受到地物二向性反射的影响,航空遥感数据中存在亮度梯度现象,但目前仍然缺乏针对亮度梯度效应专门开展的实验研究。以美国加利福尼亚州中部的果园为研究区,基于沿太阳主平面方向(along solar plane,ASP)、垂直太阳主平面方向(perpendicularly to solar plane,PSP)和南北方向飞行并扫描成像获取的三景MASTER遥感影像,利用剖面分析研究了不同波段、植被指数的亮度梯度效应,并提出了一种多项式拟合校正方法。结果表明:受到热点现象的影响,PSP图像具有最明显的亮度梯度效应,而ASP图像的亮度梯度效应可以忽略不计;植被指数可以削弱亮度梯度效应的影响,但是在热点方向仍然会存在低估的情况。PSP与ASP的比值图像可以较好地消除地物本身以及背景的影响,利用该比值建立的分段多项式模型可以有效地校正由照射角度和观测角度带来的亮度梯度效应。
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.