Abstract
Landsat-TM of 2001 covering Iceland (15.5°W-21°W, 64.5°N-67°N) was processed using SAGA GIS for testing distance-based Vegetation Indices (VIs): four approaches of Perpendicular Vegetation Index (PVI) and two approaches of Transformed Soil Adjusted Vegetation Index TSAVI. The PVI of vegetation from the soil background line indicated healthiness as a leaf area index (LAI). The results showed that the reflectance for vegetation has a linear relation with soil background line. Four PVI models and two TSAVI shown coefficients of determination with LAI. The dataset demonstrate variations in the calculated coefficients. The mode in the histograms of the PVI based on four different algorithms show the difference:-7.1,-8.36, 2.78 and 7.0. The dataset for the two approaches of TSAVI: first case ranges in 4.4.-80.6 with a bell-shape mode of a histogram (8.09 to 23.29) for the first algorithm and an irregular shape for the second algorithm with several modes starting from 0.11 to 0.2 and decreasing to 0.26. SAGA GIS permits the calculation of PVI and TSAVI by computed NDVI based on the intersection of vegetation and soil background. Masking the NIR and R, a linear regression of grids was performed using an equation embedded in SAGA GIS. The advantages of the distance-based PVI and TSAVI consists in the adjusted position of pixels on the soil brightness line which refines it comparing to the slope-based VIs. The paper demonstrates SAGA GIS application in agricultural studies.
Publisher
Centre for Evaluation in Education and Science (CEON/CEES)
Reference55 articles.
1. Abburu, S., Golla, S.B. 2015. Satellite Image Classification Methods and Techniques: A Review. International Journal of Computer Applications, 119(8): pp. 20-25;
2. Ahmet, K.R., Akter, S. 2017. Analysis of landcover change in southwest Bengal delta due to floods by NDVI, NDWI and K-means cluster with Landsat multi-spectral surface reflectance satellite data. Remote Sensing Applications: Society and Environment, 8: pp.168-181;
3. Baret, F., Guyot, G. 1991. Potential and limitations of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment, 104: pp.88-95;
4. Baret, F., Guyot, G., Major, D. 1989. TSAVI: A vegetation index which minimizes soil brightness effects on LAI and APAR estimation. Conference IEEE Xplore;
5. Bhandari, A.K., Kumar, A., Singh, G.K. 2012. Feature Extraction using Normalized Difference Vegetation Index (NDVI). a Case Study of Jabalpur City. Procedia Technology, 6: pp.612-621;
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献