Adaptive filtering and structure-tracking for statistical analysis of geological features in radar images

1992 ◽  
Vol 18 (9) ◽  
pp. 1169-1184 ◽  
Author(s):  
Ph. Blondel ◽  
C. Sotin ◽  
Ph. Masson
Keyword(s):  
Statistical Analysis ◽  
Adaptive Filtering ◽  
Radar Images ◽  
Geological Features

scholarly journals Influence of the Lineament Geological Features on the Hydrologic Flow Direction of Wadi Al Kuf Catchment Area, Cyrenaica, Northeastern Libya

2019 ◽  
Vol 34 (3) ◽  
pp. 153-164
Author(s):  
Ammar A Ammar
Keyword(s):  
Catchment Area ◽  
Flow Direction ◽  
Rock Fracture ◽  
Main Trend ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Radar Images ◽  
Set Systems ◽  
Geological Features ◽  
Al Jabal Al Akhdar

Wadi Al Kuf Catchment Area WKCA is one of the largest watershed basins on Al Jabal al Akhdar Cyrenaica anticlinorium, the area is more than 960Km2, and considers as a semi-wet basin. This basin highly affected with lineaments geological features just like morphometric and tectonics types including fissures, fault systems and joints set systems in the highly karst lime stones of Al Jabal al Akhdar group lithological formations. These lineaments phenomena were measured and extracted from the radar images of digital terrain model of 30 meters space grid, and the hyper spectral Landsat 8 of 15 meters pixel resolution, they were processed and interpreted by several geospatial geomatics and geological software. The direction orientation and the rock density of these fissures, fractures, joints set systems, faults and the morphometric dendritic drainage pattern had been measured and illustrated from the rose diagram analysis and the geological map. The mainstream of this catchment area WKCA is the 6th order and mainly parallel to the main trend direction with the first escarpment circular fault at the major orogeny tectonic fault of Al Jabal al Akhdar uplift, and these lineaments features is averaged 58.3o  with the azimuth degree along the mainstream. The drainage density,  lineaments density analysis and distribution of the WKCA have been classified as low lineaments rock fractures in the eastern boundary of the basin, moderate lineaments rock fissures in the middle of the basin and high density of rock fracture in the western and northern boundary of the basin, these had reflected the deep percolations and infiltrations to the ground water-bearing aquifer in the WKCA through the secondary and the tertiary porosity of the hydrological karst system.

scholarly journals Joint statistical correction of clutters, spokes and beam height for a radar derived precipitation climatology in southern Germany

2012 ◽  
Vol 16 (11) ◽  
pp. 4101-4117 ◽  
Author(s):  
A. Wagner ◽  
J. Seltmann ◽  
H. Kunstmann
Keyword(s):  
Statistical Analysis ◽  
Cell Tracking ◽  
Weather Radar ◽  
Radar Data ◽  
Small Scale ◽  
Correction Algorithm ◽  
Rain Gauges ◽  
Radar Images ◽  
Statistical Correction ◽  
High Level

Abstract. First results of radar derived climatology have emerged over the last years, as datasets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as continuous storage of radar data was often not achieved before. This kind of climatology demands a high level of data quality. Small deviations or minor systematic under- or overestimations in single radar images become a major cause of error in statistical analysis. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. We present a new statistical post-correction scheme based on a climatological analysis of seven years of radar data of the Munich weather radar (2000–2006) operated by DWD (German Weather Service). Original radar products are used subject only to corrections within the signal processor without any further corrections on single radar images. The aim of this statistical correction is to make up for the average systematic errors caused by clutter, propagation, or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This analysis revealed the following basic effects: the decrease of rain amount as a function of height and distance from the radar, clutter effects such as clutter remnants after filtering, holes by eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the bright band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction which minimises measuring effects. The second module corrects clutter effects and disturbances and the third one realises a mean adjustment to selected rain gauges. Two different sets of radar products are used. The statistical analysis as well as module 1 and module 2 of the correction algorithm are based on frequencies of the six reflectivity levels within the so-called PX product. For correction module 3 and for the validation of the correction algorithm, rain amounts are calculated from the 8-bit so-called DX product. The correction algorithm is created to post-correct climatological or statistical analysis of radar data with a temporal resolution larger than one year. The correction algorithm is used for frequencies of occurrence of radar reflectivities which enables its application even for radar products such as DWD's cell-tracking-product CONRAD. Application (2004–2006) and validation (2007–2009) periods of this correction algorithm with rain gauges show an increased conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) between mean annual rain amounts of rain gauges and corresponding radar pixels decreases from 262 mm to 118 mm excluding those pairs of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

scholarly journals Thermal Tourism and Geoheritage: Examining Visitor Motivations and Perceptions

Resources ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 58
Author(s):  
Anna Chrobak ◽  
Francesca Ugolini ◽  
David Pearlmutter ◽  
Antonio Raschi
Keyword(s):  
Statistical Analysis ◽  
General Public ◽  
Survey Methods ◽  
Social Aspects ◽  
Health And Wellness ◽  
Cultural Significance ◽  
Considerable Potential ◽  
Site Survey ◽  
Geological Features ◽  
Interest And Knowledge

Kúpele Vyžne Ružbachy spa and San Giovanni spa are very well known spas located in Slovakia and in Italy. Both spas are surrounded by environmental and historical richness, including geological features that hold considerable potential for geotourism. In order to gauge the promotional value of these geological features, this study investigates: (a) The motivation of tourists for visiting the area, (b) the level of visitors’ interest and knowledge regarding the area’s geological features, (c) their assessment of the attractiveness and accessibility of these features, (d) their overall opinion about the area for geotourism, and (e) indications for utilizing these features to improve the landscape knowledge of the general public. The data were collected using on-site survey methods and examined by statistical analysis. Results of the survey show that the attraction of tourists to these areas is due not only to health and wellness benefits, but also to social aspects and the desire for exploring new places. It was found that the geological elements in both locations hold significant geotourism potential—and efforts to increase visitors’ awareness of their environmental and cultural significance could be decisive in capitalizing on the attraction of these unique sites. Improvement of the accessibility to the sites would be highly recommended as a way to increase tourism diversity.

scholarly journals Shuttle Imaging Radar Views of Some Geological Features in the Arabian Peninsula

GeoArabia ◽  
1997 ◽  
Vol 2 (2) ◽  
pp. 165-178 ◽  
Author(s):  
Khattab G. Al-Hinai ◽  
Abdallah E. Dabbagh ◽  
Weston C. Gardner ◽  
Muhammad A. Khan ◽  
Salih Saner
Keyword(s):  
Remote Sensing ◽  
Arabian Peninsula ◽  
Space Shuttle ◽  
Remote Sensing Data ◽  
Karst Terrain ◽  
Radar Images ◽  
Imaging Radar ◽  
Geological Features ◽  
Geologic Maps ◽  
Geologic Interpretation

ABSTRACT The Space Shuttle Endeavor, carrying Shuttle Imaging Radar (SIR), has imaged selected parts of the Earth during two missions in April and October, 1994. The SIR instrument acquired remote sensing data in L, C and X bands. The main objective of the experiment was to assess the utility of radar images for multiple geologic, hydrologic and environmental applications. The geologic interpretation of the L-band image strips, over the Arabian Peninsula, reveals faults, folds, joints, details of harrats (basalt flows), karst terrain, and drainage systems beneath thin sand cover which are not visible on other remote sensing images (Landsat and SPOT) and are not shown on existing geologic maps.

Use of homomorphic transforms in locally adaptive filtering of radar images

2000 ◽  
Author(s):  
Vladimir V. Lukin ◽  
Vladimir P. Melnik ◽  
Victor I. Chemerovsky ◽  
Sari Peltonen ◽  
Pauli Kuosmanen
Keyword(s):  
Adaptive Filtering ◽  
Radar Images ◽  
Locally Adaptive

scholarly journals Joint statistical correction of clutters, spokes and beam height for a radar climatology in Southern Germany

2012 ◽  
Vol 9 (4) ◽  
pp. 4703-4746
Author(s):  
A. Wagner ◽  
J. Seltmann ◽  
H. Kunstmann
Keyword(s):  
Statistical Analysis ◽  
Weather Radar ◽  
Radar Data ◽  
Small Scale ◽  
Correction Algorithm ◽  
Rain Gauges ◽  
Radar Images ◽  
Statistical Correction ◽  
First Results ◽  
High Level

Abstract. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. This kind of climatology demands a high level of data quality. Little deviations or minor systematic underestimations or overestimations in single radar images become a major cause of error in statistical analysis. First results of radar derived climatology have emerged over the last years, as data sets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as storage of radar data was not achieved before. We present a new statistical post-correction scheme, which is based on seven years of radar data of the Munich weather radar (2000–2006) that is operated by DWD (German Weather Service). The typical correction algorithms for single radar images, such as clutter corrections, are used. Then an additional statistical post-correction based on the results of a climatological analysis from radar images follows. The aim of this statistical correction is to correct systematic errors caused by clutter effects or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This robust analysis revealed the following basic effects: the decrease of rain rate in relation to height and distance from the radar, clutter effects such as remaining clutter, eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the Bright Band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction, which minimizes measuring effects. The second module corrects clutter effects and the third one realizes a mean adjustment to selected rain gauges. Two different radar products are used. The statistical analysis as well as module one and module two of the correction algorithm are based on frequencies of occurrence of the so-called PX-product with six reflectivity levels. For correction module 3 and for the validation of the correction algorithm rain rates are calculated from the 8-bit-depth so-called DX-product. An application (2004–2006) and a validation (2007–2009) of this correction algorithm with rain gauges show a much higher conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) decreases from 262 mm to 118 mm excluding those pair of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

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