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- Title
光谱与纹理信息结合的黄河三角洲土壤盐渍化信息提取 ——以垦利区为例.
- Authors
黄静; 赵庚星; 奚雪; 崔昆; 高鹏
- Abstract
Soil salinization is the key problem that restricts the agricultural development in the Yellow River Delta. It is significant to grasp the soil salinization information accurately for the protection and development of land resources. In this study, the Sentinel-2 remote sensing image on April 17th, 2019 in Kenli District, which is the core region of the Yellow River Delta, was used as the data source. Under the softwares ENVI and e Cognition, the GLCM method was used to extract the texture feature information of remote sensing images, such as Second Moment, Contrast, Entropy, and Correlation. Combined with the spectral feature information such as NDVI and SI, the classification of saline soil in the reclamation area was identified by preset classification rules. The results showed that four texture feature statistics of Second Moment, Contrast, Entropy, and Correlation were added, and the spectral information was combined to classify the saline soil in Kenli District. The overall classification accuracy and Kappa coefficient were 92.4% and 0.89, respectively. Compared withthe classification method using only spectral information, the overall classification accuracy was improved by 10.5 percent points. The producer and user precision of each classification category were significantly improved compared with the classification results based only on spectral information. The classification effect of moderate saline soil was the best, and the producer and user precision were the highest, which were 95.0% and 95.9%, respectively. In this study, a method of extracting salinized soil information in coastal areas using remote sensing spectrum combined with texture features was proposed, which improved the classification accuracy of salinized soil and provided a new way for accurately grasping soil salinization information
- Subjects
SOIL salinization; REMOTE sensing; SOIL classification; AGRICULTURAL development; LAND resource; SOIL salinity
- Publication
Journal of Agricultural Resources & Environment / Nongye Ziyuan yu Huanjing Xuebao, 2022, Vol 39, Issue 3, p594
- ISSN
2095-6819
- Publication type
Article
- DOI
10.13254/j.jare.2021.0025