Geography and Natural Resources

MINERAL DETECTION BASED ON SATELLITE IMAGES OF LANDSAT TM SENSOR ON THE EXAMPLE OF DASHKESAN REGION

 

V.M.Mammadaliyeva, V.R.Nasirova

Abstract. The article is devoted to the identification of deposits of iron minerals, as well as the degree of their influence on the health of forest vegetation. In the course of the study, on the basis of multispectral satellite images, the spectral indices FM Ratio, which is an indicator of the reserves of iron minerals, and the SIPI index, reflecting the degree of plant health, were de­ter­mined. After calculating the SIPI index, all forest vege­tation areas were classified into three polygons: healthy, damaged and destroyed. Based on the results of pro­ces­sing, we can say that over 25 years the area of healthy forests and vegetation increased by 1273 hectares, da­maged – decreased by 2290 hectares, and destroyed in­creased by 1 018 hectares. According to the table for fer­rous iron compounds based on the calculation of the FM Ratio index in the Dashkesan region for 1986-2011, this type of mineral decreased by 13.23 hectares in the zone of healthy forest vegetation, increased by 36 hectares in damaged areas, and decreased by 1408 hectares in des­troyed forests. Based on these results, it can be said that this type of mineral mainly influenced all classes of fo­rest vegetation.

 

Keywords: iron minerals, forests health, multi­spec­tral images, spectral indices, FM Ratio, SIPI

 

REFERENCES

  1. Landsat missions. Landsat-5. URL: https://www.usgs.gov/core-science-systems/nli/landsat/landsat-5 (20 янв. 2021)
  1. Mulligan C.N., Yong R.N. and Gibbs B.F. Remediation technologies for metal-contaminated soils and groundwater: an evaluation. Engineering Geology, Vol. 60, Is. 1-4, 2001, pp 193-207. DOI: 10.1016/S0013-7952(00)00101-0
  2. Segal D. “Theoretical Basis for Differentiation of Ferric-Iron Bearing Minerals, Using Landsat MSS Data”. Proceedings of Symposium for Remote Sensing of Environment, 2nd Thematic Conference on Remote Sensing for Exploratory Geology, Fort Worth, TX, 1982, pp. 949-951
  3. United States Geological Survey. Earth Ex­plo­rer. URL: https://earthexplorer.usgs.gov (20 янв. 2021)
  4. “Indices gallery”, ArcGIS Pro, ESRI, 2018. URL: http://pro.arcgis.com/en/pro-app/help/data/imagery/indices-gallery.htm (20 янв. 2021)
  5. Кобелева Н.В., Рогачев С.А., Чичкова Е.Ф. Оценка пространственно-динамической дифферен­циации экосистем Арктических хасыреев на основе расчета спектральных индексов по данным кос­ми­ческой съемки. XVIII Всесоюзная Открытая кон­фе­ренция «Современные проблемы дистанционного зондирования Земли из космоса», Москва, 16-20 но­ября 2020 года
  6. Колесникова О.Н., Черепанов А.С. Воз­мож­ности ПК ENVI для обработки мультиспектральных и гиперспектральных данных. Геоматика, №3, 2009, c. 24-27.

 

Publication Date: March 1, 2021

Download the article