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ONLINE COURSE – Using Google Earth Engine in Ecological Studies (GEEE01) This course will be delivered live

22 July 2024 - 26 July 2024

ONLINE COURSE – Using Google Earth Engine in Ecological Studies (GEEE01) This course will be delivered live

Event Date

Monday, July 22nd, 2024

Course Format

This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.

Time Zone

TIME ZONE – Western European Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.

Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).

About This Course

Google Earth Engine (GEE) is a cloud computing platform for processing satellite imagery and other geospatial and observational data. GEE is currently the most complete and efficient platform for performing remote sensing analysis, as it provides access to a large database of satellite imagery and the computational power needed to analyse these images. While other remote sensing programs require the user to have sufficient space and computing power available, all data and processes in GEE are done in the cloud through Google's infrastructure. GEE provides a code editor that works with JavaScript and Python. GEE is the future of remote sensing.

By the end of the course, participants should:
 Know the catalogue of spatial datasets provided by GEE.
 Know the most important satellite sensors for environmental studies in GEE.
 Know how to get remote sensing products from GEE.
 Process and develop new remote sensing (sub-)products in GEE.
 Classify satellite imagery in GEE.
 Perform different types of spatial analyses in satellite imagery in GEE.

Intended Audiences

The target audience for this training is students, researchers, technicians, teachers, or other
professionals who work in the areas of remote sensing, environment, geo-informatics, geomatics,
geospatial engineering, biology, ecology, and biogeography.


Delivered remotely

Course Details

Time Zone – Western European Time

Availability – 25 Places

Duration – 5 days

Contact hours – Approx. 35 hours

ECT’s – Equal to 3 ECT’s

Language – English

Teaching Format

The topics will be presented and discussed in the theoretical classes to stimulate the interest of the
participants and to provide the set of knowledge considered necessary and relevant for a complete
understanding of the Google Earth Engine platform. In the practical classes, participants are invited
to think about and solve a set of problems to consolidate the knowledge acquired in the theoretical
lectures. The practical work proposed on the computer aims to train students in solving a set of
typical remote sensing problems related to the topics of the course program. The objective is for
participants to obtain the necessary tools that will allow them to use Google Earth Engine and to
deepen their knowledge autonomously. No data will be provided to the participants because all the
necessary data are stored in GEE.

Assumed quantitative knowledge

Solid knowledge of Geographical Information Systems and Remote Sensing is necessary. This course will suppose the attendees to know how to analyse remote sensing data.

Assumed computer background

No programming experience in JavaScript or Python will be necessary, although having programming knowledge will be extremely useful. However, this is not a course on programming. We will not teach JavaScript or Python but provide the necessary scripts to run analyses in GEE.

Equipment and software requirements

A laptop/personal computer, a list of software you need to install will be sent the week before the course starts.


The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
£ 480.00

Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.

If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com



Monday 22nd

Classes from 09:30 to 17:30

 Introduction to Google Earth Engine:
o Understand the fundamentals of how Google Earth Engine operates
o Visualize geospatial information in GEE
o Know the catalogue of the most important satellite images in the environmental area
o Build the first scripts in GEE and how to run them
o GEE related platforms

Tuesday 23rd

Classes from 09:30 to 17:30

 Introduction to remote sensing products and analyses in Google Earth Engine:
o Select, visualize and access the metadata of satellite image data series (e.g., MODIS, Landsat, Sentinel)
o Filter the data by spatial and temporal extents
o Aggregate data over time, space and bands using reducer functions
o Build image composites and mosaics
o Conduct cloud masking operations
o Geospatial computations and operations (e.g., obtain terrain products from DEMs and calculate spectral indexes)
o Import spatial data as Assets

Wednesday 24th

Classes from 09:30 to 17:30

 Process, classify and analyse multispectral images:
o Quality assessment of satellite images
o Learn the image classification algorithms available in GEE
o Perform unsupervised classifications
o Photo-interpretation of satellite images and build datasets of training areas (regions of interest)
o Conduct spectral separability analyses
o Perform supervised classifications
o Evaluate final image classifications
o Export outputs to Google Drive

Thursday 25th

Classes from 09:30 to 17:30

 Analyse time-series data and the temporal evolution of vegetation productivity and land use
o Calculate spectral indices
o Analyse available and ready-to-use products of vegetation productivity proxies and
LULC maps
o Build and export time-series plots (e.g., seasonality plots, anomaly analysis)
o Conduct non-parametric trend analyses using time-series data
o Time series modelling using linear regressions
o Export outputs to Google Drive


Friday 26th

Classes from 09:30 to 17:30

 Learn advanced spatial modelling tools:
o Import species databases into GEE (vector data or tabular databases) as assets
o Search and import environmental variables for modelling procedures
o Correlation analyses of environmental variables
o Search information about modelling algorithms and classifiers available in GEE
o Visualize and calibrate ecological niche models (e.g. Maxent)
o Conduct modelling analyses and assess the predictive performance of the models
o Visualize model projections in GEE
o Export model outputs to Google Drive

Dr. Neftali Sillero
Dr. Neftali Sillero
Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns, from species to populations and individuals. For this, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems, Remote Sensing, Ecological Niche Modelling, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases, ecological modelling of species’ ranges, identification of biogeographical regions and species’ chorotypes, mapping and modelling road-kill hotspots, and spatial analyses of home ranges.

He has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea, where he is the PI of the NA2RE project (www.na2re.ismai.pt), the New Atlas of Amphibians and Reptiles of Europe

Personal website
Work Webpage

  • Ecological Niche Modelling Using R (ENMR)
  • Advanced Ecological Niche Modelling Using R (ANMR)
  • GIS And Remote Sensing Analyses With R (GARM)
  • Ecological Niche Modelling Using R (ENMR)
  • Advanced Ecological Niche Modelling Using R (ANMR)
  • GIS And Remote Sensing Analyses With R (GARM)
Dr. Salvador Arenas-Castro
Dr. Salvador Arenas-Castro

Dr. Salvador Arenas-Castro is a broad-spectrum ecologist with interesting in different
integrative perspective of the fundamental ecology, macroecology and biogeography
with their both application and relationship to climate and land management. He is also
exploring other research sources in agroecology, forestry, spatial ecology, and
ecoinformatics, all addressed by explicitly considering the spatial component of
ecological processes, mainly applying spatially explicit modelling approaches, GIS and
remote sensing techniques. Please check his webpage for further information:

Google Scholar: https://scholar.google.com/citations?user=UAYiB5UAAAAJ&hl=es&oi=ao
ResearchGate: https://www.researchgate.net/profile/Salvador-Arenas-Castro


22 July 2024
26 July 2024
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The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
£ 480.00