#maptimeDavis R – Species Distribution Modeling: Bigfoot

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When? Tuesday, May 29, 1:00-3:00 in the DSI Classroom – room 360 Shields Library

Come learn to predict species distributions based on observation data, using R. Following a tutorial from Rspatial.org, Elise Hellwig will coach us through modeling the distribution of Sasquatch using the R programming language.

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#maptimeDavis Planet, a remote sensing data source

 

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Flooding in the Yolo Bypass in 2017 captured by Planet doves (© 2017 Planet)

When? Tuesday, May 22, 1:00-3:00 in the DSI Classroom – room 360 Shields Library

Orestis Herodotou, Software Engineer at Planet, a satellite imaging company in the Bay Area, will be coming to show everyone how to work with Planet data (satellite imagery with an almost daily return interval).  Don’t miss this workshop because it won’t be offered again soon.

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#maptimeDavis Collecting Location Data with Phones and Tablets

When? Tuesday, May 15, 1:00-3:00 in the DSI Classroom – room 360 Shields Library

Anywhere you go, you can be a sensor and collect all sorts of useful geographic data. We’ll cover a variety of options, how to use them and how to extract data, including:

  • GPS Tracking
  • Field maps
  • GeoTagging Photos
  • Field Forms with location
  • Geographic Annotations

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When data disagree: Incorporating information from multiple sources into a comprehensive spatial model

Quinn_unSeminar_2018Presented by Quinn Hart (Digital Applications Manager, UC Davis Library)

Tuesday, MAY 8th 2018,
12-1pm @ the DSI ,
Shields Library Room 360

 

unSeminar Abstract:

Satellite imagery and GIS modelling allow us the power to address complex environmental questions over large regions.  But, what how do we address issues when these data don’t agree with more local sensors?  Can we combine data from multiple sources, with varying resolutions and biases, into a single, comprehensive spatial model? We will discuss a modelling effort being conducted in collaboration with California Irrigation Information Management Information System (CIMIS) program to create new Evapotranspiration maps of California water use zones based on data from the Department of Water Resources (DWR) weather stations and the GOES weather satellite, collected over 13 years. The spatial modelling efforts have led to inconsistencies with some DWR weather stations being assigned to inappropriate zones.  How can we best utilize all of the available data and correct for these mismatches? How will we know if the implemented changes are good ones?

This talk may be of interest to those thinking about data integration, geospatial and modelling errors, evapotranspiration research, and working with DWR and other weather data.

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#maptimeDavis Humanitarian Mapathon

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Spring quarter’s #maptimeDavis OpenStreetMap Humanitarian Mapathon will support disaster planning and relief by identifying routes and communities in satellite imagery.   Join the geospatial community on May 8, 2018, from 1:00-3:00 in the DSI Classroom (360 Shields Library) for an OSM editing session that includes a tutorial for those who are new or need a refresher.  No experience is necessary!

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#maptimeDavis Learn to High Performance Compute: Geo Style

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Have you been doing geospatial processes that takes hours, days, or weeks to run? Been wondering if there’s an easy way to make it go faster?

Come learn some ways to take your toolbox to the next level with High Performance Computing (HPC). We’ll discuss and walk-through some examples of taking a iterative processes and turning them into parallel processes that can leverage more power from a single computers or multiple computers (clusters).

When? Tuesday, May 1, 1:00-3:00 in the DSI Classroom – room 360 Shields Library

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#maptimeDavis Mapping Surface Water Change with Google Earth Engine

greatsaltlakeIn this special 3 hour #maptimeDavis session, Ani Ghosh will teach attendees how to use Google Earth Engine for spatial analysis questions related to mapping surface water. Google Earth Engine code editor uses Earth Engine JavaScript API to access various datasets, perform spatial analysis and data visualization in your browser. Prior experience with any programming language (javascript, R, Python… even writing functions for Excel) will be helpful but is not necessary.  This workshop is scheduled to last three hours to allow for plenty of time to learn and try Earth Engine, but participants do not need to stay for the entire session.

When? Tuesday, April 24, 1:00-4:00

Where?  The Data Science Initiative Classroom – Shields Library room 360

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