The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklin’s exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context

30-m HRSC DTM Mosaic of Gale Crater, Mars

Digital terrain model (DTM) mosaic of Gale crater, Mars, processed from High-Resolution Stereo Camera (HRSC) stereo images using the modification of DLR-VICAR described by Kim and Muller (2009). Format: GeoTiff Projection: Equidistant cylindrical Datum: Spheroid (r = 3396.190 km) Bit depth: Float32 Grid-spacing: 30 m/pixel Terrain reference: 200-m MOLA and HRSC blended global DTM (Fergason et al. 2018) HRSC source images: H1938_0000, H1927_0000, and H1916_0000The first author is now at Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California. Contact: [email protected]

CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK

Classification and identification of agricultural products are usually done manually. This method is prone to error and subjectivity of the user. The other method, laboratory testing, can only be done by professional and takes time. Classification and identification of cane sugar in Indonesia is also done with similar process with no standardization. In the production of cane sugar, several stages and condition produce different kinds of sugar, resulting in the need of supervision. In automation and standardization of quality, quantized identification process needs to be done. System was designed as Artificial Neural Network with one hidden layer using Levenberg-Marquardt algorithm. Colour and textural features were extracted from 120 images of cane sugar for Artificial Neural Network inputs. After feature reduction, the designed system could identify 8 kinds of cane sugar with success rate of 85%. Designed system was also tested for different learning rate, activating function, ratio of training and testing set and different testing conditions. Application with GUI was also made for user

The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

International audienceThis 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for theExoMars Rosalind Franklin rover mission. The map represents our current understanding ofbedrock units and their relationships prior to Rosalind Franklin’s exploration of this location.The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units.The bedrock units were identified using visible and near-infrared remote sensing datasets.The objectives of this map are (i) to identify where the most astrobiologically relevant rocksare likely to be found, (ii) to show where hypotheses about their geological context (withinOxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform boththe long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activityplanning for rover exploration, and (iv) to allow the samples analysed by the rover to beinterpreted within their regional geological context