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利用众包估算射野大小的全球分布。

Estimating the global distribution of field size using crowdsourcing.

机构信息

International Institute for Applied Systems Analysis, ESM, Laxenburg, Austria.

OPC Nantes Métropol, Nantes, France.

出版信息

Glob Chang Biol. 2019 Jan;25(1):174-186. doi: 10.1111/gcb.14492. Epub 2018 Nov 22.

Abstract

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.

摘要

越来越多的证据表明,小农农场对全球粮食生产做出了重大贡献,但目前缺乏关于农业田块大小的空间明确数据。使用遥感自动划分田块大小或使用普查数据估计国家以下一级的平均农场规模是两种已被采用的方法。然而,这两种方法都存在局限性,例如,使用遥感自动划分田块大小尚未在全球范围内实施,而使用普查数据时空间分辨率非常粗糙。本文展示了一种使用众包全球量化和绘制农业田块大小的独特方法。2017 年 6 月开展了一项活动,要求参与者使用 Geo-Wiki 应用程序,从 Google Maps 和 Bing 查看非常高分辨率的卫星图像并进行视觉解释。在活动期间,参与者收集了全球 130 万个独特位置的田块大小数据。利用这个样本,我们制作了迄今为止最精确的全球田块大小地图,并估计了全球、各大洲和各国农业区不同大小田块(从小到大都有)的比例。结果表明,小农农场在全球农业区占比高达 40%,这意味着,与目前全球 12%和 24%的两个不同估计值相比,全球可能有更多的小农农场。全球田块大小地图和众包数据集是公开的,可用于综合评估模型,在不同背景下对农业动态进行比较研究,用于遥感田块大小划分的培训和验证,以及对实现消除饥饿、实现粮食安全和改善营养、促进可持续农业等可持续发展目标做出潜在贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3a4/7379266/c8dd477384c8/GCB-25-174-g001.jpg

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