Product

Data downloading

The UrbanWatch database is provided for personal use at no cost for academic, research, and/or teaching purposes.  A database release agreement must be agreed to before these licensed data can be released. The Laboratory for Remote Sensing and Environmental Change (LRSEC) at the University of North Carolina at Charlotte must be acknowledged on any derivative product, whether printed or electronic, including, for example, a printed map, a raster, or vector graphic, a web-based application, etc.

UrbanWatch is built on strong collaborations. Partnerships involve both data hosting as well as technology research and development.  If you are interested in collaborating with LRSEC on data hosting, R&D, or other activities, please contact us.

Below a Google Map will be loaded for you to choose the city of interest for data downloading. To facilitate data downloading, we have divided each city into multiple grids (approximately 6000 × 7000 meters each) and allow the users to select the interested grids from a preview image of a city using IDs. All maps are in GeoTIFF format and have embedded georeferencing information. The value of each pixel in the maps corresponds to a specific LCLU class, i.e., red-building, gray-road, purple-parking lot, dark green-tree canopy, light green-grass/shrub, blue-water, yellow-agriculture, dark red-barren, and white-others. 

How to Display the Products in Color Maps?
The products are three-band images. To visualize them in color maps, load the products in ArcGIS Pro and set the Stretch Type to None in the Symbology settings. This will ensure that the display matches the exact color scheme shown on our website.

How to Extract Single-Band Land Cover and Land Use Maps from the Three-Band Products?
To generate single-band land cover and land use maps from our three-band products, use the provided Python code within the ArcGIS Pro Python environment. Depending on your version of ArcGIS Pro, you can do this by navigating to: Start  →ArcGIS Pro Folder → Jupyter Notebook → New → Python 3. Then, copy and paste the provided code into the notebook, making sure to update the input and output directories to import and save the data accordingly.

Please cite the following paper if using the dataset:
Zhang, Y., Chen, G., Myint, S.W., Zhou, Y., Hay, G.J., Vukomanovic, J., & Meentemeyer, R.K. (2022). UrbanWatch: A 1-meter resolution land cover and land use database for 22 major cities in the United States. Remote Sensing of Environment, 278: 113106.

Loading UrbanWatch products ............

A nine-class urban classification scheme with diverse geographic patches 

Class ID Category Color Classification Description
0 Building   A human-made structure with a roof and walls across various areas, such as office buildings, stores, houses, townhouses, and condos.
1 Road   A paved or leveled surface used for transportation, such as highways, sidewalks, and driveways.
2 Parking Lot   An area designated for parking vehicles, differing from roads by markings and vehicle presence.
3 Tree Canopy   Woody vegetation taller than 2m, found in parks, yards, and along streets.
4 Grass/Shrub   Small plants lower than 2m, including lawns, bushes, and grasslands.
5 Agriculture   Land used for crop cultivation, including wheat, corn, and soy.
6 Water   Water bodies like rivers, lakes, ponds, oceans, and streams.
7 Barren   Rock, sand, or soil with minimal vegetation, including deserts and quarries.
8 Others   Miscellaneous land cover not classified above, such as courts and transmission towers.