干旱区生态环境知识资源中心(Arid): Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan

Arid

DOI	10.1371/journal.pone.0259695
	Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan
	Gunal, Elif; Wang, Xiukang; Kilic, Orhan Mete; Budak, Mesut; Al Obaid, Sami; Ansari, Mohammad Javed; Brestic, Marian
通讯作者	Gunal, E (corresponding author)，Tokat Gaziosmanpasa Univ, Fac Agr, Dept Soil Sci & Plant Nutr, Tokat, Turkey. ; Wang, XK (corresponding author)，Yanan Univ, Coll Life Sci, Yanan, Peoples R China.
来源期刊	PLOS ONE
ISSN	1932-6203
出版年	2021
卷号	16 期号:11
英文摘要	Soil salinity is the most common land degradation agent that impairs soil functions, ecosystem services and negatively affects agricultural production in arid and semi-arid regions of the world. Therefore, reliable methods are needed to estimate spatial distribution of soil salinity for the management, remediation, monitoring and utilization of saline soils. This study investigated the potential of Landsat 8 OLI satellite data and vegetation, soil salinity and moisture indices in estimating surface salinity of 1014.6 ha agricultural land located in Dushak, Turkmenistan. Linear regression model was developed between land measurements and remotely sensed indicators. A systematic regular grid-sampling method was used to collect 50 soil samples from 0-20 cm depth. Sixteen indices were extracted from Landsat-8 OLI satellite images. Simple and multivariate regression models were developed between the measured electrical conductivity values and the remotely sensed indicators. The highest correlation between remote sensing indicators and soil EC values in determining soil salinity was calculated in SAVI index (r = 0.54). The reliability indicated by R2 value (0.29) of regression model developed with the SAVI index was low. Therefore, new model was developed by selecting the indicators that can be included in the multiple regression model from the remote sensing indicators. A significant (r = 0.74) correlation was obtained between the multivariate regression model and soil EC values, and salinity was successfully mapped at a moderate level (R2: 0.55). The classification of the salinity map showed that 21.71% of the field was non-saline, 29.78% slightly saline, 31.40% moderately saline, 15.25% strongly saline and 1.44% very strongly. The results revealed that multivariate regression models with the help of Landsat 8 OLI satellite images and indices obtained from the images can be used for modeling and mapping soil salinity of small-scale lands.
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000755305800041
WOS关键词	METHODS PLSR ; INDEXES ; IMAGES
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/375846
作者单位	[Gunal, Elif] Tokat Gaziosmanpasa Univ, Fac Agr, Dept Soil Sci & Plant Nutr, Tokat, Turkey; [Wang, Xiukang] Yanan Univ, Coll Life Sci, Yanan, Peoples R China; [Kilic, Orhan Mete] Tokat Gaziosmanpasa Univ, Arts & Sci Fac, Geog Dept, Tokat, Turkey; [Budak, Mesut] Siirt Univ, Agr Fac, Soil Sci & Plant Nutr Dept, Siirt, Turkey; [Al Obaid, Sami] King Saud Univ, Coll Sci, Dept Bot & Microbiol, Riyadh, Saudi Arabia; [Ansari, Mohammad Javed] Mahatma Jyotiba Phule Rohilkhand Univ, Hindu Coll Moradabad, Dept Bot, Bareilly, Uttar Pradesh, India; [Brestic, Marian] Slovak Univ Agr, Dept Plant Physiol, Nitra, Slovakia
推荐引用方式 GB/T 7714	Gunal, Elif,Wang, Xiukang,Kilic, Orhan Mete,et al. Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan[J],2021,16(11).
APA	Gunal, Elif.,Wang, Xiukang.,Kilic, Orhan Mete.,Budak, Mesut.,Al Obaid, Sami.,...&Brestic, Marian.(2021).Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan.PLOS ONE,16(11).
MLA	Gunal, Elif,et al."Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan".PLOS ONE 16.11(2021).