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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >COMBINING MULTIFREQUENCY MICROWAVE AND OPTICAL DATA FOR CROP MANAGEMENT
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COMBINING MULTIFREQUENCY MICROWAVE AND OPTICAL DATA FOR CROP MANAGEMENT

机译:结合多频微波和光学数据进行作物管理

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The potential for he combined use of microwave and optical data for crop management is explored with the use of images acquired in the visible, near-infrared, and thermal spectrum and the synthetic aperture radar (SAR) wavelengths in the Ku (14.85 GHz) and C (15.3 GHz) bands. The images were obtained during June 1994 and covered an agricultural site composed of large fields of partial-cover cotton, near-full-cover alfalfa, and bare soil fields of varying roughness. Results showed that the SAR Ku backscatter coefficient (Ku-band sigma degrees) teas sensitive to soil roughness and insensitive to soil moisture conditions when vegetation was present. When soil roughness conditions were relatively similar (e.g., for cotton fields of similar row direction and for all alfalfa fields), Ku-band sigma degrees was sensitive to the fraction of the surface covered by vegetation. Under these conditions, the Ku-band sigma degrees and the optical normalized difference vegetation index (NDVI) were generally correlated. The SAR C backscatter coefficient (C-band sigma degrees) was found to be sensitive to soil moistu re conditions for cotton fields with green leaf area index (GLAI) less than 1.0 and alfalfa fields with GLAI nearly 2.0. For both low-GLAI cotton and alfalfa, C-band sigma degrees was correlated with measurements of surface temperature (T-s). A theoretical basis for the relations between Ku-band sigma degrees and NDVI and between C-band sigma degrees and T-s was presented and supported with on-site measurements. On the basis of these findings, some combined optical and radar approaches are suggested for crop management applications. (C) Elsevier Science Inc., 1997. [References: 55]
机译:利用在可见光,近红外光和热谱中获得的图像以及Ku(14.85 GHz)和200 nm合成孔径雷达(SAR)波长中获得的图像,探索了将微波和光学数据结合用于作物管理的潜力。 C(15.3 GHz)频段。这些图像是在1994年6月获得的,覆盖了一个由大面积的部分覆盖棉田,几乎完全覆盖的苜蓿田和不同粗糙度的裸露土壤田地组成的农田。结果表明,当存在植被时,SAR Ku反向散射系数(Ku带sigma度)对土壤粗糙度敏感,对土壤水分条件不敏感。当土壤粗糙度条件相对相似时(例如,对于行方向相似的棉田和所有苜蓿田),Ku带sigma度对植被覆盖的表面部分敏感。在这些条件下,Ku带的西格玛度和光学归一化植被指数(NDVI)通常是相关的。对于绿叶面积指数(GLAI)小于1.0的棉花田和GLAI近2.0的苜蓿田,SAR C后向散射系数(C带sigma度)对土壤水分条件敏感。对于低GLAI棉花和苜蓿,C波段的西格玛度与表面温度(T-s)的测量相关。提出了Ku波段sigma度和NDVI之间以及C波段sigma度与T-s之间关系的理论基础,并为现场测量提供了支持。根据这些发现,建议将一些光学和雷达方法结合起来用于作物管理应用。 (C)Elsevier Science Inc.,1997年。[参考:55]

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