國立虎尾科技大學 |

Geospatial Intelligence = Applications and Future Trends /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Geospatial Intelligence/ edited by Fatimazahra Barramou, El Hassan El Brirchi, Khalifa Mansouri, Youness Dehbi.
其他題名:	Applications and Future Trends /
其他作者:	Dehbi, Youness.
面頁冊數:	X, 180 p. 114 illus., 101 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Big Data. -
電子資源:	https://doi.org/10.1007/978-3-030-80458-9
ISBN:	9783030804589

Geospatial Intelligence = Applications and Future Trends /
Geospatial IntelligenceApplications and Future Trends /[electronic resource] :edited by Fatimazahra Barramou, El Hassan El Brirchi, Khalifa Mansouri, Youness Dehbi. - 1st ed. 2022. - X, 180 p. 114 illus., 101 illus. in color.online resource. - Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,2522-8722. - Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,.

Spatial Data and Artificial Intelligence -- Towards a Multi-agents Model for Automatic Big Data Processing to Support Urban planning -- Geospatial Forecasting and Social Media Exploration Based on Sentiment Analysis: Application to Flood Forecasting -- Deep Convolution Neural Network for Automated Method of Road Extraction on Aerial Imagery -- Enhancing the Management of Traffic Sequence Following Departure Trajectories -- A Multiagent and Machine Learning based Intrusion Detection System for Drone Networks -- Towards a Deep Learning Approach for Automatic Semantic Segmentation of 3D Lidar point Clouds in Urban Areas -- Artificial and Geospatial Intelligence Driven Digital Twins Architecture Development Against the Worldwide Twin Crisis Caused by Covid-19 -- Remote Sensing and Artificial Intelligence -- Opportunities for Artificial Intelligence in Precision Agriculture Using Satellite remote Sensing -- Monitoring Land Productivity Trends in Souss-Massa Region Using Landsat Time series Data to Support SDG Target 15.3 -- Subimages Based Approach for Landslide Susceptibility Mapping Using Convolutional Neural Network -- Lithological Mapping for a Semi-arid Area Using GEOBIA and PBIA Machine Learning Approaches with Sentinel-2 Imagery: Case Study of Skhour Rehamna, Morocco -- Optimization of Object-based Image Analysis with Genetic Programming to Generate Explicit Knowledge from Worldview 2 Data for Urban Mapping -- Machine Learning and Remote Sensing in Mapping and Estimating Rosemary Cover biomass.

This book explores cutting-edge methods combining geospatial technologies and artificial intelligence related to several fields such as smart farming, urban planning, geology, transportation, and 3D city models. It introduces techniques which range from machine and deep learning to remote sensing for geospatial data analysis. The book consists of two main parts that include 13 chapters contributed by promising authors. The first part deals with the use of artificial intelligence techniques to improve spatial data analysis, whereas the second part focuses on the use of artificial intelligence with remote sensing in various fields. Throughout the chapters, the interest for the use of artificial intelligence is demonstrated for different geospatial technologies such as aerial imagery, drones, Lidar, satellite remote sensing, and more. The work in this book is dedicated to the scientific community interested in the coupling of geospatial technologies and artificial intelligence and exploring the synergetic effects of both fields. It offers practitioners and researchers from academia, the industry and government information, experiences and research results about all aspects of specialized and interdisciplinary fields on geospatial intelligence. .

ISBN: 9783030804589

Standard No.: 10.1007/978-3-030-80458-9doiSubjects--Topical Terms:

1017136
Big Data.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Geospatial Intelligence = Applications and Future Trends /
LDR:04384nam a22004215i 4500 001 1090581
003 DE-He213
005 20220119143620.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783030804589 $9 978-3-030-80458-9
024 7 $a 10.1007/978-3-030-80458-9 $2 doi
035 $a 978-3-030-80458-9
050 4 $a Q334-342
050 4 $a TA347.A78
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Geospatial Intelligence $h [electronic resource] : $b Applications and Future Trends / $c edited by Fatimazahra Barramou, El Hassan El Brirchi, Khalifa Mansouri, Youness Dehbi.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a X, 180 p. 114 illus., 101 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development, $x 2522-8722
505 0 $a Spatial Data and Artificial Intelligence -- Towards a Multi-agents Model for Automatic Big Data Processing to Support Urban planning -- Geospatial Forecasting and Social Media Exploration Based on Sentiment Analysis: Application to Flood Forecasting -- Deep Convolution Neural Network for Automated Method of Road Extraction on Aerial Imagery -- Enhancing the Management of Traffic Sequence Following Departure Trajectories -- A Multiagent and Machine Learning based Intrusion Detection System for Drone Networks -- Towards a Deep Learning Approach for Automatic Semantic Segmentation of 3D Lidar point Clouds in Urban Areas -- Artificial and Geospatial Intelligence Driven Digital Twins Architecture Development Against the Worldwide Twin Crisis Caused by Covid-19 -- Remote Sensing and Artificial Intelligence -- Opportunities for Artificial Intelligence in Precision Agriculture Using Satellite remote Sensing -- Monitoring Land Productivity Trends in Souss-Massa Region Using Landsat Time series Data to Support SDG Target 15.3 -- Subimages Based Approach for Landslide Susceptibility Mapping Using Convolutional Neural Network -- Lithological Mapping for a Semi-arid Area Using GEOBIA and PBIA Machine Learning Approaches with Sentinel-2 Imagery: Case Study of Skhour Rehamna, Morocco -- Optimization of Object-based Image Analysis with Genetic Programming to Generate Explicit Knowledge from Worldview 2 Data for Urban Mapping -- Machine Learning and Remote Sensing in Mapping and Estimating Rosemary Cover biomass.
520 $a This book explores cutting-edge methods combining geospatial technologies and artificial intelligence related to several fields such as smart farming, urban planning, geology, transportation, and 3D city models. It introduces techniques which range from machine and deep learning to remote sensing for geospatial data analysis. The book consists of two main parts that include 13 chapters contributed by promising authors. The first part deals with the use of artificial intelligence techniques to improve spatial data analysis, whereas the second part focuses on the use of artificial intelligence with remote sensing in various fields. Throughout the chapters, the interest for the use of artificial intelligence is demonstrated for different geospatial technologies such as aerial imagery, drones, Lidar, satellite remote sensing, and more. The work in this book is dedicated to the scientific community interested in the coupling of geospatial technologies and artificial intelligence and exploring the synergetic effects of both fields. It offers practitioners and researchers from academia, the industry and government information, experiences and research results about all aspects of specialized and interdisciplinary fields on geospatial intelligence. .
650 2 4 $a Big Data. $3 1017136
650 1 4 $a Artificial Intelligence. $3 646849
650 0 $a Big data. $3 981821
650 0 $a Artificial intelligence. $3 559380
700 1 $a Dehbi, Youness. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1398020
700 1 $a Mansouri, Khalifa. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1398019
700 1 $a El Brirchi, El Hassan. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1398018
700 1 $a Barramou, Fatimazahra. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1398017
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030804572
776 0 8 $i Printed edition: $z 9783030804596
776 0 8 $i Printed edition: $z 9783030804602
830 0 $a Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development, $x 2522-8714 $3 1282677
856 4 0 $u https://doi.org/10.1007/978-3-030-80458-9
912 $a ZDB-2-EES
912 $a ZDB-2-SXEE
950 $a Earth and Environmental Science (SpringerNature-11646)
950 $a Earth and Environmental Science (R0) (SpringerNature-43711)