scholarly journals Spatial Data Lake for Smart Cities: From Design to Implementation

2020 ◽  
Vol 1 ◽  
pp. 1-15
Author(s):  
Rodrique Kafando ◽  
Rémy Decoupes ◽  
Lucile Sautot ◽  
Maguelonne Teisseire
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Smart Cities ◽  
Real Data ◽  
Heterogeneous Data ◽  
Geographic Information ◽  
Sensor Data ◽  
Remote Sensing Images ◽  
Thematic Information ◽  
General Data

Abstract. In this paper, we propose a methodology for designing data lake dedicated to Spatial Data and an implementation of this specific framework. Inspired from previous proposals on general data lake Design and based on the Geographic information – Metadata normalization (ISO 19115), the contribution presented in this paper integrates, with the same philosophy, the spatial and thematic dimensions of heterogeneous data (remote sensing images, textual documents and sensor data, etc). To support our proposal, the process has been implemented in a real data project in collaboration with Montpellier Métropole Méditerranée (3M), a metropolis in the South of France. This framework offers a uniform management of the spatial and thematic information embedded in the elements of the data lake.

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>

scholarly journals Understanding Urban Growth in Beijing-Tianjin-Hebei Region over the Past 100 Years Using Old Maps and Landsat Data

2021 ◽  
Vol 13 (16) ◽  
pp. 3264 ◽  
Author(s):  
Shuang Li ◽  
Zhongqiu Sun ◽  
Yafei Wang ◽  
Yuxia Wang
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Spatial Data ◽  
Urban Expansion ◽  
Remote Sensing Images ◽  
The Past ◽  
Old Maps ◽  
The World ◽  
The City

Studying urban expansion from a longer-term perspective is of great significance to obtain an in-depth understanding of the process of urbanization. Remote sensing data are mostly selected to investigate the long-term expansion of cities. In this study, we selected the world-class urban agglomeration of Beijing-Tianjin-Hebei (BTH) as the study area, and then discussed how to make full use of multi-source, multi-category, and multi-temporal spatial data (old maps and remote sensing images) to study long-term urbanization. Through this study, we addressed three questions: (1) How much has the urban area in BTH expanded in the past 100 years? (2) How did the urban area expand in the past century? (3) What factors or important historical events have changed the development of cities with different functions? By comprehensively using urban spatial data, such as old maps and remote sensing images, geo-referencing them, and extracting built-up area information, a long-term series of urban built-up areas in the BTH region can be obtained. Results show the following: (1) There was clear evidence of dramatic urban expansion in this area, and the total built-up area had increased by 55.585 times, from 126.181 km2 to 7013.832 km2. (2) Continuous outward expansion has always been the main trend, while the compactness of the built-up land within the city is constantly decreasing and the complexity of the city boundary is increasing. (3) Cities in BTH were mostly formed through the construction of city walls during the Ming and Qing dynasties, and the expansion process was mostly highly related to important political events, traffic development, and other factors. In summary, the BTH area, similarly to China and most regions of the world, has experienced rapid urbanization and the history of such ancient cities should be further preserved with the combined use of old maps.

scholarly journals A NOVEL REMOVAL METHOD FOR DENSE STRIPES IN REMOTE SENSING IMAGES

2016 ◽  
Vol III-6 ◽  
pp. 57-61 ◽  
Author(s):  
Xinxin Liu ◽  
Huanfeng Shen ◽  
Qiangqiang Yuan ◽  
Liangpei Zhang ◽  
Qing Cheng
Keyword(s):  
Remote Sensing ◽  
Real Data ◽  
Model Optimization ◽  
Remote Sensing Images ◽  
Qualitative And Quantitative ◽  
Statistical Property ◽  
Alternating Direction ◽  
Proposed Model ◽  
The Common ◽  
Reliable Solution

In remote sensing images, the common existing stripe noise always severely affects the imaging quality and limits the related subsequent application, especially when it is with high density. To well process the dense striped data and ensure a reliable solution, we construct a statistical property based constraint in our proposed model and use it to control the whole destriping process. The alternating direction method of multipliers (ADMM) is applied in this work to solve and accelerate the model optimization. Experimental results on real data with different kinds of dense stripe noise demonstrate the effectiveness of the proposed method in terms of both qualitative and quantitative perspectives.

scholarly journals Remote Sensing and Geographic Information System in Water Erosion Assessment

2020 ◽  
Author(s):  
Nirmal Kumar ◽  
S. K. Singh ◽  
G. P. Obi Reddy ◽  
V. N. Mishra ◽  
R. K. Bajpai
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Data ◽  
Soil Loss ◽  
Water Erosion ◽  
Geographic Information ◽  
Geographical Information ◽  
Comprehensive Overview

The aim of this review paper is to provide a comprehensive overview of geographical information system and remote sensing–based water erosion assessment. With multispectral and multi-temporal low cost data at various resolutions, remote sensing plays an important role for mapping the distribution and severity of water erosion and for modeling the risk and/or potential of soil loss. The ability of geographic information system to integrate spatial data of different types and sources makes its role unavoidable in water erosion assessment. The role of satellite data in identification of eroded lands and in providing inputs for erosion modeling has been discussed. The role of GIS in mapping eroded lands based on experts’ opinion, in generating spatial data inputs from sources other than remote sensing and in integrating the inputs to model the potential soil loss has been discussed.

scholarly journals A Precision Evaluation Method for Remote Sensing Data Sampling Based on Hexagon Discrete Grid

2020 ◽  
Author(s):  
Yue Ma ◽  
Guoqing Li ◽  
Xiaochuang Yao ◽  
Jin Ben ◽  
Qianqian Cao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation System ◽  
Evaluation Method ◽  
Remote Sensing Data ◽  
Accuracy Evaluation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Hexagonal Grids ◽  
Discrete Grid

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

scholarly journals Integration and Exploitation of Sensor Data in Smart Cities through Event-Driven Applications

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1372 ◽  
Author(s):  
Manuel Garcia Alvarez ◽  
Javier Morales ◽  
Menno-Jan Kraak
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Spatial Information ◽  
Smart Cities ◽  
Spatial Data Analysis ◽  
Sensor Data ◽  
Reference Architecture ◽  
Real Time Processing ◽  
Time Processing ◽  
Event Driven

Smart cities are urban environments where Internet of Things (IoT) devices provide a continuous source of data about urban phenomena such as traffic and air pollution. The exploitation of the spatial properties of data enables situation and context awareness. However, the integration and analysis of data from IoT sensing devices remain a crucial challenge for the development of IoT applications in smart cities. Existing approaches provide no or limited ability to perform spatial data analysis, even when spatial information plays a significant role in decision making across many disciplines. This work proposes a generic approach to enabling spatiotemporal capabilities in information services for smart cities. We adopted a multidisciplinary approach to achieving data integration and real-time processing, and developed a reference architecture for the development of event-driven applications. This type of applications seamlessly integrates IoT sensing devices, complex event processing, and spatiotemporal analytics through a processing workflow for the detection of geographic events. Through the implementation and testing of a system prototype, built upon an existing sensor network, we demonstrated the feasibility, performance, and scalability of event-driven applications to achieve real-time processing capabilities and detect geographic events.

scholarly journals RESEARCH ON MULTI-SOURCE SATELLITE IMAGE DATABASE MANAGEMENT SYSTEM

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 565-568
Author(s):  
N. Fu ◽  
L. Sun ◽  
H. Z. Yang ◽  
J. Ma ◽  
B. Q. Liao
Keyword(s):  
Remote Sensing ◽  
Data Storage ◽  
Management System ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Database Management System ◽  
Sensor Data ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Effective Organization

Abstract. For the exploration and analysis of electricity, it is necessary to continuously acquire multi-star source, multi-temporal, multi-level remote sensing images for analysis and interpretation. Since the overall data has a variety of features, a data structure for multi-sensor data storage is proposed. On the basis of solving key technologies such as real-time image processing and analysis and remote sensing image normalization processing, the .xml file and remote sensing data geographic information file are used to realize effective organization between remote sensing data and remote sensing data. Based on GDAL design relational database, the formation of a relatively complete management system of data management, shared publishing and application services will maximize the potential value of remote sensing images in electricity remote sensing.

scholarly journals THE ROLE OF GEOMATICS ENGINEER IN SMART CITIES: A VIEW WITHIN THE FRAMEWORK OF TURKISH 2020–2023 NATIONAL SMART CITIES STRATEGY AND ACTION PLAN

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 333-341
Author(s):  
K. Konur ◽  
R. M. Alkan
Keyword(s):  
Spatial Data ◽  
Information Technologies ◽  
Smart Cities ◽  
Action Plan ◽  
Geographic Information ◽  
Geographic Information Technologies ◽  
Geographic Data ◽  
Technological Developments ◽  
Made In

Abstract. The development of technology resulted major revolutions in the cities. With the integration of technological developments into cities, the concept of smart cities began to emerge. Today, applications are made on smart cities in many countries. It is not possible to build a smart city without geographic data. It is one of the main duties of Geomatics Engineers to produce, use, process and finalize the geographic data and present it to the user. In this study, referring to the role of Geomatics Engineer in smart cities across Turkey 2020-2023 National Smart Cities Strategy and Action Plan framework is made in the investigations. When this plan is examined, it is seen that the importance of geographical/geo-spatial data and geo-information technologies for the realization of smart cities is an undeniable fact. In the 2020–2023 National Smart Cities Strategy and Action Plan, it has been clearly demonstrated that Geographic Information Systems and Geographic Information Technologies have a great role in creating smart cities.

scholarly journals ANALISIS LAHAN KRITIS DAN ARAHAN LAHAN DALAM PENGEMBANGAN WILAYAH PADA SUBDAS DI KABUPATEN KAYONG UTARA MENGGUNAKAN TEKNIK PENGINDERAAN JAUH DAN SISTEM INFORMASI GEOGRAFIS

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Murti Anom Suntoro ◽  
Dwi Astiani ◽  
Wiwik Ekyastuti
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Data ◽  
Geographic Information ◽  
Director General ◽  
Landsat 8 ◽  
Degraded Land ◽  
Technical Guidance

Critical land is a damaged land, thus losing or decreasing its function to the specified or expected limits. The identification and critical lands mapping is essential for the planning and determination of priority watersheds in order to the utilization and development of natural resources and land rehabilitation and soil conservation. Remote sensing is a technique that enable people to collect data without direct field measurement. The using of Landsat 8 image then analyzed by using Geographic Information System (GIS) is being expected to improve the ability to classify land cover, the map was then overlad with parameter map based on Regulation of Director General of Management of Watershed and Social Forestry Number P. 4 / V-Set / 2013 about technical guidance on the preparation of spatial data of other critical lands to identify critical lands in Kayong Utara Regency.Keywords: Degraded land, Geographic Information System (GIS), Remote sensing, overlay

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