Day 1 Session 2 Introduction to Geospatial Raster and Vector Data with Python

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=b5pAVpf78hE

Overview: • Introduction to Geospatial Raster and Vector Data with Python is an interactive workshop designed to empower you with the skills to query, analyze, and visualize geospatial raster and vector data. In this hands-on session, you'll work with real-world remote sensing datasets and environmental data from Amsterdam using your own laptop and the Jupyter notebook programming environment. • Topics we’ll cover include how Python handles spatial data structures, coordinate reference systems, rasters, and vectors. Throughout we’ll use powerful geospatial libraries like pystac-client, rioxarray, and geopandas to fetch, open, and plot raster and vector datasets using Cloud Optimized Geotiffs (COGs). We’ll touch on how this enables accessing and processing large datasets from the cloud for big data workflows. • Additionally we’ll cover how to effectively manipulate raster data: managing missing data points, cropping to specific regions of interest, and computing zonal statistics with vector areas of interest. • Finally, you'll discover how to use xarray and dask to run computations lazily or in parallel on raster datasets. Join us to unlock the power of Python and harness the full potential of geospatial data for your research and projects! • Instructors: • Ryan Avery, Machine Learning Engineer, Development Seed • Ryan is a Machine Learning Engineer at Development Seed. He develops machine learning models to detect land-use and land cover change in medium and high resolution satellite imagery. He is passionate about helping organizations make sound decisions that improve environmental outcomes and livelihoods. • Previously, Ryan was a graduate student in the Water, Vegetation, and Society Lab (WAVES). While there, he created CropMask_RCNN, a project to train state of the art models to predict crop circle boundaries in drylands. Ryan previously worked with the Mapping Africa project, where he worked on mapping smallholder farms in Ghana using PlanetScope imagery to improve agricultural land use planning and food security in the region. • When he’s not coding or teaching coding workshops, he enjoys climbing boulders in the Bay Area, learning strategy games, and practicing jiu-jitsu. Ryan received a Masters in Geography from UC Santa Barbara. • Chuck Daniels, Cloud Engineer, Development Seed • Chuck is a data engineer at Development Seed. He builds flexible data-driven systems and is an advocate of using open data to solve environmental and social issues. He works with our team that builds infrastructure for data providers like NASA to innovate new ways to distribute data on the cloud. He builds core infrastructure for Cumulus, which helps to better leverage cloud computing for data processing, storage, and retrieval of NASA’s Earth observation data. • Chuck is an experienced engineer with a background in cloud operations and software architecture. He has worked across several industries, including e-commerce and wellness, and has served in roles ranging from e-commerce architect to director of IT. • Chuck holds a B.S. with a dual-major in Computer Science and Mathematics, and a minor in Physics. He received a Master’s Degree in Computer Science with a concentration in massively parallel algorithms from the University of Maryland, College Park. • Link: • https://carpentries-incubator.github....

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