Research on extraction of Zizyphus jujuba planting area in Jia county of Shaanxi / 中国中药杂志

With digital satellite remote sensing image data of GF-1,in 2018 the object-oriented classification method was used to extract Zizyphus jujuba planting area in Jia county of Shaanxi province. The results showed that the remote sensing classification method based on rule set could extract and reckon Z. jujube planting area in the study area effectively. The planting area of Z. jujube in Jia county was about 5. 34×104 hm2 and the area of consistent accuracy was 97. 92%. The method used in this study could provide a technical reference for the area extraction of the same type of medicinal materials. And it is of great significance to provide decision support for the protection and utilization of Z. jujube resources.

Extracting Paeonia lactiflora planted area in Dangshan of Anhui province based on ZY-3 remote sensing image / 中国中药杂志

In order to comprehensively monitor the dynamic change of Paeonia lactiflora planting area,the investigation of P. lactiflora planting area in Dangshan was carried out. It can provide reference for the planting detection of P. lactiflora in Huaibei Plain.Based on remote sensing technology,this paper extracts the planting area of P. lactiflora in Dangshan in 2018 by using the minimum distance method,maximum likelihood method,parallel hexahedron method and Mahalanobis distance method,using the remote sensing image of ZY-3 Satellite as the data source,and makes a comparative analysis with the results. The results show that the maximum likelihood method is better than the other three methods. This method can provide reference for remote sensing monitoring of P. lactiflora planting area in China.

Study of extracting natural resources of Chinese medicinal materials planted area in Luoning of Henan province based on UAV of low altitude remote sensing technology and remote sensing image of satellite / 中国中药杂志

The study is aimed to effectively obtain the planting area of traditional Chinese medicine resources. The herbs used as the material for traditional Chinese medicine are mostly planted in natural environment suitable mountainous areas. The UAV low altitude remote sensing data were used as the samples and the GF-2 remote sensing images were applied for the data source to extract the planting area of Salvia miltiorrhiza and Artemisia argyi in Luoning county combined with field investigation. Remote sensing satellite data of standard processing obtain specific remote sensing data coverage. The UAV data were pre-processed to visually interpret the species and distribution of traditional Chinese medicine resources in the sample quadrat. Support vector machine( SVM) was used to classify and estimate the area of traditional Chinese medicine resources in Luoning county,confusion matrix was used to determine the accuracy of spatial distribution of traditional Chinese medicine resources. The result showed that the application of UAV of low altitude remote sensing technology and remote sensing image of satellite in the extraction of S. miltiorrhiza and other varieties planting area was feasible,it also provides a scientific reference for poverty alleviation policies of the traditional Chinese medicine Industry in local areas.Meanwhile,research on remote sensing classification of Chinese medicinal materials based on multi-source and multi-phase high-resolution remote sensing images is actively carried out to explore more effective methods for information extraction of Chinese medicinal materials.

Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model / 中国中药杂志

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level.

Study of extracting Peucedanum praeruptorum planted area in Ningguo of Anhui province based on multi-source and multi-phase image / 中国中药杂志

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Peucedanum praeruptorum planted area in Ningguo prefecture of Anhui province as an example, the multispectral remote sensing images that include Landsat-8 with a 30 m resolution and China-made GF-1 with a 16 m resolution were used as data source. Since the spectral characteristics of P. praeruptorum in the two periods are different from those of other crops, the changes of the images at two stages in the same year could be used to extract the P. praeruptorum planted area intercropped in cultivated land. Then the texture and spectral characteristics of young pecan trees were used to extract the P. praeruptorum planted area intercropped in woodland. The results showed that the extracted area of planted P. praeruptorum with the original imagery of 30 m spatial resolution and 16 m spatial resolution was 25 635.43,24 585.43 mu, respectively.