Remote sensing technology for mapping and monitoring vegetation cover (Case study: Semirom-Isfahan, Iran)

Document Type : Original Research Paper

Authors

1 MSc., College of Natural Resources, Isfahan University of Technology, Isfahan, Iran

2 Prof., College of Natural Resources, Isfahan University of Technology, Isfahan, Iran

3 Asst. Prof., College of Natural Resources, Isfahan University of Technology, Isfahan, Iran

4 Assoc., Prof., College of Natural Resources, Isfahan University of Technology., Isfahan, Iran

10.7508/pj.2015.02.005

Abstract

To determine the suitable indices for vegetation cover and production assessment based on the remote sensing data, simultaneous digital data with field data belonging to the spring rangeland of the Semirom-Isfahan province were analyzed. During two years of monitoring the annual, grass, forb, and shrub vegetation cover and the total production data from 86 were collected. The Global Positioning System (GPS) was used to measure the coordinates of plots and transects. Geometric correction and histogram equalization were applied in image processing, and image digital numbers were converted to reflectance numbers. In the next stage, all vegetation indices were calculated from the Advanced Wide Field Sensor (AWiFS) image data and compared with the vegetation cover estimates, at monitoring points, made during field assessments. A linear regression model was used to select suitable vegetation indices. The results showed that there were significant relationships between the satellite data and the vegetative characteristics. Among the indices, the Normalized Difference Vegetation Index (NDVI) consistently showed significant relationships with the vegetation cover. The estimation of the vegetation cover with the NDVI vegetation index was more accurately predicted within rangeland systems. Using the produced model from the NDVI index vegetation crown cover, percentage maps were produced in three class percentages for each image. Generally introduced indices provided accurate quantitative estimation of the parameters. Therefore, it was possible to estimate cover and production as important factors for range monitoring using the AWiFS data. The Remote sensing data and the Geographic Information System are the most effective tools in natural resource management.

Keywords

References

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Pollution
Volume 1, Issue 2 - Serial Number 2
April 2015
Pages 165-174

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