What's new in Learn ArcGIS November 2022

[SilpaGadi]

New Learn Lessons

A Learn Lesson is a step-by-step tutorial that uses a real-world scenario to introduce key ArcGIS tools and workflows. Here's a roundup of new lessons in the Learn ArcGIS Gallery that have appeared in the last month.

Connect a 3D digital model to additional table data(ArcGIS Pro)

 

In this lesson, as the real estate manager working on the De Zalmhaven complex project in Rotterdam, Netherlands, you need to keep the real estate agents and the owner of the project up to date on the status of the units available for sale or lease. You want to not only share with them the 3D model of the building complex but also enhance that model with additional information contained in a separate table, which documents each unit’s space usage and availability. After setting up an ArcGIS Pro scene, you’ll add to it the 3D model and connect the data table to the model. You’ll then publish the ArcGIS Pro scene as a web scene to Portal for ArcGIS. All your collaborators will be able to access the web scene in their web browser or through ArcGIS Pro. Unlike other lessons in the BIM and GIS series, this workflow is only available for ArcGIS Enterprise implementations.

Identify gaps in wheat production (ArcGIS Pro)

Food production relies on many factors such as land suitability, climatic variability, and crop planning. Agroclimatic information is key to national organizations to estimate potential yields and identify areas where food production can be increased. The Food and Agriculture Organization (FAO) has developed the Global Agro-Ecological Zones (GAEZ) dataset to provide key information on land utilization, agroclimatic resources, and agricultural production to analyze and identify opportunities to improve yields and food production. In this lesson, you'll take on the role of an analyst who'll use the GAEZ data to analyze wheat production trends in the Yaqui Valley, Mexico.

Improve data quality with attribute rules(ArcGIS Pro)

In this lesson, you will act as a GIS specialist working for the City of White Rock in British Columbia, Canada. You have been tasked with helping the city's mobile workers maintain street light poles. There are four types of tests performed in the field to ensure the quality of each pole. The mean value of these four tests represents the overall test result, which indicates if a street light pole has passed or failed inspection.

Your job is to manage the inspection data. To ensure its quality, you'll create three attribute rules. Attribute rules are user-defined rules that can constrain, calculate, or validate the attribute values of a dataset. To enforce data quality during data entry, you'll create a constraint rule. To automate the data editing process, you'll create an immediate calculation rule. To ensure each street light pole has passed the inspection test, you'll create a validation rule.

Reveal lake shrinkage due to severe drought (Imagery and remote sensing )

Severe droughts and higher temperatures due to climate change are of increasing concern around the world. As regional and global temperatures are significantly increasing, the water levels are dropping in many major water bodies that people, plants, and animals depend on. One way you can raise awareness of this important issue is by visualizing how much lakes are shrinking using satellite imagery and GIS.

Drought is not the only cause of lake shrinkage. Many lakes rise and fall due to regular seasonal variation. Some may be drained for maintenance or irrigation purposes or dammed for other human development purposes. However, the lakes that you will explore in this lesson have severe drought as a significant contributing factor for their falling water levels.

In this lesson, you will access imagery layers using the World Imagery Wayback app, configure a web map with bookmarks to several major lakes that are shrinking due to severe drought, and create a story with interactive swipe maps to compare the before and after imagery of the lakes.