论文部分内容阅读
在合理的大气物理假设前提下，本文通过对遥感方程的推导，论证了遥感传感器各通道接收的亮度Ｒｉｊ与地物的反射亮度Ｗｉｊ呈线性相关。依据这一地空波谱数据的相关关系，笔者在对典型铜多金属矿床的野外波谱实测基础上，经与ＴＭ遥感数据进行相关分析，建立了典型矿床的地面波谱反射率数据与ＴＭ图像最佳波段数据的相关模型，并据这些相关模型，将ＴＭ图像反演成与矿床地面波谱有关的地空相关图像，同时建立了矿床光谱识别模型，并据其进行了计算机图像矿床光谱异常识别。ＴＭ数据的地空相关性研究的应用结果表明，矿床的地面波谱研究及其与遥感ＴＭ数据的相关分析方法在成矿预测、找矿靶区定位中应用效果颇佳，是多金属矿产信息提取值得借鉴的方法。
On the premise of reasonable atmospheric physics assumption, this paper demonstrates that the brightness Rij received by each channel of the remote sensing sensor is linearly correlated with the reflection brightness Wij of the object by deducing the remote sensing equation. Based on the correlation of the ground-air spectral data, based on the field measurements of the typical copper polymetallic deposits, the author established the correlation between TM data and TM data, and established the best spectral reflectance data and TM images According to these correlation models, the TM images are inverted into the ground-space related images related to the ground surface spectra of the deposit. At the same time, the spectral recognition model of the deposit is established, and the spectral anomalies of the computer image deposits are identified. The results of ground-air correlation study of TM data show that the ground-based spectral study of the deposit and its correlation analysis with remote sensing TM data are quite effective in locating ore-forming prediction and prospecting targets and are good candidates for information extraction of polymetallic minerals Worth learning method.