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Discriminating the invasive species, ‘Lantana’ using vegetation indices

  • Research Article
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Abstract

Invasive species have been the focus of environmentalists due to their undesired impact on the ecosystem. Spread of Lantana (Lantana camara L.), an invasive plant species, has been found in diverse geophysical environments causing a threat to the native flora. Various eradication programmes have been attempted such as burning, chemical sprays, bio-control agents and physical plugging mechanism for removing such invasive species in India. The efforts and success of these programmes need to be augmented with a correct, quick and cost effective technique of mapping in order to locate them, understand their spatial extent and hence make the process comprehensive. Also Lantana’s appearance as dense vegetation patches in remote sensing data causes problems for estimating forest canopy density. Remote sensing provides a possible solution in qualitatively and quantitatively evaluating terrestrial surface vegetation cover using spectral measure-ments. This research paper addresses issues and techniques adopted to detect and extract Lantana, and can be used for various applications in forestry as well as in eradication programmes. This study attempted to understand the appropriate band combination using Landsat data and generating vegetation indices in order to extract Lantana patches in an accurate manner. Twenty nine different vegetation indices were analyzed for their effectiveness in differentiating Lantana from other classes. The study showed that SAVI (Soil Adjusted Vegetation Index) is most favorable in discriminating Lantana followed by Perpendicular Vegetation Index-3 in the optimum bio-window (February to April).

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Abbreviations

VI 1:

Simple Ratio

VI 2:

NDVI (Normalised Difference Vegetation Index)

VI 3:

TVI (Transformed Vegetation Index)

VI 4:

CTVI (Corrected Transformed Vegetation Index)

VI 5:

TTVI (Thiam’s Transformed Vegetation Index)

VI 6:

RVI (Ratio Vegetation Index)

VI 7:

NRVI (Normalised Ratio Vegetation Index)

VI 8:

PVI (Perpendicular Vegetation Index)

VI 9:

PVI (Perpendicular Vegetation Index)-1

VI 10:

PVI (Perpendicular Vegetation Index)-2

VI 11:

PVI (Perpendicular Vegetation Index)-3

VI 12:

DVI (Difference Vegetation Index)

VI 13:

AVI (Ashburn Vegetation Index)

VI 14:

SAVI_L1 (Soil Adjusted Vegetation Index)

VI 15:

SAVI_L0.5 (Soil Adjusted Vegetation Index)

VI 16:

SAVI_L0.25 (Soil Adjusted Vegetation Index)

VI 17:

TSAVI (Transformed SAVI)

VI 18:

TSAVI (Transformed SAVI)-1

VI 19:

TSAVI (Transformed SAVI)-2

VI 20:

WDVI (Weighted Difference Vegetation Index)

VI 21:

MSAVI (Modified SAVI)

VI 22:

MSAVI (Modified SAVI)-1

VI 23:

MSAVI (Modified SAVI)-2

VI 24:

GEMI (Global Environment Monitoring Index)

VI 25:

EVI (Enhanced Vegetation Index)

VI 26:

AVI (Advanced Vegetation Index)

VI 27:

BI (Bare Soil Index)

VI 28:

SI (Shadow Index)

VI 29:

Thermal Index (TI)

Landsat TM:

Landsat Thematic Mapper

Landsat ETM:

Landsat Enhanced Thematic Mapper

MSS:

Multispectral Scanner

LAI:

Leaf Area Index

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Authors and Affiliations

  1. Geomatics Division, Department of Civil Engineering, IIT Roorkee, Roorkee, 247667, Uttarakhand, India

    Rashmi Kandwal

  2. Indian Institute of Remote Sensing, Dehra Dun, 248001, Uttarakhand, India

    C. Jeganathan & S. P. S. Kushwaha

  3. International Institute for Geo Information Science and Earth Observation, Enschede, The Netherlands

    Valentyn Tolpekin

Authors
  1. Rashmi Kandwal
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  2. C. Jeganathan
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  3. Valentyn Tolpekin
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  4. S. P. S. Kushwaha
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Correspondence to Rashmi Kandwal.

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Kandwal, R., Jeganathan, C., Tolpekin, V. et al. Discriminating the invasive species, ‘Lantana’ using vegetation indices. J Indian Soc Remote Sens 37, 275–290 (2009). https://doi.org/10.1007/s12524-009-0027-5

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  • DOI: https://doi.org/10.1007/s12524-009-0027-5

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