Extracting features from images

The ability to classify an image leads us to another remote sensing capability. Now that you’ve worked with shapefiles over the last few chapters, have you ever wondered where they come from? Vector GIS data such as shapefiles are typically extracted from remotely sensed images such as the examples we’ve seen so far.

Extraction normally involves an analyst clicking around each object in an image and drawing the feature to save it as data. But with good remotely-sensed data and proper pre-processing, it is possible to automatically extract features from an image.

For this example, we’ll take a subset of our Landsat 8 thermal image to isolate a group of barrier islands in the Gulf of Mexico. The islands appear white as the sand is hot and the cooler water appears black (you can download this image from https://github.com/PacktPublishing/Learning-Geospatial-Analysis-with-Python-Fourth-Edition/raw/main/B19730_07_Asset_Files/islands...