Philly ETE 2020 – Matthew Hanson – Open Standards and Open Software for Geospatial Imagery

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Abstract

As massive amounts of new geospatial data are collected, it is increasingly challenging to search and find data of interest. New upcoming NASA missions, such as NISAR and SWOT will be generating tens of terabytes a day, while commercial small satellites (i.e., Cubesats) are launching earth observation satellites at an exponential rate. However, every data provider uses different interfaces for users to access this data, resulting in users spending significant time figuring out how to find, access, use the data, often creating customized tools for each different dataset.

Geospatial standards (led by the Open Geospatial Consortium) have been around for decades, and have proven to be vital in making data available as standardized services, but have not covered standardization of metadata fields. A new set of OGC and community-based standards aim to simplify the ability to discover and use both open public datasets, as well as commercial datasets from the emerging group of Cubesat data providers. With the development of Open Standards, common Open-Source libraries and utilities can be built to leverage this new data, providing a consistent way to access and use geospatial imagery from multiple disparate sources.

About Matthew Hanson

Matthew Hanson started studying photographic science in the early 1990’s, when traditional photography was being replaced with digital imaging. This led to further studies into remote sensing and digital image processing where he worked developing algorithms in registration, object detection and identification for government applications.

In 2010 Matthew transitioned to working on earth science applications – climate change, biomass estimation, machine learning for agriculture, but most importantly he worked on making it easier for scientists to use remote sensing data so they could spend their time doing science, not software. For this, he started contributing to various Open Source projects for geospatial and remote sensing applications.

In the last few years at Development Seed and now at Element 84, he has worked on backend cloud processing for both small satellites as well as NASA Earth Science projects. Most recently he has been working on standards to improve interoperability of geospatial data for cloud native applications.