ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目...ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目前利用ALI数据的全色波段以及多光谱波段进行高精度图像融合的研究较少,本文进行的实验是分别利用HSV变换、主成分分析(PCA)、Brovey变换、Gram-Schmidt变换等融合方法对ALI数据进行图像融合,通过图像融合结果的质量评价指标得出较好融合方法是HSV变换。展开更多
Mangroves are woody plant communities in the intertidal zone of tropical and subtropical coasts that play an important role in these zones. The infrared wave band is one of the key bands in the remote sensing identifi...Mangroves are woody plant communities in the intertidal zone of tropical and subtropical coasts that play an important role in these zones. The infrared wave band is one of the key bands in the remote sensing identification of mangrove forest, and ALI（advanced land imagery） has a large number of infrared bands. Two angle indices were proposed based on liquid water absorption at band 5p and band 5 of EO-1 ALI, denoted as β1.25 and β1.65 respectively. A decision tree method was adopted to identify mangrove forest using remote sensing techniques for β1.25–β1.65 and NDVI（normalized difference vegetation index） for EO-1 ALI imagery acquired at Shenzhen Bay. The results showed that the reflectance of mangrove forests at band 5p and band 5 was significantly lower than that of terrestrial vegetation due to the characteristics of coastal wetlands of mangrove forests. This resulted in a greater β1.25–β1.65 value for mangrove forest than terrestrial vegetation. The decision tree method using β1.25–β1.65 and NDVI effectively identifies mangrove forest from other land cover categories. The misclassification and leakage rates were 4.29% and 5.11% respectively. ALI sensors with many infrared bands could play an important role in discriminating mangrove forest.展开更多
文摘ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目前利用ALI数据的全色波段以及多光谱波段进行高精度图像融合的研究较少,本文进行的实验是分别利用HSV变换、主成分分析(PCA)、Brovey变换、Gram-Schmidt变换等融合方法对ALI数据进行图像融合,通过图像融合结果的质量评价指标得出较好融合方法是HSV变换。
基金National Natural Science Foundation of China(41201461)
文摘Mangroves are woody plant communities in the intertidal zone of tropical and subtropical coasts that play an important role in these zones. The infrared wave band is one of the key bands in the remote sensing identification of mangrove forest, and ALI（advanced land imagery） has a large number of infrared bands. Two angle indices were proposed based on liquid water absorption at band 5p and band 5 of EO-1 ALI, denoted as β1.25 and β1.65 respectively. A decision tree method was adopted to identify mangrove forest using remote sensing techniques for β1.25–β1.65 and NDVI（normalized difference vegetation index） for EO-1 ALI imagery acquired at Shenzhen Bay. The results showed that the reflectance of mangrove forests at band 5p and band 5 was significantly lower than that of terrestrial vegetation due to the characteristics of coastal wetlands of mangrove forests. This resulted in a greater β1.25–β1.65 value for mangrove forest than terrestrial vegetation. The decision tree method using β1.25–β1.65 and NDVI effectively identifies mangrove forest from other land cover categories. The misclassification and leakage rates were 4.29% and 5.11% respectively. ALI sensors with many infrared bands could play an important role in discriminating mangrove forest.
