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How can you use remote sensing data to analyze urban land use?

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Urban land use is a key indicator of the environmental, social, and economic aspects of a city. However, measuring and monitoring it can be challenging, especially for large and dynamic areas. Remote sensing data, such as satellite images, aerial photos, and radar, can provide valuable information on the spatial and temporal patterns of urban land use. In this article, you will learn how to use remote sensing data to analyze urban land use and its implications for environmental consulting.

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Sandip Sen

Geospatial Database Engineer at TAQA Water Solution, Abu Dhabi GIS Analyst | CAD to SDE | Network utility | Network…

1 What is remote sensing data?

Remote sensing data is any data that is collected from a distance, without direct contact with the object or area of interest. Remote sensing data can be classified into two types: passive and active. Passive remote sensing data relies on the natural radiation or reflection of the object or area, such as sunlight or heat. Active remote sensing data involves sending a signal to the object or area and receiving the response, such as radar or lidar. Remote sensing data can have different spatial, spectral, temporal, and radiometric resolutions, depending on the sensor and platform used.

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Sandip Sen

Geospatial Database Engineer at TAQA Water Solution, Abu Dhabi GIS Analyst | CAD to SDE | Network utility | Network analysis | Python | Geopandas | postgreSql | ArcGIS pro | ArcGIS Online | ArcSde | ArcFM | FME
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Remote sensing data is like having a superpower to observe and gather information about the Earth without actually being there. It's like having special eyes and sensors on satellites or planes that can see and measure things from afar. For instance, think about Google Earth – when you zoom in and see detailed maps and satellite images, that's remote sensing data in action. It helps us study and understand the Earth's surface, track changes over time, and monitor things like weather patterns, vegetation health, or urban development, all from a distance. In my opinion, the explanation of remote sensing data resonates well with the idea of having a unique ability to perceive and understand our planet from a distance.

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2 How to obtain remote sensing data?

There are many sources of remote sensing data available for urban land use analysis. Some of them are free and open, such as the Landsat, Sentinel, or MODIS satellites, while others are commercial and require a license, such as the WorldView or QuickBird satellites. You can also acquire your own remote sensing data using drones, planes, or balloons, but you need to consider the legal and ethical issues involved. Depending on your research question and budget, you can choose the most suitable remote sensing data for your urban land use analysis.

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Sandip Sen

Geospatial Database Engineer at TAQA Water Solution, Abu Dhabi GIS Analyst | CAD to SDE | Network utility | Network analysis | Python | Geopandas | postgreSql | ArcGIS pro | ArcGIS Online | ArcSde | ArcFM | FME
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Obtaining remote sensing data involves diverse sources: Satellite Data Providers: NASA and ESA offer datasets through missions like Landsat and Sentinel. Commercial entities like Maxar and Planet provide high-resolution imagery. Government Agencies: USGS provides Landsat data, and national space agencies contribute datasets. Many offer free or low-cost access. Online Platforms: Google Earth Engine and Earthdata offer tools and datasets, simplifying data discovery and analysis. Commercial Providers: Maxar and Planet supply high-quality, specialized data, often requiring payment. Remote Sensing Software: QGIS, ArcGIS, and ENVI facilitate data processing and analysis.

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3 How to process remote sensing data?

Before analyzing remote sensing data, you need to process it to make it ready for interpretation and visualization. Georeferencing involves assigning geographic coordinates to each pixel of the data, so that it can be aligned with other spatial data and maps. Atmospheric correction is necessary to remove the effects of the atmosphere, such as haze, clouds, or dust, on the remote sensing data. Radiometric correction adjusts the brightness and contrast of the data, so that it can be comparable across different sensors and dates. Image enhancement applies filters, transformations, or techniques to improve the visual quality and clarity of the data. Finally, image classification assigns each pixel of the data to a land use category based on its spectral or spatial characteristics.

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Sandip Sen

Geospatial Database Engineer at TAQA Water Solution, Abu Dhabi GIS Analyst | CAD to SDE | Network utility | Network analysis | Python | Geopandas | postgreSql | ArcGIS pro | ArcGIS Online | ArcSde | ArcFM | FME
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Processing remote sensing data involves several key steps: 1. Data Access: 2. Data Preprocessing: 3. Image Registration: 4. Image Enhancement: 5. Image Classification: 6. Change Detection: 7. Geospatial Analysis: 8. Data Integration: 9. Validation: 10. Presentation: Software tools like QGIS, ArcGIS, and ENVI are essential for these tasks. Regularly update skills to leverage new techniques and technologies, contributing to more accurate and insightful remote sensing analyses.

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4 How to analyze remote sensing data?

Once you have processed your remote sensing data, you can analyze it to answer your urban land use questions. Change detection is a common method which involves comparing two or more remote sensing data sets from different dates or sensors to identify and quantify the changes in urban land use over time or space. Pattern analysis measures and describes the spatial distribution and arrangement of urban land use, such as density, diversity, fragmentation, or connectivity using indices, metrics, or models. Impact assessment assesses the environmental, social, or economic impacts of urban land use, such as air quality, biodiversity, carbon emissions, or livability using indicators, scenarios, or simulations.

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5 How to visualize remote sensing data?

Visualizing remote sensing data is a key component to effectively communicate and present your urban land use analysis results. There are a variety of tools and platforms that can help you create engaging visualizations, such as maps created with ArcGIS, QGIS or Google Earth; charts created with Excel, R or Tableau; and infographics created with Canva, Piktochart or Adobe Illustrator. These visualizations can show the spatial distribution and variation of urban land use, as well as the statistical and numerical aspects, such as trends, proportions, or correlations. Infographics also offer an opportunity to tell a story or convey a message about urban land use.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you use remote sensing data to analyze urban land use?

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1 What is remote sensing data?

2 How to obtain remote sensing data?

3 How to process remote sensing data?

4 How to analyze remote sensing data?

5 How to visualize remote sensing data?

6 Here’s what else to consider

Environmental Consulting

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How can you use remote sensing data to analyze urban land use?

1

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3

4

5

6

1 What is remote sensing data?

2 How to obtain remote sensing data?

3 How to process remote sensing data?

4 How to analyze remote sensing data?

5 How to visualize remote sensing data?

6 Here’s what else to consider

Environmental Consulting

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