基于变化矢量分析的土地利用变化检测方法研究
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摘要
土地利用变化检测既是全球变化研究的重要内容，又是资源可持续利用中进行科学决策和管理的重要依据。利用遥感技术进行土地利用变化检测是获取土地利用变化信息最经济有效的方式。因此，基于遥感技术的土地利用变化检测方法研究，一直是遥感应用研究的重要方面。本文采用TM、ASTER等多种数据源，研究了基于变化矢量分析的土地利用变化检测方法。
本文综合运用了遥感、地理信息系统、数字图像处理、模式识别、人工智能，以及数值分析、数理统计等多学科知识，针对变化检测技术的几个关键问题，包括多时相遥感影像相对辐射校正，分类特征提取及分类方法确定，基于CVA的变化检测方法，分类精度评价方法等，从理论、方法、试验等多方面进行了研究，并利用研究成果，对华北平原的试验区做了地物类型变化的检测。
本文主要有如下四个创新性研究成果：
1、提出一种基于特征角点的多时相遥感影像相对辐射校正算法。
该算法通过提取特征角点并自动匹配同名点来选取稳定地物点。首先在基准影像中采用特征提取方法，自动提取出梯度变化较大的角点，然后采用动态模板匹配法，在待处理影像中确定匹配控制点。由于筛选出的控制点对都有很高的相关性，它们的反射率都是较为稳定的，可以用于相对辐射校正。该算法的好处之一在于可以广泛选取稳定地物点，除了暗目标和亮目标之外，很多中间DN值的稳定地物点都可用于相对辐射正，提高了校正精度：好处之二是由于采取自动选取稳定地物点的方法，因此该算法的自动化程度较高。通过试验证明，该方法有较高的校正精度，经过相对辐射校正后的影像的RMSE有明显降低，并且具有较好的目视效果。
2、采用主成分变换、K—T变换等方法，从原始数据中提取了15种分类特征，其样本分离性要明显好于原始数据。通过试验证明，采用15种分类特征进行分类的精度，比原始数据的分类精度有较大的提高。
3、提出一种基于直方图曲率的CVA变化检测算法。
本文提出采用变化强度和相关系数双阈值进行图像二值分割的策略，提出通过变化强度直方图和相关系数直方图的曲率来确定二值图像分割阈值的范围，明确指出变化强度的最佳阈值是介于其直方图的频率峰值和最大曲率所对应的变
Land use change detection is an important aspect of global change research, and it plays an important role in resource sustainable utilization. Land use change detection by Remote Sensing technology is the most economical and efficient way to obtain land use change information. Therefore, researches on land use change detection methods based on Remote Sensing technology are important aspects of Remote Sensing applicable research.
The purpose of the research presented on this dissertation is to explore modified methodologies for extracting land use change information based on change vector analysis method. Multifarious knowledges, such as Remote Sensing technology, Geographical Information System, digital image processing technology, pattern recognition , artificial intelligence, numerical analysis, and statistics are integraed in this research. High spatial resolution data, such as TM, ETM+, and ASTER data, are utilized in our research. The main original reseach results are as follows:
First, an algorithm of relative radiometric nornalization technique based on feature corner was developed. With a new feature corner detection adaptive algorithm based on gray gradient and a new control point matching algorithm based on unequidistant dynamic template being developed, The algorithm could select stable ground points by extracting feature corners and matching homonymous ground points automatically. The first virtue of the algorithm is that it can select stable ground points widely instead of the limitation of bright object or dark object. The second virtue of
本文综合运用了遥感、地理信息系统、数字图像处理、模式识别、人工智能，以及数值分析、数理统计等多学科知识，针对变化检测技术的几个关键问题，包括多时相遥感影像相对辐射校正，分类特征提取及分类方法确定，基于CVA的变化检测方法，分类精度评价方法等，从理论、方法、试验等多方面进行了研究，并利用研究成果，对华北平原的试验区做了地物类型变化的检测。
本文主要有如下四个创新性研究成果：
1、提出一种基于特征角点的多时相遥感影像相对辐射校正算法。
该算法通过提取特征角点并自动匹配同名点来选取稳定地物点。首先在基准影像中采用特征提取方法，自动提取出梯度变化较大的角点，然后采用动态模板匹配法，在待处理影像中确定匹配控制点。由于筛选出的控制点对都有很高的相关性，它们的反射率都是较为稳定的，可以用于相对辐射校正。该算法的好处之一在于可以广泛选取稳定地物点，除了暗目标和亮目标之外，很多中间DN值的稳定地物点都可用于相对辐射正，提高了校正精度：好处之二是由于采取自动选取稳定地物点的方法，因此该算法的自动化程度较高。通过试验证明，该方法有较高的校正精度，经过相对辐射校正后的影像的RMSE有明显降低，并且具有较好的目视效果。
2、采用主成分变换、K—T变换等方法，从原始数据中提取了15种分类特征，其样本分离性要明显好于原始数据。通过试验证明，采用15种分类特征进行分类的精度，比原始数据的分类精度有较大的提高。
3、提出一种基于直方图曲率的CVA变化检测算法。
本文提出采用变化强度和相关系数双阈值进行图像二值分割的策略，提出通过变化强度直方图和相关系数直方图的曲率来确定二值图像分割阈值的范围，明确指出变化强度的最佳阈值是介于其直方图的频率峰值和最大曲率所对应的变
Land use change detection is an important aspect of global change research, and it plays an important role in resource sustainable utilization. Land use change detection by Remote Sensing technology is the most economical and efficient way to obtain land use change information. Therefore, researches on land use change detection methods based on Remote Sensing technology are important aspects of Remote Sensing applicable research.
The purpose of the research presented on this dissertation is to explore modified methodologies for extracting land use change information based on change vector analysis method. Multifarious knowledges, such as Remote Sensing technology, Geographical Information System, digital image processing technology, pattern recognition , artificial intelligence, numerical analysis, and statistics are integraed in this research. High spatial resolution data, such as TM, ETM+, and ASTER data, are utilized in our research. The main original reseach results are as follows:
First, an algorithm of relative radiometric nornalization technique based on feature corner was developed. With a new feature corner detection adaptive algorithm based on gray gradient and a new control point matching algorithm based on unequidistant dynamic template being developed, The algorithm could select stable ground points by extracting feature corners and matching homonymous ground points automatically. The first virtue of the algorithm is that it can select stable ground points widely instead of the limitation of bright object or dark object. The second virtue of
引文
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