scholarly journals Analysis of interactive effects of DEM resolution and basin subdivision level on runoff simulation in Kaidu River Basin, China

2016 ◽  
Vol 48 (4) ◽  
pp. 1100-1117 ◽  
Author(s):  
J. Sun ◽  
Y. P. Li ◽  
G. H. Huang ◽  
C. X. Wang
Keyword(s):  
River Basin ◽  
Spatial Data ◽  
Process Model ◽  
Spatial Information ◽  
Model Performance ◽  
Interactive Effects ◽  
Runoff Simulation ◽  
Dem Resolution ◽  
Kaidu River ◽  
Subdivision Level

Uncertainties in spatial data associated with basin topography, drainage networks, and land cover characteristics may affect the performance of runoff simulation. Such uncertainties are mainly derived from selection of digital elevation model (DEM) resolution and basin subdivision level. This study focuses on assessing the effects of DEM resolution and basin subdivision level on runoff simulation with a semi-distributed land use-based runoff process model. Twenty-four scenarios based on various DEM resolutions and subdivision levels are analyzed for the Kaidu River Basin. Results can be used for quantifying the uncertainty of input data about spatial information on model simulation, disclosing the interaction between DEM resolution and subdivision level, as well as identifying the optimal system inputs. Results show that the model performance could be enhanced with the increased subdivision level. Results also reveal that the interaction of DEM resolution and subdivision level has slight effects on modeling outputs. Multi-objective fuzzy evaluation is used to further examine the uncertainty in DEM resolution and basin subdivision level on model performance. The results indicate an optimal combination of input parameters is suitable for Kaidu River Basin which could lead to more reliable results of the hydrological simulation.

Study on snowmelt runoff simulation in the Kaidu River basin

2007 ◽  
Vol 50 (S1) ◽  
pp. 26-35 ◽  
Author(s):  
YiChi Zhang ◽  
BaoLin Li ◽  
AnMing Bao ◽  
ChengHu Zhou ◽  
Xi Chen ◽  
...  
Keyword(s):  
River Basin ◽  
Snowmelt Runoff ◽  
Runoff Simulation ◽  
Kaidu River

DARCY RIBEIRO UNIVERSITY CAMPUS MAP – 2017- TECHNICAL NOTE

2018 ◽  
Vol 7 (2) ◽  
Author(s):  
Rafael Sanzio Araújo dos Anjos ◽  
Jose Leandro de Araujo Conceição ◽  
Jõao Emanuel ◽  
Matheus Nunes
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Technical Note ◽  
University Campus ◽  
Communication Tool ◽  
Sources Of Information ◽  
Data Manipulation ◽  
Geographic Space ◽  
The Many ◽  
New Generation

The spatial information regarding the use of territory is one of the many strategies used to answer and to inform about what happened, what is happening and what may happen in geographic space. Therefore, the mapping of land use as a communication tool for the spatial data made significant progress in improving sources of information, especially over the last few decades, with new generation remote sensing products for data manipulation.

An Optimal Framework for Spatial Query Optimization Using Hadoop in Big Data Analytics

2019 ◽  
Vol 12 ◽  
Author(s):  
Pankaj Dadheech ◽  
Dinesh Goyal ◽  
Sumit Srivastava ◽  
Ankit Kumar
Keyword(s):  
Big Data ◽  
Query Optimization ◽  
Spatial Data ◽  
Spatial Information ◽  
Big Data Analytics ◽  
Spatial Query ◽  
Data Process ◽  
Boolean Queries ◽  
Spatial Query Optimization ◽  
Hadoop System

Spatial queries frequently used in Hadoop for significant data process. However, vast and massive size of spatial information makes it difficult to process the spatial inquiries proficiently, so they utilized the Hadoop system for process Big Data. We have used Boolean Queries & Geometry Boolean Spatial Data for Query Optimization using Hadoop System. In this paper, we show a lightweight and adaptable spatial data index for big data which will process in Hadoop frameworks. Results demonstrate the proficiency and adequacy of our spatial ordering system for various spatial inquiries.

scholarly journals An Analysis of Existing Production Frameworks for Statistical and Geographic Information: Synergies, Gaps and Integration

2021 ◽  
Vol 10 (6) ◽  
pp. 374
Author(s):  
Francisco Javier Ariza-López ◽  
Antonio Rodríguez-Pascual ◽  
Francisco J. Lopez-Pellicer ◽  
Luis M. Vilches-Blázquez ◽  
Agustín Villar-Iglesias ◽  
...  
Keyword(s):  
Spatial Data ◽  
Process Model ◽  
Statistical Data ◽  
Legal Framework ◽  
Public Agencies ◽  
Quality Model ◽  
Statistical Process ◽  
The Third ◽  
Spatial Data Quality ◽  
Statistical Area

The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the possibility and need to achieve a better integration between them through the interoperability of systems, processes, and data. The statistical area is well led and has well-defined frameworks. The geospatial area does not have clear leadership and the large number of standards establish a framework that is not always obvious. On the other hand, the lack of a general and common legal framework is also highlighted. Additionally, three examples are offered: the first is the application of the spatial data quality model to the case of statistical data, the second of the application of the statistical process model to the geospatial case, and the third is the use of linked geospatial and statistical data. These examples demonstrate the possibility of transferring experiences/advances from one area to another. In this way, we emphasize the conceptual proximity of these two areas, highlighting synergies, gaps, and potential integration.

scholarly journals Development of Multilayer-Based Map Matching to Enhance Performance in Large Truck Fleet Dispatching

2021 ◽  
Vol 10 (2) ◽  
pp. 79
Author(s):  
Ching-Yun Mu ◽  
Tien-Yin Chou ◽  
Thanh Van Hoang ◽  
Pin Kung ◽  
Yao-Min Fang ◽  
...  
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Spatial Information ◽  
Data Retrieval ◽  
Spatial Data Mining ◽  
Map Matching ◽  
Matching Algorithm ◽  
Table Method ◽  
Look Up Table ◽  
The Look

Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large truck fleets in the context of the current complex network of roads. Therefore, this paper proposes a multilayer-based map matching algorithm with different spatial data structures to deal rapidly with large amounts of coordinate data. Using the dimension reduction technique, the geodesic coordinates can be transformed into plane coordinates. This study provides multiple layer grouping combinations to deal with complex road networks. We integrated these techniques and employed a puncture method to process the geometric computation with spatial data-mining approaches. We constructed a spatial division index and combined this with the puncture method, which improves the efficiency of the system and can enhance data retrieval efficiency for large truck fleet dispatching. This paper also used a multilayer-based map matching algorithm with raster data structures. Comparing the results revealed that the look-up table method offers the best outcome. The proposed multilayer-based map matching algorithm using the look-up table method is suited to obtaining competitive performance in identifying efficiency improvements for large truck fleet dispatching.

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 SPATIAL DATA: FROM CARTOGRAPHY TO GEODATABASE

2017 ◽  
Vol 43 (4) ◽  
pp. 142-146 ◽  
Author(s):  
Ugo FALCHI
Keyword(s):  
Spatial Data ◽  
Common Good ◽  
Spatial Information ◽  
Geographic Information ◽  
The Public ◽  
Significant Acceleration ◽  
Management And Development ◽  
The Status ◽  
History Of ◽  
Essential Knowledge

The final goal of this paper was to fix a brief summary on the status of geographic information in Italy due to the technological steps and national regulations. The acquisition, processing and sharing of spatial data has experienced a significant acceleration thanks to the development of computer technology and the acknowledgment of the need for standardization and homogenization of information held by pub­lic authorities and individuals. The spatial data represents the essential knowledge in the management and development of a territory both in terms of planning for safety and environmental prevention. In Italy there is an enormous heritage of spatial information which is historically affected by a problem of consistency and uniformity, in order to make it often contradictory in its use by the public decision-maker and private par­ties. The recent history of geographic information is characterized by a significant effort aimed at optimiz­ing this decisive technical and cultural heritage allowing the use of it to all citizens in a logic of sharing and re-use and may finally represent a common good available to all.

scholarly journals Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach

2005 ◽  
Vol 2 (3) ◽  
pp. 639-690 ◽  
Author(s):  
G. P. Zhang ◽  
H. H. G. Savenije
Keyword(s):  
River Basin ◽  
Overland Flow ◽  
Model Performance ◽  
Source Area ◽  
Subsurface Water ◽  
Watershed Hydrology ◽  
Rainfall Runoff ◽  
Data Set ◽  
Physically Based ◽  
Infiltration Excess

Abstract. Based on the Representative Elementary Watershed (REW) approach, the modelling tool REWASH (Representative Elementary WAterShed Hydrology) has been developed and applied to the Geer river basin. REWASH is deterministic, semi-distributed, physically based and can be directly applied to the watershed scale. In applying REWASH, the river basin is divided into a number of sub-watersheds, so called REWs, according to the Strahler order of the river network. REWASH describes the dominant hydrological processes, i.e. subsurface flow in the unsaturated and saturated domains, and overland flow by the saturation-excess and infiltration-excess mechanisms. Through flux exchanges among the different spatial domains of the REW, surface and subsurface water interactions are fully coupled. REWASH is a parsimonious tool for modelling watershed hydrological response. However, it can be modified to include more components to simulate specific processes when applied to a specific river basin where such processes are observed or considered to be dominant. In this study, we have added a new component to simulate interception using a simple parametric approach. Interception plays an important role in the water balance of a watershed although it is often disregarded. In addition, a refinement for the transpiration in the unsaturated zone has been made. Finally, an improved approach for simulating saturation overland flow by relating the variable source area to both the topography and the groundwater level is presented. The model has been calibrated and verified using a 4-year data set, which has been split into two for calibration and validation. The model performance has been assessed by multi-criteria evaluation. This work is the first full application of the REW approach to watershed rainfall-runoff modelling in a real watershed. The results demonstrate that the REW approach provides an alternative blueprint for physically based hydrological modelling.

scholarly journals PREFACE – ISPRS Geospatial Week 2019

2019 ◽  
Vol IV-2/W5 ◽  
pp. 1-1
Author(s):  
G. Vosselman ◽  
S. J. Oude Elberink ◽  
M. Y. Yang
Keyword(s):  
Remote Sensing ◽  
Data Quality ◽  
Spatial Data ◽  
Laser Scanning ◽  
Spatial Information ◽  
Smart Cities ◽  
International Workshop ◽  
Crowd Sourcing ◽  
Spatial Data Quality ◽  
Information Sciences

<p><strong>Abstract.</strong> The ISPRS Geospatial Week 2019 is a combination of 13 workshops organised by 30 ISPRS Working Groups active in areas of interest of ISPRS. The Geospatial Week 2019 is held from 10–14 June 2019, and is convened by the University of Twente acting as local organiser. The Geospatial Week 2019 is the fourth edition, after Antalya Turkey in 2013, La Grande Motte France in 2015 and Wuhan China in 2017.</p><p>The following 13 workshops provide excellent opportunities to discuss the latest developments in the fields of sensors, photogrammetry, remote sensing, and spatial information sciences:</p> <ul> <li>C3M&amp;amp;GBD – Collaborative Crowdsourced Cloud Mapping and Geospatial Big Data</li> <li>CHGCS – Cryosphere and Hydrosphere for Global Change Studies</li> <li>EuroCow-M3DMaN – Joint European Calibration and Orientation Workshop and Workshop onMulti-sensor systems for 3D Mapping and Navigation</li> <li>HyperMLPA – Hyperspectral Sensing meets Machine Learning and Pattern Analysis</li> <li>Indoor3D</li> <li>ISSDQ – International Symposium on Spatial Data Quality</li> <li>IWIDF – International Workshop on Image and Data Fusion</li> <li>Laser Scanning</li> <li>PRSM – Planetary Remote Sensing and Mapping</li> <li>SarCon – Advances in SAR: Constellations, Signal processing, and Applications</li> <li>Semantics3D – Semantic Scene Analysis and 3D Reconstruction from Images and ImageSequences</li> <li>SmartGeoApps – Advanced Geospatial Applications for Smart Cities and Regions</li> <li>UAV-g – Unmanned Aerial Vehicles in Geomatics</li> </ul> <p>Many of the workshops are part of well-established series of workshops convened in the past. They cover topics like UAV photogrammetry, laser scanning, spatial data quality, scene understanding, hyperspectral imaging, and crowd sourcing and collaborative mapping with applications ranging from indoor mapping and smart cities to global cryosphere and hydrosphere studies and planetary mapping.</p><p>In total 143 full papers and 357 extended abstracts were submitted by authors from 63 countries. 1250 reviews have been delivered by 295 reviewers. A total of 81 full papers have been accepted for the volume IV-2/W5 of the International Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Another 289 papers are published in volume XLII-2/W13 of the International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences.</p><p>The editors would like to thank all contributing authors, reviewers and all workshop organizers for their role in preparing and organizing the Geospatial Week 2019. Thanks to their contributions, we can offer an excessive and varying collection in the Annals and the Archives.</p><p>We hope you enjoy reading the proceedings.</p><p>George Vosselman, Geospatial Week Director 2019, General Chair<br /> Sander Oude Elberink, Programme Chair<br /> Michael Ying Yang, Programme Chair</p>

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