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Advanced Image Processing Techniques for Remote Sensing Applications
Details
The main objective of this book is to propose a systematic approach to estimate crop yield (Paddy, Groundnut) for remote sensing applications using NOAA and Landsat 8 satellite images. In general the received imagery are noisy in nature. So, to tackle this issue spatial and frequency domain based denoising techniques were proposed and discussed in detail by implemented on both NOAA and Landsat 8 images. After this, In this book, empirical crop yield estimation models are proposed for both NOAA and Landsat 8 satellite data to estimate crop yields of both Paddy, groundnut with remote sensing images and meteorological parameters. By this, it can be said that this research work can be used as a secondary opinion in the estimation of crop yield over the study area.
Autorentext
K. Sateesh Kumar lavora come professore assistente presso lo SNIST di Hyderabad. Le sue aree di interesse sono l'elaborazione digitale delle immagini, il telerilevamento e l'apprendimento automatico, ecc. Prof. G. Sreenivasulu, professore di ECE, SVUCE, S V University. Ha diverse pubblicazioni internazionali in riviste e conferenze rinomate.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786206781790
- Genre Maths
- Anzahl Seiten 168
- Herausgeber LAP LAMBERT Academic Publishing
- Größe H220mm x B150mm x T11mm
- Jahr 2023
- EAN 9786206781790
- Format Kartonierter Einband
- ISBN 6206781798
- Veröffentlichung 04.09.2023
- Titel Advanced Image Processing Techniques for Remote Sensing Applications
- Autor Kanagala Sateesh Kumar , Gunapati Sreenivasulu
- Untertitel A Systematic Approach to Estimate Crop Yield using NOAA/Landsat 8 Satellites Data Through Denoising and Enhancement
- Gewicht 268g
- Sprache Englisch