
# Learn How This Was Made

Ensuring that medical facilities are easily accessible to local residents is crucial for community well-being. With Atlas, you can use travel time catchment areas to pinpoint underserved communities and strategically plan the location of new healthcare services.

Follow these steps to enhance accessibility to healthcare:

## Step 1: Data Setup

Begin by importing data on existing healthcare facilities into the platform. Find your area of interest that you want to assess in detail.

![Healthcare Facilities](/static/guides/analysing-access-to-healthcare/healthcare-facilities.jpg)

## Step 2: Travel Time Analysis

Utilize Atlas’ **Travel Time analysis** to create catchment areas that simulates how far a resident can get in a specified time. A common guideline for travel time to a healthcare service for residents is to aim for a travel time of 30 minutes or less.

![Travel Time Analysis](/static/guides/analysing-access-to-healthcare/travel-time-analysis.jpg)

## Step 3: Calculate Population Served

Quantifying the population residing in the catchment areas allows for a nuanced understanding of healthcare needs and aids in strategic resource allocation.

1. Overlay Demographic Data

   Import demographic data, including population distribution

2. Use **Zonal Statistics** to calculate the population served within each catchment area

![Zonal Statistics](/static/guides/analysing-access-to-healthcare/zonal-statistics-healthcare.jpg)

## Step 4: Identify Underserved Communities

To ensure effective healthcare access, it's vital to identify areas where communities might be underserved or face challenges in reaching medical facilities.

1. Pinpoint regions with limited coverage. These areas signify blackspots where residents may face challenges in accessing healthcare services
2. Overlay population density onto these regions to gauge the impact on residents

![Zonal Statistics Underserved](/static/guides/analysing-access-to-healthcare/zonal-statistics-underserved.jpg)

![Access to Healthcare](/static/guides/analysing-access-to-healthcare/results-healthcare.jpg)

## Conclusion

By employing Travel Time Analysis and geospatial analysis on Atlas, you can proactively address healthcare accessibility challenges. This guide empowers you to identify underserved communities, strategically plan new healthcare service locations, and contribute to improved healthcare access for the larger population.


Analysing Access to Healthcare Services


# Learn How This Was Made

This map showcases how you can use the Atlas Application to download DEM files for your project and evaluate the slope of a location.

## Step 1: Draw or upload your area of interest

In this guide, I will analyze the slope for a site near Nairobi, Kenya.

I chose to create my area of interest (AOI) by drawing a circle using the tools in the top left corner. Feel free to use any polygon at any place in the world.

![area of interest](/static/guides/slope/area_of_interest.jpg)

Note: You may also upload any types of geodata to the application (we support most vector formats).

## Step 2: Download the DEM file for the area of interest

First, I need access to a Digital Elevation Model (DEM), which can be used to calculate elements such as slope, contours, and more. In Atlas, we have an integration for extracting DEM files from [Joerd](https://github.com/tilezen/joerd/blob/master/docs/attribution.md).

You can import DEM files directly using this integration. I select the integration by either searching for "Terrain tiles" in the search bar or by clicking the shortcut for the integration as shown in the picture.

![shortcut for integration](/static/guides/slope/shortcut_integration.jpg)

In the integration, all I have to do is select the "Area of interest" and click import.

Now I have a DEM file for the area of interest, in this case we have a 9m horizontal resolution (The resolution is given in the layer name). The best resolution the integration can provide is 4 meters. The resolution is scaled depending on the size of the area of interest.

![DEM imported](/static/guides/slope/dem_imported.jpg)

## Step 3: Calculate the slope in percentage or degrees

Now that we have a DEM file, we can easily conduct analyses such as slope analysis, aspect analysis, and more. To achieve this, you need to go to the raster operations.

![raster operations](/static/guides/slope/raster_operations.jpg)

Here we see a range of "Terrain Analysis" options, including Aspect Analysis, Contour, Hillshade, and Slope analysis. For this guide, I will use the slope analysis.

![terrain analysis](/static/guides/slope/terrain_analysis.jpg)

In the slope analysis, you need to select the DEM file we created previously and choose whether you want the result in percentage or degrees.

![slope analysis](/static/guides/slope/slope_analysis.jpg)

After that, simply click "Run" and see the result being created.

![slope result](/static/guides/slope/slope_result.jpg)

I want to style the result to make the colors more understandable, so I click the "Styling" option for the resulting layer (named "slope").

![styling slope](/static/guides/slope/styling_slope.jpg)

## Step 4: Extract the contour lines

To extract contour lines, go back to the raster operations and select the "Contour" option. This tool allows you to generate contour lines from your DEM file, which can help you understand the terrain's elevation changes. After selecting the DEM file and setting the contour interval, click "Run" to create the contour lines.

![extract contour lines](/static/guides/slope/extract_contour.jpg)

You can further style the contour lines for better visualization by using the "Styling" option.

![styled contour lines](/static/guides/slope/styled_contour.jpg)

## Step 5: (Optional) Get an overview of flat areas using the Advanced slope analysis

For a more detailed analysis, you can use the Advanced slope analysis to identify flat areas. This can be particularly useful for construction planning or agricultural purposes. In the raster operations, select "Advanced slope analysis" and adjust the parameters to highlight areas with minimal slope. Run the analysis and style the results as needed.

![advanced slope analysis](/static/guides/slope/advanced_slope.jpg)

## Conclusion

Using the Atlas Application, you can efficiently download DEM files, evaluate the slope, and extract contour lines to better understand the elevation of your area of interest. This guide walked you through the steps of drawing or uploading your area of interest, downloading a DEM file, calculating the slope, and extracting contour lines. Optional advanced analyses, like identifying flat areas, can provide additional insights for specific applications. Happy mapping!


Evaluate the Slope of a Location


# Creating an Accessibility Map: Step by Step Guide

In this guide, we will outline the process to build an accessibility map for Berlin's subway system using the Open Street Map (OSM) integration and the Travel Time Analysis. Creating the map should take less than 5 minutes.

## Step 1: Extracting the Data from Open Street Map

To start, we will be extracting the necessary data using the Open Street Map integration.

1. First, we need to move the map to the area you are interested in, for this map, I wanted to evaluate the subway network of Berlin.
2. Secondly, we need to select the OSM integration. Is is accessible in the right sidepanel.
   ![osm integrations](/static/guides/identify-areas-with-easy-subway-access/osm_int.jpg)

3. After clicking the OSM (Open Street Map) integration, we have to find the extraction we want from the list of "tags to query", alternatively you may enter a spesific custom tag.
   [All available OSM tags](https://taginfo.openstreetmap.org/tags)

For this case, I want to use subway=station, and I select that from the list.
![osm query](/static/guides/identify-areas-with-easy-subway-access/subway_stations.jpg)

## Step 2: Performing the Travel Time Analysis

1. To activate the analysis, I enter the "Analysis" tab. alternatively one may search for the spesific analysis in the search bar in the right side panel. The first thing I need to do is to select the dataset we have extracted from OSM.
   ![Test](/static/guides/identify-areas-with-easy-subway-access/travel2_1.jpg)

To achieve this, I click on the "Switch to dataset", and select the OSM extraction from the dropdown menu.
![Switch to datasets](/static/guides/identify-areas-with-easy-subway-access/travel2.jpg)

2. For this example, we use the 5 and 10 minutes walking times to view the network. Alternatively, you could evaluate the travel time with bike or with a car if that better suits your need.
   After clicking run, the results looks like this:
   ![Initial result](/static/guides/identify-areas-with-easy-subway-access/travel3.jpg)

## Step 3: Finalizing the Visual Presentation

At the current stage, the analysis looks OK. But in order to truly capture the visual aspect of the different time travels I want to style the datalayer. To do this, I select the "Styling" from the dropdown menu in the result layer.
![Styling prepare](/static/guides/identify-areas-with-easy-subway-access/res1.jpg)

I want to select the "Style based on attribute" and further select the attribute that represent the time aspect.
![Styling](/static/guides/identify-areas-with-easy-subway-access/res2.jpg)

Here you can select whichever styling suits you the best, but I want to have something indicating green for short time - and red for longer time needed. As such, I adjust the number of steps for the Quantize styling, and select a color map that goes from green to red.

Lastly, I want to alter the basemap to properly showcase the result. To do this, I click on the "Map Settings" in the bottom right part of the map.
![Styling](/static/guides/identify-areas-with-easy-subway-access/mapsettings.jpg)

## Results

The resulting map looks like this.

![Styling](/static/guides/identify-areas-with-easy-subway-access/result4.jpg)

We hope you found this tutorial helpful, and feel free to duplicate the map or create a subway map of your own city. Your feedback and questions are greatly appreciated!


Identify Areas with Easy Subway Access


# Learn How This Was Made

Are you looking for the perfect location for your real estate investments? With Atlas, you can streamline the process by leveraging geospatial analyses.

In this short guide, we’ll walk you through the steps of using the platform to identify high-value locations based on specific criteria, such as population density and proximity to essential amenities like schools, kindergartens, cafes, bus stops, and more.

## Step 1: Analyzing Existing Population Density

Understanding the population distribution in your target area is crucial for making informed real estate decisions. The analysis of population density provides valuable insights into the concentration and distribution of people, helping you identify areas with potential demand and growth.

1. **Upload Population Density Raster**

   Begin by uploading the Population Density raster in GeoTIFF format ([Source](https://data.humdata.org/dataset/united-kingdom-high-resolution-population-density-maps-demographic-estimates))

   This data serves as a foundation for your analysis, allowing you to visualize the density of the existing population across the selected area.

![Population Density Raster](/static/guides/site-planning-in-real-estate/population-density-raster.jpg)

2. **Generate Hexagonal Grid**

   Use the **Create Grid** analysis tool to create a grid of 250x250m hexagons within your area of interest. Hexagons offer a spatially uniform representation, providing a balanced view of population density distribution.

![Zonal Statistics](/static/guides/site-planning-in-real-estate/zonal-statistics.jpg)

3. **Zonal Statistics for Hexagons**

   Execute the **Zonal Statistics** tool to calculate the mean population density within each hexagon. This information creates a background layer that not only reflects overall density patterns but also aids in identifying areas with potential growth opportunities.

![Hexagons](/static/guides/site-planning-in-real-estate/hexagons-zonal.jpg)

## Step 2: Adding Relevant Datasets

To make well-informed decisions in real estate site selection, it's essential to consider not only population density but also the surrounding environment. Atlas allows you to enhance your analysis by incorporating various datasets, providing a comprehensive understanding of the area.

**Add Various Datasets:**

- **Railway:** Understand the accessibility and connectivity of the area, which can influence property value.
- **Café:** Identify areas with commercial and recreational amenities, contributing to the overall appeal of a location.
- **School and Kindergarten:** Evaluate proximity to educational institutions, appealing to families and impacting property values.
- **Bus and Roads:** Assess the transportation infrastructure, a critical factor for convenience and accessibility.

![Adding Data](/static/guides/site-planning-in-real-estate/adding-data.jpg)

## Step 3: Constraint Analysis for Optimal Site Selection

Performing a **Constraint Analysis** on Atlas is a pivotal step in narrowing down potential real estate sites based on specific criteria. This process helps you filter through the available options, ensuring that the chosen location aligns with your project's objectives.

![Constraint Analysis](/static/guides/site-planning-in-real-estate/constraint-analysis.jpg)

**Define Parameters for Constraints:**

- **Bus within 200m**
  - Include buildings within a 200-meter radius of a bus stop to enhance accessibility and convenience.
- **Railway outside of 200m**
  - Exclude buildings within a 200-meter radius of a railway to minimize noise and safety concerns.
- **Kindergarten within 500m**
  - Include buildings with a nearby kindergarten to attract families and promote a family-friendly environment.
- **School within 500m**
  - Include buildings within a 500-meter radius of a school, catering to families with school-going children.
- **Cafés within 200m**
  - Include buildings within a 200-meter radius of cafes to offer recreational and social amenities.

By applying these constraints you find locations that meet specific criteria.

## Results

After executing the Constraint Analysis on Atlas, you will be presented with a refined list of potential real estate sites that meet your specified criteria. This final step involves reviewing the results and making informed decisions for your project.

![Results](/static/guides/site-planning-in-real-estate/results.jpg)


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