基于SWCI-NDVI特征空间的县域耕地地力遥感反演

doi:10.13287/j.1001-9332.202101.016

应用生态学报 ›› 2021, Vol. 32 ›› Issue (1): 252-260.doi: 10.13287/j.1001-9332.202101.016

基于SWCI-NDVI特征空间的县域耕地地力遥感反演

李因帅¹, 赵庚星^1*, 王卓然¹, 崔昆¹, 奚雪¹, 窦家聪²

¹山东农业大学资源与环境学院/土肥资源高效利用国家工程实验室, 山东泰安 271018;
²山东省农业技术推广总站, 济南 250013

收稿日期:2020-07-01 接受日期:2020-10-26 出版日期:2021-01-15 发布日期:2021-07-15
通讯作者: * E-mail: zhaogx@sdau.edu.cn
作者简介:李因帅, 男, 1998年生, 硕士研究生。主要从事土地资源与信息研究。E-mail: sdauzhlys@163.com
基金资助:
国家自然科学基金项目(41877003)、山东省重大科技创新工程项目(2019JZZY010724)和山东省“双一流”奖补资金(SYL2017XTTD02)

Remote sensing inversion of cultivated land fertility at county scale based on SWCI-NDVI feature space

LI Yin-shuai¹, ZHAO Geng-xing^1*, WANG Zhuo-ran¹, CUI Kun¹, XI Xue¹, DOU Jia-cong²

¹College of Resources and Environment, Shandong Agricultural University/National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, Tai'an 271018, Shandong, China;
²Shandong General Station of Agricultural Technology Extension, Ji’nan 250013, China

Received:2020-07-01 Accepted:2020-10-26 Online:2021-01-15 Published:2021-07-15
Contact: * E-mail: zhaogx@sdau.edu.cn
Supported by:
National Natural Science Foundation of China (41877003), the Major Scientific and Technological Innovation Project in Shandong Province (2019JZZY010724) and the Supplementary Fund for “Double First-Class” Award in Shandong Province (SYL2017XTTD02).

摘要/Abstract

摘要： 利用遥感反演县域耕地地力状况,快速、准确、高效地实现耕地定级,是区域耕地资源利用与管理的客观需求。本研究以东平县为研究区,利用Landsat-TM卫星影像和耕地地力评价资料,构建以地表含水量指数(SWCI)、归一化植被指数(NDVI)为特征参量的水分植被地力指数(MVFI),进而优选得到最佳反演模型,并在县域空间上进行推广应用和精度验证。结果表明: MVFI与耕地地力综合指数(IFI)的相关系数为-0.753,能综合反映小麦长势、土壤墒情和地力水平,具有明确的生物物理意义;最佳反演模型为二次模型,反演精度较高;模型适用于县域耕地地力的反演,反演结果与地力评价结果的空间分布规律和均匀程度相似,高、中、低等级耕地的面积差均低于2.9%。本研究提出的基于特征空间理论的耕地地力遥感反演方法,可有效提高县域耕地地力的评价效率和预测精度。

关键词: 耕地地力, 遥感, 反演模型, 特征空间, 洛伦茨曲线, 基尼系数

Abstract: It is objective needs during utilization and management of regional cultivated land resource to use remote sensing to accurately and efficiently retrieve the status of cultivated land fertility at county level and realize the gradation of cultivated land rapidly. In this study, with Dongping County as a case, using Landsat TM satellite imagery and cultivated land fertility evaluation data, the moisture vegetation fertility index (MVFI) was constructed based on surface water capacity index (SWCI) and normalized difference vegetation index (NDVI), and then the optimal inversion model was optimized to obtain the best inversion model, which was further applied and verified at the county scale. The results showed that the correlation coefficient between MVFI and integrated fertility index (IFI) was -0.753, which could comprehensively reflect the growth of winter wheat, soil moisture and land fertility, and had clear biophysical significance. The best inversion model was the quadratic model, with high inversion accuracy. This model was suitable for the inversion of cultivated land fertility in the county. The spatial distribution and uniformity of the inversion results were similar to the results of soil fertility evaluation. The area differences between the high, medium and low grades were all less than 2.9%. This study provided a remote sensing inversion method of cultivated land fertility based on the feature space theory, which could effectively improve the evaluation efficiency and prediction accuracy of cultivated land fertility at the county scale.

Key words: cultivated land fertility, remote sensing, inversion model, feature space, Lorenz curve, Gini coefficient

李因帅, 赵庚星, 王卓然, 崔昆, 奚雪, 窦家聪. 基于SWCI-NDVI特征空间的县域耕地地力遥感反演[J]. 应用生态学报, 2021, 32(1): 252-260.

LI Yin-shuai, ZHAO Geng-xing, WANG Zhuo-ran, CUI Kun, XI Xue, DOU Jia-cong. Remote sensing inversion of cultivated land fertility at county scale based on SWCI-NDVI feature space[J]. Chinese Journal of Applied Ecology, 2021, 32(1): 252-260.

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基于SWCI-NDVI特征空间的县域耕地地力遥感反演

Remote sensing inversion of cultivated land fertility at county scale based on SWCI-NDVI feature space

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