With the rapid development of remote sensing technology, remotely sensed data are playing more and more significant role in many fields, such as urban planning, geoscience, digital earth etc.
随着遥感技术的飞速发展，遥感数据成为城市规划、地球科学研究、数字地球等重大科学研究和工程建设的重要数据源。
Uncertainty in the classified remotely sensed data is one of the most important elements of the data quality.
不确定性是评价分类专题类别数据质量最主要的方面。
Meteorological data are spatially interpolated to attain the spatial resolution matching remotely sensed data.
对气象数据进行空间插值以获取与遥感数据一致的空间分辨率。
Stratification is one of the key techniques in stratified sampling investigation and monitoring using remotely sensed data.
分层技术是遥感分层抽样调查与监测方法中的关键技术之一。
The generalized model characterizing most remotely sensed data pixel-level fusion techniques is very important for theory analysis and application.
研究遥感数据像素级融合统一模型及相应的实现技术具有重要的理论和应用价值。
This paper conveys the application of genetic algorithms (GA) which are used to improve unsupervised training and thereby increase the classification accuracy of remotely sensed data.
本文将遗传算法(GA)应用于非监督训练，提高了遥感数据的分类精度。
The invention relates to a supervised classification method of multi-class hyperspectrum remotely sensed data, which comprises the following steps: (1), reading the hyperspectrum data;
一种高光谱遥感数据多类别监督分类方法，包含以下步骤：（1）读入 高光谱数据；
The invention relates to a supervised classification method of multi-class hyperspectrum remotely sensed data, which comprises the following steps: (1), reading the hyperspectrum data;
一种高光谱遥感数据多类别监督分类方法，包含以下步骤：（1）读入 高光谱数据；
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