Identification of vegetation from satellite derived hyper spectral indices

Autor: Archana Nandibewoor, Prashanth Adiver, Ravindra S. Hegadi
Rok vydání: 2014
Předmět:
Zdroj: 2014 International Conference on Contemporary Computing and Informatics (IC3I).
Popis: One of the emerging technologies that can be used to study the rate of vegetation is hyper spectral remote sensing. Hyper spectral satellite image of Western part of Indiana is adopted for our study. This data was further used to calculate different spectral indices. The study on spectral indices which show some significant changes with variation in Vegetation are presented in this paper. These spectral indices are used to monitor the vegetation. The spectral indices that are used are NDVI (normalized differential Vegetation index), SRPI (simple Ratio pigment index), red edge (Clrededge) and SG (VI green). All these spectral indices stated above showed significant changes with change in rate of chlorophyll and nitrogen Concentration. In the graph plotted for different wavelengths verses the reflectance values showed different Curves for change in the area. From this study it can be inferred that the hyper spectral data can also be used to find area containing dense forest, farm lands and bare land. Hence Satellite images can give lot of information that needs to be explored.
Databáze: OpenAIRE