Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas ...Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas synthetic aperture radar(SAR)imagery is sensitive to changes in growth states and morphological structures.Crop-type mapping with a single type of imagery sometimes has unsatisfactory precision,so providing precise spatiotemporal information on crop type at a local scale for agricultural applications is difficult.To explore the abilities of combining optical and SAR images and to solve the problem of inaccurate spatial information for land parcels,a new method is proposed in this paper to improve crop-type identification accuracy.Multifeatures were derived from the full polarimetric SAR data(GaoFen-3)and a high-resolution optical image(GaoFen-2),and the farmland parcels used as the basic for object-oriented classification were obtained from the GaoFen-2 image using optimal scale segmentation.A novel feature subset selection method based on within-class aggregation and between-class scatter(WA-BS)is proposed to extract the optimal feature subset.Finally,crop-type mapping was produced by a support vector machine(SVM)classifier.The results showed that the proposed method achieved good classification results with an overall accuracy of 89.50%,which is better than the crop classification results derived from SAR-based segmentation.Compared with the ReliefF,mRMR and LeastC feature selection algorithms,the WA-BS algorithm can effectively remove redundant features that are strongly correlated and obtain a high classification accuracy via the obtained optimal feature subset.This study shows that the accuracy of crop-type mapping in an area with multiple cropping patterns can be improved by the combination of optical and SAR remote sensing images.展开更多
The surface and internal structure difference of yellow and black dormant chlamydospores of Ustilaginoidea virens on mid-and late-season rice were examined by scanning electron microscopy(SEM) and transmission electro...The surface and internal structure difference of yellow and black dormant chlamydospores of Ustilaginoidea virens on mid-and late-season rice were examined by scanning electron microscopy(SEM) and transmission electron microscopy(TEM).SEM revealed that the spherical yellow and black chlamydospores had prominent spines,with the diameters from 3 to 6 μm and 4 to 6 μm,respectively.The spines were 200-700 nm and 400-1 100 nm long in yellow and black chlamydospores,respectively.Variance analysis showed that there was no difference in diameter of the yellow chlamydospores but significant difference among the black ones collected from both rice cropping types.Similarly,there was no difference in length of the spines on the same color chlamydospores but extremely different between the yellow and black chlamydospores collected from the two cropping types.TEM revealed that the cell wall of both color chlamydospores were composed of two layers,the thick endosporium and thin exosporium,and the thickness of the former layer of the black chlamydospores was nearly two times as that of the yellow ones.The organelles in yellow chlamydospores such as the nucleus were obviously visible,but invisible in black ones.The cytoplasm of black chlamydospores was occupied by a big lipid globule.This study suggests that the formation of dormant chlamydospores of U.virens is related with the structural changes in the cell.展开更多
基金The authors acknowledge that this study was financially supported by the National Key R&D Programs of China(No.2017YFB0504201)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA20020101)+1 种基金and the Natural Science Foundation of China(No.61473286 and No.61375002)Our sincere thanks go to the students at the State Key Laboratory of Remote Sensing Science for their assistance during the field survey campaigns.
文摘Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas synthetic aperture radar(SAR)imagery is sensitive to changes in growth states and morphological structures.Crop-type mapping with a single type of imagery sometimes has unsatisfactory precision,so providing precise spatiotemporal information on crop type at a local scale for agricultural applications is difficult.To explore the abilities of combining optical and SAR images and to solve the problem of inaccurate spatial information for land parcels,a new method is proposed in this paper to improve crop-type identification accuracy.Multifeatures were derived from the full polarimetric SAR data(GaoFen-3)and a high-resolution optical image(GaoFen-2),and the farmland parcels used as the basic for object-oriented classification were obtained from the GaoFen-2 image using optimal scale segmentation.A novel feature subset selection method based on within-class aggregation and between-class scatter(WA-BS)is proposed to extract the optimal feature subset.Finally,crop-type mapping was produced by a support vector machine(SVM)classifier.The results showed that the proposed method achieved good classification results with an overall accuracy of 89.50%,which is better than the crop classification results derived from SAR-based segmentation.Compared with the ReliefF,mRMR and LeastC feature selection algorithms,the WA-BS algorithm can effectively remove redundant features that are strongly correlated and obtain a high classification accuracy via the obtained optimal feature subset.This study shows that the accuracy of crop-type mapping in an area with multiple cropping patterns can be improved by the combination of optical and SAR remote sensing images.
文摘The surface and internal structure difference of yellow and black dormant chlamydospores of Ustilaginoidea virens on mid-and late-season rice were examined by scanning electron microscopy(SEM) and transmission electron microscopy(TEM).SEM revealed that the spherical yellow and black chlamydospores had prominent spines,with the diameters from 3 to 6 μm and 4 to 6 μm,respectively.The spines were 200-700 nm and 400-1 100 nm long in yellow and black chlamydospores,respectively.Variance analysis showed that there was no difference in diameter of the yellow chlamydospores but significant difference among the black ones collected from both rice cropping types.Similarly,there was no difference in length of the spines on the same color chlamydospores but extremely different between the yellow and black chlamydospores collected from the two cropping types.TEM revealed that the cell wall of both color chlamydospores were composed of two layers,the thick endosporium and thin exosporium,and the thickness of the former layer of the black chlamydospores was nearly two times as that of the yellow ones.The organelles in yellow chlamydospores such as the nucleus were obviously visible,but invisible in black ones.The cytoplasm of black chlamydospores was occupied by a big lipid globule.This study suggests that the formation of dormant chlamydospores of U.virens is related with the structural changes in the cell.
