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Produktbild: Google Earth Engine and Artificial Intelligence for Earth Observation

Google Earth Engine and Artificial Intelligence for Earth Observation

Aus der Reihe Earth Observation

Fr. 193.00

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

09.06.2025

Herausgeber

Vishakha Sood + weitere

Verlag

Elsevier Science & Technology

Seitenzahl

578

Maße (L/B/H)

22.9/15.2/3 cm

Gewicht

765 g

Sprache

Englisch

ISBN

978-0-443-27372-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

09.06.2025

Herausgeber

Verlag

Elsevier Science & Technology

Seitenzahl

578

Maße (L/B/H)

22.9/15.2/3 cm

Gewicht

765 g

Sprache

Englisch

ISBN

978-0-443-27372-8

EU-Ansprechpartner

Kolibri 360 GmbH
Ettore-Bugatti-Straße 6-14
51149 Köln
DE
produktsicherheit@kolibri360.de

Herstelleradresse

Elsevier Science & Technology
London Wall 125
EC2Y 5AS London
GB
tradeorders@elsevier.com

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  • Produktbild: Google Earth Engine and Artificial Intelligence for Earth Observation

  • Section A - Introduction of AI-driven GEE cloud computinge
    based remote sensing

    1. Introduction to Google Earth Engine: A comprehensive workflow
    2. Role of GEE in earth observation via remote sensing
    3. A meta-analysis of Google Earth Engine in different scientific domains
    4. Exploration of science of remote sensing and GIS with GEE
    5. Cloud computing platformsebased remote sensing big data applications
    6. Role of various machine and deep learning classification algorithms in Google Earth Engine: A comparative analysis
    7. Google Earth Engine and artificial intelligence for SDGs

    Section B - Emerging applications of GEE in Earth observation

    8. Machine learning algorithms for air quality and air pollution monitoring using GEE
    9. Investigation of surface water dynamics from the Landsat series using Google Earth Engine: A case study of Lake Bafa
    10. Monitoring of land cover changes and dust events over the last 2 decades using Google Earth Engine: Hamoun wetland, Iran
    11. Leveraging Google Earth Engine for improved groundwater management and sustainability
    12. Customized spatial data cube of urban environs using Google Earth Engine (GEE)
    13. A novel self-supervised framework for satellite image classification in the Google Earth Engine cloud computing platform
    14. Assessment and monitoring of forest fire using vegetation indices and AI/ML techniques over google earth engine
    15. Utilizing google earth engine and remote sensing with machine learning algorithms for assessing carbon stock loss and atmospheric impact through pre- and postfire analysis
    16. Time series of Sentinel-1 and Sentinel-2 imagery for parcel-based crop-type classification using Random Forest algorithm and Google Earth Engine
    17. Multi-temporal monitoring of impervious surface areas (ISA) changes in an Arctic setting, using ML, remote sensing data, and GEE
    18. Estimation of snow or ice cover parameters using Google Earth engine and AI
    19. Climate change challenges: The vital role of Google Earth Engine for sustainability of small islands in the archipelagic countries
    20. Evaluating machine learning algorithms for classifying urban heterogeneous landscapes using GEE
    21. Application of analytic hierarchy process for mapping flood vulnerability in Odisha using Google Earth Engine
    22. Deep learning-based method for monitoring precision agriculture using Google Earth Engine
    23. Role of AI and IoT in agricultural applications using Google Earth Engine
    24. Mature and immature oil palm classification from image Sentinel-2 using Google earth engine (GEE)
    25. Tracking land use and land cover changes in Ghaziabad district of India using machine learning and Google Earth engine

    Section C - Challenges and future trends of GEE

    26. Challenges and limitations for cloud-based platforms and integration with AI algorithms for earth observation data analytics
    27. AI-driven tools and technologies for agriculture land use & land cover classification using earth observation data analytics