Читать книгу Earth Observation Using Python - Rebekah B. Esmaili - Страница 2
Table of Contents
Оглавление1 Cover
4 Foreword
7 Part I: Overview of Satellite Datasets 1 A TOUR OF CURRENT SATELLITE MISSIONS AND PRODUCTS 1.1 History of Computational Scientific Visualization 1.2 Brief Catalog of Current Satellite Products 1.3 The Flow of Data from Satellites to Computer 1.4 Learning Using Real Data and Case Studies 1.5 Summary References 2 OVERVIEW OF PYTHON 2.1 Why Python? 2.2 Useful Packages for Remote Sensing Visualization 2.3 Maturing Packages 2.4 Summary References 3 A DEEP DIVE INTO SCIENTIFIC DATA SETS 3.1 Storage 3.2 Data Formats 3.3 Data Usage 3.4 Summary References
8 Part II: Practical Python Tutorials for Remote Sensing 4 PRACTICAL PYTHON SYNTAX 4.1 “Hello Earth” in Python 4.2 Variable Assignment and Arithmetic 4.3 Lists 4.4 Importing Packages 4.5 Array and Matrix Operations 4.6 Time Series Data 4.7 Loops 4.8 List Comprehensions 4.9 Functions 4.10 Dictionaries 4.11 Summary References 5 IMPORTING STANDARD EARTH SCIENCE DATASETS 5.1 Text 5.2 NetCDF 5.3 HDF 5.4 GRIB2 5.5 Importing Data Using Xarray 5.6 Summary References 6 PLOTTING AND GRAPHS FOR ALL 6.1 Univariate Plots 6.2 Two Variable Plots 6.3 Three Variable Plots 6.4 Summary References 7 CREATING EFFECTIVE AND FUNCTIONAL MAPS 7.1 Cartographic Projections 7.2 Cylindrical Maps 7.3 Polar Stereographic Maps 7.4 Geostationary Maps 7.5 Creating Maps from Datasets Using OpenDAP 7.6 Summary References 8 GRIDDING OPERATIONS 8.1 Regular One‐Dimensional Grids 8.2 Regular Two‐Dimensional Grids 8.3 Irregular Two‐Dimensional Grids 8.4 Summary References 9 MEANINGFUL VISUALS THROUGH DATA COMBINATION 9.1 Spectral and Spatial Characteristics of Different Sensors 9.2 Normalized Difference Vegetation Index (NDVI) 9.3 Window Channels 9.4 RGB 9.5 Matching with Surface Observations 9.6 Summary References 10 EXPORTING WITH EASE 10.1 Figures 10.2 Text Files 10.3 Pickling 10.4 NumPy Binary Files 10.5 NetCDF 10.6 Summary
9 Part III: Effective Coding Practices 11 DEVELOPING A WORKFLOW 11.1 Scripting with Python 11.2 Version Control 11.3 Virtual Environments 11.4 Methods for Code Development 11.5 Summary References 12 REPRODUCIBLE AND SHAREABLE SCIENCE 12.1 Clean Coding Techniques 12.2 Documentation 12.3 Licensing 12.4 Effective Visuals 12.5 Summary References
10 Conclusion
11 Appendix A: INSTALLING PYTHON A.1 Download Tutorials for This Book A.2 Download and Install Anaconda A.3 Package Management in Anaconda
12 Appendix B: JUPYTER NOTEBOOK
13 Appendix C: ADDITIONAL LEARNING RESOURCES
15 Appendix E: FINDING, ACCESSING, AND DOWNLOADING SATELLITE DATASETS
17 Index
