Cloud computing and interactive mapping with Earth Engine and open-source GIS

Abstract

My invited presentation at the GeoInsider webinar.

GEE教程在B站：https://gishub.org/bilibili

讲座视频: https://www.bilibili.com/video/BV1Ep4y1X7tJ

Full text

Cloud computing and interactive mapping
with Eah Engine and open-source GIS
吴秋生
Qiusheng Wu, PhD
Depament of Geography
University of Tennessee, Knoxville
hps://wetlands.io
hps://gishub.org/geoinsider
GeoInsider webinar
May 28, 2020
slides

About me
●Education
○2015 Ph.D. in Geography, University of Cincinnati
○2011 M.A. in Geography, University of Cincinnati
○2007 B.S. in GIS, Sun Yat-sen University
●Appointments
○2019 – present Assistant Professor of Geography, University of Tennessee
○2015 – 2019 Assistant Professor of Geography, Binghamton University
●Editorships
○2018 – present Associate Editor, Remote Sensing, MDPI (Impact Factor: 4.118)
○2016 – present Associate Editor, Wetlands, Springer Nature (Impact Factor: 1.854)
●Publications
○38 in total (11 as the rst author)
●Proles
○Personal Website | Google Scholar | Research Gate | GitHub | YouTube | Twier
2

Outline
●Eah Engine overview
●Introducing geemap
●Geemap tutorials
●QGIS Eah Engine Plugin
●Mapping suace waters
●Q&A
3

Eah Engine overview
4

Google Eah vs. Eah Engine
●Google Eah
○Google Eah enables you to travel and learn about the world through a viual globe. You can
view satellite imagery, maps, terrain, 3D buildings and much more.
●Eah Engine
○Eah Engine, on the other hand, is a tool for analyzing geospatial information.
○Although Eah Engine has a data catalog, not everything available in Google Eah is
available for analysis in the Eah Engine catalog. Similarly, much of the data in Eah Engine is
not currently available for visualization in Google Eah.
5
hps://eahengine.google.com
hps://google.com/eah
vs.
Image Viewer Photoshop

What is Eah Engine?
6
https://earthengine.google.com/

Google Eah Engine
Before Earth Engine
7

Google Eah Engine
Before Earth Engine
After Earth Engine
8

Google Data Centers
9
Credits to Michael DeWitt

Eah Engine Data Catalog
10
600+ public datasets
MODIS
250m daily
Vector Data
WDPA, TIGER, WHC
Weather & Climate
NOAA NCEP, OMI, ...
Terrain &
Land Cover
1+ PB of new data every month
100+ datasets added yearly
30+ petabytes of data
Landsat & Sentinel
10-30m, weekly
... and upload your own vectors and
rasters
https://developers.google.com/earth-engine/datasets/
Credits to Michael DeWitt

Eah Engine JavaScript Code Editor
11
https://code.earthengine.google.com/
Landsat NDWI example: https://code.earthengine.google.com/6850087dba0919bb8ca89de3ba363eac

Eah Engine JavaScript API vs. Python API
Eah Engine JavaScript Code Editor
●Rich documentation and tutorials
●Easy to get staed
●Built-in interactive mapping functionality
●Built-in authentication
●Eah Engine Apps
●Can’t install additional package
12
Eah Engine Python API
●Lacks documentation and tutorials
●Easier language syntax
●Easy to share code between scripts
●Batch processing (e.g., expoing images)
●Executing code block by block
●More IDEs with debugging capability
●Numerous Python packages
●Many ploing and visualization options
●Integration with open-source GIS
●A lot of basemaps to choose from
●Accessing data stored locally
●Deep learning
Credits to Tyler Erickson

Eah Engine JavaScript API vs. Python API
13

Introducing geemap
14

Introducing geemap
●A Python package for interactive mapping
with Google Eah Engine and ipyleaet.
●GitHub: hps://github.com/giswqs/geemap
15

Installing geemap
●PyPI
○pip install geemap
●conda-forge
○conda create -n gee python
○conda activate gee
○conda install -c conda-forge geemap
●GitHub
○pip install git+hps://github.com/giswqs/geemap
●How to update geemap?
○pip install -U geemap
○conda update -c conda-forge geemap
○geemap.update_package()
●国内如何挂载VPN使用geemap？
16

Geemap tutorials
17

Video tutorials
18
https://gishub.org/youtube-gee http://gishub.org/bilibili

Video tutorials
1. Introducing the geemap Python package for interactive mapping with Google Earth Engine (video | gif | notebook)
2. Using basemaps in geemap and ipyleaflet for interactive mapping with Google Earth Engine (video | gif | notebook)
3. Introducing the Inspector tool for Earth Engine Python API (video | gif | notebook)
4. Creating a split-panel map for visualizing Earth Engine data (video | gif | notebook)
5. Using drawing tools to interact with Earth Engine data (video | gif | notebook)
6. Creating an interactive map with a marker cluster (video | gif | notebook)
7. Converting data formats between GeoJSON and Earth Engine (video | gif | notebook)
8. Automated conversion from Earth Engine JavaScripts to Python scripts and Jupyter notebooks (video | gif | notebook)
9. Interactive plotting of Earth Engine data with minimal coding (video | gif | notebook)
10. Using shapefiles with Earth Engine without having to upload data to GEE (video | gif | notebook)
11. Exporting Earth Engine Image and ImageCollection as GeoTIFF and Numpy array (video | gif | notebook)
12. Computing zonal statistics with Earth Engine and exporting results as CSV or shapefile (video | gif | notebook)
13. Calculating zonal statistics by group with Earth Engine (video | gif | notebook)
14. Adding a customized legend for Earth Engine data (video | gif | notebook)
15. Converting Earth Engine JavaScripts to Python code directly within Jupyter notebook (video | gif | notebook)
16. Adding animated text to GIF images generated from Earth Engine data (video | gif | notebook)
17. Adding colorbar and images to GIF animations generated from Earth Engine data (video | gif | notebook)
18. Creating Landsat timelapse animations with animated text using Earth Engine (video | gif | notebook)
19. How to search and import datasets from Earth Engine Data Catalog (video | gif | notebook)
20. Using timeseries inspector to visualize landscape changes over time (video | gif | notebook)
21. Exporting Earth Engine maps as HTML files and PNG images (video | gif | notebook)19
http://gishub.org/geemap

Want more tutorials?
●A collection of 360+ Jupyter Python notebook examples for using Google
Eah Engine with interactive mapping
(hps://github.com/giswqs/eahengine-py-notebooks)
●Submit a Feature Request on the geemap GitHub repository
(hps://github.com/giswqs/geemap/issues )
●Follow my Google Eah Engine Project on Research Gate
(hps://www.researchgate.net/project/Google-Eah-Engine-4)
20

Key features
●Conveing GEE
JavaScripts to
Python code directly
within Jupyter
notebook by simply
copy-and-paste
21

Key features
●Batch conversion
from GEE
JavaScripts to
Jupyter notebooks
22

Key features
●Search and impo
datasets from Eah
Engine Data Catalog
23

Key features
●Search Eah Engine
API Documentation
directly within
Jupyter notebook
24

Key features
●Add basemaps (e.g.,
XYZ and WMS tiles)
not available in GEE
JavaScript Code
Editor
25
https://viewer.nationalmap.gov/services/

Key features
●Add customized
legends for Eah
Engine data
26

Key features
●Use the Inspector
tool to interact with
Eah Engine data
27

Key features
●Interactive ploing
of Eah Engine data
with minimal coding
28

Key features
●Create timelapse
animations with
animated text
29

Key features
●Use timeseries
inspector to
visualize landscape
changes over time
30

Key features
●Create an
interactive map with
marker cluster
31

Key features
●Use shapeles with
Eah Engine without
having to upload
data to your GEE
account
32

Key features
●Add animated text
and colorbar to
animations created
from Eah Engine
data
33

Key features
●Expo map as HTML
and PNG
34

QGIS Eah Engine Plugin
35

What is QGIS?
36
https://qgis.org/

QGIS Eah Engine Plugin
37

QGIS Eah Engine Examples
38
https://github.com/giswqs/qgis-earthengine-examples

QGIS Eah Engine Plugin Demo
39

Mapping Suace Water Dynamics
40

RSE Paper
41
●Eah Engine App
●GEE Source Code
●GitHub Repo
hps://gishub.org/2019-rse
download aicle

Eah Engine App
42

Study Area and Geospatial Datasets
43
▪Study Area
▪3 HUC-8 subbasins (16,576 km2 in total)
▪26 HUC-10 watersheds (318 ~ 998 km2)
▪Datasets
▪LiDAR data (2011-2016) - 107.65 GB
▪NAIP imagery (2009, 2010, 2012, 2014, 2015, 2017)
▪National Wetlands Inventory [NWI] (1980s)
▪JRC Global Suace Water (1984-2018)

Multi-temporal NAIP aerial imagery (1-m)
44

NAIP-derived Wetland Inundation Maps
45

Landsat-derived Inundation Maps
46

Any questions
Qiusheng Wu, PhD
Depament of Geography
University of Tennessee
Email: qwu18@utk.edu
Website: hps://wetlands.io
Twier: hps://twier.com/giswqs
wetlands.io
Thank you!