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Rice monitoring and production estimation using multitemporal RADARSAT

机译:使用多时相RADARSAT进行水稻监测和产量估算

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Rice monitoring and production estimation has special significance to China, as rice is the staple grain and accounts for 42% of the crop production in this country. Radar remote sensing is appropriate for monitoring rice because the areas where this crop is cultivated are often cloudy and rainy. Synthetic Aperture Radar (SAR) is thus anticipated to be the dominant high-resolution remote sensing data source for agricultural applications in tropical and subtropical regions. IP also provides revisit schedules suitable for agricultural monitoring. This paper presents the results of a study examining the backscatter behavior of rice as a function of time using multitemporal RADARSAT data acquired in 1996 and 1997. A rice-type distribution map was produced, showing four 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 the yield, as well as on the taste and quality of the rice, with the longer growing varieties having the best taste and the highest productivity. The rice production of three counties and two administrative regions, totaling 5000 km(2), was estimated in this study. The accuracy of the rice classification was found to be 91% (97% after postclassification filtering) providing confidence that multitemporal RADARSAT data is capable of rice mapping. An empirical growth model was then applied to the results of the rice classification, which related radar backscatter values to rice life spans. These life spans could then be used to sum up the production estimates, which were obtained from agronomic models already in use for rice by local agronomists. These models related the yield of rice to their life span based on empirical observations for each type of rice. The resulting productivity estimate could not be compared to any other existing data on yield production for the study-area, but was well received by the local authorities. Based on the studies carried out in the Zhaoqing test site since 1993, it is suggested that rice production estimates require three radar data acquisitions taken at three different stages of crop growth and development. These three growth stages an: at the end of the transplanting and seedling development period, during the ear differentiation period, and at the beginning of the harvest period. Alternatively, if multiparameter radar data is available, only two data acquisitions may be needed. These would be at the end of the transplanting and seedling development period, and at the beginning of the harvest period. This paper also proposes an operational scenario for rice monitoring and production estimation. (C) 2001 Elsevier Science Inc. All rights reserved. [References: 37]
机译:稻米的监测和产量估算对中国具有特殊意义,因为稻米是主粮,占该国作物产量的42%。雷达遥感适用于监测稻米,因为该作物的种植地通常阴雨多雨。因此,合成孔径雷达(SAR)有望成为热带和亚热带地区农业应用的主要高分辨率遥感数据源。知识产权还提供适用于农业监测的再访时间表。本文介绍了一项研究结果,该研究使用1996年和1997年获得的多时相RADARSAT数据研究了稻米随时间的反向散射行为。绘制了一种稻米类型分布图,显示了四种不同寿命的稻米,其寿命从80天到120-125天。稻米的寿命对稻米的产量,口感和品质都有重要影响,而生长时间更长的品种具有最佳的口感和最高的生产率。这项研究估计了三个县和两个行政区的水稻总产量为5000 km(2)。水稻分类的准确性被发现为91%(后分类过滤后为97%),这提供了对多时间RADARSAT数据能够进行水稻作图的信心。然后将经验增长模型应用于水稻分类的结果,该模型将雷达反向散射值与水稻寿命相关联。然后可以将这些寿命用于总结产量估算值,这些估算值是从当地农学家已经用于水稻的农艺模型获得的。这些模型基于对每种水稻的经验观察,将水稻的产量与其寿命联系起来。得出的生产率估算值无法与研究区域任何其他现有的产量相关数据进行比较,但得到了地方当局的好评。根据自1993年以来在肇庆试验场进行的研究,建议水稻产量估算需要在作物生长和发育的三个不同阶段进行三个雷达数据采集。这三个生长阶段分别是:在移栽和育苗期结束时,在穗分化期和收获期开始时。或者,如果多参数雷达数据可用,则可能仅需要两次数据采集。这些将在移栽和育苗期结束时以及收获期开始时进行。本文还提出了水稻监测和产量估算的操作方案。 (C)2001 Elsevier Science Inc.保留所有权利。 [参考:37]

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