改善时间序列土地覆被产品的时空不一致性

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Ling Zhu, Jun Liu, Shuyuan Jiang, Jingyi Zhang
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引用次数: 0

摘要

近年来,时间序列土地覆被产品发展迅速。然而,传统的分类策略很少考虑时间的连续性和空间的一致性,导致多期产品之间存在不合理的变化。针对存在的问题,本文提出了矩阵分解模型和优化的隐马尔可夫模型(HMM)来提高时间序列土地覆被图的一致性。本文还将结果与时空窗口滤波模型进行了比较。在奇异值分解(SVD)模型中引入空间权重信息,结合图像的特征值和特征向量构建回归模型,预测不合理的变量像素,完成矩阵分解模型的构建。为了解决依赖专家经验和缺乏空间关系这两个问题,本文对模型进行了优化,提出了 HMM 土地覆被转换(HMM_LCT)模型。矩阵分解模型和 HMM_LCT 模型的总体准确率分别为 90.74% 和 89.87%。研究发现,矩阵分解模型的一致性调整效果优于 HMM_LCT 模型。矩阵分解模型还可以调整土地覆被轨迹,更好地表达地表物体的变化趋势。经过矩阵分解模型的一致性调整后,前 15 类土地覆被轨迹的累计比例达到 99.47%,其中 83.01%为三年未发生变化的稳定地类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvement of Spatio-Temporal Inconsistency of Time Series Land Cover Products
In recent years, time series land cover products have been developed rapidly. However, the traditional classification strategy rarely considers time continuity and spatial consistency, which leads to the existence of unreasonable changes among the multi-period products. In order to solve the existing problems, this paper proposes a matrix decomposition model and an optimized hidden Markov model (HMM) to improve the consistency of the time series land cover maps. It also compares the results with the spatio-temporal window filtering model. The spatial weight information is introduced into the singular value decomposition (SVD) model, and the regression model is constructed by combining the eigenvalues and eigenvectors of the image to predict the unreasonable variable pixels and complete the construction of the matrix decomposition model. To solve the two problems of reliance on expert experience and lack of spatial relationships, this paper optimizes the model and proposes the HMM Land Cover Transition (HMM_LCT) model. The overall accuracy of the matrix decomposition model and the HMM_LCT model is 90.74% and 89.87%, respectively. It is found that the matrix decomposition model has a better effect on consistency adjustment than the HMM_LCT model. The matrix decomposition model can also adjust the land cover trajectory to better express the changing trend of surface objects. After consistent adjustment by the matrix decomposition model, the cumulative proportion of the first 15 types of land cover trajectories reached 99.47%, of which 83.01% were stable land classes that had not changed for three years.
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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