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Radarsat Data for Operational Rice Monitoring and its Potential for Yield Estimation

机译:运算稻田监测的雷达数据及其产量估计潜力

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Rice monitoring and yield estimation has special significance to China, as rice is the staple grain and accounts for 42% of the crop yield for this country. Radar remote sensing is appropriate for monitoring rice, as cultivated areas are most often cloudy and rainy. For this reason, SAR is anticipated to be the dominant data source in tropic and sub-tropical regions and also provide re-visit schedules suitable for agricultural monitoring. This paper presents the results of a study examining the backscatter behavior of rice using multi-temporal RADARSAT dataset acquired in 1996 and 1997. A rice-type distribution map was produced, showing 4 types of rice with different life spans ranging from 80 days, to 120-125 days. The life span of a rice crop has significant impact on yield, as well as the taste and quality of the rice. The yield of three counties and two administrative regions, totaling 5000 square kilometers, are estimated in this study. The accuracy was found to be 91%, providing confidence that multi-temporal RADARSAT data is capable of rice monitoring and yield estimation. Based on the studies carried out in the Zhaoqing test site, it is suggested that rice yield estimations require three radar data acquisitions taken at 3 stages of crop growth circle. That is at the end of the seedling development period, in the ear differentiation period, and at the beginning of the havest period. Alternatively, if multiparameter radar data is available, only two data acquisitions are required: at the end of the seedling period, and at the beginning of the harvest period. In 1999, we started a pilot experiment on operational rice monitoring and potential yield estimation using multi-temporal RADARSAT data. Finally, this paper proposes a pilot scenario for operational rice monitoring and yield estimation.
机译:水稻监测和产量估计对中国具有特殊意义,因为米饭是针脚粮食,占该国家作物产量的42%。雷达遥感适合监测米饭,因为耕地面积往往多云和多雨。因此,预计SAR是热带和亚热带地区的主要数据源,也提供适合农业监测的重新访问时间表。本文介绍了研究米饭的研究结果,使用1996年和1997年获得的多时间雷达数据集进行了稻米的反向散射行为。制作了一种稻米型分布图,显示4种稻米,不同的生活跨度范围从80天范围内120-125天。稻米作物的寿命对产量产生重大影响,以及米饭的味道和质量。本研究估计三个县和两个行政区的产量和两个行政区,总计5000平方公里。发现准确性为91%,提供了多时间雷达数据能够进行水稻监测和产量估计的信心。基于肇庆试验现场进行的研究,建议水稻产量估计需要在作物生长圈的3个阶段采取三个雷达数据采集。这是在幼苗发展时期的结束时,在耳区分化期间,并且在HAPEST期初。或者,如果可以使用多游艇计雷达数据,则仅需要两个数据采集:在苗期结束时,并且在收获期的开始时。 1999年,我们开始使用多时间雷达数据的运营水稻监测和潜在产量估计试验试验。最后,本文提出了一种用于运营水稻监测和产量估计的试验方案。

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