卫星遥感估产技术在大豆区域收入保险中的应用

doi:10.12133/j.smartag.2020.2.3.202006-SA002

Smart Agriculture ›› 2020, Vol. 2 ›› Issue (3): 139-152.doi: 10.12133/j.smartag.2020.2.3.202006-SA002

• 信息处理与决策 • 上一篇

卫星遥感估产技术在大豆区域收入保险中的应用

陈爱莲^1,²(), 李家裕³, 张圣军³, 朱玉霞^1,²(), 赵思健^1,², 孙伟^1,², 张峭^1,²

^1.中国农业科学院农业信息研究所农业风险分析与管理研究中心，北京 100081
^2.农业农村部农业信息服务技术重点实验室，北京 100081
^3.中国太平洋财产保险股份有限公司山东分公司，山东济南 250001

收稿日期:2020-06-05 修回日期:2020-09-18 出版日期:2020-09-30
基金资助:
中国农业科学院农业信息研究所科技创新工程项目(CAAS-ASTIP-2016-AII);青年探索研究项目(2019JKY022)
作者简介:陈爱莲（1984－），女，博士，助理研究员，研究方向为遥感应用。E-mail: chenailian@caas.cn。
通信作者:

Application of Satellite Remote Sensing Yield Estimation Technology in Regional Revenue Protection Crop Insurance: A Case of Soybean

CHEN Ailian^1,²(), LI Jiayu³, ZHANG Shengjun³, ZHU Yuxia^1,²(), ZHAO Sijian^1,², SUN Wei^1,², ZHANG Qiao^1,²

^1.Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
^2.Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Agriculture, Beijing 100081, China
^3.China Pacific Property Insurance Company Limited Shandong Branch, Jinan 250001, China

Received:2020-06-05 Revised:2020-09-18 Online:2020-09-30

摘要/Abstract

摘要：

本研究针对中国近年来重点发展的创新型区域收入保险缺少第三方实时客观产量数据的问题，引入了卫星遥感估产技术，探讨其应用模式和适用性。以山东省嘉祥县大豆区域收入保险为例，基于哨兵2号卫星遥感数据提取大豆种植地块，计算归一化植被指数（NDVI）和作物生理参数，结合气象卫星遥感数据与实地抽样测产数据，建立了多参数线性回归模型估算大豆产量。研究结果显示，卫星遥感获取的研究区大豆种植面积为124 km²，与当地农业局上报的127 km²相差3 km²；采用实测地块验证，种植分布地块遥感识别精度达90%；产量估算结果显示，2018年8月23日大豆结荚期的NDVI和9月7日大豆鼓粒期的NDVI对大豆单产的解释度最佳，多参数回归模型计算全区平均产量为244,500 kg/km²，与常年299,800 kg/km²相比，体现了受灾严重的农情；产量估算数据与实测数据之间的回归系数达0.92，可满足应用需求。结果表明，基于哨兵2号卫星遥感数据能够准确识别研究区大豆种植分布，并能在大豆收获后最快一周完成产量估算，指导保险公司的理赔工作。

关键词: 农业保险, 区域收入保险, 卫星遥感, 产量估算, 哨兵2号

Abstract:

In recent years, revenue protection crop insurance is an innovative insurance that has been prioritized in China. But it still lacks the support of the third-party yield data around crop harvest time. Aiming to provide objective yield data for revenue protection crop insurance, satellite remote sensing production estimation technology was employed to discuss its application mode and applicability. Taking the soybean revenue protection insurance in Jiaxiang county, Shandong province as an example, we first extracted soybean planting plots, calculated vegetation index and crop physiological parameters based on Sentinel-2 satellite images in 2018 . Combining to TRMM precipitation data from TRMM precipitation-monitoring radar satellite and MODIS land surface temperature data from Terra/Aqua satellite and site yield data, we established a multi-parameter linear regression model, and estimated soybean yield per unit area. The crop extraction results showed that the soybean planting area in the study area was 1.24 km², which was in good agreement with the 1.27 km² reported by the local agricultural bureau; and with using the actual measurement plots, the remote sensing identification accuracy of the planting distribution plots reached 90%. The yield estimation results showed that the NDVI of the soybean pod stage on August 23 and the leaf area index of the soybean seedling stage on September 7 explained the soybean yield per hectare the best, and the average estimated yield of the whole area was 244,500 kg/m², which reflects the severely affected agricultural conditions, comparing to 299,800 kg/km² in previous years.The regression coefficient between the estimated yield data and the measured data reached 0.92, which meet the application needs.With this results, the estimated yield of different towns can be summarized, and the regional yield was present, and was used as the real yield in 2018, multiplying with the average soybean price around October 11 to December 10 from the local price bureau, the real revenue was obtained. Compared the real revenue to the expected revenue in the contract of insurance, the claims work was decided. The results indicated that the Sentinel-2 satellite data could be used to identify the soybean planting distribution in the study area accurately, and to complete the yield estimation as soon as one week after the soybean harvest, which could guide the insurance company's claims work. The whole methodology is capable of aiding the claims work in revenue protection crop insurance.

Key words: agricultural insurance, regional insurance income, satellite remote sensing, yield estimation, Sentinel-2

中图分类号:

陈爱莲, 李家裕, 张圣军, 朱玉霞, 赵思健, 孙伟, 张峭. 卫星遥感估产技术在大豆区域收入保险中的应用[J]. 智慧农业（中英文）, 2020, 2(3): 139-152.

CHEN Ailian, LI Jiayu, ZHANG Shengjun, ZHU Yuxia, ZHAO Sijian, SUN Wei, ZHANG Qiao. Application of Satellite Remote Sensing Yield Estimation Technology in Regional Revenue Protection Crop Insurance: A Case of Soybean[J]. Smart Agriculture, 2020, 2(3): 139-152.

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卫星遥感估产技术在大豆区域收入保险中的应用

Application of Satellite Remote Sensing Yield Estimation Technology in Regional Revenue Protection Crop Insurance: A Case of Soybean

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