2020 SCGIS 23rd Annual Conference

Jul 8, 2020 to Jul 10, 2020, Asilomar Conference Center, Monterey CA

Pre-Conference workshops: Tuesday July 7, 2020

Workshops

Laptops with ArcGIS software will be provided for all pre-conference workshops unless otherwise noted. 

Web GIS for Conservation - Mobile Solutions for Field Operations

July 7, 2020 9:00am

Venue: Asilomar Conference Center, Monterey CA

Lead(s): Esri Representative - To be confirmed

Fees: Student $90   Member $105  Non-Member $140

Overview of new holistic desk-field-mobile systems for field conservation supporting:

  • Smarter allocation of field crew time
  • Realtime field data reporting
  • Enhanced spatial information resources for field crews
  • Faster, simpler field data capture
  • Options for citizen science & volunteer-based field efforts

For more reading, see

https://www.esri.com/en-us/solutions/industries/sustainability/conservation/protected-area-management

https://www.esri.com/en-us/arcgis/products/field-operations/overview

https://community.esri.com/groups/mobile-gis

Spatial Analysis Workflows in ArcGIS Pro

July 7, 2020 9:00am

Venue: Asilomar Conference Center, Monterey CA

Lead(s): Miriam Schmidts (Esri)

Fees: Student $90   Member $105  Non-Member $140

Now that you’ve got a start with ArcGIS Pro, you may be wondering what kinds of analysis you can do with it? Can you run the analyses in ArcGIS Pro that you’re used to running in ArcMap? What other analyses can be done in ArcGIS Pro that you might not even be aware of? Come to this workshop to explore common ArcGIS Pro analysis workflows for Raster Suitability analysis that you might have done in ArcMap, and demystify some of the Spatial Statistics tools such as Hot Spot, and Space-time pattern analysis. If time permits, we will also dive deeper into Spatial Statistics in the afternoon, and take a look at Regression Analysis and Geographically weighted regression tools in ArcGIS Pro.

Spatial Data Analysis with R

July 7, 2020 9:00am

Venue: Asilomar Conference Center, Monterey CA

Lead(s): Andy Lyons (Visit Website)

Fees: Student $90   Member $105  Non-Member $140

R has become increasingly popular in ecology and conservation due to its strong base of statistical and data manipulation functions, open source development environment, active user community, and large number of packages tailored for conservation and spatial analysis. This workshop will cover the basics of working with spatial data in R including importing vector and raster data into R, common data manipulations such as projections and format conversions, basic visualization, querying spatial objects with attribute values and spatial relationships, geoprocessing, automating workflows with R code, working with online data and services, preparing data for analyses, select spatial statistics, and using the R-ArcGIS Bridge.

Some prior experience with GIS is expected. People who have not used R before are welcome to take the workshop, but are expected to complete an introductory R workshop before the conference, such as the Introduction to R for Data Science course from EdEx, Introduction to R by Claudia Engel, Intro to R from DataCamp ($), or a similar course.

Introduction to Remote Sensing using Open Source Tools

July 7, 2020 9:00am

Venue: Asilomar Conference Center, Monterey CA

Lead(s): Cindy Schmidt (NASA) and Nancy Thomas (UC Berkeley) (Visit Website)

Fees: Student $90   Member $105  Non-Member $140

*This workshop requires you to bring your own laptop to participate.

This workshop introduces the basic principles of digital satellite and aerial imagery and is appropriate for attendees who have some understanding of geospatial data but have little or no experience in remote sensing. We will introduce the basic principles of understanding remotely sensed data, including key satellites, sensors, and resources commonly used in conservation applications. Participants will learn how to find and download satellite and aerial imagery, how to display and enhance digital imagery, and basic techniques for image interpretation and analysis. After participants have developed an understanding of the fundamentals of remote sensing, we will introduce more advanced analysis for land cover change assessment and image classification. Participants will explore the process of analyzing imagery from multiple dates in order to map and quantify change over time. All lessons will be taught using entirely free and open source platforms (QGIS and R) to help make remote sensing analysis accessible to everybody.