Google tools for GIS Applications

Google tools for GIS Applications, available at $64.99, has an average rating of 4.1, with 50 lectures, based on 38 reviews, and has 282 subscribers.

You will learn about Cloud SQL – Managed PostGIS in the cloud Big Query Cloud Storage Data Studio Colaboratory – Jupyter notebooks in the cloud Automation with cloud shell scripts Earth Engine Mapping APIs – geolocation, routing, elevation and more This course is ideal for individuals who are Geospatial professionals who want to learn more about leveraging Google Cloud Platform and mapping APIs for geospatial applications It is particularly useful for Geospatial professionals who want to learn more about leveraging Google Cloud Platform and mapping APIs for geospatial applications.

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Summary

Title: Google tools for GIS Applications

Price: $64.99

Average Rating: 4.1

Number of Lectures: 50

Number of Published Lectures: 47

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 47

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Cloud SQL – Managed PostGIS in the cloud

Big Query

Cloud Storage

Data Studio

Colaboratory – Jupyter notebooks in the cloud

Automation with cloud shell scripts

Earth Engine

Mapping APIs – geolocation, routing, elevation and more

Who Should Attend

Geospatial professionals who want to learn more about leveraging Google Cloud Platform and mapping APIs for geospatial applications

Target Audiences

Geospatial professionals who want to learn more about leveraging Google Cloud Platform and mapping APIs for geospatial applications

This course is an overview of Google Cloud Platform tools, analytical tools, and mapping API’s that may be of interest to geospatial professionals.  The course is broad rather than deep.  My goal is to show you how to get started with many different products with an emphasis on geospatial applications.  In many cases there are existing courses that cover the details but with little information on geospatial applications and this course is intended to fill in those gaps.

Google has an amazing set of tools available in the cloud and elsewhere.  We start with implementing an instance of PostGIS in the Google cloud. Then we import some of that geospatial data into BigQuery for super fast analytical queries.  The results of those queries can be visualized in a variety of ways in Data Studio and those visualizations are easily shared.  I also demonstrate how to store files in the cloud, get started with Google Earth Engine for remote sensing analysis, Colaboratory as a hosted Jupyter Notebook environment, and mapping APIs that allow display of web maps, geolocation, routing, and elevations for any point on earth.

NOTE: As of today April 9, 2022 this course has over 6 1/2 hours of content and covers Cloud SQL, Big Query, Data Studio, Cloud Storage, and Cloud Shell automation. I believe this in itself to be worth the price of the course so I am releasing it now but I will be adding sections on Colaboratory, Earth Engine, and the mapping API’s in May 2022.

This course is different from most of my courses because Google tools are not strictly open source.  There are costs associated with them. But rest assured, Google is very generous with its products.  Some are completely free to use, some have a free tier that you can use up to a certain amount for free, and even their premium products are very affordable for small businesses as you only pay for what you use.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: What is The Cloud?

Lecture 3: Overview of Google tools for geospatial applications

Lecture 4: Organization of the Google Cloud Platform

Lecture 5: Signing up for a Google user account (optional)

Lecture 6: Signing up with Google Cloud Platform

Lecture 7: Setting up a project in the Google Cloud Platform

Chapter 2: Gloud SQL – PostGIS in the cloud

Lecture 1: Database 101 (Mostly optional.)

Lecture 2: Starting an instance of PostgreSQL (and PostGIS) in the cloud

Lecture 3: Connecting with PgAdmin4 and loading data

Lecture 4: Connecting with QGIS and viewing geospatial data

Chapter 3: Big Query

Lecture 1: Introduction to Big Query

Lecture 2: Getting started and importing data

Lecture 3: Writing queries that join multiple tables

Lecture 4: Joining tables based on spatial criteria

Lecture 5: Performance considerations – overview

Lecture 6: Evaluating performance and optimizing queries

Lecture 7: Evaluating performance – part 2

Lecture 8: Data visualization in Big Query

Chapter 4: Automation with the Cloud Shell

Lecture 1: Using the Cloud Shell command line

Lecture 2: Automating tasks with the Cloud Shell Editor

Chapter 5: Data Studio – Visualizations and dashboards

Lecture 1: What is data studio?

Lecture 2: Creating our data source

Lecture 3: Making our first dashboard

Lecture 4: Adding interactive data controls

Lecture 5: Odds and ends

Lecture 6: Calculated fields and the CASE statement

Lecture 7: Reviewing the data flow of this project

Lecture 8: Adding a second (and third) data source to the report

Lecture 9: Adding a second page to the report

Lecture 10: Copying the page and modifying it for raptors

Lecture 11: Sharing the dashboard

Lecture 12: Advanced – Combining multiple tables into one

Lecture 13: Advanced – Blending data sources in Data Studio

Chapter 6: Cloud Storage

Lecture 1: Overview of cloud storage

Lecture 2: Making files publicly accesible

Lecture 3: Cloud storage from the command line

Lecture 4: Backing up BigQuery and CloudSQL to Cloud Storage

Lecture 5: Installing gcloud and controlling cloud resources from your local computer

Chapter 7: Colaboratory – Jupyter notebooks in the cloud

Lecture 1: Jupyter Notebooks 101 (optional)

Lecture 2: Google Colaboratory 101

Lecture 3: Tour of Google Colaboratory

Lecture 4: Accessing file-based data stored in bulic bucket in Google Cloud Storage

Lecture 5: Accessing data stored in a Google Cloud SQL database

Lecture 6: Accessing data stored in BigQuery

Chapter 8: Google APIs for GIS applications

Lecture 1: What is an API?

Lecture 2: Introduction to Postman

Instructors

Michael Miller
GIS Programming

Rating Distribution

1 stars: 1 votes

2 stars: 1 votes

3 stars: 5 votes

4 stars: 8 votes

5 stars: 23 votes

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