| 摘要: |
| 作物系数是计算作物需水量和农田蒸散量必要的参数,作物系数的遥感获取对于农田生态系统的水分平衡研究具有重要意义。利用Landsat ETM 遥感影像及Penman-Montieth方程,通过计算不同生长状况下棉花的作物需水量和参考作物蒸散量,实现棉花作物系数的遥感获取;在此基础上进一步分析作物系数对反照率、气象因子和植被生长参数等的敏感性。结果表明:1)利用遥感获取作物系数的空间分布是有效可行的;2)作物系数主要受植被生长状况的影响,反照率和气象因子对作物系数的影响相对次要;3)作物系数随气温、大气压、空气湿度和风速等气象因素的增大而增大,并且这种正效应随着植被覆盖度的增大而增大;4)作物系数与作物生长状况直接相关,仅仅根据作物生长阶段确定作物系数存在不合理性。 |
| 关键词: 作物系数 遥感 棉花 作物需水量 石河子 |
| DOI：10.11841/j.issn.1007-4333.2007.03.052 |
| 修订日期：2006-11-10 |
| 基金项目:江西师范大学校科研和教改项目;国家科技攻关项目 |
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| Retrieving crop coefficient for cotton under different growth status with Landsat ETM+ image |
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| Abstract: |
| Crop water requirement is an important parameter in irrigation scheduling.And the crop coefficient is a key to estimate crop water requirement by multiplying with the reference crop evapotranspiration.Crop coefficient was always be approximated from crop developing days.The method must have some defections because crop coefficient is a parameter related to crop growth status,climate condition and surface albedo.Since the crop growth status and some other factors relating to crop coefficient are spatial heterogeneous and remote sensing has advantage in obtaining the distributing parameters for vegetation and climate factor.In this paper,based on the Penman-Monteith equation,the reference crop evapotranspiration and potential evapotranspiration for cotton under different growth status was estimated with measured meteorological data,the crop coefficient for cotton was retrieved from a Landsat ETM image and the sensitivity of crop coefficient to the influence factors were analysed.The results showed that: the crop coefficient retrieved from ETM image was greater than the ones suggested by FAO and crop coefficient was influenced and decided by NDVI that represented crop growth status;while surface albedo that had a very larger variance for the sparse vegetation cover had scarcely any effect on crop coefficient and the climate factors had litter influence on crop coefficient too;with the vegetation cover fraction developing,the climate factor had much more positive effect on crop coefficient. |
| Key words: crop coefficient,remote sensing,cotton,crop water requirement,Shihezi |
