{"product_id":"earth-observation-using-python-9781119606888","title":"Earth Observation Using Python","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eLearn basic Python programming to create functional and effective visualizations from earth observation satellite data sets\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThousands of satellite datasets are freely available online, but scientists need the right tools to efficiently analyze data and share results. Python has easy-to-learn syntax and thousands of libraries to perform common Earth science programming tasks.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eEarth Observation Using Python: A Practical Programming Guide \u003c\/i\u003epresents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eGain Python fluency using real data and case studies\u003c\/li\u003e \u003cli\u003eRead and write common scientific data formats, like netCDF, HDF, and GRIB2\u003c\/li\u003e \u003cli\u003eCreate 3-dimensional maps of dust, fire, vegetation indices and more\u003c\/li\u003e \u003cli\u003eLearn to adjust satellite imagery resolution, apply quality control, and handle big files\u003c\/li\u003e \u003cli\u003eDevelop useful workflows and learn to share c\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eForeword\u003c\/p\u003e \u003cp\u003eIntroduction\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 A Tour of Current Satellite Missions and Products\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 History of Computational Scientific Visualization\u003c\/p\u003e \u003cp\u003e1.2 Brief catalog of current satellite products\u003c\/p\u003e \u003cp\u003e1.2.1 Meteorological and Atmospheric Science\u003c\/p\u003e \u003cp\u003e1.2.2 Hydrology\u003c\/p\u003e \u003cp\u003e1.2.3 Oceanography and Biogeosciences\u003c\/p\u003e \u003cp\u003e1.2.4 Cryosphere\u003c\/p\u003e \u003cp\u003e1.3 The Flow of Data from Satellites to Computer\u003c\/p\u003e \u003cp\u003e1.4 Learning using Real Data and Case Studies\u003c\/p\u003e \u003cp\u003e1.5 Summary\u003c\/p\u003e \u003cp\u003e1.6 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Overview of Python\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Why Python?\u003c\/p\u003e \u003cp\u003e2.2 Useful Packages for Remote Sensing Visualization\u003c\/p\u003e \u003cp\u003e2.2.1 NumPy\u003c\/p\u003e \u003cp\u003e2.2.2 Pandas\u003c\/p\u003e \u003cp\u003e2.2.3 Matplotlib\u003c\/p\u003e \u003cp\u003e2.2.4 netCDF4 and h5py\u003c\/p\u003e \u003cp\u003e2.2.5 Cartopy\u003c\/p\u003e \u003cp\u003e2.3 Maturing Packages\u003c\/p\u003e \u003cp\u003e2.3.1 xarray\u003c\/p\u003e \u003cp\u003e2.3.2 Dask\u003c\/p\u003e \u003cp\u003e2.3.3 Iris\u003c\/p\u003e \u003cp\u003e2.3.4 MetPy\u003c\/p\u003e \u003cp\u003e2.3.5 cfgrib and eccodes\u003c\/p\u003e \u003cp\u003e2.4 Summary\u003c\/p\u003e \u003cp\u003e2.5 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 A Deep Dive into Scientific Data Sets\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Storage\u003c\/p\u003e \u003cp\u003e3.1.1 Single-values\u003c\/p\u003e \u003cp\u003e3.1.2 Arrays\u003c\/p\u003e \u003cp\u003e3.2 Data Formats\u003c\/p\u003e \u003cp\u003e3.2.1 Binary\u003c\/p\u003e \u003cp\u003e3.2.2 Text\u003c\/p\u003e \u003cp\u003e3.2.3 Self-describing data formats\u003c\/p\u003e \u003cp\u003e3.2.4 Table-Driven Formats\u003c\/p\u003e \u003cp\u003e3.2.5 geoTIFF\u003c\/p\u003e \u003cp\u003e3.3 Data Usage\u003c\/p\u003e \u003cp\u003e3.3.1 Processing Levels\u003c\/p\u003e \u003cp\u003e3.3.2 Product Maturity\u003c\/p\u003e \u003cp\u003e3.3.3 Quality Control\u003c\/p\u003e \u003cp\u003e3.3.4 Data Latency\u003c\/p\u003e \u003cp\u003e3.3.5 Re-processing\u003c\/p\u003e \u003cp\u003e3.4 Summary\u003c\/p\u003e \u003cp\u003e3.5 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Practical Python Syntax\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 \"Hello Earth\" in Python\u003c\/p\u003e \u003cp\u003e4.2 Variable Assignment and Arithmetic\u003c\/p\u003e \u003cp\u003e4.3 Lists\u003c\/p\u003e \u003cp\u003e4.4 Importing Packages\u003c\/p\u003e \u003cp\u003e4.5 Array and Matrix Operations\u003c\/p\u003e \u003cp\u003e4.6 Time Series Data\u003c\/p\u003e \u003cp\u003e4.7 Loops\u003c\/p\u003e \u003cp\u003e4.8 List Comprehensions\u003c\/p\u003e \u003cp\u003e4.9 Functions\u003c\/p\u003e \u003cp\u003e4.10 Dictionaries\u003c\/p\u003e \u003cp\u003e4.11 Summary\u003c\/p\u003e \u003cp\u003e4.12 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Importing Standard Earth Science Datasets\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Text\u003c\/p\u003e \u003cp\u003e5.2 NetCDF\u003c\/p\u003e \u003cp\u003e5.3 HDF\u003c\/p\u003e \u003cp\u003e5.4 GRIB2\u003c\/p\u003e \u003cp\u003e5.5 Importing Data using xarray\u003c\/p\u003e \u003cp\u003e5.5.1 netCDF\u003c\/p\u003e \u003cp\u003e5.5.2 GRIB2\u003c\/p\u003e \u003cp\u003e5.5.3 Accessing datasets using OpenDAP\u003c\/p\u003e \u003cp\u003e5.6 Summary\u003c\/p\u003e \u003cp\u003e5.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Plotting and Graphs for All\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Univariate Plots\u003c\/p\u003e \u003cp\u003e6.1.1 Histograms\u003c\/p\u003e \u003cp\u003e6.1.2 Barplots\u003c\/p\u003e \u003cp\u003e6.2 Two Variable Plots\u003c\/p\u003e \u003cp\u003e6.2.1 Converting Data to a Time Series\u003c\/p\u003e \u003cp\u003e6.2.2 Useful Plot Customizations\u003c\/p\u003e \u003cp\u003e6.2.3 Scatter Plots\u003c\/p\u003e \u003cp\u003e6.2.4 Line Plots\u003c\/p\u003e \u003cp\u003e6.2.5 Adding data to an existing plot\u003c\/p\u003e \u003cp\u003e6.2.6 Plotting two side-by-side plots\u003c\/p\u003e \u003cp\u003e6.2.7 Skew-T Log-P\u003c\/p\u003e \u003cp\u003e6.3 Three Variable Plots\u003c\/p\u003e \u003cp\u003e6.3.1 Filled Contour\u003c\/p\u003e \u003cp\u003e6.3.2 Mesh Plots\u003c\/p\u003e \u003cp\u003e6.4 Summary\u003c\/p\u003e \u003cp\u003e6.5 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Creating Effective and Functional Maps\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Cartographic Projections\u003c\/p\u003e \u003cp\u003e7.1.1 Projections\u003c\/p\u003e \u003cp\u003e7.1.2 Plate Carrée\u003c\/p\u003e \u003cp\u003e7.1.3 Equidistant Conic\u003c\/p\u003e \u003cp\u003e7.1.4 Orthographic\u003c\/p\u003e \u003cp\u003e7.2 Cylindrical Maps\u003c\/p\u003e \u003cp\u003e7.2.1 Global plots\u003c\/p\u003e \u003cp\u003e7.2.2 Changing projections\u003c\/p\u003e \u003cp\u003e7.2.3 Regional Plots\u003c\/p\u003e \u003cp\u003e7.2.4 Swath Data\u003c\/p\u003e \u003cp\u003e7.2.5 Quality Flag Filtering\u003c\/p\u003e \u003cp\u003e7.3 Polar Stereographic Maps\u003c\/p\u003e \u003cp\u003e7.4 Geostationary Maps\u003c\/p\u003e \u003cp\u003e7.5 Plotting datasets using OpenDAP\u003c\/p\u003e \u003cp\u003e7.6 Summary\u003c\/p\u003e \u003cp\u003e7.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Gridding Operations\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Regular 1D grids\u003c\/p\u003e \u003cp\u003e8.2 Regular 2D grids\u003c\/p\u003e \u003cp\u003e8.3 Irregular 2D grids\u003c\/p\u003e \u003cp\u003e8.3.1 Resizing\u003c\/p\u003e \u003cp\u003e8.3.2 Regridding\u003c\/p\u003e \u003cp\u003e8.3.3 Resampling\u003c\/p\u003e \u003cp\u003e8.4 Summary\u003c\/p\u003e \u003cp\u003e8.5 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Meaningful Visuals through Data Combination\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Spectral and Spatial Characteristics of Different Sensors\u003c\/p\u003e \u003cp\u003e9.2 Normalized Difference Vegetation Index (NDVI)\u003c\/p\u003e \u003cp\u003e9.3 Window Channels\u003c\/p\u003e \u003cp\u003e9.4 RGB\u003c\/p\u003e \u003cp\u003e9.4.1 True Color\u003c\/p\u003e \u003cp\u003e9.4.2 Dust RGB\u003c\/p\u003e \u003cp\u003e9.4.3 Fire\/Natural RGB\u003c\/p\u003e \u003cp\u003e9.5 Matching with Surface Observations\u003c\/p\u003e \u003cp\u003e9.5.1 With user-defined functions\u003c\/p\u003e \u003cp\u003e9.5.2 With Machine Learning\u003c\/p\u003e \u003cp\u003e9.6 Summary\u003c\/p\u003e \u003cp\u003e9.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Exporting with Ease\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Figures\u003c\/p\u003e \u003cp\u003e10.2 Text Files\u003c\/p\u003e \u003cp\u003e10.3 Pickling\u003c\/p\u003e \u003cp\u003e10.4 NumPy binary files\u003c\/p\u003e \u003cp\u003e10.5 NetCDF\u003c\/p\u003e \u003cp\u003e10.5.1 Using netCDF4 to create netCDF files\u003c\/p\u003e \u003cp\u003e10.5.2 Using Xarray to create netCDF files\u003c\/p\u003e \u003cp\u003e10.5.3 Following Climate and Forecast (CF) metadata conventions\u003c\/p\u003e \u003cp\u003e10.6 Summary\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Developing a Workflow\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Scripting with Python\u003c\/p\u003e \u003cp\u003e11.1.1 Creating scripts using text editors\u003c\/p\u003e \u003cp\u003e11.1.2 Creating scripts from Jupyter Notebooks\u003c\/p\u003e \u003cp\u003e11.1.3 Running Python scripts from the command line\u003c\/p\u003e \u003cp\u003e11.1.4 Handling output when scripting\u003c\/p\u003e \u003cp\u003e11.2 Version Control\u003c\/p\u003e \u003cp\u003e11.2.1 Code Sharing though Online Repositories\u003c\/p\u003e \u003cp\u003e11.2.2 Setting-up on GitHub\u003c\/p\u003e \u003cp\u003e11.3 Virtual Environments\u003c\/p\u003e \u003cp\u003e11.3.1 Creating an environment\u003c\/p\u003e \u003cp\u003e11.3.2 Changing environments from the command line\u003c\/p\u003e \u003cp\u003e11.3.3 Changing environments in Jupyter Notebook\u003c\/p\u003e \u003cp\u003e11.4 Methods for code development\u003c\/p\u003e \u003cp\u003e11.5 Summary\u003c\/p\u003e \u003cp\u003e11.6 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Reproducible and Shareable Science\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Clean Coding Techniques\u003c\/p\u003e \u003cp\u003e12.1.1 Stylistic conventions\u003c\/p\u003e \u003cp\u003e12.1.2 Tools for Clean Code\u003c\/p\u003e \u003cp\u003e12.2 Documentation\u003c\/p\u003e \u003cp\u003e12.2.1 Comments and docstrings\u003c\/p\u003e \u003cp\u003e12.2.2 README file\u003c\/p\u003e \u003cp\u003e12.2.3 Creating useful commit messages\u003c\/p\u003e \u003cp\u003e12.3 Licensing\u003c\/p\u003e \u003cp\u003e12.4 Effective Visuals\u003c\/p\u003e \u003cp\u003e12.4.1 Make a Statement\u003c\/p\u003e \u003cp\u003e12.4.2 Undergo Revision\u003c\/p\u003e \u003cp\u003e12.4.3 Are Accessible and Ethical\u003c\/p\u003e \u003cp\u003e12.5 Summary\u003c\/p\u003e \u003cp\u003e12.6 References\u003c\/p\u003e \u003cp\u003eConclusion\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA Installing Python\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Download and Install Anaconda\u003c\/p\u003e \u003cp\u003eA.2 Package management in Anaconda\u003c\/p\u003e \u003cp\u003eA.3 Download sample data for this book\u003c\/p\u003e \u003cp\u003e\u003cb\u003eB Jupyter Notebooks\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 Running on a Local Machine (New Coders)\u003c\/p\u003e \u003cp\u003eB.2 Running on a Remote Server (Advanced)\u003c\/p\u003e \u003cp\u003eB.3 Tips for Advanced Users\u003c\/p\u003e \u003cp\u003eB.3.1 Customizing Notebooks with Configuration Files\u003c\/p\u003e \u003cp\u003eB.3.2 Starting and Ending Python Scripts\u003c\/p\u003e \u003cp\u003eB.3.3 Creating Git Commit templates\u003c\/p\u003e \u003cp\u003e\u003cb\u003eC Additional Learning Resources\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eD Tools\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eD.1 Text Editors and IDEs\u003c\/p\u003e \u003cp\u003eD.2 Terminals\u003c\/p\u003e \u003cp\u003e\u003cb\u003eE Finding, Accessing, and Downloading Satellite Datasets\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eE.1 Ordering data from NASA EarthData\u003c\/p\u003e \u003cp\u003eE.2 Ordering data from NOAA\/CLASS\u003c\/p\u003e \u003cp\u003e\u003cb\u003eF Acronyms\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAcknowledgements\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48866405351767,"sku":"9781119606888","price":127.76,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119606888.jpg?v=1722278489","url":"https:\/\/bookcurl.com\/products\/earth-observation-using-python-9781119606888","provider":"Book 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