Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This stud...Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.展开更多
外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最...外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最小均方(Least Mean Square,LMS)对消算法。首先利用模糊函数估计杂波的频率和时延分布,构建含频率信息的多个参考信号。再把多个参考信号插入LMS算法中推导了扩展LMS算法,利用扩展LMS算法可以同时对消静、动杂波。扩展LMS算法能降低对消剩余,提高目标的信噪比,仿真分析和实测数据处理验证了算法的有效性。展开更多
基金supported by the Knowledge Innovation Program of Chinese Academy of Sciences(No.KZCX2-YWJC402)the Hundred Talents Program of Chinese Academy of Sciences(No.A0815)+1 种基金the National Natural Science Foundation of China(No.41371474)supported by the Chinese Academy of Sciences Visiting Professorships for Senior International Scientists in 2011(No.2011T2Z18)
文摘Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.
文摘外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最小均方(Least Mean Square,LMS)对消算法。首先利用模糊函数估计杂波的频率和时延分布,构建含频率信息的多个参考信号。再把多个参考信号插入LMS算法中推导了扩展LMS算法,利用扩展LMS算法可以同时对消静、动杂波。扩展LMS算法能降低对消剩余,提高目标的信噪比,仿真分析和实测数据处理验证了算法的有效性。
