首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   20篇
  免费   0篇
  国内免费   2篇
安全科学   2篇
环保管理   2篇
综合类   7篇
基础理论   8篇
污染及防治   2篇
社会与环境   1篇
  2024年   1篇
  2022年   4篇
  2019年   1篇
  2017年   1篇
  2014年   2篇
  2011年   1篇
  2010年   2篇
  2006年   4篇
  2005年   3篇
  2003年   2篇
  1999年   1篇
排序方式: 共有22条查询结果,搜索用时 26 毫秒
21.
如果用“成也小铸造,败也小铸造”来形容安徽 巢湖含山县曾经辉煌的民间小铸造,一点也不为过。 最近,记者来到巢湖含山,近距离接触那些还在熊熊 燃烧的冲天炉。探访这里的小铸造。 上世纪七八十年代,林立的烟囱和熊熊的冲天炉 是欣欣向荣的标志。但现在,人们再看到这熊熊燃烧 的冲天炉的时候,却无法乐起来。在素有“铸造之乡” 的巢湖含山,曾经在部分乡镇遍地开花的“小铸造”, 曾经是一些村民的致富之道。即使在现在含山境内各 种规模的四百三十多家铸造企业中,“小铸造”仍然占 半数以上,还不包括那些非法的小铸造,而这些“小 铸造”中仅仅在林头镇境内就有一百多家。  相似文献   
22.
Wheat is the second-largest food crop in Tibet, China. Along with economic development, the pattern of wheat production in Tibet has changed dramatically, potentially affecting the balance of grain supply and demand, as well as food security. A clear understanding of the spatiotemporal patterns and other factors affecting wheat production can provide a necessary basis for the scientific management and efficient production of wheat. Based on the wheat yield from 1990 to 2020 in 74 county-level units of Tibet, this study analyzed the spatial and temporal change patterns of Tibetan wheat production and its impacting factors using the Gini coefficient, center of gravity move method, advantage index, exploratory spatial data analysis (ESDA), and geographically weighted regression model (GWR). Results showed that: (1) the total wheat production in Tibet rose from 1990 to 1999, fluctuated, and then decreased from 1999 to 2020. The production areas are mainly concentrated in the southern Tibetan Valley and counties in the Three Rivers region of eastern Tibet. (2) The spatial distribution and agglomeration pattern of wheat in Tibet is relatively stable, and the production center shows a slight fluctuation trend from west to east during the 1990-2020 time period. (3) Based on the comprehensive advantage index (CAI), Tibet’s wheat production in advantaged areas, slightly advantaged areas, slightly disadvantaged areas, and disadvantaged areas accounted for 13.5%, 8.1%, 9.5%, and 40.5% of the total production, respectively; indicating that the regional distribution of CAI exhibits spatial agglomeration rather than sporadic distribution. The patterns are HH (high-high), LH (low-high), and random; 29 hot spots are mainly distributed in Lhasa, Shannan, and Nyingchi, while the cold spots are mainly distributed in Xigazê and Ngari; and (4) the impacting factors on Tibet’s wheat production mainly include effective irrigation areas and agricultural mechanization level as positive factors, and regional gross agricultural product as the main negative factor. In addition, rainfall, other grain output, livestock inventory at the end of the year, and the number of non-primary industries also have an impact on wheat production. Wheat planting area in Tibet has been declining in recent years, thus exhibiting a significant pattern of spatial agglomeration. The three dominant factors affecting the emerging spatiotemporal pattern of wheat production in Tibet are the irrigation condition, mechanization, and local economic development levels. Based on the above conclusions, the study suggests building a high-yield wheat area consistent with local conditions by strictly protecting arable land, improving irrigation conditions, and increasing machinery investment. Depending on the counties of high-yield areas, Tibetan farmers and herders should cultivate the bases of wheat production and build a wheat base for local wheat consumption. © 2022 Science Press. All rights reserved.  相似文献   
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号