Hey,
I'm Maddie Grady
Earth Observation Specialist and Spatial Scientist
I'm Maddie Grady
Earth Observation Specialist and Spatial Scientist
I love unpicking big data, solving mysteries and discovering new things about our world!
You can find me engrossed in Python environments, building software to analyse changes in land cover,
modelling ecological systems or sourcing information to build databases of the
real world in GIS software.
At heart I am a problem solver. I love to take things apart and figure out the solution.
Whether it's determining the most efficient code to analyse a time series or discovering
the best graph or animation to spread the message I've found in some data,
I love the challenge of finding out how it can be done and devising and working on the solution.
As long as I have some sort of problem or something to puzzle over I'm happy!
Currently, I am a Scientist at Planet, where I research novel ways to derive information and insights
from Planet's remote sensing products.
Prior to this I was a Spatial Scientist at Forest Research using remote sensing tecnologies to make maps of tree canopy and forest species.
I started my career a PhD researcher at Aberystwyth University, where I developed software to detect changes on the Earth's surface through time from satellites.
Python
GIS
Machine Learning and Statistics
Data Visulisation
Examples of some of the exciting projects I've had the opportunity to be heavily involved with.
Check out my resume for further details.
Crop Growth Stage Identification
Planet, Julius-Kuehn InstitutDeveloping software and statistics to identify the growth stages of crops from Planet time series data and Land Surface Temperature.
Project Website
Locating Larch
Forest ResearchDeveloping software and statistical approaches to assign probablities of larch presence to a time series of satellite imagery, based on the defoliation of larch stands.
Individual Tree Identification
Forest ResearchDeveloping python software to delinate individual tree canopies using aerial photography, LiDAR, segmentation and machine learning.
Deep Learning for Tree Canopy Delination
Forest Research, Cambridge University, Aberdeen UniversityTransfer learning of R-CNN model to identify tree canopy.
Google Colab Notebook
Land Cover Change Detection
Aberystwyth University, Welsh Government, Geosmart DecisionsDevelopment of a novel approach to monitor current and historic land cover change using old map regions and statistical deviations in new image data.
Red Kite Habitat Modeling
Aberystwyth UniversityModelling of the ecological nice of Red Kites in Wales. Generating a series of habitat maps and datasets of bird numbers and suitibility.
Report
