March 22-26, 2020 | Walter E. Washington Convention Center | Washington, DC

17
Feb

Geo Week Round-up: Digital Twins for flooding | High-density lidar | L3Harris AI contract

Welcome to the Geo Week News weekly update! The articles below have been hand picked from recent geospatial news. A new update is posted each Monday.

Missed last week? Browse all the weekly updates here.

City-scale digital twins for flood resilience

Climate change – due to its role in extreme weather events and rising seas – is exacerbating flood risks, especially in coastal and low-lying areas. At the same time, populations in flood zones and the coastal regions continue to increase – worsening an already deadly and costly situation. There are projections that by 2030, around half the people in the world will be living within 100 km of a coastline.

In response to these threats, cities are striving to improve their flood resilience with data-driven planning, development, and operations. Some cities are accomplishing this through the use of digital twins to improve the resilience of current infrastructure and to support ongoing development and future planning.

Read more: GIM 

Why invest in high density lidar?

Because lidar forms the topographic basis for the stormwater model updates and the existing 2007 lidar data was not meeting the FEMA/USGS specifications, a new lidar survey was necessary. Accordingly, SWFWMD partnered with the Public Works Department of Hillsborough County and the Stormwater Engineering Division of the City of Tampa to plan and fund a new lidar mission for the county and city

Read more: LIDAR Magazine

L3Harris Technologies Selected by US Air Force for Artificial Intelligence Contract

The Air Force Life Cycle Management Center has awarded L3Harris Technologies (NYSE:LHX) a multimillion-dollar contract to develop a software platform that will make it easier for analysts to use artificial intelligence (AI) to identify objects in large data sets.

Read more: Business Wire

30 Years of Human-Related Change

NUCI is product of Maxar’s Persistent Change Monitoring (PCM), an image-based change detection process that isolates changes that persist over time, and more specifically, urbanization and other human-related changes. The NUCI database provides a history of change areas, represented as polygons, on an annual basis from 1987 through 2016. With traditional image-to-image change detection methods, distinguishing among spurious, seasonal, and persisted changes can be difficult and time consuming. With NUCI, all of the work has been done for you. Over 13,000 multi-temporal Landsat images were analyzed, and the results filtered, enabling you to readily focus on thirty years of persistent land cover changes.

Read more: Esri

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