Harmonized in situ JECAM datasets for agricultural land use mapping and monitoring in tropical countries

A. Jolivot, V. Lebourgeois, M. Ameline, Valérie Andriamanga, Beatriz Bellón, Mathieu Castets, A. Crespin-Boucaud, P. Defourny, Santiana Diaz, M. Dièye, S. Dupuy, R. Ferraz, R. Gaetano, M. Gély, C. Jahel, Bertin Kabore, C. Lelong, G. le Maire, L. Leroux, D. Lo Seen, Mary Muthoni, B. Ndao, T. Newby, Cecília Lira Melo de Oliveira Santos, Eloise Rasoamalala, M. Simões, I. Thiaw, Alice Timmermans, A. Tran, A. Bégué
{"title":"Harmonized in situ JECAM datasets for agricultural land use mapping and monitoring in tropical countries","authors":"A. Jolivot, V. Lebourgeois, M. Ameline, Valérie Andriamanga, Beatriz Bellón, Mathieu Castets, A. Crespin-Boucaud, P. Defourny, Santiana Diaz, M. Dièye, S. Dupuy, R. Ferraz, R. Gaetano, M. Gély, C. Jahel, Bertin Kabore, C. Lelong, G. le Maire, L. Leroux, D. Lo Seen, Mary Muthoni, B. Ndao, T. Newby, Cecília Lira Melo de Oliveira Santos, Eloise Rasoamalala, M. Simões, I. Thiaw, Alice Timmermans, A. Tran, A. Bégué","doi":"10.5194/ESSD-2021-125","DOIUrl":null,"url":null,"abstract":"Abstract. The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural census are often poorly georeferenced, and crop types are difficult to photo-interpret directly from satellite imagery. In this paper, we present nine datasets collected in a standardized manner between 2013 and 2020 in seven tropical and subtropical countries within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative. These quality-controlled datasets are distinguished by in situ data collected at field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crop and 6 817 non-crop) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics, but also, to assess the performances and the robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP .","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth System Science Data Discussions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/ESSD-2021-125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Abstract. The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural census are often poorly georeferenced, and crop types are difficult to photo-interpret directly from satellite imagery. In this paper, we present nine datasets collected in a standardized manner between 2013 and 2020 in seven tropical and subtropical countries within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative. These quality-controlled datasets are distinguished by in situ data collected at field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crop and 6 817 non-crop) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics, but also, to assess the performances and the robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP .
用于热带国家农业土地利用制图和监测的统一原位JECAM数据集
摘要正如在发展中国家和新兴国家所观察到的那样,用于卫星图像分类的作物类型参考数据集的可用性非常有限,无法用于复杂的农业系统。事实上,农业用地是非常动态的,农业普查往往缺乏地理参考,作物类型很难直接从卫星图像中进行照片解释。本文介绍了在国际作物评估与监测联合试验(JECAM)倡议框架下,以标准化方式在2013年至2020年期间在七个热带和亚热带国家收集的9个数据集。这些有质量控制的数据集的特点是由当地专家在现场尺度上收集的现场数据,具有精确的地理坐标,并遵循共同的协议。总的来说,数据集完成了27074个多边形(20257个作物和6817个非作物),以详细的关键词记录。这些数据集可用于制作和验证热带地区的农业用地地图,也可用于评估大范围热带农业系统中农田和作物类型/做法分类方法的性能和稳健性。该数据集可在https://doi.org/10.18167/DVN1/P7OLAP上获得。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信