基于遥感和GIS的印度贾巴尔普尔小麦种植面积估算

U. Rawat, Ankit Yadav, P. Pawar, Aniket Rajput, Devendra Vasht, S. Nema
{"title":"基于遥感和GIS的印度贾巴尔普尔小麦种植面积估算","authors":"U. Rawat, Ankit Yadav, P. Pawar, Aniket Rajput, Devendra Vasht, S. Nema","doi":"10.9734/AJAEES/2021/V39I230533","DOIUrl":null,"url":null,"abstract":"Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing. Original Research Article Rawat et al.; AJAEES, 39(2): 88-94, 2021; Article no.AJAEES.65961 89","PeriodicalId":204208,"journal":{"name":"Asian Journal of Agricultural Extension, Economics and Sociology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India)\",\"authors\":\"U. Rawat, Ankit Yadav, P. Pawar, Aniket Rajput, Devendra Vasht, S. Nema\",\"doi\":\"10.9734/AJAEES/2021/V39I230533\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing. Original Research Article Rawat et al.; AJAEES, 39(2): 88-94, 2021; Article no.AJAEES.65961 89\",\"PeriodicalId\":204208,\"journal\":{\"name\":\"Asian Journal of Agricultural Extension, Economics and Sociology\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Agricultural Extension, Economics and Sociology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/AJAEES/2021/V39I230533\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Agricultural Extension, Economics and Sociology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/AJAEES/2021/V39I230533","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

利用卫星图像对作物进行制图和分类是一项具有挑战性的任务,它可以最大限度地减少实地考察的复杂性。最近发射的Sentinel-2卫星具有13个光谱波段、较短的重访时间和3种不同分辨率(10 m、20 m和60 m)的测定,此外,图像的免费可用性使其成为植被制图的良好选择。本研究旨在利用印度中央邦贾巴尔普尔(Jabalpur)单一日期Sentinel-2图像对作物进行分类。采用无监督分类方法进行分类。本研究将Sentinel-2的近红外、红、绿、蓝4个光谱波段进行叠加分类。结果表明:小麦种植面积为83.07%;克/脉冲占14.64%;其他作物,2.28%。利用Sentinel-2影像进行分类的总体准确率为85.71%,总体Kappa Statistics为0.819%。因此,本研究发现,Sentinel-2在贾巴尔普尔农业区的遥感制图中具有很大的潜力。Rawat et al.;生物工程学报,39(2):88-94,2021;文章no.AJAEES。65961 89
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India)
Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing. Original Research Article Rawat et al.; AJAEES, 39(2): 88-94, 2021; Article no.AJAEES.65961 89
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Contribution of Agricultural Manufacturing in the Egyptian Economic Growth: Kaldor's Hypotheses Financial Feasibility of Poultry Layer Farms in Chittoor District, India Impact of Front Line Demonstration on Yield and Economics of Okra [Abelmoschus esculentus (L.)] in Banswara District of Rajasthan Status of Rural Women in Dairy Farming in Amritsar District of Punjab A Comparative Economic Analysis of Tulsi and Other Competitive Crops in Central Part of India
×
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