Emerging trends, techniques, and applications in geospatial data science:
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey PA, USA
IGI Global
[2023]
|
| Series: | Advances in geospatial technologies (AGT)
|
| Subjects: | |
| Links: | http://doi.org/10.4018/978-1-6684-7319-1 http://doi.org/10.4018/978-1-6684-7319-1 https://doi.org/10.4018/978-1-6684-7319-1 https://doi.org/10.4018/978-1-6684-7319-1 http://doi.org/10.4018/978-1-6684-7319-1 http://doi.org/10.4018/978-1-6684-7319-1 |
| Abstract: | "This book provides an overview of basic concepts of data science, related tools & technologies, and algorithms for handling the relevant challenges in real-time applications domains. The book covers a detailed description to the readers with practical ideas of using AI, IoT, machine learning to deal with the analysis, modeling and predications from big data. This book comprises of topics which provide in depth understanding of various latest tools and techniques used in the analysis of geospatial big data for real-time applications, as well as to deal with the relevant challenges for future applications. Overall this publication 'The Geospatial Data Science: Emerging Trends, Techniques and Applications', would help the readers to understand the value and importance of big data to individuals as well as homes and organizations. In addition, it will provide insights to undertake research work in future challenging areas" |
| Physical Description: | 1 Online-Ressource (xv, 309 Seiten) Diagramme |
| ISBN: | 9781668473214 1668473216 |
| DOI: | 10.4018/978-1-6684-7319-1 |
Staff View
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| 505 | 8 | |a Chapter 1. Understanding geospatial data -- Chapter 2. Spatiotemporal data engineering -- Chapter 3. Spatio-temporal outlier detection: methods, applications, and research directions -- Chapter 4. Applications of deep learning for vehicle detection using geospatial data -- Chapter 5. An insight into applications of IoT in the agricultural sector -- Chapter 6. IoT-based smart and precision agricultural applications -- Chapter 7. Machine learning-based handling of geospatial big data from hyperspectral sensors for urban area characterization -- Chapter 8. Applying a deep learning approach for building extraction from high-resolution remote sensing imagery -- Chapter 9. Analysis of real estate prices using geospatial data: models and tools -- Chapter 10. Applications of artificial intelligence and machine learning in geospatial data -- Chapter 11. Emerging trends in the mapping of contaminated snow using hyperspectral images and field spectra -- Chapter 12. Artificial intelligence for defence: a comprehensive study on applying AI for the airforce, navy, and army | |
| 520 | 3 | |a "This book provides an overview of basic concepts of data science, related tools & technologies, and algorithms for handling the relevant challenges in real-time applications domains. The book covers a detailed description to the readers with practical ideas of using AI, IoT, machine learning to deal with the analysis, modeling and predications from big data. This book comprises of topics which provide in depth understanding of various latest tools and techniques used in the analysis of geospatial big data for real-time applications, as well as to deal with the relevant challenges for future applications. Overall this publication 'The Geospatial Data Science: Emerging Trends, Techniques and Applications', would help the readers to understand the value and importance of big data to individuals as well as homes and organizations. In addition, it will provide insights to undertake research work in future challenging areas" | |
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| contents | Chapter 1. Understanding geospatial data -- Chapter 2. Spatiotemporal data engineering -- Chapter 3. Spatio-temporal outlier detection: methods, applications, and research directions -- Chapter 4. Applications of deep learning for vehicle detection using geospatial data -- Chapter 5. An insight into applications of IoT in the agricultural sector -- Chapter 6. IoT-based smart and precision agricultural applications -- Chapter 7. Machine learning-based handling of geospatial big data from hyperspectral sensors for urban area characterization -- Chapter 8. Applying a deep learning approach for building extraction from high-resolution remote sensing imagery -- Chapter 9. Analysis of real estate prices using geospatial data: models and tools -- Chapter 10. Applications of artificial intelligence and machine learning in geospatial data -- Chapter 11. Emerging trends in the mapping of contaminated snow using hyperspectral images and field spectra -- Chapter 12. Artificial intelligence for defence: a comprehensive study on applying AI for the airforce, navy, and army |
| ctrlnum | (ZDB-98-IGB)9781668473214 (OCoLC)1379388624 (DE-599)BVBBV048931833 |
| discipline | Geographie |
| doi_str_mv | 10.4018/978-1-6684-7319-1 |
| format | Electronic eBook |
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| id | DE-604.BV048931833 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-11T15:38:05Z |
| institution | BVB |
| isbn | 9781668473214 1668473216 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034195772 |
| oclc_num | 1379388624 |
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| physical | 1 Online-Ressource (xv, 309 Seiten) Diagramme |
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| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | IGI Global |
| record_format | marc |
| series2 | Advances in geospatial technologies (AGT) |
| spellingShingle | Emerging trends, techniques, and applications in geospatial data science Chapter 1. Understanding geospatial data -- Chapter 2. Spatiotemporal data engineering -- Chapter 3. Spatio-temporal outlier detection: methods, applications, and research directions -- Chapter 4. Applications of deep learning for vehicle detection using geospatial data -- Chapter 5. An insight into applications of IoT in the agricultural sector -- Chapter 6. IoT-based smart and precision agricultural applications -- Chapter 7. Machine learning-based handling of geospatial big data from hyperspectral sensors for urban area characterization -- Chapter 8. Applying a deep learning approach for building extraction from high-resolution remote sensing imagery -- Chapter 9. Analysis of real estate prices using geospatial data: models and tools -- Chapter 10. Applications of artificial intelligence and machine learning in geospatial data -- Chapter 11. Emerging trends in the mapping of contaminated snow using hyperspectral images and field spectra -- Chapter 12. Artificial intelligence for defence: a comprehensive study on applying AI for the airforce, navy, and army Geoinformatik (DE-588)7571300-7 gnd Datenverarbeitung (DE-588)4011152-0 gnd |
| subject_GND | (DE-588)7571300-7 (DE-588)4011152-0 |
| title | Emerging trends, techniques, and applications in geospatial data science |
| title_auth | Emerging trends, techniques, and applications in geospatial data science |
| title_exact_search | Emerging trends, techniques, and applications in geospatial data science |
| title_full | Emerging trends, techniques, and applications in geospatial data science Loveleen Gaur (Amity University, India & Taylor’s University, Malaysia & University of the South Pacific, Fiji), P.K. Garg (Indian Institute of Technology, Roorkee, India) |
| title_fullStr | Emerging trends, techniques, and applications in geospatial data science Loveleen Gaur (Amity University, India & Taylor’s University, Malaysia & University of the South Pacific, Fiji), P.K. Garg (Indian Institute of Technology, Roorkee, India) |
| title_full_unstemmed | Emerging trends, techniques, and applications in geospatial data science Loveleen Gaur (Amity University, India & Taylor’s University, Malaysia & University of the South Pacific, Fiji), P.K. Garg (Indian Institute of Technology, Roorkee, India) |
| title_short | Emerging trends, techniques, and applications in geospatial data science |
| title_sort | emerging trends techniques and applications in geospatial data science |
| topic | Geoinformatik (DE-588)7571300-7 gnd Datenverarbeitung (DE-588)4011152-0 gnd |
| topic_facet | Geoinformatik Datenverarbeitung |
| url | http://doi.org/10.4018/978-1-6684-7319-1 |
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