vegetation continuous The scale-location specific control on distribution was investigated through wavelet transforms approaches in subtropical mountain-hill region, Fujian, China. The Normalized Difference Vegetatio...vegetation continuous The scale-location specific control on distribution was investigated through wavelet transforms approaches in subtropical mountain-hill region, Fujian, China. The Normalized Difference Vegetation Index （NDVI） was calculated as an indicator of vegetation greenness using Chinese Environmental Disaster Reduction Satellite images along latitudinal and longitudinal transects. Four scales of variations were identified from the local wavelet spectrum of NDVI, with much stronger wavelet variances observed at larger scales. The characteristic scale of vegetation distribution within mountainous and hilly regions in Southeast China was around 20 km. Significantly strong wavelet coherency was generally examined in regions with very diverse topography, typically characterized as small mountains and hills fractured by rivers and residents. The continuous wavelet based approaches provided valuable insight on the hierarchical structure and its corresponding characteristic scales of ecosystems, which might be applied in defining proper levels in multilevel models and optimal bandwidths in Geographically Weighted Regression.展开更多
The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components o...The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first,and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next,the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.展开更多
基金supported by the National Natural Science Foundation of China(NSFC)(Grant No.41071267)Scientific Research Foundation for Returned Scholars,Ministry of Education of China(Grant No.[2012]940)the Science & Technology Department of Fujian Province,China(Grant Nos.2012I0005,2012J01167)
文摘vegetation continuous The scale-location specific control on distribution was investigated through wavelet transforms approaches in subtropical mountain-hill region, Fujian, China. The Normalized Difference Vegetation Index （NDVI） was calculated as an indicator of vegetation greenness using Chinese Environmental Disaster Reduction Satellite images along latitudinal and longitudinal transects. Four scales of variations were identified from the local wavelet spectrum of NDVI, with much stronger wavelet variances observed at larger scales. The characteristic scale of vegetation distribution within mountainous and hilly regions in Southeast China was around 20 km. Significantly strong wavelet coherency was generally examined in regions with very diverse topography, typically characterized as small mountains and hills fractured by rivers and residents. The continuous wavelet based approaches provided valuable insight on the hierarchical structure and its corresponding characteristic scales of ecosystems, which might be applied in defining proper levels in multilevel models and optimal bandwidths in Geographically Weighted Regression.
基金supported by National Natural Science Foundation of China(Grant Nos.611711226120131861471019)
文摘The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first,and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next,the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.
