Remote sensing and statistical analyses for exploration and prediction of soil salinity in a vulnerable area to seawater intrusion

土壤盐分 盐度 归一化差异植被指数 环境科学 VNIR公司 土壤水分 土壤科学 土工试验 决定系数 线性回归 多元统计 水文学(农业) 遥感 数学 统计 气候变化 地质学 海洋学 岩土工程 高光谱成像
作者
Hazem T. Abd El-Hamid,Fahad Alshehri,Ahmed El-Zeiny,Hoda Nour-Eldin
出处
期刊:Marine Pollution Bulletin [Elsevier BV]
卷期号:187: 114555-114555 被引量:13
标识
DOI:10.1016/j.marpolbul.2022.114555
摘要

Soils along the Egyptian coast are vulnerable to environmental degradation and soil salinity problems. The main objective of this study is to identify and rapidly predict salt affected soils using remote sensing data and multivariate statistical analysis. To achieve this objective, the Operational Land Imager 8 (OLI) of Landsat imagery acquired in March 2022 was processed through the Maximum Likelihood classifier to assess Landscape features and to produce Normalized difference salinity index (NDSI) and normalized difference vegetation index (NDVI). Water and soil samples were collected from 13 field sites as ground truth data and to investigate representative physical and chemical properties. Linear regression model was used to predict soil salinity while soil parameters were mapped using Inverse Distance Weight (IDW) in ArcGIS 10.5. In order to explore the soil salinity content using VNIR-SWIR spectra, this work investigated the potential of Partial least squares regression (PLS regression) and SVM (Support vector machine). For simulating salinity in the investigated area, a total number of 65 different sites were identified considering that almost 75 % (50 sites) were used to develop the model and 25 % (15 sites) for validation of the established model. The results indicated that EC levels of water samples are not suitable for irrigation (> 3 mS/cm). Majority of the collected soil samples represent saline-alkaline soils. NDSI ranged from -0.83 to 0.57 with mean of -0.25. Based on the variance of components, 90 % of data were obtained from the first three PCA. The PLS model's R2 score of 0.763 and extremely low p value indicates how well it predicts soil salinity. SVM model R2, on the other hand, is 0.719. Further, Ca++ and Mg++ are the main significant parameters selected in the predicted model. This shows that remote sensing data and multivariate analysis are very important tools to map spatial variation and predict soil salinity. The developed model for salinity considered both the spectral retrieved parameters and lab analyses of cations giving higher accuracy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
xiaofeng5838完成签到,获得积分10
刚刚
ronnie完成签到,获得积分10
刚刚
3秒前
寒冷芷蕊完成签到,获得积分20
3秒前
3秒前
Jane完成签到,获得积分10
3秒前
一氧化二氢完成签到,获得积分10
9秒前
凡事发生必有利于我完成签到,获得积分10
10秒前
yihaiqin完成签到 ,获得积分10
14秒前
轩辕剑身完成签到,获得积分0
14秒前
coolkid完成签到 ,获得积分0
15秒前
你怎么那么美完成签到,获得积分10
15秒前
游艺完成签到 ,获得积分10
18秒前
冬月完成签到 ,获得积分10
18秒前
薛乎虚完成签到 ,获得积分10
19秒前
20秒前
大胖完成签到,获得积分10
20秒前
野火197完成签到,获得积分10
24秒前
25秒前
量子星尘发布了新的文献求助10
28秒前
April完成签到,获得积分10
28秒前
周舟完成签到 ,获得积分10
31秒前
V_I_G完成签到 ,获得积分10
32秒前
nick完成签到,获得积分10
33秒前
高高高完成签到 ,获得积分10
36秒前
彪壮的亦瑶完成签到 ,获得积分10
37秒前
科研通AI2S应助科研通管家采纳,获得10
39秒前
Perry应助科研通管家采纳,获得60
39秒前
Akim应助科研通管家采纳,获得10
39秒前
鱼雷完成签到,获得积分10
40秒前
廿伊发布了新的文献求助10
42秒前
我是125完成签到,获得积分10
44秒前
依人如梦完成签到 ,获得积分10
45秒前
46秒前
PDIF-CN2完成签到,获得积分10
50秒前
雪雪完成签到 ,获得积分10
51秒前
52秒前
Willow完成签到,获得积分10
55秒前
研研研完成签到,获得积分10
56秒前
大橙子发布了新的文献求助10
58秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038128
求助须知:如何正确求助?哪些是违规求助? 3575831
关于积分的说明 11373827
捐赠科研通 3305610
什么是DOI,文献DOI怎么找? 1819255
邀请新用户注册赠送积分活动 892655
科研通“疑难数据库(出版商)”最低求助积分说明 815022