基于遥感和gis模型的墨西哥半干旱雅基河谷小麦产量估算

Agronomie Pub Date : 2004-09-01 DOI:10.1051/AGRO:2004037
Julio C. Rodríguez, B. Duchemin, R. Hadria, C. Watts, J. Garatuza, A. Chehbouni, S. Khabba, G. Boulet, E. Palacios, A. Lahrouni
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引用次数: 42

摘要

在1999/2000农业季节,在半干旱的雅基河谷(墨西哥西北部)的冬小麦田进行了一项试验。该数据集用于校准由STICS模拟的叶面积指数(LAI)的演变,发现其与野外反射率测量结果非常吻合。经校正后,对净辐射、土壤水分和蒸散发的季节水平和趋势进行了满意的模拟,但作物温度高估了约2.5°C。在更大的范围内,通过对比管理实践,在16个油田上运行了STICS。模拟结果表明,播期越晚,产量可预测性显著降低,与观测结果一致。野外和卫星资料(Landsat-ETM+、Terra-MODIS和植被)NDVI的季节变化非常接近。然而,也注意到一些困难:高LAI值下NDVI的饱和和1公里空间尺度上的平滑变率,以及需要一种可靠的卫星数据处理方法。
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Wheat yield estimation using remote sensing and the STICS model in the semiarid Yaqui valley, Mexico
During the 1999/2000 agricultural seasons, an experiment was carried out on winter wheat fields in the semiarid Yaqui Valley (Northwest Mexico). This data set was used to calibrate the evolution of the leaf area index (LAI) simulated by STICS, which was found to be in excellent agreement with estimates obtained from field reflectance measurements. After calibration, STICS was able to simulate satisfactorily the seasonal levels and trends observed in net radiation, soil moisture and evapotranspiration, but the crop temperature was overestimated by about 2.5 °C. On a larger scale, STICS was run on 16 fields with contrasting management practices. The simulations indicate that yield predictability is significantly lower for later sowing dates, consistent with observations. The seasonal variations of field and satellite data (Landsat-ETM+, Terra-MODIS and VEGETATION) NDVI were very close. However, some difficulties were noted: saturation of NDVI at high LAI values and smoothed variability on a 1-km spatial scale, as well as the need for a sound methodology for processing satellite data.
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