH series at the same site. This correlation allows adjusting linear relationships between in situ and GRACE-based series for the major tributaries of the Amazon river. The regression coefficients decrease from up to down stream along the rivers reaching the theoretical value 1 at the Amazon's mouth in the Atlantic Ocean. The variation of the regression coefficients versus the distance from estuary is analysed for the largest rivers in the basin. In a second step, a classification of the proportionality between in situ and GRACE time-series is proposed.

A missão espacial Gravity Recovery and Climate Experiment (GRACE) é dedicada às medidas das variações temporais no campo gravitacional da Terra. Neste estudo, os coeficientes de Stokes disponibilizados pelo Groupe de Recherche en Géodésie Spatiale (GRGS) com intervalos de 10 dias foram convertidos no equivalente à altura d'água (EWH) para um período de 4 anos na bacia Amazônica (de julho de 2002 a maio de 2006). As amplitudes sazonais do EWH no centro da bacia são as maiores encontradas no mundo (~1250 mm). Os erros na estimativa do EWH são de ~130 mm, incluindo os erros nos coeficientes de Stokes, erros de vazamento de informações das bacias vizinhas (12 ~ 21 mm) e truncamento do espectro (10 ~ 15 mm). Neste trabalho, são feitas comparações entre as informações de altura d'água in-situ medidas em 233 estações hidrológicas (HS) na bacia Amazônica com EWH obtido pelo GRACE. Embora o EWH e as HS meçam diferentes corpos d'água, na maioria dos casos, uma alta correlação (até 80 por cento) é encontrada entre ambas as séries ao mesmo local. Esta alta correlação permite ajustar uma relação linear entre as séries para os maiores tributários do rio Amazonas. O coeficiente de regressão decresce da montante para a vazante, tendendo para o valor teórico 1 na foz do rio Amazonas. A variação deste coeficiente versus a distância ao estuário é analisada para os maiores rios da bacia. Em uma segunda etapa, uma classificação da defasagem entre as séries dos dados in-situ e GRACE são apresentadas.