Point set generalization is one of the essential problems in map generalization. On the demands analysis of point set generalization, this paper proposes a method to generalize point sets based on the Kohonen Net mode...Point set generalization is one of the essential problems in map generalization. On the demands analysis of point set generalization, this paper proposes a method to generalize point sets based on the Kohonen Net model; the standard SOM algorithm has been improved so as to preserve the spatial distribution properties of the original point set. Examples illustrate that this method suits the generalization of point sets.展开更多
现有的卫星热红外数据在时间与空间分辨率上存在矛盾,导致难以获取高时空分辨率地表温度(land surface temperature,LST),制约了城市热环境精细化监测能力.将辐射能量模型与地理加权回归(geographical weighted regression,GWR)模型集...现有的卫星热红外数据在时间与空间分辨率上存在矛盾,导致难以获取高时空分辨率地表温度(land surface temperature,LST),制约了城市热环境精细化监测能力.将辐射能量模型与地理加权回归(geographical weighted regression,GWR)模型集成用于地表温度模拟,基于6S(Second Simulation of Satellite Signal in the Solar Spectrum)辐射传输模型模拟不同太阳位置时地表像元接收的直射辐射能量与散射辐射能量,利用美国陆地卫星影像(Landsat 8 TM)数据结合地表辐射传输方程模拟不同时刻的波段下行辐射、短波净辐射近似值以及过境时刻的波段地表反射率,进一步模拟过境时刻的归一化植被指数(normalized differential vegetation index,NDVI)尺度因子.最后采用高时间分辨率的风云四号(FY-4)静止卫星数据,利用GWR降尺度方法模拟日间逐小时地表温度.为评估模拟地表温度的精度,将模拟结果与中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)获取的相近时刻的地表温度产品数据进行对比验证.结果表明,模型模拟的精度均方根误差(root mean square error,RMSE)为1.37℃,平均绝对误差(mean absolute error,MAE)为1.04℃,R^(2)为0.6968,相对误差直方图显示大部分像元的模拟精度误差都小于3℃,表明能够较好地模拟地表温度.展开更多
Between 1850 and 1900, state geological surveys in the Midwest underwent an ideological shift by transforming from institutions based on applied science to those based on pure science. Three factors influenced this pr...Between 1850 and 1900, state geological surveys in the Midwest underwent an ideological shift by transforming from institutions based on applied science to those based on pure science. Three factors influenced this process： the acquisition of permanent status from state governments, the establishment of the USGS （United States Geological Survey）, and the increase in regional professional scientific societies and publications in the Midwest. These factors aided in the transformation of research projects by state geologists. These projects grew more focused, of higher quality, and increased in number during this time-period. State governments still expected Midwestern geological surveys to meet the practical needs of their respective states as this transformation continued, but surveys complemented these goals with projects more closely related to pure science. This shift encouraged the research goals of surveys to investigate projects more closely related to pure scientific pursuits, and significantly aided in the growth of the earth sciences in the nineteenth Century and early twentieth Century.展开更多
Big data is a strategic highland in the era of knowledge-driven economies, and it is also a new type of strategic resource for all nations. Big data collected from space for Earth observation—so-called Big Earth Data...Big data is a strategic highland in the era of knowledge-driven economies, and it is also a new type of strategic resource for all nations. Big data collected from space for Earth observation—so-called Big Earth Data—is creating new opportunities for the Earth sciences and revolutionizing the innovation of methodologies and thought patterns. It has potential to advance in-depth development of Earth sciences and bring more exciting scientific discoveries.The Academic Divisions of the Chinese Academy of Sciences Forum on Frontiers of Science and Technology for Big Earth Data from Space was held in Beijing in June of 2015.The forum analyzed the development of Earth observation technology and big data, explored the concepts and scientific connotations of Big Earth Data from space, discussed the correlation between Big Earth Data and Digital Earth, and dissected the potential of Big Earth Data from space to promote scientific discovery in the Earth sciences, especially concerning global changes.展开更多
基金Supported by the Science and Research Development Program Foundation of Yangtze University, the National Natural Science Foundation of China （No. 40571133） and the Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping （No. 2006（25））.
文摘Point set generalization is one of the essential problems in map generalization. On the demands analysis of point set generalization, this paper proposes a method to generalize point sets based on the Kohonen Net model; the standard SOM algorithm has been improved so as to preserve the spatial distribution properties of the original point set. Examples illustrate that this method suits the generalization of point sets.
文摘现有的卫星热红外数据在时间与空间分辨率上存在矛盾,导致难以获取高时空分辨率地表温度(land surface temperature,LST),制约了城市热环境精细化监测能力.将辐射能量模型与地理加权回归(geographical weighted regression,GWR)模型集成用于地表温度模拟,基于6S(Second Simulation of Satellite Signal in the Solar Spectrum)辐射传输模型模拟不同太阳位置时地表像元接收的直射辐射能量与散射辐射能量,利用美国陆地卫星影像(Landsat 8 TM)数据结合地表辐射传输方程模拟不同时刻的波段下行辐射、短波净辐射近似值以及过境时刻的波段地表反射率,进一步模拟过境时刻的归一化植被指数(normalized differential vegetation index,NDVI)尺度因子.最后采用高时间分辨率的风云四号(FY-4)静止卫星数据,利用GWR降尺度方法模拟日间逐小时地表温度.为评估模拟地表温度的精度,将模拟结果与中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)获取的相近时刻的地表温度产品数据进行对比验证.结果表明,模型模拟的精度均方根误差(root mean square error,RMSE)为1.37℃,平均绝对误差(mean absolute error,MAE)为1.04℃,R^(2)为0.6968,相对误差直方图显示大部分像元的模拟精度误差都小于3℃,表明能够较好地模拟地表温度.
文摘Between 1850 and 1900, state geological surveys in the Midwest underwent an ideological shift by transforming from institutions based on applied science to those based on pure science. Three factors influenced this process： the acquisition of permanent status from state governments, the establishment of the USGS （United States Geological Survey）, and the increase in regional professional scientific societies and publications in the Midwest. These factors aided in the transformation of research projects by state geologists. These projects grew more focused, of higher quality, and increased in number during this time-period. State governments still expected Midwestern geological surveys to meet the practical needs of their respective states as this transformation continued, but surveys complemented these goals with projects more closely related to pure science. This shift encouraged the research goals of surveys to investigate projects more closely related to pure scientific pursuits, and significantly aided in the growth of the earth sciences in the nineteenth Century and early twentieth Century.
基金supported by the Academic Divisions of the Chinese Academy of Sciences Forum on Frontiers of Science and Technology for Big Earth Data from Space
文摘Big data is a strategic highland in the era of knowledge-driven economies, and it is also a new type of strategic resource for all nations. Big data collected from space for Earth observation—so-called Big Earth Data—is creating new opportunities for the Earth sciences and revolutionizing the innovation of methodologies and thought patterns. It has potential to advance in-depth development of Earth sciences and bring more exciting scientific discoveries.The Academic Divisions of the Chinese Academy of Sciences Forum on Frontiers of Science and Technology for Big Earth Data from Space was held in Beijing in June of 2015.The forum analyzed the development of Earth observation technology and big data, explored the concepts and scientific connotations of Big Earth Data from space, discussed the correlation between Big Earth Data and Digital Earth, and dissected the potential of Big Earth Data from space to promote scientific discovery in the Earth sciences, especially concerning global changes.
