A spatiotemporal shape model fitting method for within-season crop phenology detection

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL ISPRS Journal of Photogrammetry and Remote Sensing Pub Date : 2024-08-30 DOI:10.1016/j.isprsjprs.2024.08.009
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Abstract

Crop phenological information must be reliably acquired earlier in the growing season to benefit agricultural management. Although the popular shape model fitting (SMF) method and its various improved versions (e.g., SMF by the Separate phenological stage, SMF-S) have been successfully applied to after-season crop phenology detection, these existing methods cannot be applied to within-season crop phenology detection. This discrepancy arises due to the fact that, in the within-season scenario, phenological stages can beyond the defined cut-off time. Consequently, enhancing the alignment of the vegetation index (VI) curve segments prior to the cut-off time does not necessarily guarantee accurate within-season phenological detection. To resolve this issue, a new method named spatiotemporal shape model fitting (STSMF) was developed. STSMF does not seek to optimize the local curve matching between the target pixel and the shape model; instead, it determines similar local VI trajectories in the neighboring pixels of previous years. The within-season phenology of the target pixel was thus estimated from the corresponding phenological stage of the determined local VI trajectories. When compared with ground phenology observations, STSMF outperformed the existing SMF and SMF-S which were modified for the within-season scenario (SMFws and SMFSws) with the smallest mean absolute differences (MAE) between observed phenological stages and their corresponding model estimates. The MAE values averaged over all phenological stages for STSMF, SMFSws, and SMFws were 9.8, 12.4, and 27.1 days at winter wheat stations; 8.4, 14.9, and 55.3 days at corn stations; and 7.9, 12.4, and 64.6 days at soybean stations, respectively. Intercomparisons between after-season and within-season regional phenology maps also demonstrated the superior performance of STSMF (e.g., correlation coefficients for STSMF and SMFSws are 0.89 and 0.80 at the maturity stage of winter wheat). Furthermore, the performance of STSMF was less affected by the detection time and the determination of shape models. In conclusion, the straightforward, effective, and stable nature of STSMF makes it suitable for within-season detection of agronomic phenological stages.

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用于作物季内物候检测的时空形状模型拟合方法
作物物候信息必须在生长季节早期可靠获取,才能有利于农业管理。尽管流行的形状模型拟合(SMF)方法及其各种改进版本(例如,SMF by the Separate phenological stage,SMF-S)已成功应用于作物季后物候检测,但这些现有方法无法应用于作物季内物候检测。造成这种差异的原因是,在季内情况下,物候期可能会超出规定的截止时间。因此,在截止时间之前加强植被指数(VI)曲线段的对齐并不一定能保证季内物候检测的准确性。为了解决这个问题,我们开发了一种名为时空形状模型拟合(STSMF)的新方法。STSMF 并不寻求优化目标像素与形状模型之间的局部曲线匹配,而是确定相邻像素往年的相似局部 VI 轨迹。因此,目标像元的季内物候是根据确定的局部 VI 轨迹的相应物候阶段估算的。与地面物候观测结果相比,STSMF 的表现优于现有的 SMF 和 SMF-S(SMFws 和 SMFSws),后者针对季内情景进行了修改,观测到的物候阶段与其相应的模型估计值之间的平均绝对差值(MAE)最小。STSMF、SMFSws 和 SMFws 在所有物候期的平均 MAE 值在冬小麦站分别为 9.8、12.4 和 27.1 天;在玉米站分别为 8.4、14.9 和 55.3 天;在大豆站分别为 7.9、12.4 和 64.6 天。季后和季内区域物候图之间的相互比较也证明了 STSMF 的卓越性能(例如,在冬小麦成熟期,STSMF 和 SMFSws 的相关系数分别为 0.89 和 0.80)。此外,STSMF 的性能受检测时间和形状模型确定的影响较小。总之,STSMF 简单、有效、稳定的特性使其适用于农艺物候期的季内检测。
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来源期刊
ISPRS Journal of Photogrammetry and Remote Sensing
ISPRS Journal of Photogrammetry and Remote Sensing 工程技术-成像科学与照相技术
CiteScore
21.00
自引率
6.30%
发文量
273
审稿时长
40 days
期刊介绍: The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive. P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields. In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.
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