Investigation of Spatio-temporal Variations of Soil Salinization in the Yellow River Delta Based on Remote Sensing Data Fusion Technique
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摘要:
目的 研究2005 ~ 2018年黄河三角洲地区土壤盐分在年内和年际尺度上的时空变化特征。 方法 基于2005 ~ 2018年春季覆盖黄河三角洲地区的MODIS和Landsat系列数据,采用增强型自适应反射率时空融合模型(ESTARFM)获得30米分辨率高频地表反射率数据。基于2005年实测土壤盐分数据和Landsat地表反射率数据,采用随机森林方法建立土壤盐分反演模型,反演2005 ~ 2018年黄河三角洲地区春季土壤盐分数据,分析土壤盐分含量的时空演变特征。 结果 ESTARFM融合数据具有较为理想的精度,地表反射率总体误差在4%以内。年内尺度上,2 ~ 4月份黄河三角洲地区土壤盐分含量呈总体下降趋势,3 ~ 4月份存在盐分含量短期回升现象,进入4月份后,土壤盐分含量明显下降,非盐渍土和轻度盐渍土占比增加。年际尺度上,2005 ~ 2018年研究区土壤盐分含量呈先升后降趋势,最大值出现在2009年(4.262 g kg−1),最小值出现在2005年(3.604 g kg−1)。2009年以来,研究区内非盐渍土和轻度盐渍土面积显著增加,盐土面积显著减少,盐渍化程度明显改善。 结论 增强型自适应反射率时空融合模型可用于高频次土壤盐分数据反演,反演结果可加深对土壤盐分年内和年际变化规律的认识。 Abstract:Objective The spatio-temporal variations of soil salt content (SSC) at seasonal and inter-annual scales will be inversed in the Yellow River Delta from 2005 to 2018. Method This study derived 30-m resolution high-frequency surface reflectance data over the Yellow River Delta from 2005 to 2018 with the integration of the Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat series sensors data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). Based on soil sampling data in 2005 and the Landsat-5 Thematic Mapper (TM) surface reflectance data, a random forest model was established to model the relationship between SSC and spectral reflectance. The model was used to estimate multi-temporal SSC data from 2005 to 2018, based on which the spatio-temporal variations in SSC were analyzed. Result The ESTARFM performed well for deriving Landsat-like reflectance data with an overall uncertainty < 4%. On seasonal scales, SSC showed a downward trend from February to April, with an occasional short-term rise in SSC from March to April. From April onwards, SSC decreased significantly, shown as the increasing proportions of non-saline soils and slightly saline soils. On inter-annual scales, SSC first increased and then decreased from 2005–2018. The highest SSC value appeared in 2009 (4.262 g kg−1), and the lowest SSC value appeared in 2005 (3.604 g kg−1). Since 2009, the area of slightly saline soils has increased significantly, which means a substantial improvement in soil salinization. Conclusion The ESTARFM method can be used for high-frequency SSC mapping, which promotes our understanding towards intra- and inter-annual dynamics of soil salinity. -
Key words:
- Yellow River Delta /
- Soil salt content /
- Spatio-temporal variations /
- Data fusion /
- Random Forest
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表 1 盐渍土分级标准[18]
Table 1. Classification standard of saline soils
盐化等级
Level of salinization非盐渍土
Non-saline soil轻度
Slightly中度
Medium重度
Heavy盐土
Saline soil盐分总含量(g kg−1) 0.0 ~ 1.0 1.0 ~ 2.0 2.0 ~ 4.0 4.0 ~ 6.0 > 6.0 表 2 遥感数据类型及获取日期
Table 2. Remotely sensed data and the acquisition date
数据类型
Data type行列号
Row and column年份
Year获取日期
Acquisition dateLandsat-5 TM 121/34 2005 Feb-01, Apr-22 2009 Jan-27, Apr-01, May-03 Landsat-7 ETM + 121/34 2012 Jan-12, Apr-01, Apr-17, May-03 2015 Feb-05, Apr-26 2018 Feb-13, Apr-02, Apr-18, May-04 MCD43A4 h27v05 2005 Feb-01, Feb-17, Mar-05,Mar-21, Apr-06, Apr-22 2009 Jan-27, Feb-12, Feb-28,Mar-16, Apr-01, Apr-17 2012 Jan-12, Feb-13, Feb-29,Mar-16, Apr-01 2015 Feb-05, Feb-21, Mar-09,Mar-25, Apr-10, Apr-26 2018 Feb-13, Mar-01, Mar-17, Apr-02 表 3 Landsat与MODIS传感器波段对应关系
Table 3. Spectral band settings of Landsat and MODIS sensors
TM波段
TM band波长(nm)
WavelengthETM + 波段
ETM + band波长(nm)
WavelengthMODIS波段
MODIS band波长(nm)
WavelengthBand1 450 ~ 520 Band1 450 ~ 515 Band3 459 ~ 479 Band2 520 ~ 600 Band2 525 ~ 605 Band4 545 ~ 565 Band3 630 ~ 690 Band3 630 ~ 690 Band1 620 ~ 670 Band4 760 ~ 900 Band4 750 ~ 900 Band2 841 ~ 876 Band5 1550 ~ 1750 Band5 1550 ~ 1750 Band6 1628 ~ 1652 Band7 2080 ~ 2350 Band7 2090 ~ 2350 Band7 2105 ~ 2155 表 4 不同等级盐渍土在对应年分区间的动态度(%)
Table 4. Dynamic degrees (%) of different levels of saline soils in the corresponding years
年份区间
Year非盐土
Non saline soil轻度
Slightly中度
Medium重度
Heavy盐土
Saline soil2005 ~ 2009 2.1 −14.3 −4.8 −1.8 28.9 2009 ~ 2012 −1.8 −1.8 5.0 7.7 −11.4 2012 ~ 2015 12.0 31.5 −2.7 −10.7 9.0 2015 ~ 2018 5.2 −5.0 −1.1 6.9 −6.3 表 5 不同等级盐渍土间转移矩阵(%)
Table 5. Transfer matrix among different levels of saline soils
类型
Type年份区间
Year非盐渍土
Non saline soil轻度
Slightly中度
Medium重度
Heavy盐土
Saline soil水域及建设用地
Water area and
construction land非盐渍土 2005 ~ 2009 54.1 4.7 5.7 6.1 0.8 1.6 2009 ~ 2012 70.4 3.6 2.5 4.3 1.2 0.7 2012 ~ 2015 70.6 13.1 10.2 5.6 1.1 1.6 2015 ~ 2018 66.3 11.6 9.6 9.5 1.1 1.1 轻度 2005 ~ 2009 8.1 12.3 5.7 1.7 0.9 1.7 2009 ~ 2012 3.2 20.7 7.2 2.7 1.6 2.2 2012 ~ 2015 2.4 25.4 16.0 7.3 2.0 2.3 2015 ~ 2018 5.2 26.2 12.3 4.5 1.1 1.4 中度 2005 ~ 2009 17.3 44.8 35.5 13.2 5.0 8.7 2009 ~ 2012 12.3 53.1 52.1 26.5 8.9 11.4 2012 ~ 2015 8.5 32.8 39.7 27.4 9.9 7.8 2015 ~ 2018 12.4 40.6 44.0 24.1 6.7 6.9 重度 2005 ~ 2009 11.0 21.1 30.0 28.0 13.0 12.9 2009 ~ 2012 9.6 15.2 29.0 41.2 31.0 17.1 2012 ~ 2015 14.3 9.9 18.4 26.3 19.4 10.3 2015 ~ 2018 12.0 11.4 22.7 37.7 28.5 11.5 盐土 2005 ~ 2009 3.3 5.9 12.8 35.0 59.0 17.0 2009 ~ 2012 1.2 1.7 3.6 12.2 37.8 13.1 2012 ~ 2015 1.8 4.5 6.2 20.4 47.5 20.2 2015 ~ 2018 0.8 1.5 2.9 12.4 44.5 16.8 水域及建设用地 2005 ~ 2009 6.2 11.2 10.5 16.0 21.3 58.1 2009 ~ 2012 3.3 5.8 5.6 13.1 19.4 55.5 2012 ~ 2015 2.5 14.2 9.5 13.1 20.2 57.8 2015 ~ 2018 3.3 8.6 8.6 11.8 18.1 62.4 -
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