The Spatial Model of Paddy Productivity Based on Environmental Vulnerability in Each Phase of Paddy Planting

Rahmatia Susanti, S. Supriatna, R. Rokhmatulah, M. D. Manessa, A. Poniman, Yoniar Hufan Ramadhani
{"title":"The Spatial Model of Paddy Productivity Based on Environmental Vulnerability in Each Phase of Paddy Planting","authors":"Rahmatia Susanti, S. Supriatna, R. Rokhmatulah, M. D. Manessa, A. Poniman, Yoniar Hufan Ramadhani","doi":"10.14710/geoplanning.8.2.127-136","DOIUrl":null,"url":null,"abstract":"The national primary always growth and increase in line with the increase in population, such as the rise of rice consumption in Indonesia.  Paddy productivity influenced by the physical condition of the land and the declining of those factors can detected from the environmental vulnerability parameters. Purpose of this study was to compile a spatial model of paddy productivity based on environmental vulnerability in each planting phase using the remote sensing and GIS technology approaches. This spatial model is compiled based on the results of the application of two models, namely spatial model of paddy planting phase and paddy productivity. The spatial model of paddy planting phase obtained from the analysis of vegetation index from Sentinel-2A imagery using the random forest classification model. The variables for building the spatial model of the paddy planting phase are a combination of NDVI vegetation index, EVI, SAVI, NDWI, and time variables. The overall accuracy of the paddy planting phase model is 0.92 which divides the paddy planting phase into the initial phase of planting, vegetative phase, generative phase, and fallow phase. The paddy productivity model obtained from environmental vulnerability analysis with GIS using the linear regression method. The variables used are environmental vulnerability variables which consist of hazards from floods, droughts, landslides, and rainfall. Estimation of paddy productivity based on the influence of environmental vulnerability has the best accuracy done at the vegetative phase of 0.63 and the generative phase of 0.61 while in the initial phase of planting cannot be used because it has a weak relationship with an accuracy of 0.35.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoplanning Journal of Geomatics and Planning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/geoplanning.8.2.127-136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

The national primary always growth and increase in line with the increase in population, such as the rise of rice consumption in Indonesia.  Paddy productivity influenced by the physical condition of the land and the declining of those factors can detected from the environmental vulnerability parameters. Purpose of this study was to compile a spatial model of paddy productivity based on environmental vulnerability in each planting phase using the remote sensing and GIS technology approaches. This spatial model is compiled based on the results of the application of two models, namely spatial model of paddy planting phase and paddy productivity. The spatial model of paddy planting phase obtained from the analysis of vegetation index from Sentinel-2A imagery using the random forest classification model. The variables for building the spatial model of the paddy planting phase are a combination of NDVI vegetation index, EVI, SAVI, NDWI, and time variables. The overall accuracy of the paddy planting phase model is 0.92 which divides the paddy planting phase into the initial phase of planting, vegetative phase, generative phase, and fallow phase. The paddy productivity model obtained from environmental vulnerability analysis with GIS using the linear regression method. The variables used are environmental vulnerability variables which consist of hazards from floods, droughts, landslides, and rainfall. Estimation of paddy productivity based on the influence of environmental vulnerability has the best accuracy done at the vegetative phase of 0.63 and the generative phase of 0.61 while in the initial phase of planting cannot be used because it has a weak relationship with an accuracy of 0.35.
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
基于环境脆弱性的水稻种植各阶段生产力空间模型
国家的初级消费总是随着人口的增加而增长和增加,例如印度尼西亚大米消费量的增加。从环境脆弱性参数中可以看出稻田生产力受土地物理条件的影响及其变化趋势。利用遥感和GIS技术手段,构建基于环境脆弱性的水稻种植期生产力空间模型。该空间模型是在水稻种植期空间模型和水稻生产力空间模型应用结果的基础上编制的。利用随机森林分类模型对Sentinel-2A影像的植被指数进行分析,得到水稻种植期的空间模型。构建水稻种植期空间模型的变量为NDVI植被指数、EVI、SAVI、NDWI和时间变量的组合。水稻种植期模型的总体精度为0.92,将水稻种植期分为种植初期、营养期、生殖期和休耕期。利用GIS进行环境脆弱性分析,采用线性回归方法建立了水稻生产力模型。使用的变量是环境脆弱性变量,包括洪水、干旱、山体滑坡和降雨的危害。基于环境脆弱性影响的水稻生产力估算在营养期和生殖期精度最高,分别为0.63和0.61,而在种植初期与0.35的精度关系较弱,不能使用。
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
Geoplanning Journal of Geomatics and Planning
Geoplanning Journal of Geomatics and Planning Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.00
自引率
0.00%
发文量
5
审稿时长
4 weeks
期刊最新文献
An Application of Cellular Automata (CA) and Markov Chain (MC) Model in Urban Growth Prediction: A case of Surat City, Gujarat, India The Effects of Green Open Spaces on Microclimate and Thermal Comfort in Three Integrated Campus in Yogyakarta, Indonesia Assessing Vulnerability of Agriculture to Drought in East Java, Indonesia: Application of GIS and AHP Impact Deforestation on Land Surface Temperature: A Case Study Highland Kundasang, Sabah Shoreline Dynamics in the Very Small Islands of Karimunjawa – Indonesia: A Preliminary Study
×
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