GIS and Remote Sensing Application for Vegetation Mapping

Mapping vegetation using remotely sensed images involves considering various factors, procedures, and strategies. The accessibility of remote sensing images has greatly increased due to advancements in remote sensing technology. Different types of images, characterized by their spectral, spatial, radiometric, and temporal properties, are suitable for different vegetation mapping purposes. To identify and map vegetation cover from remotely sensed images, it is often necessary to first create a vegetation classification system, either at the community or at the species level. Following this, the goal is to establish connections between the identified vegetation categories (communities or species) within this classification system and the distinguishable spectral characteristics present in remote sensing data. This spectral classification is eventually transformed into the types of plants during the image interpretation process, also known as image processing. This book chapter provides an overview of the process of classifying and mapping plant cover using remote sensing data. Additionally, it includes a case study at the end of the chapter, which can be highly valuable for researchers working in the same field.