4.8 Article

Stereoselective Total Syntheses of C18-Oxo Eburnamine-Vincamine Alkaloids

期刊

ORGANIC LETTERS
卷 24, 期 12, 页码 2409-2413

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.orglett.2c00661

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资金

  1. National Natural Science Foundation of China [U21A20278]
  2. Sichuan Science and Technology Program [2021YJ0221]

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This study examines the Risk of Tendency to Desertification Index (RTDI) in a semiarid region of Brazil by analyzing a series of soil and vegetation spectral indexes, climate indexes, and human impact. The study aims to validate and adapt the RTDI methodology, considering a temporal analysis from 1995 to 2015. The results show that the RTDI, with quartile interval class distribution during the dry period and using the SAVI parameter L=1, performs better in identifying areas susceptible to desertification. The study highlights the importance of soil and vegetation parameters in classifying the level of the risk of tendency to desertification.
This is study is of the Risk of Tendency to Desertification Index (RTDI). It comprises a group of soil and vegetation spectral indexes, climate indexes and human impact to identify the degree of desertification of a semiarid region of Brazil. This study the goal is to examine, validate and adapt the RTDI methodology in the considering a temporal analysis between the years of 1995 and 2015 taking into account the seasonality. The RTDI was also tested according to the class distribution range, using equal and quartile intervals, considering the variation of the SAVI L parameter (0.8, 0.9 and 1). In addition to that, the results of the collected field data were validated including the verification and categorization of the desertification degree according to experienced professionals. It was done comparative analysis pixel / point by performance indexes, identifying areas that are susceptible to desertification, according to the field survey and the estimates obtained the RTDI. The application of the RTDI with quartile interval class distribution, during the dry period and using the SAVI parameter L =1, presented better performance than the other method variations. The applied indexes driving force estimates showed that the parameters related to the soil and vegetation were decisive in terms of the classification level of the risk of tendency to desertification.

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