整合 S1A 微波遥感和 DSSAT CROPGRO 仿真模型,估算花生面积和产量

IF 4.5 1区 农林科学 Q1 AGRONOMY European Journal of Agronomy Pub Date : 2024-09-13 DOI:10.1016/j.eja.2024.127348
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引用次数: 0

摘要

这项研究旨在证实微波遥感和模拟模型,以有效划定花生种植面积,并通过整合估算产量。作物种植面积和产量估算的近实时信息对决策至关重要。我们下载了 2019 年和 2020 年花生季风季节(6 月至 10 月)整个作物生长期的 S1A SAR 数据,并使用 MAPSCAPE RIICE 软件进行处理,以提取泰米尔纳德邦研究地区的花生种植面积。使用多日期 Sentinel 1 A 合成孔径雷达数据生成的花生光谱分贝曲线显示,播种时花生的分贝最小,豆荚发育阶段达到峰值,之后向成熟期下降。生成的花生面积图的分类准确率分别为 85.2% 和 84.8%,卡帕系数为 0.70,在 2019 年和 2020 年花生季风季节绘制的花生总面积分别为 104343 公顷和 116199 公顷。DSSAT 模型模拟的 LAI 与 2019 和 2020 年 Kharif 季风季节在研究区域 30 个监测点观测到的 LAI 之间的平均吻合度分别为 75.01% 和 84.94%,而产量的吻合度分别为 82.11% 和 83.70%,均方根误差小于 20%。通过同化卫星图像和 DSSAT 模型的 dB,分别估算了花生 LAI 和产量的空间分布。估计的平均空间 LAI 为 2.81 和 3.52,而平均空间豆荚产量为 2124 和 2195 公斤公顷-1,均方根误差均小于 20%。
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Integrating S1A microwave remote sensing and DSSAT CROPGRO simulation model for groundnut area and yield estimation

This study sought to corroborate microwave remote sensing and simulation models to efficiently delineate groundnut cultivation area and to estimate the yield by integration. Near real-time information on crop acreage and yield estimation is essential for making policy decisions. S1A SAR data were downloaded for entire crop growth period of groundnut during Kharif monsoon seasons (June – October) of 2019 and 2020 and were processed using MAPSCAPE RIICE software to extract groundnut cultivated area in the study districts of Tamil Nadu. Spectral dB curve groundnut generated using multi-date Sentinel 1 A SAR data showed a minimum at sowing, reached a peak at the pod development stage and decreased after that towards maturity. Groundnut area map was generated with a classification accuracy of 85.2 and 84.8 per cent with a kappa coefficient of 0.70, and total groundnut area of 104343 and 116199 ha was mapped during Kharif monsoon season 2019 and 2020, respectively. The mean agreement of 75.01 and 84.94 per cent was observed between DSSAT model simulated LAI and observed LAI at thirty monitoring locations in the study area during Kharif monsoon season 2019 and 2020, respectively, whereas agreement for yield was 82.11 and 83.70 per cent with RMSE of less than 20 per cent. Spatial distribution of groundnut LAI and yield was estimated by assimilating dB from satellite image and from DSSAT model, respectively. The estimated mean spatial LAI was 2.81 and 3.52, whereas mean spatial pod yield was 2124 and 2195 Kg ha−1 during Kharif monsoon season 2019 and 2020, respectively with RMSE of less than 20 per cent and R2 for integrating satellite products and simulation model for spatial estimates during both the year was >0.70, it shows the fitness of products towards increased accuracy of estimation.

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来源期刊
European Journal of Agronomy
European Journal of Agronomy 农林科学-农艺学
CiteScore
8.30
自引率
7.70%
发文量
187
审稿时长
4.5 months
期刊介绍: The European Journal of Agronomy, the official journal of the European Society for Agronomy, publishes original research papers reporting experimental and theoretical contributions to field-based agronomy and crop science. The journal will consider research at the field level for agricultural, horticultural and tree crops, that uses comprehensive and explanatory approaches. The EJA covers the following topics: crop physiology crop production and management including irrigation, fertilization and soil management agroclimatology and modelling plant-soil relationships crop quality and post-harvest physiology farming and cropping systems agroecosystems and the environment crop-weed interactions and management organic farming horticultural crops papers from the European Society for Agronomy bi-annual meetings In determining the suitability of submitted articles for publication, particular scrutiny is placed on the degree of novelty and significance of the research and the extent to which it adds to existing knowledge in agronomy.
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