Combined use of optical and radar satellite data for the detection of tillage and irrigation operations: Case study in Central Morocco

灌溉 遥感 耕作 环境科学 阈值 卫星 水文学(农业) 地理 计算机科学 地质学 人工智能 工程类 生态学 岩土工程 航空航天工程 图像(数学) 生物
作者
Rachid Hadria,Benoı̂t Duchemin,Frédéric Baup,Thuy Le Toan,Alexandre Bouvet,Gérard Dedieu,Michel Le Page
出处
期刊:Agricultural Water Management [Elsevier]
卷期号:96 (7): 1120-1127 被引量:37
标识
DOI:10.1016/j.agwat.2009.02.010
摘要

The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season. The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations. The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.
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