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首页> 外文会议>Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII >Monitoring crop coefficient of orange orchards using energy balance and the remote sensed NDVI
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Monitoring crop coefficient of orange orchards using energy balance and the remote sensed NDVI

机译：使用能量平衡和遥感NDVI监测橙果园的作物系数

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The structure of vegetation is paramount in regulating the exchange of mass and energy across the biosphere-atmosphere interface. In particular, changes in vegetation density affected the partitioning of incoming solar energy into sensible and latent heat fluxes that may result in persistent drought through reductions in agricultural productivity and in the water resources availability. Limited research with citrus orchards has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigation when crop coefficient (K_c) estimate, derived from remotely sensed multispectral vegetation indices (VIs), are incorporated into irrigation-scheduling algorithms.rnThe purpose of this article is the application of an empirical reflectance-based model for the estimation of K_c and evapotranspiration fluxes (ET) using ground observations on climatic data and high-resolution VI_s from ASTER TERRA satellite imagery. The remote sensed K_c data were used in developing the relationship with the normalized difference vegetation index (NDVI) for orange orchards during summer periods. Validation of remote sensed data on ET, K_c and vegetation features was deal through ground data observations and the resolution of the energy balance to derive latent heat flux density (λE), using measures of net radiation (R_n) and soil heat flux density (G) and estimate of sensible heat flux density (H) from high frequency temperature measurements (Surface Renewal technique).rnThe chosen case study is that of an irrigation area covered by orange orchards located in Eastern Sicily (Italy) during the irrigation seasons 2005 and 2006.
机译：植被的结构对于调节跨生物圈-大气界面的质量和能量交换至关重要。特别是，植被密度的变化影响了传入的太阳能划分为显热通量和潜热通量，这可能通过降低农业生产率和水资源利用率而导致持续干旱。对柑橘园的有限研究表明，由于更好的用水量估算和将来自遥感多光谱植被指数（VIs）的作物系数（K_c）估算值结合到灌溉计划算法中时，灌溉时间更合适，灌溉计划得到了改善.rn本文的目的是应用基于经验反射率的模型，利用对气候数据和来自ASTER TERRA卫星影像的高分辨率VI_s的地面观测，估算K_c和蒸散通量（ET）。遥感的K_c数据用于建立与夏季果园的归一化植被指数（NDVI）的关系。 ET，K_c和植被特征的遥感数据的验证通过地面数据观测和能量平衡的解析来进行，以使用净辐射（R_n）和土壤热通量密度（G ）并根据高频温度测量（表面更新技术）估算显热通量密度（H）。rn选定的案例研究是2005年和2006年灌溉季节位于西西里岛东部（意大利）的橙色果园覆盖的灌溉区域。

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