基于卫星影像的NDVI和RVI植被指数比较

Abdurrahman Gonenc, M. S. Özerdem, Emrullah Acar
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引用次数: 11

摘要

遥感是在不直接接触物体的情况下获取物体物理特性的信息。这些信息是通过传感器获得的。这些传感器不与物体接触。有两种不同的遥感系统。这些是主动和被动传感器系统。无源传感器系统通过太阳发出的光线来测量物体反射的光线的能量。另一方面,主动传感器系统通过向物体发射射线来测量物体反射的能量。无源传感器系统可以作为光学传感器系统的一个例子。Landsat-8卫星与光学传感器系统一起工作。合成孔径雷达(SAR)系统是主动传感器系统的一个例子。SAR系统在所有天气条件下都有广泛的用途,它们是一种高分辨率显示地球的雷达系统。Radarsat-2卫星有SAR传感器系统。本研究的目的是通过使用两种不同类型传感器的Landsat-8和Radarsat-2卫星图像来比较每种植被指数。本文对雷达植被指数(RVI)和归一化植被指数(NDVI)进行了研究。RVI指数的计算采用Radarsat-2 FQ卫星2015年4月8日多时段全极化影像的四个不同波段(HH、HV、VH、VV)的后向散射系数。在NDVI指数的计算中,使用了2015年5月25日Landsat-8卫星影像的波段5(近红外)和波段4(红色)。研究区选择了戴尔大学农业区。确定了该农业区100个不同的GPS点,计算了这些点的RVI和NDVI值。通过统计学方法观察到RVI与NDVI指数之间具有良好的相关性。
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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. 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. In this study, Radar Vegetation Index (RVI) and Normalized Difference Vegetation Index (NDVI) were investigated. 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. 100 different GPS points belonging to this agricultural area were determined and RVI and NDVI values of these points were calculated. A good correlation was observed between RVI and NDVI indices with the aid of statistically approach.
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