scholarly journals Airborne laser scan data: a valuable tool with which to infer weather radar partial beam blockage in urban environments

2016 ◽  
Vol 9 (10) ◽  
pp. 5063-5075 ◽  
Author(s):  
Roberto Cremonini ◽  
Dmitri Moisseev ◽  
Venkatachalam Chandrasekar
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Forest Canopy ◽  
Weather Radar ◽  
Urban Environments ◽  
Data Sets ◽  
Propagation Models ◽  
Weather Radars ◽  
Airborne Laser ◽  
Spatial Data Sets

Abstract. High-spatial-resolution weather radar observations are of primary relevance for hydrological applications in urban areas. However, when weather radars are located within metropolitan areas, partial beam blockages and clutter by buildings can seriously affect the observations. Standard simulations with simple beam propagation models and digital elevation models (DEMs) are usually not able to evaluate buildings' contribution to partial beam blockages. In recent years airborne laser scanners (ALSs) have evolved to the state-of-the-art technique for topographic data acquisition. Providing small footprint diameters (10–30 cm), ALS data allow accurate reconstruction of buildings and forest canopy heights. Analyzing the three weather C-band radars located in the metropolitan area of Helsinki, Finland, the present study investigates the benefits of using ALS data for quantitative estimations of partial beam blockages. The results obtained applying beam standard propagation models are compared with stratiform 24 h rainfall accumulation to evaluate the effects of partial beam blockages due to constructions and trees. To provide a physical interpretation of the results, the detailed analysis of beam occultations is achieved by open spatial data sets and open-source geographic information systems.

scholarly journals Airborne laser scan data: a valuable tool to infer partial beam-blockage in urban environment

2016 ◽  
Author(s):  
Roberto Cremonini ◽  
Dmitri Moisseev ◽  
V. Chandrasekar
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Forest Canopy ◽  
Propagation Model ◽  
Data Sets ◽  
Weather Radars ◽  
Airborne Laser ◽  
Digital Elevation ◽  
Spatial Data Sets ◽  
Scan Data

Abstract. High spatial resolution weather radar observations are of primary relevance for hydrological applications in urban areas. However, when weather radars are located within metropolitan areas, partial beam blockages and clutter by buildings can seriously affect the observations. Standard simulations with simple beam propagation models and digital elevation models (DEMs) are usually not able to evaluate the buildings contribution to partial beam blockages. In the recent years airborne laser scanners (ALS) evolved to the state-of-the-art technique for topographic data acquisition. ALS data, providing small footprint diameters (10–30 cm), allow accurate reconstruction of buildings and forest canopy heights. Analysing the three weather C-band radars located in the metropolitan area of Helsinki, Finland, the present study investigates the benefits of using ALS data for quantitative estimations of partial beam blockings. The results obtained applying beam standard propagation model are compared with stratiform 24-hour rainfall accumulation to evaluate the effect of partial beam blocking due to the constructions and trees. To provide the physical interpretation of the results, the detailed analysis of beam occultations is achieved by open spatial data sets and interface services with open source Geographic Information Systems.

scholarly journals An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level

2020 ◽  
Vol 12 (1) ◽  
pp. 580-597
Author(s):  
Mohamad Hamzeh ◽  
Farid Karimipour
Keyword(s):  
Spatial Data ◽  
Spatial Models ◽  
Model Performance ◽  
Essential Elements ◽  
Petroleum System ◽  
Petroleum Exploration ◽  
System Level ◽  
Data Sets ◽  
Petroleum Potential ◽  
Spatial Data Sets

AbstractAn inevitable aspect of modern petroleum exploration is the simultaneous consideration of large, complex, and disparate spatial data sets. In this context, the present article proposes the optimized fuzzy ELECTRE (OFE) approach based on combining the artificial bee colony (ABC) optimization algorithm, fuzzy logic, and an outranking method to assess petroleum potential at the petroleum system level in a spatial framework using experts’ knowledge and the information available in the discovered petroleum accumulations simultaneously. It uses the characteristics of the essential elements of a petroleum system as key criteria. To demonstrate the approach, a case study was conducted on the Red River petroleum system of the Williston Basin. Having completed the assorted preprocessing steps, eight spatial data sets associated with the criteria were integrated using the OFE to produce a map that makes it possible to delineate the areas with the highest petroleum potential and the lowest risk for further exploratory investigations. The success and prediction rate curves were used to measure the performance of the model. Both success and prediction accuracies lie in the range of 80–90%, indicating an excellent model performance. Considering the five-class petroleum potential, the proposed approach outperforms the spatial models used in the previous studies. In addition, comparing the results of the FE and OFE indicated that the optimization of the weights by the ABC algorithm has improved accuracy by approximately 15%, namely, a relatively higher success rate and lower risk in petroleum exploration.

scholarly journals Mining Co-Location Patterns with Rare Events from Spatial Data Sets

2006 ◽  
Vol 10 (3) ◽  
pp. 239-260 ◽  
Author(s):  
Yan Huang ◽  
Jian Pei ◽  
Hui Xiong
Keyword(s):  
Spatial Data ◽  
Rare Events ◽  
Data Sets ◽  
Location Patterns ◽  
Spatial Data Sets

scholarly journals Using TSX/TDX Pursuit Monostatic SAR Stacks for PS-InSAR Analysis in Urban Areas

2018 ◽  
Vol 11 (1) ◽  
pp. 26 ◽  
Author(s):  
Ziyun Wang ◽  
Timo Balz ◽  
Lu Zhang ◽  
Daniele Perissin ◽  
Mingsheng Liao
Keyword(s):  
Urban Areas ◽  
Urban Environments ◽  
Deformation Monitoring ◽  
Data Sets ◽  
Persistent Scatterer Interferometry ◽  
Operating Modes ◽  
Monitoring Procedure ◽  
Urban Monitoring ◽  
Indispensable Tool ◽  
Scientific Testing

Persistent Scatterer Interferometry (PS-InSAR) has become an indispensable tool for monitoring surface motion in urban environments. The interferometric configuration of PS-InSAR tends to mix topographic and deformation components in differential interferometric observations. When the upcoming constellation missions such as, e.g., TanDEM-L or TWIN-L provide new standard operating modes, bi-static stacks for deformation monitoring will be more commonly available in the near future. In this paper, we present an analysis of the applicability of such data sets for urban monitoring, using a stack of pursuit monostatic data obtained during the scientific testing phase of the TanDEM-X (TDX) mission. These stacks are characterized by extremely short temporal baselines between the TerraSAR-X (TSX) and TanDEM-X acquisitions at the same interval. We evaluate the advantages of this acquisition mode for urban deformation monitoring with several of the available acquisition pairs. Our proposed method exploits the special properties of this data using a modified processing chain based on the standard PS-InSAR deformation monitoring procedure. We test our approach with a TSX/TDX mono-static pursuit stack over Guangzhou, using both the proposed method and the standard deformation monitoring procedure, and compare the two results. The performance of topographic and deformation estimation is improved by using the proposed processing method, especially regarding high-rise buildings, given the quantitative statistic on temporal coherence, detectable numbers, as well as the PS point density of persistent scatters points, among which the persistent scatter numbers increased by 107.2% and the detectable height span increased by 78% over the standard processing results.

scholarly journals Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

2017 ◽  
Vol 21 (7) ◽  
pp. 3859-3878 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhuis ◽  
Nick van de Giesen
Keyword(s):  
Temporal Variability ◽  
Urban Areas ◽  
Rainfall Variability ◽  
Urban Environments ◽  
Hydrological Processes ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Hydrological Response ◽  
Weather Radars ◽  
New Instruments

Abstract. In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

scholarly journals Refinement Algoritm of Hypotheses Testing Research Based on Geochronological Tracking

2020 ◽  
Vol 6 (1) ◽  
pp. 86-93
Author(s):  
R. Ivakin ◽  
Y. Ivakin ◽  
S. Potapichev
Keyword(s):  
Spatial Data ◽  
Optimization Problem ◽  
Retrospective Studies ◽  
Subject Area ◽  
Statistical Testing ◽  
Time Interval ◽  
Data Sets ◽  
Hypotheses Testing ◽  
Practical Application ◽  
Spatial Data Sets

Geochronological tracking is an effective information technology for digital cartographic spatial data sets processing. It is widely known in retrospective patterns research about geographic relocation of figures, or any other units for a given time interval. Software component of geochronological tracking is becoming one the most popular GIS-integrated applications. The article presents the basic provisions for the algorithmization of the geochronological tracking procedure for statistical testing of retrospective studies hypotheses. We can observe the results of solving this optimization problem in a general form and in a number of the most typical variants. The obtained results of solving the optimization problem are interpreted in terms of the retrospective studies subject area. There are shown the ways of further practical application of the optimized algorithm in the tasks of modern logistics, data mining and formalized knowledge.

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