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Dear LOR user,

Thank you for being a big part of this community. To better support the initiatives around open educational resources in the state of Michigan, all resources on the Michigan Virtual Learning Object Repository (LOR) are being moved to #GoOpen Michigan (link is external) on September 30th, 2018. During the transition, our LOR will be moved to an archived state, not allowing new user registration or new content to be added. An email with more details was sent to registered users of the LOR in September. To make use of the great resources on the platform, we encourage you to create an account and add your own new resources to the #GoOpen Michigan platform (link is external).

Project

In this project, students perform a viewshed analysis to determine the visual impact of a wind farm with four large turbines in a study area in England. A viewshed is the area visible from a specific vantage point. Viewshed analysis shows areas where observers can see an object or objects, or conversely, areas that can be seen from those objects.

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In this project, students will map Medicare costs by local hospital service regions, explore the spatial patterns of costs to see where they're high and low, and perform a hot spot analysis to see where high and low costs are statistically significant. 

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In these lessons, students play the role of a GIS specialist for a North Dakota advocacy group. The group wants to alert state and federal officials to this negative effect of the oil boom in order to receive more resources for housing and shelters. Students first download tabular (table-based) data on homelessness. Then, they map the data in ArcMap by joining it to state geography.

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Student's objective in this project is to ensure the programs are offered where they're most needed. To do so, students create a map by adding and enriching a layer of ZIP Codes with demographic data from ArcGIS Online. They also apply smart mapping and style the layer to show median household income by ZIP Code area.

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In this project, students identify areas at highest risk of flooding and landslides during a major rain event. They first explore the region's dramatic geography and identify how the most flood-prone areas correspond with large population centers. Then, they determine where landslides are most likely to occur and summarize the population in these at-risk areas.

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In this project, students will learn how to find the area that drains to a storm drain and the route that pollutants will take if they are dumped or washed into the drain. They will find the upstream drainage area, called a watershed, for a storm drain near Blackman Elementary School in Tennessee. Then they find the downstream flow path to where it empties into the Gulf of Mexico.

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In this lesson, students take on the role of a county official tasked with spreading awareness of the disaster. Using imagery of the affected area, they create a web mapping application that allows users to easily compare the area before and after the disaster. Users should also to be able to measure the extent of the impact.

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As GIS technicians, students examine dams along the Mersey River Watershed to determine whether there are any locations suitable for the construction of a fishway. Once they identify the best potential location, they will calculate the dam's upstream watershed to help determine how much additional habitat could be made accessible by constructing the fishway.

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In this project, you'll assume the role of a geospatial scientist working with the Montana Forestry Department to analyze the damage in Glacier National Park. You'll first compare Landsat 8 imagery from before and after the fires. Then, you'll change the band combination of the post-fire imagery in order to emphasize burn scars and make a qualitative judgment.

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In this project, you’ll build a web mapping application that identifies which region of Samut Songkhram province should be the focus of conservation efforts. You’ll retrieve one image for each decade since the 1970s from the Living Atlas Landsat archive for the entire study area. Once you have the images, you will alter the available multispectral data to enhance vegetation, land, and water.

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