Estimation of vegetation level and agricultural lands of Babolsar city through Sentinel 2 satellite images using NDVI index

Quantitative and qualitative monitoring of vegetation is one of the main applications of remote sensing knowledge. Estimating the area of vegetation and agricultural lands in the traditional way is time consuming. Remote sensing is of great importance for providing up-to-date information, duplicate coverage, sensing in different spectral ranges, quantitative and digital sensing of surface phenomena. This study was conducted to estimate the level of vegetation and agricultural lands of Babolsar county through Sentinel 2 satellite images using NDVI index.

The present research method is descriptive-analytical based on the data of Sentinel 2 satellite images of 2019. These images were extracted from the USGS website. After extraction, the images are processed in remote sensing software systems and geographic information systems, and the required results have been extracted.

After receiving the Sentinel 2 satellite images, the bands 2, 3, 4, 8, which have a spatial resolution of 10 meters, after preprocessing and atmospheric corrections, based on IDL programming language, using NDVI index, Sentinel 2 ROI were obtained, then output. Threshold was calculated between a maximum of 1 and a minimum of 0.5 and with a Shape file output in ENVI and Arc Map software, the area of vegetation and the area under cultivation of agricultural lands in Babolsar county were calculated and concluded on the date of obtaining satellite images. Discussion and

The results showed that the area of arable land and vegetation of Babolsar city is estimated to be more than 52%. Overall accuracy of 95% and kappa coefficient of 89% by evaluating the output of NDVI index showed that Sentinel 2 images can be used to extract vegetation and arable lands.