About:RSpatial.org, led by Dr. Hijmans, we’ll cover how to process and manipulate spatial data using R. Here is your chance to learn from one of the best! Please join us for this introduction into R Spatial.
#maptime is time for making maps! Join the UC Davis geospatial community for a mapping skills workshop series. Workshops take place Mondays 1:10-3:00pm in the DSI Classroom, 360 Shields Library. Register for workshops on the UC Davis Library’s Workshops Page.
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.
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.
Presented byQuinn Hart (Digital Applications Manager, UC Davis Library)
Tuesday, MAY 8th 2018, 12-1pm @ the DSI ,
Shields Library Room 360
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.