The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utili...The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utilize 3D physical seismic modeling experiments. A 3D channel sand body physical seismic model is constructed and two acquisition systems are designed with wide azimuth （16 lines） and narrow azimuth （8 lines） to model 3D seismic data acquisition and processing seismic work flows. From analysis of migrated time slice data with high quality and small size, we conclude that when the overlying layers are smooth and lateral velocities have little change, both wide and narrow azimuth observation systems in 3D acquisition can be used for obtaining high precision imaging and equivalent resolution of the channel sand body.展开更多
Based on the 16d-composite MODIS （moderate resolution imaging spectroradiometer）-NDVI（normalized difference vegetation index） time-series data in 2004, vegetation in North Tibet Plateau was classified and seasonal...Based on the 16d-composite MODIS （moderate resolution imaging spectroradiometer）-NDVI（normalized difference vegetation index） time-series data in 2004, vegetation in North Tibet Plateau was classified and seasonal variations on the pixels selected from different vegetation type were analyzed. The Savitzky-Golay filtering algorithm was applied to perform a filtration processing for MODIS-NDVI time-series data. The processed time-series curves can reflect a real variation trend of vegetation growth. The NDVI time-series curves of coniferous forest, high-cold meadow, high-cold meadow steppe and high-cold steppe all appear a mono-peak model during vegetation growth with the maximum peak occurring in August. A decision-tree classification model was established according to either NDVI time-series data or land surface temperature data. And then, both classifying and processing for vegetations were carried out through the model based on NDVI time-series curves. An accuracy test illustrates that classification results are of high accuracy and credibility and the model is conducive for studying a climate variation and estimating a vegetation production at regional even global scale.展开更多
基金supported by the National Basic Research Program (the 973 Program, No. 2007CB209601).
文摘The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utilize 3D physical seismic modeling experiments. A 3D channel sand body physical seismic model is constructed and two acquisition systems are designed with wide azimuth （16 lines） and narrow azimuth （8 lines） to model 3D seismic data acquisition and processing seismic work flows. From analysis of migrated time slice data with high quality and small size, we conclude that when the overlying layers are smooth and lateral velocities have little change, both wide and narrow azimuth observation systems in 3D acquisition can be used for obtaining high precision imaging and equivalent resolution of the channel sand body.
基金the Frontier Program of the Knowledge Innovation Program of Chinese Academy of Sciences
文摘Based on the 16d-composite MODIS （moderate resolution imaging spectroradiometer）-NDVI（normalized difference vegetation index） time-series data in 2004, vegetation in North Tibet Plateau was classified and seasonal variations on the pixels selected from different vegetation type were analyzed. The Savitzky-Golay filtering algorithm was applied to perform a filtration processing for MODIS-NDVI time-series data. The processed time-series curves can reflect a real variation trend of vegetation growth. The NDVI time-series curves of coniferous forest, high-cold meadow, high-cold meadow steppe and high-cold steppe all appear a mono-peak model during vegetation growth with the maximum peak occurring in August. A decision-tree classification model was established according to either NDVI time-series data or land surface temperature data. And then, both classifying and processing for vegetations were carried out through the model based on NDVI time-series curves. An accuracy test illustrates that classification results are of high accuracy and credibility and the model is conducive for studying a climate variation and estimating a vegetation production at regional even global scale.
基金This work was supported by the Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20190027)Youth Innovation Promotion Association,Chinese Academy of Science(No.2021255)+2 种基金Shandong Energy Research Institute Enterprise Joint Fund(SE1 U202312)"Strategic Priority Research Program"of the Chinese Academy of Sciences(No.XDA02020000)the National Natural Science Foundation of China(No.22273065).
