Do high-resolution satellite indices at field level reduce basis risk of satellite-based weather index insurance?

IF 1.5 Q3 AGRICULTURAL ECONOMICS & POLICY Agricultural Finance Review Pub Date : 2021-08-11 DOI:10.1108/afr-12-2020-0177
W. Kölle, M. Buchholz, O. Musshoff
{"title":"Do high-resolution satellite indices at field level reduce basis risk of satellite-based weather index insurance?","authors":"W. Kölle, M. Buchholz, O. Musshoff","doi":"10.1108/afr-12-2020-0177","DOIUrl":null,"url":null,"abstract":"PurposeSatellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.Design/methodology/approachIn this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.FindingsThe results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.Originality/valueTo the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Finance Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/afr-12-2020-0177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 3

Abstract

PurposeSatellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.Design/methodology/approachIn this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.FindingsThe results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.Originality/valueTo the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
野外高分辨率卫星指数是否降低了卫星气象指数保险的基本风险?
目的最近考虑了基于卫星的天气指数保险,以降低基于站点的天气指数险的高基差风险。然而,由于使用了空间分辨率相对较低的卫星数据,还无法确定没有山脉、森林和湖泊等令人不安的景观元素的卫星指数。设计/方法/方法在这种情况下,基于中分辨率成像光谱仪(MODIS)(250×250 m)和高分辨率陆地卫星5/8(30×30 m)图像,使用归一化差异植被指数(NDVI)来研究基于卫星的天气指数合同的更高空间分辨率对对冲冬小麦产量的影响。为德国东北部的三个农场设计了田地和农场两级的保险合同。结果表明,随着卫星数据空间分辨率的提高,基于卫星的天气指数保险合同的基本风险可以降低。然而,研究结果也表明,与田间水平相比,农场水平的基于NDVI的保险合同设计也降低了基准风险。研究表明,更高分辨率的卫星数据是有利的,而实地一级的卫星指数并不能降低基准风险。原创性/价值据作者所知,与农场水平相比,首次在田间水平研究了提高卫星图像空间分辨率对基于卫星的天气指数保险的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Agricultural Finance Review
Agricultural Finance Review AGRICULTURAL ECONOMICS & POLICY-
CiteScore
3.70
自引率
18.80%
发文量
24
期刊介绍: Agricultural Finance Review provides a rigorous forum for the publication of theory and empirical work related solely to issues in agricultural and agribusiness finance. Contributions come from academic and industry experts across the world and address a wide range of topics including: Agricultural finance, Agricultural policy related to agricultural finance and risk issues, Agricultural lending and credit issues, Farm credit, Businesses and financial risks affecting agriculture and agribusiness, Agricultural policies affecting farm or agribusiness risks and profitability, Risk management strategies including the use of futures and options, Rural credit in developing economies, Microfinance and microcredit applied to agriculture and rural development, Financial efficiency, Agriculture insurance and reinsurance. Agricultural Finance Review is committed to research addressing (1) factors affecting or influencing the financing of agriculture and agribusiness in both developed and developing nations; (2) the broadest aspect of risk assessment and risk management strategies affecting agriculture; and (3) government policies affecting farm profitability, liquidity, and access to credit.
期刊最新文献
Multi-step commodity forecasts using deep learning Regional analysis of agricultural bank liquidity Data-driven determination of plant growth stages for improved weather index insurance design Utilizing FSA conservation loan programs to support farm conservation activities Evaluation of alternative farm safety net program combination strategies
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1