Comparison of NDVI and RVI vegetation indices using satellite images

Remote Sensing is the acquisition of information about its physical properties without direct contact with an object. This information is obtained through sensors. These sensors do not come into contact with objects. There are two different systems for remote sensing. These are Active and Passive Sensor Systems. Passive Sensor Systems measure the energy of the rays reflected from the objects by the rays sent by the sun. On the other hand, Active Sensor Systems measure the energy reflected from the objects by transmitting their rays to the object. Active Sensor Systems do not need the Sun because they work with their own energy. Therefore, night or season conditions in Active Sensor Systems are not important. Passive Sensor Systems can be shown as an example of optical sensor systems. The Landsat-8 satellite works with an optical sensor system. Synthetic Aperture Radar (SAR) systems are examples of active sensor systems. SAR systems have a wide range of usage in all weather conditions and they are a radar system that displays the earth in high resolution. Radarsat-2 satellite has SAR sensor systems. The aim of this study is to compare each of the vegetation indices by using Landsat-8 and Radarsat-2 satellite images with two different types of sensors. Vegetation indices have a variety of uses such as climate change, vegetation diversity and drought. In this study, Radar Vegetation Index (RVI) and Normalized Difference Vegetation Index (NDVI) were investigated. NDVI is divided into the sum of the difference of NIR (Near Infrared) and RED bands. The NDVI range is between -1 and +1. The negative values indicate wetlands or glacial areas, while the values close to +1 indicate areas where vegetation density and diversity increase. The RVI range is between 0-1. The ground flatness increases as it approaches 0. As it approaches 1, vegetation increases. For the calculation of the RVI index, the back-scattering coefficient of the four different bands (HH, HV, VH, VV) of the multi-time full-polarimetric Radarsat-2 FQ satellite image dated 8 April 2015 was used. In the calculation of NDVI index, Band 5 (Near Infrared) and Band 4 (Red) of the Landsat-8 satellite image of May 25, 2015 were used. Dicle University agricultural areas were chosen as the study area. 281 different GPS points belonging to this agricultural area were determined and RVI and NDVI values of these points were calculated. When the obtained values are analyzed statistically, a good correlation was observed between RVI and NDVI indices. As a result of two different data sets; The correlation and determination coefficients between RVI and NDVI values were found to be r = 0.6926 r2 = 0.4797 and r = 0.6403 r2 = 0.4100, respectively.