DETECTION OF CLAY MINERALS BASED ON SATELLITE IMAGES OF LANDSAT TM / ETM+ SENSORS

• Main Authors: Valida Mehman Mammadaliyeva, Vusala Rahib Nasirova
• Format: Article
• Language: English
• Published: Science and Innovation Center Publishing House 2020-12-01
• Series: Siberian Journal of Life Sciences and Agriculture
• Subjects: дистанционное зондирование; landsat; глинистые минералы; лес; растительность; электронные карты
• Online Access: http://journal-s.org/index.php/vmno/article/view/12957
• ISSN: 2658-6649; 2658-6657

Determine the content of clay minerals and the state of forest vegetation in the same areas. Materials and methods. To identify the dependence, multispectral images of the earth’s surface were used, obtained with the help of Landsat satellites in different years (1986 and 2011). During the study, the reserves of clay minerals in the Dashkesan region of Azerbaijan were determined, as well as the spectral index SIPI (index of insensitivity to the structure of the pigment), reflecting the degree of plant health in this region. The identification of areas with a high content of clay materials was made by calculating the ratio of images in the spectral ranges SWIR 1 and SWIR 2. Electronic maps have been drawn up. An overall decrease in the area of such plots for 25 years by 5831 hectares was revealed. The SIPI index values were also calculated. Based on the obtained values of this index, a classification of all areas of forest vegetation into three classes was made: with healthy, damaged and destroyed vegetation. Electronic maps have been compiled showing the division of forest cover into 3 zones in accordance with the specified classes. This processing algorithm was applied to data from 1986 and 2011. For each year, maps of the location of clay minerals and SIPI values were compiled. These maps were superimposed on each other and the content of clay minerals in each of 3 different zones was determined. Results. Analysis of the dynamics showed that the area of sites with clay minerals increased by 2233 hectares in the zone of healthy forest vegetation, decreased by 8064 hectares in the damaged areas, and did not change in the destroyed forests. Conclusion. The presented method was also used to identify areas containing ferrous and ferric compounds.