常春艳, 赵庚星, 李 晋, 王 凌, 王卓然. 黄河三角洲典型生态脆弱区土壤退化遥感反演[J]. 农业工程学报, 2015, 31(9): 127-132. DOI: 10.11975/j.issn.1002-6819.2015.09.020
    引用本文: 常春艳, 赵庚星, 李 晋, 王 凌, 王卓然. 黄河三角洲典型生态脆弱区土壤退化遥感反演[J]. 农业工程学报, 2015, 31(9): 127-132. DOI: 10.11975/j.issn.1002-6819.2015.09.020
    Chang Chunyan, Zhao Gengxing, Li Jin, Wang Ling, Wang Zhuoran. Remote sensing inversion of soil degradation in typical vulnerable ecological region of Yellow River Delta[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(9): 127-132. DOI: 10.11975/j.issn.1002-6819.2015.09.020
    Citation: Chang Chunyan, Zhao Gengxing, Li Jin, Wang Ling, Wang Zhuoran. Remote sensing inversion of soil degradation in typical vulnerable ecological region of Yellow River Delta[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(9): 127-132. DOI: 10.11975/j.issn.1002-6819.2015.09.020

    黄河三角洲典型生态脆弱区土壤退化遥感反演

    Remote sensing inversion of soil degradation in typical vulnerable ecological region of Yellow River Delta

    • 摘要: 黄河三角洲是典型的生态环境脆弱区,土壤质量不高,盐渍化状况普遍,快速准确掌握该区土壤退化状况,对退化土壤恢复重建、可持续利用具有重要意义。该研究选择黄河三角洲垦利县为研究区,以2008年实测数据为依据,通过建立土壤退化评价指标体系,以参评因素权重与隶属度值加权组合构建土壤退化综合指数,在GIS支持下对土壤退化进行了综合评价;采用与实测同时相的TM影像数据,结合不同程度退化土壤光谱特征、土壤退化综合指数与波段灰度值的相关性分析,筛选土壤退化敏感波段,进而构建土壤退化敏感光谱指数,并建立基于敏感光谱指数的土壤退化综合指数反演模型,最终筛选出拟合程度最高的指数模型作为研究区土壤退化的反演模型,对模型进行精度分析,并利用2008年遥感影像验证反演结果;将该反演模型应用于2011年和2013年的遥感影像,并对研究区2008-2013年的土壤退化状况及动态变化进行了分析。结果显示:基于土壤退化综合指数评价结果,研究区土壤退化程度从沿海到内陆呈现由高到低过渡的趋势;TM1、TM2、TM3波段为土壤退化敏感波段,基于此3个波段组合的土壤退化光谱指数构建的土壤退化遥感反演模型有较高的精度,R2为0.7182,其验证均方根误差、相对误差和决定系数分别为0.0241、3.66%和0.6724,反演结果与同年基于实测数据的综合评价结果相一致;研究区2008-2013年土壤退化状况总体变化不大,有逐渐改善趋势。

       

      Abstract: Abstract: The Yellow River Delta is a typical eco-environmental fragile region where soil quality is not high and salinization is universal, and it is of great significance for the rehabilitation and reconstruction of degraded soil to know the situation of degradation soil quickly and accurately in the region. This research chose Kenli County in the Yellow River Delta as the research area and the measured data in 2008 as the basis, and the comprehensive evaluation of soil degradation was carried out based on soil degradation composite index, which was built by weighted combination of soil degradation evaluation index weight and membership value. Using TM image that was at the same time as the measured data, the spectral characteristics of different soil degradation levels were researched, and the correlations between soil degradation composite index and the bands' gray values were analyzed; with the combination of qualitative and quantitative methods, the sensitive bands were screened. Then the sensitive spectral indices of soil degradation were built, based on which the remote sensing inversion model of soil degradation was established, and the exponential model was selected ultimately which had the highest fitting precision. Verified on the accuracy and the inversion results, the model was applied to the remote sensing images in 2011 and 2013, and the soil degradation dynamics were analyzed during 2008-2013 at last. The results showed the lower-degree degradation soil in the study area was far away from the ocean, and degradation degree of soil in close distance from ocean was relatively high; taken altogether, the extent of soil degradation from the coast to the inland in the study area showed a trend from high to low. The sensitive bands were TM1, TM2 and TM3, and the spectral indices of soil degradation based on the combination of these 3 sensitive bands were characteristic spectral indices of soil degradation. The regression function models were built by soil degradation spectral indices and soil degradation composite index, and the exponential model was the best, which had the highest F value and the best fitting. The remote sensing inversion model of exponential form based on the characteristic spectral indices of soil degradation had more higher accuracy, whose R2 was 0.7182, and validation RMSE, relative error and determination coefficient were 0.0241, 3.66% and 0.6724, respectively. By contrast, the inversion results were consistent with the comprehensive evaluation results based on the measured data in the same year; in particular, the inversion results were more ideal in the area where the land types were relatively simple and the spectral information was relatively clear. The condition of soil degradation changed little in the study area during 2008-2013, and the specific performances were that the area of mild degradation soil increased and degradation soil at other grades decreased, a small amount of moderate degradation soil turned into mild, and there was a gradual improvement in the trend as a whole. This study provides technical support for monitoring the degradation soil in the Yellow River Delta, and provides decision-making basis for the sustainable utilization and protection of land resources in this area.

       

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