Major forests and plant species discrimination in Mudumalai forest region using airborne hyperspectral sensing

Journal of Asia-Pacific Biodiversity

Parul Srivastava¹  Purabi Saikia²  Arvind Chandra Pandey²  Nikhil Lele³  Amit Kumar⁴  Bodi Surya Pratap Chandra Kishore⁴  Mohamed Latif Khan⁴  Bimal Kumar Bhattacharya⁵ 

[1]Corresponding author. Tel.: [phone]

[2]IUCN-Commission on Ecosystem Management, South Asia, India

[3]Department of Environmental Sciences, Central University of Jharkhand, Ranchi, 835205, India

[4]Department of Geoinformatics, Central University of Jharkhand, Ranchi, 835205, India

[5]Space Application Centre, ISRO, Ahmedabad, 380015, India

关键词: AVIRIS-NG;    Mudumalai forest region;    Plant species characterization;    Spectral angle mapper;    Spectroradiometer measurement;    Support vector machine;   

DOI  :  

来源: DOAJ

【 摘 要 】

The present study focused on forest type classification and major plant species assemblages in Mudumalai forest region using Airborne Visible/Infrared Imaging Spectrometer Next Generation. The phytosociological analysis exhibited a total of 657 individuals (1095 individuals ha-1) of 24 tree species belonging to 22 genera and 18 families. The highest tree density was contributed by Tectona grandis (132 individuals ha-1 and 12.05% of total tree density) followed by Anogeissus latifolia (105 individuals ha-1 and 9.59% of total tree density). The support vector machine study showed the dominance of Southern Tropical Semi-Evergreen forests (31%) followed by Southern Tropical moist deciduous forests (26.7%) and Southern Tropical dry deciduous forests (24.8%) with a very high accuracy (92.37%). The comparative analysis of the existing forest types with Champion and Seth’s (1968) classification of forests exhibited a change of 30% in forest types in terms of their structure, composition, and extent over a period of 50 years. The spectral angle mapper–based study emphasized the defining role of elevation, rainfall, and temperature in species distribution, and physiognomy with dominance of A. latifolia (∼19.22%). The study implies the high spectral fidelity of airborne images for forest type mapping and plant species discrimination in tropical forests.

【 授权许可】

Unknown