地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (6): 1118-1130.doi: 10.12082/dqxxkx.2021.200404
管琪卉1(), 丁明军1,2,*(
), 张华1,2, 王鹏1,2
收稿日期:
2020-07-29
修回日期:
2020-12-27
出版日期:
2021-06-25
发布日期:
2021-08-25
通讯作者:
丁明军
作者简介:
管琪卉(1995— ),女,江西赣州人,硕士生,研究方向为土地利用/覆被变化研究。E-mail: guanqihui0825@163.com
基金资助:
GUAN Qihui1(), DING Mingjun1,2,*(
), ZHANG Hua1,2, WANG Peng1,2
Received:
2020-07-29
Revised:
2020-12-27
Online:
2021-06-25
Published:
2021-08-25
Contact:
DING Mingjun
Supported by:
摘要:
时空融合技术是目前解决单一遥感数据源难以同步获取高时空分辨率数据的有效途径。然而,如何设置参数使模型融合效果最佳,如何设置在植被监测中广泛应用的植被指数的融合步骤,进而获得最佳的植被指数时序数据,目前仍不明晰。本文以长江中下游平原地区的典型县域—南昌县为例,基于Landsat和MODIS多时相数据对当前主流时空融合模型—ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model)进行参数敏感性分析,并系统地对比分析了2组融合实验RI(先融合波段反射率后计算植被指数)和IR(先计算植被指数后直接融合)的融合效果。结果表明: ① ESTARFM算法中参数的敏感性在波段反射率、植被指数融合中表现出相似的特征,随着滑动窗口与相似像元数量的增大,融合误差整体呈现出先减小后趋于稳定或增大的趋势;在ESTARFM算法应用中,存在着最佳参数设置范围;② 相较于RI组,IR组模拟结果精度更高(R2RI-NDVI=0.866,R2IR-NDVI=0.953,R2RI-EVI =0.814,R2IR-EVI =0.930),且能够较好地削弱“斑块”现象,更好地表征出细小地物和纹理特征。研究结果为遥感数据时空融合模型在地块破碎、种植制度多变的复杂环境中的应用提供借鉴和参考。
管琪卉, 丁明军, 张华, 王鹏. ESTARFM算法在长江中下游平原地区的适用性研究[J]. 地球信息科学学报, 2021, 23(6): 1118-1130.DOI:10.12082/dqxxkx.2021.200404
GUAN Qihui, DING Mingjun, ZHANG Hua, WANG Peng. Analysis of Applicability about ESTARFM in the Middle-Lower Yangtze Plain[J]. Journal of Geo-information Science, 2021, 23(6): 1118-1130.DOI:10.12082/dqxxkx.2021.200404
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