Examples

Python notebook examples

Important

geeViz.geeView map outputs will not display correctly in these example notebooks below. They will correctly display when you run them.

Getting Started using geeViz

• Starter geeViz geeView Notebook
  • Importing geeViz.geeView
  • Adding a GEE image (NLCD) to the Map and viewing and querying it
  • Visualizing multiple layers on the map
  • Introducing map query lookup tables and custom styles
  • Visualizing vectors and rasters on the map
  • Visualizing GEE layers as a local geojson vector
  • Using geeView’s Map.addTimeLapse function to visualize an imageCollection

Visualize multi-temporal imageCollections

• LCMS Viewer Intro Notebook
  • First, we’ll take a look at the foundation of the geeViz.geeView module - the LCMS Data Explorer
  • Create your own LCMS Viewer
  • Time lapses enable quick visualization of multi-temporal imageCollections

Visualize Annual NLCD

• Annual NLCD geeViz Viewer
  • View and explore NLCD Land Cover and Land Use
  • View and explore Annual NLCD Fractional Impervious Surface
  • View and explore Annual NLCD Spectral Change

Visualize MapBiomas Datasets

• Visualizing MapBiomas Datasets
  • Make a basic viewer
  • Calculating and Exporting Statistics¶
  • Create Sankey Charts

Visualize Aboveground Biomass

• Visualizing Aboveground Biomass
  • Make a basic viewer

Visualize Dynamic World

• Visualizing Dynamic World
  • Make a basic viewer
  • Visualizing Dynamic World over time
  • Create Sankey Charts

Visualize the Global Land Cover Dataset

• Visualizing Global Land Cover
  • Make a basic viewer
  • Calculating and Exporting Landcover Statistics¶
  • Create Sankey Charts

Visualize LCMS and LCMAP Outputs

• LCMAP and LCMS Outputs Viewer
  • Bring in LCMAP outputs
  • Bring in LCMS GEE collections

Leverage geeViz.getImagesLib to consistently process Landsat data

• Create High Quality Landsat Composites
  • Setting up numerous parameters available for processing Landsat data
  • Improving composite outputs by including Landsat 7
  • Improving cloud masking using the cloudScore method
  • Improving cloud shadow masking using TDOM

Interactively summarize data

• Visualizing Area Summaries
  • Basic Area Charting
  • Line and Sankey Charts
  • Ways of adding area charting layers
  • Charting Non-Thematic Data
  • Charting Images
  • Charting Images Without Color and Name Properties
  • Charting Time Lapses
  • Charting Thematic Data without set properties
    • Setting properties for charting
  • Comparing map output versions
  • Other charting summary zone selection methods

Learn how geeViz compares to geeMap

• A comparison between geeViz and geeMap’s map visualization capabilities
  • First, we’ll take a look at the two different map interfaces
  • Some methods are similar between the methods available
  • Using geeMap and geeViz together

Run LandTrendr

• Run LandTrendr and Visualize Outputs
  • Create Annual Median Composites
    • Set up parameters
    • Create Composites
  • Run LandTrendr
    • Set up LandTrendr Parameters
    • Run LandTrendr
  • Exporting

Visualize LandTrendr Outputs

• Visualize LandTrendr Outputs
  • Set up parameters
  • Visualize and Inspect LandTrendr Annual Fitted Time Series
    • LandTrendr Change Detection

Visualize LCMS and LCMAP Outputs

• LCMAP and LCMS Outputs Viewer
  • Bring in LCMAP outputs
  • Bring in LCMS GEE collections

Visualize CCDC Outputs

• CCDC Visualization Notebook
  • Bring in CCDC data and set parameters
  • View and query raw CCDC outputs
  • Change detection using CCDC
  • Create fitted time series
  • Combining CCDC outputs
  • Combining CCDC Outputs for Change Detection

Crosswalk LCMS Levels

• Learn to crosswalk LCMS datasets to different levels
  • First, we’ll take a look at the various levels for LCMS data
  • Learn how to crosswalk and symbolize LCMS products at a specific level
  • Crosswalk and visualize all LCMS products and levels
  • The v2024-10 release introduces a new set of classes for Change
  • Now, we’ll look at how to crosswalk and symbolize the various products and levels of LCMS data
  • Next, we’ll take a look at the accuracy of LCMS at different levels

Python script examples

Any of the following scripts

import geeViz.examples.timeLapseExample
import geeViz.examples.getLandsatWrapper
import geeViz.examples.getSentinel2Wrapper
import geeViz.examples.getCombinedLandsatSentinel2Wrapper
import geeViz.examples.harmonicRegressionWrapper
import geeViz.examples.LANDTRENDRWrapper
import geeViz.examples.LANDTRENDRViz
import geeViz.examples.CCDCViz
import geeViz.examples.lcmsViewerExample
import geeViz.examples.LCMAP_and_LCMS_Viewer
import geeViz.examples.phEEnoVizWrapper
import geeViz.examples.LANDTRENDRViz
import geeViz.examples.GFSTimeLapse

Other examples

Landscape Change Monitoring System Training Notebooks