数字农科院2.0

Interpretable salinization estimation model for Dongying City based on integrated multi-dimensional spectral indices with XGBoost-driven transformations

文献类型： 外文期刊

作者： Jicun Yang;Bing Guo;Miao Lu;Baomin Han;Rui Zhang

作者机构：

关键词： multi-dimensional index combination;soil salinization;spectral transformation;XGBoost

期刊名称： Geomatics, Natural Hazards and Risk

ISSN： 1947-5713

年卷期： 2025 年 16 卷 1 期

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Against the backdrop of intensifying global climate change and anthropogenic activities, soil salinization is becoming increasingly severe, posing a significant threat to agricultural production and sustainable development. This study collected sample data from Dongying City, Shandong Province as the research area, focusing on investigating the effectiveness of combining mixed-scale transformations and high-dimensional spectral indices in model inversion. The research process involved spectral transformations, upon which hybrid transformations were constructed. Subsequently, sensitive spectral bands were identified, leading to the development of two-dimensional and three-dimensional spectral indices. These indices served as feature variables to construct three types of models: Extreme Gradient Boosting (XGBoost), Partial Least Squares Regression (PLSR), and Convolutional Neural Network (CNN). The optimal model was evaluated using SHAP interpretability analysis. The results demonstrate that the proposed processing methods effectively enhance band sensitivity, improve model accuracy and generalization capability. Index operations conducted across different spectral bands can enhance spectral sensitivity characteristics or suppress the influence of noise to some extent. The outcomes provide a theoretical framework for optimizing spectral indices. The analysis reveals the salt-response mechanisms and noise resistance differences among various indices, facilitating the advancement of salinization monitoring towards greater precision, intelligence, and cost-effectiveness.

分类号：

  • 相关文献

[1]基于XGBoost算法的山东烟叶质量预测模型初探. 别瑞,周婷云,周显升,姜滨,周永,邱军,曹建敏. 2022

[2]基于无人机多源遥感数据和机器学习的高通量棉花估产研究. 冯美臣,苏悦,林涛,余汛,宋扬,金秀良. 2025

[3]The salinization process and its response to the combined processes of climate change–human activity in the Yellow River Delta between 1984 and 2022. Bing Guo,Yifeng Liu,Junfu Fan,Miao Lu,Wenqian Zang,Chuan Liu,Baoyu Wang,Xiangzhi Huang,Jibao Lai,Hongwei Wu. 2023

[4]Impacts of land use and salinization on soil inorganic and organic carbon in the middle-lower Yellow River Delta. Yang GUO,Xiujun WANG,Xianglan LI,Minggang XU,Yuan LI,Haonan ZHENG,Yongming LUO,Pete SMITH. 2021

[5]Rare Taxa Drive the Response of Soil Fungal Guilds to Soil Salinization in the Taklamakan Desert. Lin, Litao,Jing, Xin,Lucas-Borja, Manuel Esteban,Shen, Congcong,Wang, Yugang,Feng, Wenting. 2022

[6]Reinforced soil salinization with distance along the river: A case study of the Yellow River Basin. Wang X.,Zhang H.,Zhang Z.,Zhang C.,Zhang K.,Pang H.,Bell S.M.,Li Y.,Chen J.. 2023

[7]Bacillus amyloliquefaciens strain Q1 inoculation enhances salt tolerance of barley seedlings by maintaining the photosynthetic capacity and intracellular Na+/K+ homeostasis. Liu, Hongjiang,Amoanimaa-Dede, Hanna,Zhang, Yanli,Wu, Xiaojian,Deng, Fenglin,Qin, Yuan,Qiu, Haiping,Ouyang, Younan,Wang, Yanli,Zeng, Fanrong. 2024

[8]Subsurface application of organic ameliorant in saline soils increases microbial necromass accumulation in mineral-associated organic matter. Jiashen Song,Hongyuan Zhang,Anna Gunina,Kevin Z. Mganga,Fangdi Chang,Ru Yu,Jie Zhou,Aiping Chen,Yuyi Li. 2025

[9]Assessment of tillage practices in ameliorating salt-affected arable lands: A meta-analysis. Jianyu Tao,Xiaoyuan Liu,Zhongbin Zhang,Xinhua Peng. 2025

[10]Monitoring of Soil Salinization and Analysis of Driving Factors in the Oasis Zone of South Xinjiang. Zhao, Jiahao,Fan, Yanmin,Xuan, Junwei,Shi, Mingjie,Wang, Dejun,Wu, Hongqi,Bi, Yanan,Li, Yunhao. 2025

[11]Comprehensive screening of salt-tolerant rice germplasm using a fuzzy membership and PCA-based evaluation model. Dingsha Jin,Asif Iqbal,Mengshu Huang,Yuqing Liu,Yage Zhang,Youzhen Lin,Liqiong Tang,Xinhua Wang,Junjie Wang,Guangping Cao,Yanchao Xu,Peng Xu,Xiaoning Wang. 2025

[12]The Responses of Extracellular Enzyme Activities to Saline Conditions: A Data Synthesis. Tao, Jianyu,Liu, Xiaoyuan,Chen, Shi. 2025

[13]The CAZyme family regulates soil organic carbon accumulation under amendments application in saline-alkali soil. Bai, Xiaolong,Wu, Jinmin,Zhang, Bangyan,Li, Yuyi,Tian, Feng,Zhao, Hui,Wang, Bin. 2025

[14]Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification. Sun, Ye,Zhao, Zhiyuan,Tong, Hailong,Sun, Baiming,Liu, Yanbiao,Ren, Nanqi,You, Shijie. 2023

[15]HPO-empowered machine learning with multiple environment variables enables spatial prediction of soil heavy metals in coastal delta farmland of China. Yingqiang Song,Dexi Zhan,Zhenxin He,Wenhui Li,Wenxu Duan,Zhongkang Yang,Miao Lu. 2023

[16]Monitoring Land Use Changes in the Yellow River Delta Using Multi-Temporal Remote Sensing Data and Machine Learning from 2000 to 2020. Yunyang Zhu,Linlin Lu,Zilu Li,Shiqing Wang,Yu Yao,Wenjin Wu,Rajiv Pandey,Aqil Tariq,Ke Luo,Qingting Li. 2024

[17]Tree-Structured Parzan Estimator–Machine Learning–Ordinary Kriging: An Integration Method for Soil Ammonia Spatial Prediction in the Typical Cropland of Chinese Yellow River Delta with Sentinel-2 Remote Sensing Image and Air Quality Data. Yingqiang Song,Mingzhu Ye,Zhao Zheng,Dexi Zhan,Wenxu Duan,Miao Lu,Zhenqi Song,Dengkuo Sun,Kaizhong Yao,Ziqi Ding. 2023

[18]Integrated UAV and Satellite Multi-Spectral for Agricultural Drought Monitoring of Winter Wheat in the Seedling Stage. Xiaohui Yang,Feng Gao,Hongwei Yuan,Xiuqing Cao. 2024

[19]Comparative Analysis of Machine Learning Algorithms for Object-Based Crop Classification Using Multispectral Imagery. Madjebi Collela Be,Antsa Sarobidy Randrianantenaina,James E. Kanneh,Yingchun Han,Yaping Lei,Xiaoyu Zhi,Shiwu Xiong,Yahui Jiao,Shilong Shang,Yunzhen Ma,Beifang Yang,Lin Tao,Yabing Li. 2025

[20]A novel approach for predicting aflatoxin B1 production using regression models and whole-cell biosensors in moldy maize and peanut kernels. Lu Sun,Junning Ma,Yongping Jiang,Giorgia Purcaro,Yuanyuan Tian,Gang Wang,Weizhao Li,Bowen Tai,Fuguo Xing. 2025

作者其他论文 更多>>