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 root-mean-square error in the biomass estimation was 45.57 g/m2. This shows that the combination of the model and polarimetric decomposition components can efficiently improve the inversion precision.
Highlights
Biomass, in ecology, is the mass of living organisms in a given area or ecosystem at a given time.[1]
The BP artificial neural network (ANN) were both designed with number of neurons in the hidden layers was calculated according ttowonh1⁄4iddpeffiinffiffi×ffiffilffiaffijffiffiyþersk.∕T2h,4e9 where i and j are the numbers of neurons in the input and output layers, and k is the number of training samples
This study focused on the application of ANNs combined with a backscatter model to retrieve wetland vegetation biomass with RADARSAT-2 polarimetric synthetic aperture radar (SAR) data
Summary
In ecology, is the mass of living organisms in a given area or ecosystem at a given time.[1]. An important component of terrestrial ecosystems, play a key role in global climate change because one of their components, wetland vegetation, is the main source of the carbon in the atmosphere.[2] Wetland vegetation biomass is a key indicator for evaluating the carbon sequestration capacity of wetlands. Biomass governs the potential amount of carbon that could be released into the atmosphere because of deforestation, and regional biomass changes have been associated with important outcomes in ecosystem functional characteristics and climate change.[3] biomass estimation of the wetland vegetation plays a key role in the understanding of dynamic changes of wetland ecosystems. The advantages of remote sensing data, especially synthetic aperture radar (SAR) data, are that it can be collected repeatedly and processed conveniently, making it an efficient data source for Journal of Applied Remote Sensing
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