利用 Sentinel-2 和气象数据检测谷物产量损失并确定损失原因:南澳大利亚案例研究

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL ISPRS Journal of Photogrammetry and Remote Sensing Pub Date : 2024-05-30 DOI:10.1016/j.isprsjprs.2024.05.021
Keke Duan , Anton Vrieling , Michael Schlund , Uday Bhaskar Nidumolu , Christina Ratcliff , Simon Collings , Andrew Nelson
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引用次数: 0

摘要

极端天气会影响作物产量。遥感技术可帮助检测作物受损情况,并估算大范围极端天气造成的产量损失。我们提出了一种可扩展的新方法,用于预测亚田块层面的当季产量损失,并将其归因于极端天气。为了评估我们的方法的潜力,我们利用 2017 年至 2022 年的数据对南澳大利亚的冬季谷物围场进行了概念验证案例研究。为了检测整个生长季节的作物生长异常,我们将来自哨兵-2 的双波段增强植被指数 (EVI2) 时间序列与热时间进行了比对。预期和观测到的 EVI2 时间序列之间的偏差被定义为作物损害指数(CDI)。我们评估了 CDI 在特定物候窗口内预测产量损失的性能。最后,通过比较 CDI 大幅上升与不同极端天气指标的关系,我们探讨了哪些(组合)极端天气事件可能是造成减产的原因。我们发现,热时间的使用减小了 EVI2 时间序列在不同年份之间的时间偏差,从而有效地构建了典型的无压力作物生长曲线。与基于日历日期的时间序列相比,基于热时间的 EVI2 时间序列能更好地预测减产。小麦和大麦的 R2 分别为 0.83 和 0.91。最后,CDI 曲线和极端天气指数的综合分析有助于及时发现与天气相关的作物损害原因,同时还能捕捉子田块层面作物损害归因的空间变化。所提出的框架为作物损害的早期预警以及近实时地将损害归因于极端天气提供了基础,这将有助于采取适当的作物保护策略。
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Detection and attribution of cereal yield losses using Sentinel-2 and weather data: A case study in South Australia

Weather extremes affect crop production. Remote sensing can help to detect crop damage and estimate lost yield due to weather extremes over large spatial extents. We propose a novel scalable method to predict in-season yield losses at the sub-field level and attribute these to weather extremes. To assess our method’s potential, we conducted a proof-of-concept case study on winter cereal paddocks in South Australia using data from 2017 to 2022. To detect crop growth anomalies throughout the growing season, we aligned a two-band Enhanced Vegetation Index (EVI2) time series from Sentinel-2 with thermal time. The deviation between the expected and observed EVI2 time series was defined as the Crop Damage Index (CDI). We assessed the performance of the CDI within specific phenological windows to predict yield loss. Finally, by comparing instances of substantial increase in CDI with different extreme weather indicators, we explored which (combinations of) extreme weather events were likely responsible for the experienced yield reduction. We found that the use of thermal time diminished the temporal deviation of EVI2 time series between years, resulting in the effective construction of typical stress-free crop growth curves. Thermal-time-based EVI2 time series resulted in better prediction of yield reduction than those based on calendar dates. Yield reduction could be predicted before grain-filling (approximately two months before harvest) with an R2 of 0.83 for wheat and 0.91 for barley. Finally, the combined analysis of CDI curves and extreme weather indices allowed for timely detection of weather-related causes of crop damage, which also captured the spatial variations of crop damage attribution at sub-field level. The proposed framework provides a basis for early warning of crop damage and attributing the damage to weather extremes in near real-time, which should help to adopt appropriate crop protection strategies.

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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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