Field spectroradiometry for discrimination of wetland components: a case study of a tropical inland wetland in India

Abstract

Remote sensing has emerged as an effective tool for mapping, monitoring and assessment of wetland ecosystems. Spectral resolution of hyperspectral imagery allows collection of extensive information on dynamics of wetland components. Development of comprehensive spectral libraries using field spectroradiometry is imperative to tap the potential of hyperspectral imagery. In this study, an attempt has been made (i) to test the efficacy of field spectroradiometry data and processing techniques for identification and discrimination of wetland components, and (ii) to develop an approach for creating an extensive library for wetland components. Canopy level spectra of 13 macrophyte species representing different life-forms and water column reflectance spectra were collected seasonally at 16 sites in Bhindawas wetland of India for the years 2014 and 2015. Field spectra were processed using spectroscopic techniques including smoothing, derivative analysis and continuum removal. Results show derivative transforms to be efficient in identification and discrimination of wetland components. Magnitude and position of red-edge peak successfully discriminated different macrophytes with maximum and minimum value for Nymphoides indica and Hydrilla verticillata respectively. Continuum removal further strengthens the attributes of spectral data for species discrimination. Algorithms developed based on derivative transforms of water column spectra allow for continuous monitoring of bio-optical parameters and trophic status of the wetland. As a result of this research, sample-sets of field spectra providing a sound base for mapping and monitoring of wetland components were compiled, leading to the development of the first spectral library for an inland freshwater wetland in the Indian subcontinent. This research output in conjunction with advanced analytical tools and algorithms shall be utilized for wetland assessment in future studies.