Poyang Lake wetland vegetation biomass inversion using polarimetric RADARSAT-2 synthetic aperture radar data

Abstract

Abstract. Poyang Lake is the largest freshwater lake in China and one of the most important wetlands in the world. Vegetation, an important component of wetland ecosystems, is one of the main sources of the carbon in the atmosphere. Biomass can quantify the contribution of wetland vegetation to carbon sinks and carbon sources. Synthetic aperture radar (SAR), which can operate in all day and weather conditions and penetrate vegetation to some extent, can be used to retrieve information about vegetation structure and the aboveground biomass. In this study, RADARSAT-2 polarimetric SAR data were used to retrieve aboveground vegetation biomass in the Poyang Lake wetland. Based on the canopy backscatter model, the vegetation backscatter characteristics in the C-band were studied, and a good relation between simulated backscatter and backscatter in the RADARSAT-2 imagery was achieved. Using the backscatter model, pairs of training data were built and used to train the back propagation artificial neural network. The biomass was retrieved using this ANN and compared with the field survey results. The rootmean-square error in the biomass estimation was 45.57 g∕m 2 . This shows that the combination of the model and polarimetric decomposition components can efficiently improve the inversion precision. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Estimating the biomass of Carex cinerascens (Cyperaceae) in floodplain wetlands in Poyang Lake, China

“…The results of this study showed that the C. cinerascens biomass per unit area ranged from 0.10 to 0.58 kg/m 2 during the winter in Poyang Lake, which was consistent with the results of other studies of Poyang Lake that showed that the biomass per unit area ranged from 0.14 to 0.83 kg/m 2 (Wu et al 2012;Wu et al 2015;Xu et al 2015). Study used synthetic aperture radar to retrieve Carex biomass in Poyang Lake reported that the retrieved biomass were from 0.3 to 0.5 kg/m 2 (Shen et al 2015). Our validated results showed that the RE between the observed biomass and the predicted biomass are all between À30% and 30%, while in other studies accounted for 62.5% (Gao et al 2017).…”

“…Plant biomass is a key driver of ecosystem dynamics, thus influencing ecosystem structures and functions. As an important component of terrestrial ecosystems, biomass of wetland plant is an indispensable part of the global carbon cycle (Li and Liu 2002;Vis et al 2003;Liao et al 2013;Shen et al 2015;Du et al 2017;Guo et al 2017). Regional plant biomass changes were associated with the important outcomes in wetland ecosystem functional characteristics such as primitive productivity and carbon balance.…”

Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

“…Rapid developments of remote sensing capacities have expanded their applications into ecological, hydrological, geomorphological, and societal interests in inundated situations [37][38][39]. SAR and InSAR from active sensors have been applied in water level and wetland mapping [40][41][42][43][44][45][46]. Hyperspectral remote sensing provides promising approaches in the monitoring of global tidal wetlands [47][48][49].…”

Simulating Microwave Scattering for Wetland Vegetation in Poyang Lake, Southeast China, Using a Coherent Scattering Model

“…For wetland vegetation in the Poyang Lake area in Jiangxi, China, the modified MIMICS model and the rice scattering model (RSM) [22] developed by Cuizhen Wang were used to simulate the backscatter in the previous researches [17,18,20,21]. By ignoring the curvature of the blade and the strong coherence from the great density of grass, the simulation results of the two models have large error.…”

“…Recently developed models have focused largely on forest vegetation, natural grassland, and crop yields for crops such as soybeans, wheat, canola, and rice [3][4][5][6][7][8][9][10][11][12][13][14][15][16]. However, very little attention has been given to wetland ecosystems [17][18][19][20][21]. In order to reveal the scattering characteristics of wetland vegetation and to improve retrieval accuracy, an accurate microwave scattering model needs to be established, which is suitable for the high water content, high vegetation density, curved leaves, and lodging situation of wetland vegetation.…”