Built for
Web
Technologies
Ai
Industry
City Planning
Country
India
Satellite/Aerial Image Segmentation
Project Highlights
To find the different segments in satellite image (i.e.buildings, roads, trees, crops and water) for smart city planning
Our Solution
We have developed a Deep Neural Network by using the following data
- The dataset consists of 8-band commercial grade satellite imagery taken from Space Net dataset.
- Train collection contains few tiff files for each of the 24 locations.
- Every location has an 8-channel image containing spectral information of several wavelength channels (red, red edge, coastal, blue, green, yellow, near-IR1 and near-IR2). These files are located in data/mband/ directory.
- Also available are correctly segmented images of each training location, called mask. These files contain information about 5 different classes: buildings, roads, trees, crops and water (note that the original Kaggle contest had 10 classes).
- Resolution for satellite images is 16-bit. However, mask-files are 8-bit.