Intro to GIS: Getting started with spatial research

IDRE Visualization Portal, Math Sciences Building 5628 520 Portola Plaza, Los Angeles, CA, United States

As members of an academic community with a myriad of research initiatives, the need to map information, to spatially analyze, to geoprocess, and to visualize space and time is becoming ubiquitous. But how do you get started? The answer to this question largely depends on what you want to map, and how you want to create your map. The what is...
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Free

Introduction to GIS and Spatial Research

IDRE Portal 5628 Math Sciences Building, 520 Portola Plaza, Los Angeles, CA, United States

As members of an academic community with a myriad of research initiatives, the need to map information, to spatially analyze, to geoprocess, and to visualize space and time is becoming ubiquitous. But how do you get started? The answer to this question largely depends on what you want to map, and how you want to create your map. The what is...
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Free

Intro to GIS: Getting Started with Spatial Research

Zoom

As members of an academic community with a myriad of research initiatives, the need to map information, to spatially analyze, to geoprocess, and to visualize space and time is becoming ubiquitous. But how do you get started? The answer to this question largely depends on what you want to map, and how you want to create your map. The what is...
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Free

Introduction to GIS/Spatial Research with Python

Zoom

Register in advance: Please REGISTER using the Zoom Meeting Link before joining!   There are no pre-requisites to take this workshops, but it is recommended that you take the following two workshops: Introduction to Jupyter Version control with git As members of an academic community with a myriad of research initiatives, the need to map...
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Introduction to Spatial Statistics with Python

Zoom

Registration link: https://ucla.zoom.us/meeting/register/tJwkdu6hqj4sG9ZioB0tM8VuXxA44AWGc6W- Visual interpretations are meaningful ways to determine spatial trends in our data. However, underlying factors—such as inconsistent geographies, scale, data gaps, overlapping data—have the potential to produce incorrect assumptions, as valuable information may be conveniently hidden from the visual output. One way to address this issue is to amend your visual output...
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