4.7 Article

Towards decadal soil salinity mapping using Landsat time series data

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ELSEVIER
DOI: 10.1016/j.jag.2016.05.009

Keywords

Soil salinization; Yellow River Delta; Landsat; PLSR; Sensor intercalibration; Temporal variation

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Funding

  1. National Natural Science Foundation of China [41471352]
  2. talent introduction project [NIGLAS2015QD08]
  3. Natural Science Foundation of Jiangsu Province, China [BK20131056]

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Salinization is one of the major soil problems around the world. However, decadal variation in soil salinization has not yet been extensively reported. This study exploited thirty years (1985-2015) of Landsat sensor data, including Landsat-4/5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operational Land Imager), for monitoring soil salinity of the Yellow River Delta, China. The data were initially corrected for atmospheric effects, and then matched the spectral bands of EO-1 (Earth Observing One) ALI (Advanced Land Imager). Subsequently, soil salinity maps were derived with a previously developed PLSR (Partial Least Square Regression) model. On intra-annual scale, the retrievals showed that soil salinity increased in February, stabilized in March, and decreased in April. On inter-annual scale, soil salinity decreased within 1985-2000 (-0.74 g kg(-1)/10a, p < 0.001), and increased within 2000-2015 (0.79 g kg(-1)/10a, p < 0.001). Our study presents a new perspective for use of multiple Landsat data in soil salinity retrieval, and further the understanding of soil salinization development over the Yellow River Delta. (C) 2016 Elsevier B.V. All rights reserved.

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