|本期目录/Table of Contents|

[1]杨培杰,韩保栋,张玉燕,等.Sentinel-2影像结合空间关联随机森林模型反演裸土期耕地土壤全氮含量[J].江苏农业科学,2023,51(11):185-191.
 Yang Peijie,et al.Estimation of soil total nitrogen contents in cultivated land based on Sentinel-2 images and spatial random forest algorithm[J].Jiangsu Agricultural Sciences,2023,51(11):185-191.
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Sentinel-2影像结合空间关联随机森林模型反演裸土期耕地土壤全氮含量(PDF)
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第51卷
期数:
2023年第11期
页码:
185-191
栏目:
农业工程与信息技术
出版日期:
2023-06-05

文章信息/Info

Title:
Estimation of soil total nitrogen contents in cultivated land based on Sentinel-2 images and spatial random forest algorithm
作者:
杨培杰12韩保栋12张玉燕12赵菲12王庆兵12翟晓燕34
1.山东省国土空间生态修复中心,山东济南 250000; 2.自然资源部黄河三角洲土地利用安全野外科学观测研究站,山东滨州 251900;3.枣庄学院旅游与资源环境学院,山东枣庄 277160; 4.黎刹大学,菲律宾曼达卢永市 1552
Author(s):
Yang Peijieet al
关键词:
土壤全氮Sentinel-2影像空间关联随机森林模型裸土期耕地
Keywords:
-
分类号:
X87;S127
DOI:
-
文献标志码:
A
摘要:
为快速准确地获取区域内土壤全氮的含量信息和空间分布特征。选取山东省济南市章丘区刁镇为研究区,系统采集64个土壤样品并获取同期Sentinel-2(哨兵2号)影像数据,进一步利用皮尔逊相关分析法选择土壤全氮的敏感光谱参量作为自变量,测试得到的土壤全氮含量为因变量,分别建立基于随机森林和空间关联随机森林算法的反演模型,完成区域尺度的土壤全氮含量的遥感反演和数字制图。结果表明:哨兵2号影像的多光谱波段与土壤全氮含量相关性较低,通过波段间比值变换能够显著增强土壤全氮含量对光谱信号的响应能力,光谱指数b6/b11b8a/b12b8/b9b8a/b9和(b9-b11)/(b9+b11)对土壤的全氮含量信息最为敏感;空间关联随机森林模型的反演精度指标R2RMSE分别为0.90和0.11,相对比随机森林模型精度分别提升11.11%和26.67%,使反演模型的结构和计算效率均得到了优化;土壤全氮含量在田块尺度上的空间变异较大,与土地利用状况关系密切,村居建筑物周边土壤全氮含量处于低水平(<0.80 g/kg),远离建筑物的大片耕地区域土壤全氮含量则较高(>1.20 g/kg)。哨兵2号影像与空间关联随机森林算法相结合的遥感反演技术可为区域土壤环境信息的监测与制图分析提供有效的方法支持。
Abstract:
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备注/Memo

备注/Memo:
收稿日期:2022-08-11
基金项目:山东省教育厅公派出国留学基金(编号:2019027);环境演变与自然灾害教育部重点实验室开放课题项目(编号:2022-KF-14)。
作者简介:杨培杰(1988—),男,山东费县人,高级工程师,主要研究方向为生态修复和地质环境监测。E-mail:yangpj1232022@163.com。
通信作者:翟晓燕,女,博士,讲师,主要研究方向为生态旅游规划。E-mail:zxy18263230964@126.com。
更新日期/Last Update: 2023-06-05