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May 2025Archived

 

Field picture submitted by Elizabeth Fichtner

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NPI Assessment Questionnaires: Page

Retail Setting Training

On May 5, 2022, we hosted a refresher training for all LHD staff conducting SLAQs in a retail setting in FFY 2023. This training provides an overview of the Retail SLAQ and where to find all the resources needed to successfully complete this SLAQ.
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Data Wrangling with R
Informatics and GIS Program: Page

Drone Data 101, February 14, 2024

IGIS is pleased to present this workshop as part of UC Love Data Week University of California Division of Agriculture and Natural Resources A Zoom Workshop Wednesday, February 14, 2024, from 1:00pm to 2:00pm PST Click Here to Register Drones are well-known for their breathtaking photos and video, b...
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Informatics and GIS Program: Page

Building a Degree Day Online Decision Support Tool in R

A two-part Zoom workshop Part 1: Friday May 3, 10:30a - 12:00p PDT Part 2: Friday May 10, 10:30a - 12:00p PDT Click Here to Register Overview: Degree day models are widely used in agriculture to predict the development of plants and insects.
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Informatics and GIS Program: Page

Create an Attendee Map for an Event

Andy Lyons October 2022 IGIS Tech Notes describe workflows and techniques for using geospatial science and technologies in research and extension. They are works in progress, and we welcome feedback and comments below. Attendee maps are a nice way to get participants excited about an event.
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Informatics and GIS Program: Page

Finding and Using Parcel Data in California

Ben Satzman December 2022 IGIS Tech Notes describe workflows and techniques for using geospatial science and technologies in research and extension. They are works in progress, and we welcome feedback and comments below.
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Informatics and GIS Program: Page

Weather and Climate Tools & Data

Weather and climate data are needed in a variety of applications, from managing crops, to adaptation planning, to understanding long-term trends in species and ecosystems. However working with these spatial data can be challenging, due to their large size, multi-dimensionality, and unfamiliar units.
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