高光谱数据具有丰富的光谱特征,但是其空间分辨率相对较低.一些遥感数据具有与高光谱数据互补的优势,例如提供更精细的空间信息的高空间分辨率数据和具有高度信息的激光雷达LiDAR(Light Detection and Ranging)数据.通过将高光谱数据与多源遥感数据进行融合,可以弥补高光谱数据空间分辨率相对较低,空间特... 相似文献
Although a number of studies of the variation of soil transport with increase in slope angle have appeared, few include an information on the interaction of sheetwash and rainsplash on high slope angles, which is necessary to test Horton's proposed polynomial relationship. Virtually no studies are available which compare the influence of changes in soil type or antecedent moisture on established relationships. This paper reports the testing of eight soils from Alberta, Canada, under simulated rainfall on ten slopes from 3° to 30°. Material eroded was separated into that transported by rainsplash and that by sheetwash. In general, it was found that the influence of changes in slope angle on soil transport is best described by polynomial relationships, but these are shown to vary considerably between rainspash and sheetwash, between different soil types and for different antecedent moisture conditions. Despite careful control of all factors other than slope angle very high variability of results was experienced. Causes of variability are examined and the need for evaluation of the effect of test plot size on variability of results is suggested. 相似文献
The remote mapping of minerals and discrimination of ore and waste on surfaces are important tasks for geological applications such as those in mining. Such tasks have become possible using ground-based, close-range hyperspectral sensors which can remotely measure the reflectance properties of the environment with high spatial and spectral resolution. However, autonomous mapping of mineral spectra measured on an open-cut mine face remains a challenging problem due to the subtleness of differences in spectral absorption features between mineral and rock classes as well as variability in the illumination of the scene. An additional layer of difficulty arises when there is no annotated data available to train a supervised learning algorithm. A pipeline for unsupervised mapping of spectra on a mine face is proposed which draws from several recent advances in the hyperspectral machine learning literature. The proposed pipeline brings together unsupervised and self-supervised algorithms in a unified system to map minerals on a mine face without the need for human-annotated training data. The pipeline is evaluated with a hyperspectral image dataset of an open-cut mine face comprising mineral ore martite and non-mineralised shale. The combined system is shown to produce a superior map to its constituent algorithms, and the consistency of its mapping capability is demonstrated using data acquired at two different times of day. 相似文献