Forest canopy height is a basic metric characterizing forest growth and carbon sink capacity. Based on full-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) data, this study used Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) technology to estimate forest canopy height. In total the four methods of differential DEM (digital elevation model) algorithm, coherent amplitude algorithm, coherent phase-amplitude algorithm and three-stage random volume over ground algorithm (RVoG_3) were proposed to obtain canopy height and their accuracy was compared in consideration of the impacts of coherence coefficient and range slope levels. The influence of the statistical window size on the coherence coefficient was analyzed to improve the estimation accuracy. On the basis of traditional algorithms, time decoherence was performed on ALOS/PALSAR data by introducing the change rate of Landsat NDVI (Normalized Difference Vegetation Index). The slope in range direction was calculated based on SRTM (Shuttle Radar Topography Mission) DEM data and then introduced into the s-RVoG (sloped-Random Volume over Ground) model to optimize the canopy height estimation model and improve the accuracy. The results indicated that the differential DEM algorithm underestimated the canopy height significantly, while the coherent amplitude algorithm overestimated the canopy height. After removing the systematic coherence, the overestimation of the RVoG_3 model was restrained, and the absolute error decreased from 23.68 m to 4.86 m. With further time decoherence, the determination coefficient increased to 0.2439. With the introduction of range slope, the s-RVoG model shows improvement compared to the RVoG model. Our results will provide a reference for the appropriate algorithm selection and optimization for forest canopy height estimation using full-polarized L-band synthetic aperture radar (SAR) data for forest ecosystem monitoring and management.
Eucalyptus trees are a major fast-growing species in southern China. The ecological problems associated with constantly developing new Eucalyptus plantations have been the focus of extensive debate. In this study, we used spatial analysis and geostatistical methods along with four continuous national forest resource inventories and meteorological data to analyze dynamic changes in the distribution of Eucalyptus plantations in China. The productivity levels of Eucalyptus plantations were compared at different time periods by measuring annual mean productivity in permanent sample plots to provide baseline data related to the scientific management of Eucalyptus plantations. Results showed that the area of Eucalyptus plantations increased constantly in China from 1998 to 2013, expanding from 60.7 × 104 hm2 in 1998 to more than 445.5 × 104 hm2 in 2013. The productivity of Eucalyptus plantations was positively correlated with temperature and rainfall, but negatively correlated with elevation. However, these changes did not necessarily indicate an improvement in the management quality of Eucalyptus plantations, because they were mainly caused by an increased in the proportion of newly reclaimed areas for Eucalyptus afforestation and the constantly decreasing area of original Eucalyptus plantations, to which sufficient attention must be given.
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