globalchange  > 气候变化与战略
CSCD记录号: CSCD:5082308
论文题名:
基于植被指数的土壤氮素遥感估算研究
其他题名: Study on Remote Sensing Inversion of Desert Riverside Forest Soil Nitrogen Based on Vegetation Index
作者: 王家强1; 于军2; 彭杰1; 柳维扬1; 伍维模2
刊名: 西南农业学报
ISSN: 1001-4829
出版年: 2014
卷: 27, 期:1, 页码:1171-1181
语种: 中文
中文关键词: 植被指数 ; 荒漠河岸林 ; 土壤氮素 ; 遥感
英文关键词: Vegetation index ; Desert riverside forest ; Soil nitrogen ; Remote sensing
WOS学科分类: REMOTE SENSING
WOS研究方向: Remote Sensing
中文摘要: 土壤氮素是土壤肥力的重要指标之一,在粮食生产和质量上扮演着极其重要的角色。土壤氮素监测不仅是农业生产的研究热点,也是全球气候变化问题研究的热点之一,而遥感技术为土壤氮素监测提供了一种快速无损的、新的技术手段。本研究利用TM影像通过NDVI变换反演植被覆盖度,同时结合地面实测数据,分析影像植被覆盖度与实测植被覆盖度的关系,及二者在反演土壤氮素含量时的差异;并建立影像植被覆盖度与土壤全氮含量的估算模型;结果表明:影像植被覆盖度与实测植被覆盖度的相关性极显著,通过比较实测植被覆盖度与土壤全氮、碱解氮的关系,发现实测植被覆盖度与土壤全氮含量相关性极显著,而与土壤碱解氮含量相关性不显著。
英文摘要: Soil nitrogen is one of the important indexes of soil fertility,which is an important role in food production and quality. Soil nitrogen monitoring is not only a hot point of the research of agricultural production,but also one of the hot spot of research of the global climate change,but remote sensing technology provides a quick nondestructive,new technology for soil nitrogen monitoring. In the study, the TM image was used to inverse the vegetation coverage through the NDVI transform,and the surface measurement was used to analyze the relationship of the Image vegetation coverage and measured vegetation coverage,and the two difference on the inversion of soil nitrogen content. The inversion model of the image vegetation coverage and soil total nitrogen content were established. The result showed: the correlation of the Image vegetation coverage and measured vegetation coverage was very significant. The correlation of the vegetation coverage and soil total nitrogen content was very significant,but the correlation of soil alkali solution nitrogen content and the measured vegetation coverage was not significant.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/148521
Appears in Collections:气候变化与战略

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作者单位: 1.塔里木大学植物科学学院, 阿拉尔, 新疆 843300, 中国
2.塔里木大学植物科学学院, 新疆生产建设兵团塔里木盆地物资源保护与利用重点实验室, 阿拉尔, 新疆 843300, 中国

Recommended Citation:
王家强,于军,彭杰,等. 基于植被指数的土壤氮素遥感估算研究[J]. 西南农业学报,2014-01-01,27(1):1171-1181
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