Land Cover Classification of Remotely Sensed Images

Discover the intricacies of remote sensing with "Land Cover Classification of Remotely Sensed Images" by S. Jenicka. Published by Springer Nature Switzerland AG in 2021, this hardback edition spans 176 pages, making it an essential resource for students and professionals alike. The book delves into advanced techniques for classifying land cover using remotely sensed images, offering a comprehensive understanding of both gray level and multivariate texture models. The third chapter specifically highlights essential texture models, complete with relevant Matlab source codes, providing practical insights for readers. Enhance your knowledge and skills in remote sensing technology with this authoritative guide that bridges theory and application. Perfect for anyone looking to deepen their expertise in this critical field.