Detection and Transmission Process of Land Cover Time Series Using GIS and Remote Sensing Technology in Peripheral Areas (Case study: Kajor section)

Subject Areas : GEOMORPHOLOGY

Yousef darvishi ¹ , Mohammad Einali ² , Amineh Andjomshoaa ³

1 - Assistant Professor of Geography, Payame Noor University, Tehran, Iran.
2 - Department of Geospatial Information Systems, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 - Department of Architecture, Kerman Branch, Islamic Azad University, Kerman, Iran

Received: 2022-01-13 Accepted : 2022-06-09 Published : 2022-06-21

Keywords: GIS, remote sensing, Land cover time series, PeripheralAreas,

Abstract :

The ever-increasing population growth and subsequent horizontal expansion of villages has led to changes in land use, especially in protected areas, resulting in the destruction of natural areas. In order to make the best use of the land, it seems necessary to be aware of the changes in land use and the nature of human use of the land, which can be done by revealing the changes in land use. Therefore, in order to protect this area, it is not only important to understand the human factors, but also the role of natural factors, including vegetation. In this research, Landsat satellite imagery was used in 7 time periods. EVI, DVI and NDVI indices were used to study and analyse the changes in vegetation in the study area. In the present study, based on the modelling objectives, the changes in forest cover in the study area were investigated using Landsat satellite images for the years 1985, 1990, 1995, 2000, 2010, 2015 and 2017.The false colour images of the OLI sensor used were referenced to the panchromatic band using 20 ground control points and an appropriate RMSe (0.28) of the ground, then the images of the sensors MSS and TM were referenced using the image-to-image method with an RMSe of less than 0.5. In this context, the modelling of the transmission potential was performed using the learning algorithm based on the multilayer perceptron and the prediction of the changes for the best model was performed using the Markov chain. Subsequently, the accuracy of the modelling was evaluated using the statistics of hits, misses and false alarms. The results of the vegetation indicators study showed the improvement of the vegetation condition in the studied period. The results of the vegetation indicators study showed that the vegetation condition improved during the studied period. The study of land use also showed that with the current trend, the area without cover will decrease and the area with pasture and forest cover will increase. Therefore, the improvement in cover conditions can be attributed to the application of conservation measures.