Hyperspectral Vegetation Indices Calculated by Qgis Using Landsat Tm Image: a Case Study of Northern Iceland

• Main Author: Lemenkova, Polina
• Format: Text
• Language: unknown
• Published: figshare 2020
• Subjects: 90901 Cartography; FOS Environmental engineering; 50209 Natural Resource Management; FOS Earth and related environmental sciences; 40604 Natural Hazards; 50204 Environmental Impact Assessment; 120504 Land Use and Environmental Planning; FOS Social and economic geography; 50206 Environmental Monitoring; Environmental Science; 50205 Environmental Management; 90703 Environmental Technologies; 140205 Environment and Resource Economics; FOS Economics and business; 70504 Forestry Management and Environment; FOS Agriculture, forestry and fisheries; Geography; 60302 Biogeography and Phylogeography; FOS Biological sciences; Physical Geography; Arctic; Iceland
• Online Access: https://dx.doi.org/10.6084/m9.figshare.13301288; https://figshare.com/articles/journal_contribution/Hyperspectral_Vegetation_Indices_Calculated_by_Qgis_Using_Landsat_Tm_Image_a_Case_Study_of_Northern_Iceland/13301288

The vegetation indices (VIs) derived from the hyperspectral reflectance of vegetation are presented in this study for monitoring live green vegetation in the northern ecosystems of Iceland, along the fjords of Eyjafjörður and the Skagafjörður. The comparative analysis of the following VIs was performed: the NDVI, RVI, NRVI, TVI, CTVI, TTVI and SAVI. The methodology is based on the raster calculator band in a QGIS. The dataset includes a Landsat TM scene of 2013, UTM Zone 53, WGS84 captured from the GloVis. The computed bands include the NIR and R spectral bands and their combinations according to the algorithms of each of the seven VIs. The hyperspectral reflectance and crop canopy computations were applied to generate various scales of VIs and demonstrated following data range: NDVI: -0.91 to 0.65, RVI: 0.22 to 19.65, NRVI: 0.63 to 0.90, TVI: 0 to 1.12, CTVI: -0.64 to 1.07, TTVI: 0.70 to 1.18 and SAVI: -1.36 to 0.99 (roughly to 1.00). Of these, the RVI, NRVI, TVI and TTVI are adjusted to the positive values while the NDVI, CTVI and SAVI do include the negative diapason in the dataset due to the computing algorithm. The algorithms of the seven VIs are described and visualized in form of maps based on the multispectral remote sensing Landsat TM imagery identifying vegetated areas, their health condition and distribution of green areas against the bare soils, rocks, ocean water, lakes and ice-covered glaciers. The paper contributes both to the technical presentation of the QGIS functionality for the Landsat TM data processing by a raster calculator, and to the regional geographic studies of Iceland and Arctic ecosystems.