Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Poyang Lake Wetland Classification Using Time-Series ENVISAT ASAR Data and Beijing-1 Imagery
Beijing-1 and ENVISAT ASAR images were used to classify wetland aquatic macrophytes in terms of their plant functional types (PFTs) over the Poyang Lake region, China. Speckle noise filtering, systematic sensor calibration within the same polarization or between different polarizations, and accurate geo-registration were applied to the time-series SAR data. As a result, time-series backscattering data, which is described as permittivity curves in this paper, were obtained. In addition, time-series indices, described as phenological curves, were derived from Beijing-1 time-series images in the classification experiment. Based on these two curves, a rule-based classification strategy was developed to extract wetland information from the combined SAR and optical data. In the rule-based wetland classification method, DEM data, submersion time index, temporal Beijing-1 images, time-series normalized difference vegetation index (TSNDVI) images, principal component analysis (PCA), and temporal ratio of ASAR time-series images were used. In addition, a decision tree-based method was used to map the wetlands. Conclusions include the following: (1) after the preprocessing of ASAR data, it was possible to satisfactorily separate different aquatic plant functional types; (2) hydrophytes from different PFTs exhibited distinct phenological, structural, moisture, and roughness characteristics due to the impact of the annual inundation of Poyang Lake wetland; and (3) more accurate results were obtained with the rule-based method than the decision tree (DT) method. Producer’s and user’s accuracy calculated from test samples in the classification results indicate that the DT method can potentially be used for mapping aquatic PFTs, with overall producer’s accuracy exceeding 80% and higher user’s accuracy for aquatic bed wetland PFTs. A comparison of producer’s and user’s accuracy from the rule-based classification increased from 3 to 12% and 7 to 26%, respectively, for different aquatic PFTs.
Poyang Lake Wetland Classification Using Time-Series ENVISAT ASAR Data and Beijing-1 Imagery
Beijing-1 and ENVISAT ASAR images were used to classify wetland aquatic macrophytes in terms of their plant functional types (PFTs) over the Poyang Lake region, China. Speckle noise filtering, systematic sensor calibration within the same polarization or between different polarizations, and accurate geo-registration were applied to the time-series SAR data. As a result, time-series backscattering data, which is described as permittivity curves in this paper, were obtained. In addition, time-series indices, described as phenological curves, were derived from Beijing-1 time-series images in the classification experiment. Based on these two curves, a rule-based classification strategy was developed to extract wetland information from the combined SAR and optical data. In the rule-based wetland classification method, DEM data, submersion time index, temporal Beijing-1 images, time-series normalized difference vegetation index (TSNDVI) images, principal component analysis (PCA), and temporal ratio of ASAR time-series images were used. In addition, a decision tree-based method was used to map the wetlands. Conclusions include the following: (1) after the preprocessing of ASAR data, it was possible to satisfactorily separate different aquatic plant functional types; (2) hydrophytes from different PFTs exhibited distinct phenological, structural, moisture, and roughness characteristics due to the impact of the annual inundation of Poyang Lake wetland; and (3) more accurate results were obtained with the rule-based method than the decision tree (DT) method. Producer’s and user’s accuracy calculated from test samples in the classification results indicate that the DT method can potentially be used for mapping aquatic PFTs, with overall producer’s accuracy exceeding 80% and higher user’s accuracy for aquatic bed wetland PFTs. A comparison of producer’s and user’s accuracy from the rule-based classification increased from 3 to 12% and 7 to 26%, respectively, for different aquatic PFTs.
Poyang Lake Wetland Classification Using Time-Series ENVISAT ASAR Data and Beijing-1 Imagery
Fang Ding (Autor:in) / Lin Wang (Autor:in) / Iryna Dronova (Autor:in) / Kun Cao (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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