灌溉
播种
物候学
环境科学
叶面积指数
农业工程
植被指数
干旱
比例(比率)
产量(工程)
植被(病理学)
数学
农业
冬小麦
索引(排版)
归一化差异植被指数
农学
水文学(农业)
计算机科学
地理
工程类
生态学
地图学
万维网
病理
考古
生物
岩土工程
冶金
材料科学
医学
作者
Benoı̂t Duchemin,Philippe Maisongrande,Gilles Boulet,Iskander Benhadj
标识
DOI:10.1016/j.envsoft.2007.10.003
摘要
In this study we investigated the perspective offered by coupling a simple vegetation growth model and ground-based remotely-sensed data for the monitoring of wheat production. A simple model was developed to simulate the time courses of green leaf area index (GLAI), dry above-ground phytomass (DAM) and grain yield (GY). A comprehensive sensitivity analysis has allowed addressing the problem of model calibration, distinguishing three categories of parameters: (1) those, well known, derived from the present or previous wheat experiments; (2) those, phenological, which have been identified for the wheat variety under study; (3) those, related to farmer practices, which has been adjusted field by field. The approach was tested against field data collected on irrigated winter wheat in the semi-arid Marrakech plain. This data set includes estimates of GLAI with additional DAM and GY measurements. The model provides excellent simulations of both GLAI and DAM time courses. GY space variations are correctly predicted, but with a general underestimation on the validation fields. Despite this limitation, the approach offers the advantage of being quite simple, without requiring any data on agricultural practices (sowing, irrigation and fertilisation). This makes it very attractive for operational application at a regional scale. This perspective is discussed in the conclusion.
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