3-nonadecylphenol | 112128-81-1

• 分子结构分类: 有机化合物 - 苯类化合物 - 酚类
• 英文名称: 3-nonadecylphenol
• 英文别名: 3-Nonadecylphenol
• CAS: 112128-81-1
• 化学式: C₂₅H₄₄O
• 分子量: 360.624
• InChiKey: CVAJGZCZYKYYFH-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  11.6
• 重原子数：
  26
• 可旋转键数：
  18
• 环数：
  1.0
• sp3杂化的碳原子比例：
  0.76
• 拓扑面积：
  20.2
• 氢给体数：
  1
• 氢受体数：
  1

反应信息

• 作为反应物：
  描述：

  3-nonadecylphenol 在 丙酮 、 碘甲烷 作用下， 生成 Coc=1C=C(C=CC=1)ccccccccccccccccccc
  参考文献：
  名称：

  Forest fire analysis with remote sensing data

  摘要：

  Forest fires cause major damage to the environment, human health and property, and endanger life. Fires can be monitored and analysed over large areas in a timely and cost-effective manner by using satellite sensor imagery in combination with spatial analysis as provided by Geographical Information Systems (GIS). In this study, the forest area damage caused by a large fire which occurred in the Marmaris, province of Mugla in July 1996 was analysed using satellite sensor images. Digital image processing methods, such as spectral profile analysis, vegetation indices and multispectral classification, were applied to the satellite sensor images acquired before and after the forest fire. Besides the conventional maximum likelihood classification algorithm, a multilayer feed-forward neural network architecture was also used for comparison and evaluation of its effectiveness. A GIS database was constructed from the raster (satellite sensor data), vector (the forest type and topographical maps) and ancillary data (meteorological data). The GIS is being used to develop an information and decision support system to monitor and predict forest fire activity, and to enhance fire management efficiency. This study highlights the deficiencies in the current approach to fire management and emphasizes the need for an improved method along the lines outlined.

  DOI：

  10.1080/01431160118510
• 作为产物：
  描述：

  1-(3-hydroxy-phenyl)-nonadecan-2-one 在 diethylene glycol monosodium salt 、 肼 、 二乙二醇 作用下， 生成 3-nonadecylphenol
  参考文献：
  名称：

  Forest fire analysis with remote sensing data

  摘要：

  Forest fires cause major damage to the environment, human health and property, and endanger life. Fires can be monitored and analysed over large areas in a timely and cost-effective manner by using satellite sensor imagery in combination with spatial analysis as provided by Geographical Information Systems (GIS). In this study, the forest area damage caused by a large fire which occurred in the Marmaris, province of Mugla in July 1996 was analysed using satellite sensor images. Digital image processing methods, such as spectral profile analysis, vegetation indices and multispectral classification, were applied to the satellite sensor images acquired before and after the forest fire. Besides the conventional maximum likelihood classification algorithm, a multilayer feed-forward neural network architecture was also used for comparison and evaluation of its effectiveness. A GIS database was constructed from the raster (satellite sensor data), vector (the forest type and topographical maps) and ancillary data (meteorological data). The GIS is being used to develop an information and decision support system to monitor and predict forest fire activity, and to enhance fire management efficiency. This study highlights the deficiencies in the current approach to fire management and emphasizes the need for an improved method along the lines outlined.

  DOI：

  10.1080/01431160118510

文献信息

• Hierarchical Self-Assembly of Symmetric Supramolecular Double-Comb Diblock Copolymers: a Comb Density Study
  作者：Anton H. Hofman、Mehedi Reza、Janne Ruokolainen、Gerrit ten Brinke、Katja Loos

  DOI：10.1021/ma501257x

  日期：2014.9.9
• Forest fire analysis with remote sensing data
  作者：F. Sunar、C. Özkan

  DOI：10.1080/01431160118510

  日期：2001.1

  Forest fires cause major damage to the environment, human health and property, and endanger life. Fires can be monitored and analysed over large areas in a timely and cost-effective manner by using satellite sensor imagery in combination with spatial analysis as provided by Geographical Information Systems (GIS). In this study, the forest area damage caused by a large fire which occurred in the Marmaris, province of Mugla in July 1996 was analysed using satellite sensor images. Digital image processing methods, such as spectral profile analysis, vegetation indices and multispectral classification, were applied to the satellite sensor images acquired before and after the forest fire. Besides the conventional maximum likelihood classification algorithm, a multilayer feed-forward neural network architecture was also used for comparison and evaluation of its effectiveness. A GIS database was constructed from the raster (satellite sensor data), vector (the forest type and topographical maps) and ancillary data (meteorological data). The GIS is being used to develop an information and decision support system to monitor and predict forest fire activity, and to enhance fire management efficiency. This study highlights the deficiencies in the current approach to fire management and emphasizes the need for an improved method along the lines outlined.