scholarly journals An open-source semi-automated processing chain for urban obia classification

Author(s):  
T. Grippa ◽  
M. Lennert ◽  
B. Beaumont ◽  
S. Vanhuysse ◽  
N. Stephenne ◽  
...  
2017 ◽  
Vol 9 (4) ◽  
pp. 358 ◽  
Author(s):  
Taïs Grippa ◽  
Moritz Lennert ◽  
Benjamin Beaumont ◽  
Sabine Vanhuysse ◽  
Nathalie Stephenne ◽  
...  

2021 ◽  
Vol 14 (11) ◽  
pp. 6711-6740
Author(s):  
Ranee Joshi ◽  
Kavitha Madaiah ◽  
Mark Jessell ◽  
Mark Lindsay ◽  
Guillaume Pirot

Abstract. A huge amount of legacy drilling data is available in geological survey but cannot be used directly as they are compiled and recorded in an unstructured textual form and using different formats depending on the database structure, company, logging geologist, investigation method, investigated materials and/or drilling campaign. They are subjective and plagued by uncertainty as they are likely to have been conducted by tens to hundreds of geologists, all of whom would have their own personal biases. dh2loop (https://github.com/Loop3D/dh2loop, last access: 30 September 2021​​​​​​​) is an open-source Python library for extracting and standardizing geologic drill hole data and exporting them into readily importable interval tables (collar, survey, lithology). In this contribution, we extract, process and classify lithological logs from the Geological Survey of Western Australia (GSWA) Mineral Exploration Reports (WAMEX) database in the Yalgoo–Singleton greenstone belt (YSGB) region. The contribution also addresses the subjective nature and variability of the nomenclature of lithological descriptions within and across different drilling campaigns by using thesauri and fuzzy string matching. For this study case, 86 % of the extracted lithology data is successfully matched to lithologies in the thesauri. Since this process can be tedious, we attempted to test the string matching with the comments, which resulted in a matching rate of 16 % (7870 successfully matched records out of 47 823 records). The standardized lithological data are then classified into multi-level groupings that can be used to systematically upscale and downscale drill hole data inputs for multiscale 3D geological modelling. dh2loop formats legacy data bridging the gap between utilization and maximization of legacy drill hole data and drill hole analysis functionalities available in existing Python libraries (lasio, welly, striplog).


Author(s):  
Y. Tao ◽  
J.-P. Muller ◽  
P. Sidiropoulos ◽  
J. Veitch-Michaelis ◽  
V. Yershov

Within the EU FP-7 iMars project, a fully automated multi-resolution DTM processing chain, called Co-registration ASP-Gotcha Optimised (CASP-GO) has been developed, based on the open source NASA Ames Stereo Pipeline (ASP). CASP-GO includes tiepoint based multi-resolution image co-registration and an adaptive least squares correlation-based sub-pixel refinement method called Gotcha. The implemented system guarantees global geo-referencing compliance with respect to HRSC (and thence to MOLA), provides refined stereo matching completeness and accuracy based on the ASP normalised cross-correlation. We summarise issues discovered from experimenting with the use of the open-source ASP DTM processing chain and introduce our new working solutions. These issues include global co-registration accuracy, de-noising, dealing with failure in matching, matching confidence estimation, outlier definition and rejection scheme, various DTM artefacts, uncertainty estimation, and quality-efficiency trade-offs.


2019 ◽  
Vol 4 (1) ◽  
pp. 83-89
Author(s):  
Nikita Baldakov ◽  
Alexey Kudishin

The modeling of runoff from the catchment area requires automated processing of a large amount of heterogeneous data. The article presents the results of the development of tools for automating the calculation of the drainage basin characteristics based on open source software.


2016 ◽  
Vol 37 (13) ◽  
pp. 2990-3004 ◽  
Author(s):  
André Twele ◽  
Wenxi Cao ◽  
Simon Plank ◽  
Sandro Martinis

2020 ◽  
Vol 12 (2) ◽  
pp. 252
Author(s):  
Cyprien Alexandre ◽  
Rosa Johary ◽  
Thibault Catry ◽  
Pascal Mouquet ◽  
Christophe Révillion ◽  
...  

In the future, climate change will induce even more severe hurricanes. Not only should these be better understood, but there is also a necessity to improve the assessment of their impacts. Flooding is one of the most common powerful impacts of these storms. Analyzing the impacts of floods is essential in order to delineate damaged areas and study the economic cost of hurricane-related floods. This paper presents an automated processing chain for Sentinel-1 synthetic aperture radar (SAR) data. This processing chain is based on the S1-Tiling algorithm and the normalized difference ratio (NDR). It is able to download and clip S1 images on Sentinel-2 tiles footprints, perform multi-temporal filtering, and threshold NDR images to produce a mask of flooded areas. Applied to two different study zones, subject to hurricanes and cyclones, this chain is reliable and simple to implement. With the rapid mapping product of EMS Copernicus (Emergency Management Service) as reference, the method confers up to 95% accuracy and a Kappa value of 0.75.


2013 ◽  
Vol 10 (6) ◽  
pp. 1617-1621 ◽  
Author(s):  
T. Esch ◽  
M. Marconcini ◽  
A. Felbier ◽  
A. Roth ◽  
W. Heldens ◽  
...  

2016 ◽  
Vol 12 (S325) ◽  
pp. 305-310
Author(s):  
J. M. van der Hulst ◽  
D. Punzo ◽  
J. B. T. M. Roerdink

AbstractUpcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we presentSlicerAstro, an open-source extension of3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.


Author(s):  
Y. Tao ◽  
J.-P. Muller ◽  
P. Sidiropoulos ◽  
J. Veitch-Michaelis ◽  
V. Yershov

Within the EU FP-7 iMars project, a fully automated multi-resolution DTM processing chain, called Co-registration ASP-Gotcha Optimised (CASP-GO) has been developed, based on the open source NASA Ames Stereo Pipeline (ASP). CASP-GO includes tiepoint based multi-resolution image co-registration and an adaptive least squares correlation-based sub-pixel refinement method called Gotcha. The implemented system guarantees global geo-referencing compliance with respect to HRSC (and thence to MOLA), provides refined stereo matching completeness and accuracy based on the ASP normalised cross-correlation. We summarise issues discovered from experimenting with the use of the open-source ASP DTM processing chain and introduce our new working solutions. These issues include global co-registration accuracy, de-noising, dealing with failure in matching, matching confidence estimation, outlier definition and rejection scheme, various DTM artefacts, uncertainty estimation, and quality-efficiency trade-offs.


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