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

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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
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!
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