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Assessment of spatial distribution and estimation of biomass of Prosopis juliflora (Sw.) DC. in Puttlam to mannar region of Sri Lanka using remote sensing and GIS

Authors:

A. R. Gunawardena,

University of Peradeniya, LK
About A. R.
Postgraduate Institute of Agriculture
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T. T. Fernando,

University of Peradeniya, LK
About T. T.
Postgraduate Institute of Agriculture
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S. P. Nissanka ,

University of Peradeniya, LK
About S. P.
Department of Crop Science, Faculty of Agriculture
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N. D. K. Dayawansa

University of Peradeniya, LK
About N. D. K.
Department of Agricultural Engineering, Faculty of Agriculture
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Abstract

Prosopis juliflora (Sw.) DC. has been introduced to Hambantota District in the southern province of Sri Lanka during early 1950’s to rehabilitate salt affected soils in the coastal area and for firewood purposes. Within a very short period of time, this species got naturalized and started to show aggressive growing pattern. Currently, it covers almost all semi-arid areas including north-western coast of Sri Lanka. This study was conducted to identify the spatial distribution, to estimate the biomass and to map the vulnerable areas of spreading of P. juliflora in Puttalam to Mannar region of Sri Lanka using remote sensing and geographic information system (GIS). Landsat ETM+ (2005), ALOS AVNIR (2010) and GeoEye (2012) satellite data were used for the study. The existing and past situation of the distribution of this invasive species was determined using supervised and unsupervised image classification, developing NDVI and by visual interpretation. Above ground live biomass was observed through NDVI with allometric equations. A GIS-based model was developed to identify the vulnerable areas for spreading of the species. This study identified that visual interpretation of high spatial resolution satellite data is the most ideal in identification of the areas infested with P. juliflora. Further it was identified that a combination of supervised and unsupervised classification of medium spatial resolution satellite data and NDVI provides reasonable results in identifying P. juliflora infested areas with an accuracy of 78%. The results revealed that the biomass content associated with P. juliflora-associated vegetation was higher in 2010 compared to 2005 indicating spreading of the species. Vulnerable area mapping is helpful in controlling further spreading of the species. This study proves the importance and effectiveness of remote sensing and GIS in identification and assessment of areas infested with P. juliflora and their spatial spreading patterns.

Tropical Agricultural Research Vol. 25 (2): 228 – 239 (2014)

DOI: http://doi.org/10.4038/tar.v25i2.8144
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Published on 23 Nov 2015.
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