Assessment of Normalized Difference Vegetation Index by The Use of UAV Remote Sensing

Abstract

Remote Sensing has become an important tool in the field of agricultural management. Remote Sensing helps in site-specific farming management which is also known as Precision Farming. Integrating an RGB camera with an Unmanned Aerial Vehicle (UAV) is very efficient in the case of certain applications of precision farming applications. This paper deals with the evaluation of multispectral images and vegetation indices of precision agriculture application by means of a multi-rotor UAV. Remote sensing for agriculture and crop administration applications goes for giving spatially and spectrally inferred surface parameters for crop arrangement and mapping, crop projection rates and yield expectations, crop health and condition, sickness identification and supplement inadequacy, and photosynthetic color content. The high-quality images which are transmitted in real-time to the ground control station are further processed by implementing NDVI algorithm to analyze the green vegetation and water content existing in the plantation. This work demonstrates the outcomes acquired by a low-cost UAV for agricultural application with a comparable analysis of vegetation index for over two months.