Contrastive analysis of extraction of Polygonatum cyrtonema planting area based on data of "Resource 3" / 中国中药杂志

Polygonatum cyrtonema is a famous bulk medicinal material which is the medicinal and edible homologous. With the implementation of the traditional Chinese medicine industry to promote precise poverty alleviation, the planting area of P. cyrtonema in Jinzhai is becoming larger and larger in recent years. Jinzhai is located in the Dabie Mountainous area, which is the largest mountain area and county in Anhui Province. The cultivation of P. cyrtonema is scattered, and the traditional Chinese medicine resources investigation is not only inefficient and accurate. In this study,the "Resource 3"(ZY-3) remote sensing image was used as the best observation phase,and the method of support vector machine classification was used. The method of parallelepiped, minimum distance, mahalanob is distance, maximum likelihood classification and neural net were used to classify and recognize the P. cyrtonema in the whole region. In order to determine the accuracy and reliability of classification results, the accuracy of six supervised classification results was evaluated by confusion matrix method, and the advantages and disadvantages of six supervised classification methods for extracting P. cyrtonema field planting area were compared and analyzed. The results showed that the method of support vector machine classification was more appropriate than that using other classification methods. It provides a scientific basis for monitoring the planting area of P. cyrtonemain field.

Bletilla striata planting area in Ningshan county extraction based on multi-temporal remote sensing images / 中国中药杂志

Traditional Chinese medicine is planted in mountainous areas with suitable natural conditions. The planting area is complex in terrain,and the planting plots are mostly irregularly shaped. It is difficult to accurately calculate the planting area by traditional survey methods. The method of extracting Chinese herbal medicine planting area combined with remote sensing and GIS technology is of great significance for the rational development and utilization of traditional Chinese medicine resources. Taking Bletilla striata planting in Ningshan county of Shaanxi province as an example,the extraction method of planting area of traditional Chinese medicine in county was studied. High-resolution ZY-3 and GF-1 multi-spectral multi-temporal remote sensing images were used as data sources. Through field sampling,samples such as B. striata,cultivated land,forest land,water body,artificial surface,alpine meadow,etc. are collected. The spectral features,texture features and shape features of remotely identifiable objects in different planting areas and cultivated land,vegetable sheds were analyzed,confusing ground objects were eliminated and interpretation marks were establish. The method of visual interpretation is used to realize the extraction of B. striata planting areas,and the B. striata planting area are calculated by combining GIS technology. The results showed that the method of visual interpretation,using high-resolution ZY-3 and GF-1 multi-spectral multi-temporal remote sensing image data extracted the planting area of 403.05 mu. It can effectively extract the B. striata planting area in research region.

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.

Monitoring of Saposhnikovia divaricate planting area based on texture and pop information in Naiman banner / 中国中药杂志

The planting area of Chinese medicinal materials is an important basis for formulating policies such as production and poverty alleviation of Chinese medicinal materials and is determining the quantity of medicinal materials trade. Accurately mastering the information of the distribution,area and yield of Chinese medicinal materials cultivation is the basis of the adjustment of the planting structure of traditional Chinese medicine. It is now the largest planting place of Mongolian traditional Chinese medicinal materials in Naiman banner that is belonging to Tongliao city,Inner Mongolia. It is of great significance to obtain the planting area of Mongolian Chinese medicinal materials in Naiman banner in time and effectively for the development of subsequent industries. In this study,Saposhnikovia divaricata,a medicinal plant planted in Naiman banner,was selected as an example,and the fusion 2 m resolution ZY-3 remote sensing image was used as the data source. Based on the ground survey data,the sample data of each typical ground object were selected,and the spectral characteristic curves of different ground objects were obtained,and the S. divaricata spectral information was obtained. Using the filtering texture analysis method based on probability statistics,five kinds of texture image display results under different texture filtering were compared and analyzed,and finally the S. divaricata texture features based on information entropy are determined. The distribution range and planting area of S. divaricata in Naiman banner were extracted and interpreted by using the texture and spectral information of remote sensing images. The results showed that: S. divaricata was mainly distributed in the northeast and central south of Naiman banner,and the planting area was 5 336 mu( 1 mu≈667 m2). The field verification data were in good agreement with the remote sensing interpretation results,and the difference was small. It shows that the combination of spectral information and texture information can realize the discrimination of S. divaricata,and the interpretation results can provide a reference for the county to formulate the poverty alleviation action of Chinese medicinal material industry and the economic development plan of agricultural producing areas.

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.

Application of Remote Sensing Technology in Investigating Planting Area of Paeoniaceae suffruticosa in Shicheng County of Jiangxi Province / 中国药房

OBJECTIVE： To provide reference for the development and sustainable utilization of TCM industry with regional characteristics. METHODS： Taking Shicheng county of Jiangxi province as an example， field investigation was carried out on Paeoniaceae suffruticosa planting base in the county， a few representative P. suffruticosa planting bases in the county were selected as sample points， and GPS was used to locate and record the location information of sample points. The remote sensing image was automatically extracted by computer， the artificial visual interpretation method was used to get P. suffruticosa planting area image. Then combined with the field inspection verification， P. suffruticosa planting area was obtained， and the investigation results were analyzed. RESULTS： Through remote sensing interpretation of the planting area of P. suffruticosa in Shicheng county， it was obtained that the total planting area of P. suffruticosa in Shicheng county was 42 597 951.505 square meters （63 864.995 mu） in 2018， accounting for about 33％ of the cultivated land area， which was 42.12％ higher than the conventional planting area of 44 936 mu in 2013. The distribution of P. suffruticosa planting in Shicheng county was mainly concentrated in Xiaosong town and Fengshan town in the north， and Daqu town and Pingshan town in the south. CONCLUSIONS： Remote sensing technology has the advantages of fast data acquisition， large amount of information， high accuracy and strong timeliness， which greatly avoids the complexity of work， saves a lot of manpower and material resources. The technology can provide technology support for obtaining the regional planting area and distribution information of TCM such as P. suffruticosa， dynamic monitoring， scientific warning of the market status of TCM， and guiding the large-scale， standardized and intensive development of TCM cultivation.

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.