基于遥感的国外作物长势监测与产量趋势估计

国外重点产粮区的作物长势和产量增长趋势信息对于中国政府决策和制订合理的粮食政策具有重要意义,但由于地域的限制、生产方式的差异以及国外可获取的气象资料有限,气象模型和农学模型在国外估产方面尚存在不足,遥感以其便捷、快速、客观的优势已被越来越多地采用进行国外作物长势监测和产量估计。该文以美国玉米和印度水稻为例,探讨了基于1kmSPOT-VGT遥感资料进行作物长势监测和产量趋势估计的方法,并结合当地气象条件对其结果进行了分析。经检验,利用该方法得到的长势状况及空间分布与实际基本一致,产量增长趋势预测准确率为100%;在作物生长旺盛季节,植株覆盖密度较大时,EVI比NDVI能更真实地反映作物的长势状况。该研究可为国外作物长势遥感监测与产量估算业务应用提供参考。

Global crop growth condition monitoring and yield trend prediction with remote sensing

Remote sensing can be used for crop growth condition monitoring and yield prediction at global scale. Meteorological model and agricultural model are both deficient without adequate ground observations, but remote sensing model can give more accurate and perfect results. This paper did a case study on the method for maize growth condition monitoring and yield trend prediction in American based on SPOT-VGT data, as well as rice in India. The study suggests that SPOT-VGT/NDVI and SPOT-VGT/EVI with the spatial resolution of 1 km can both be used for operational global crop growth monitoring and yield prediction. The method for yield trend prediction can give the accuracy as high as 100%. In the most luxuriant period SPOT-VGT/EVI can give more exact information of crop growth condition than SPOT-VGT/NDVI.