Cloud-Based Remote Sensing with Google Earth Engine Fundamentals and Applications /

Cloud-Based Remote Sensing with Google Earth Engine Fundamentals and Applications /

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This book guides its audience-which can range from novice users to experts- though a 55-chapter tour of Google Earth Engine. A sequenced and diverse set of lab materials, this is the product of more than a year of effort from more than a hundred individuals, collecting new exercises from professors,...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Cardille, Jeffrey A. (Editor), Crowley, Morgan A. (Editor), Saah, David (Editor), Clinton, Nicholas E. (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2024.
Edition:1st ed. 2024.
Subjects:
Environmental monitoring.
Image processing.
Artificial intelligence > Data processing.
Engineering > Data processing.
Environmental Monitoring.
Image Processing.
Data Science.
Data Engineering.
Online Access:Link to Metadata
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Table of Contents:
  • Part 1: Programming and Remote Sensing Basics
  • 1. JavaScript and the Earth Engine API
  • 2. Exploring Images
  • 3. Survey of Raster Datasets
  • 4. The Remote Sensing Vocabulary.-Part 2: Interpreting Images
  • 5. Image Manipulation: Bands, Arithmetic, Thresholds, and Masks
  • 6. Interpreting an Image: Classification
  • 7. Accuracy Assessment: Quantifying Classification Quality
  • Part 3: Advanced Image Processing
  • 8. Interpreting an Image: Regression
  • 9. Advanced Pixel-based Image Transformation
  • 10. Neighborhood-based Image Transformation
  • 11. Object-based Image Analysis
  • Part 4: Interpreting Image Series
  • 12. Filter, Map, Reduce
  • 13. Exploring Image Collections
  • 14. Aggregating Images for Time Series
  • 15. Clouds and Image Compositing
  • 16. Change Detection
  • 17. Interpreting Annual Time Series with LandTrendr
  • 18. Fitting Functions to Time Series.-19. Interpreting Time Series with CCDC
  • 20. Data Fusion: Merging Classification Streams
  • 21. Exploring Lagged Effects in Time Series
  • Part 5: Vectors and Tables
  • 22. Exploring Vectors
  • 23. Raster/Vector Conversions
  • 24. Zonal Statistics
  • 25. Advanced Vector Operations
  • 26. GEEDiT - Digitizing From Satellite Imagery
  • Part 6: Advanced Topics
  • 27. Advanced Raster Visualization
  • 28. Collaborating in Earth Engine with Scripts and Assets
  • 29. Scaling up in Earth Engine
  • 30. Sharing Work in Earth Engine: Basic UI and Apps
  • 31. Combining R and Earth Engine
  • Part 7: Human Applications
  • 32. Agricultural Environments
  • 33. Urban Environments
  • 34. Built Environments
  • 35. Air pollution and population exposure
  • 36. Heat Islands
  • 37. Health Applications
  • 38. Humanitarian Applications
  • 39. Monitoring Gold Mining Activity using SAR
  • Part 8: Aquatic and Hydrological Applications
  • 40. Groundwater monitoring with GRACE
  • 41. Benthic Habitats
  • 42. Surface Water Mapping
  • 43. River morphology
  • 44. Water Balance and Drought
  • 45. Defining Seasonality: First Date of No Snow.-Part 9: Terrestrial Applications
  • 46. Active fire monitoring
  • 47. Mangroves
  • 48. Mangroves II - Change Mapping
  • 49. Forest Degradation and Deforestation
  • 50. Deforestation Viewed from Multiple Sensors
  • 51. Working With GPS & Weather Data
  • 52. Creating Presence and Absence Points
  • 53. Detecting Land Cover Change in Rangelands
  • 54. Conservation I - Assessing the spatial relationship between burned area and precipitation
  • 55. Conservation II - Assessing Agricultural Intensification Near Protected Areas.

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