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Application of MODIS images for modelling the energy balance components in the semi-arid conditions of Brazil

机译:MODIS图像在巴西半干旱条件下能量平衡分量建模中的应用

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In the semi-arid areas of Petrolina municipality, Northeast Brazil, irrigated agriculture has replaced the natural vegetation, thus the quantification of the energy exchanges between the plants and the low atmosphere is important. MODIS satellite images and agro-meteorological data for the years of 2010 and 2011 were used together, for modelling the energy balance components under these conditions. Surface albedo (α_0), NDVI and surface temperature (T_0) were the remote sensing parameters required to calculate the latent heat flux (λE) and the surface resistance to evapotranspiration (r_s) on a large scale. The daily net radiation (R_n) was retrieved from α_0, air temperature (T_a) and transmissivity (τ_(sw)), allowing the quantification of the sensible heat flux (H) by residual in the energy balance. With threshold values for r_s, it was possible to do a simplified vegetation classification. The incident solar radiation (RS↓) partitioned as R_n ranged from 0.40 to 0.51, corresponding respectively to periods after the rainy season and the driest conditions of the year, with the observed differences between irrigated crops and natural ecosystem not significant. Considering all periods along the year, the averaged fractions of R_n partitioned as H, were 31 and 78%, for irrigated crops and natural vegetation, respectively, while as λE the corresponding ratios were 69 and 22%. Heat advection from the dry areas surrounding irrigated plots was observed with λE exceeding R_n by 9% during the coldest periods. The models tested herein can be used for monitoring the energy exchanges in agro-ecosystems under conditions of land use and climate change.
机译:在巴西东北部Petrolina市的半干旱地区,灌溉农业取代了自然植被,因此量化植物与低气压之间的能量交换非常重要。将MODIS卫星图像和2010年和2011年的农业气象数据一起使用,以在这些条件下对能量平衡要素进行建模。地表反照率(α_0),NDVI和地表温度(T_0)是大规模计算潜热通量(λE)和表面蒸散阻力(r_s)所需的遥感参数。从α_0,空气温度(T_a)和透射率(τ_(sw))中获取每日净辐射(R_n),从而可以通过能量平衡中的残差来量化显热通量(H)。利用r_s的阈值,可以简化植被分类。划分为R_n的入射太阳辐射(RS↓)在0.40至0.51之间,分别对应于雨季之后和一年中最干旱的时期,而观测到的灌溉作物与自然生态系统之间的差异并不显着。考虑到一年中的所有时期,灌溉作物和天然植被的R_n的平均分数分别为H和31%,分别为H和78%,而λE则为69%和22%。在最冷的时期,观察到灌溉地块周围干旱地区的热对流,λE超过R_n 9%。本文测试的模型可用于监测土地利用和气候变化条件下农业生态系统中的能量交换。

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