利用MERIS陆地叶绿素指数(MTCI)时间序列估算安达卢西亚小麦收成

IF 0.4 Q4 REMOTE SENSING Revista de Teledeteccion Pub Date : 2018-06-29 DOI:10.4995/raet.2018.8891
V. Egea-Cobrero, V. Rodriguez-Galiano, E. Sánchez-Rodríguez, M. García-Pérez
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引用次数: 1

摘要

小麦净初级产量与卫星影像植被指数之间存在一定的关系。大多数小麦生产研究使用归一化植被指数(NDVI)来估计小麦和其他作物的产量和产量。一方面,很少有研究利用MERIS陆地叶绿素指数(MTCI)在区域水平上确定作物产量和产量。这可能是由于MERIS缺乏连续性。另一方面,哨兵2号的出现为MTCI的研究和应用开辟了新的可能性。本研究建立了两个实证模型来估算安达卢西亚地区的小麦产量和产量。为此,该研究使用了MTCI植被指数的完整时间序列(2006-2011年的每周图像),该序列来自与安达卢西亚农业和渔业统计年鉴(AEAP-Anuario de estadísticas agrarias y pesqueras de Andalucía)相关的中分辨率成像光谱仪(MERIS)传感器。为了建立这些模型,需要确定工厂的最佳发展期,以及以该最佳发展期为参考的MTCI值的基于时间的聚合,以及与指数的关系。利用农业地块地理信息系统(SIGPAC-Sistema de información geográfica de parcelas agrícolas)的覆盖范围,通过空间聚合直接观察生产和产量,并请求共同农业政策(CAP)援助。结果表明,MTCI指数与AEAP采集的产量和单产数据在95%置信水平上呈显著相关(R2 =0.81, R2 =0.57)。
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Estimación de la cosecha de trigo en Andalucía usando series temporales de MERIS Terrestrial Chlorophyll Index (MTCI)
There is a relationship between net primary production of wheat and vegetation indices obtained from satellite imaging. Most wheat production studies use the Normalised Difference Vegetation Index (NDVI) to estimate the production and yield of wheat and other crops. On the one hand, few studies use the MERIS Terrestrial Chlorophyll Index (MTCI) to determine crop yield and production on a regional level. This is possibly due to a lack of continuity of MERIS. On the other hand, the emergence of Sentinel 2 open new possibilities for the research and application of MTCI. This study has built two empirical models to estimate wheat production and yield in Andalusia. To this end, the study used the complete times series (weekly images from 2006–2011) of the MTCI vegetation index from the Medium Resolution Imaging Spectrometer (MERIS) sensor associated with the Andalusian yearbook for agricultural and fishing statistics (AEAP—Anuario de estadísticas agrarias y pesqueras de Andalucía). In order to build these models, the optimal development period for the plant needed to be identified, as did the time-based aggregation of MTCI values using said optimal period as a reference, and relation with the index, with direct observations of production and yield through spatial aggregation using coverage from the Geographic Information System for Agricultural Parcels (SIGPAC—Sistema de información geográfica de parcelas agrícolas) and requests for common agricultural policy (CAP) assistance. The obtained results indicate a significant association between the MTCI index and the production and yield data collected by AEAP at the 95% confidence level (R2 =0.81 and R2 =0.57, respectively).
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来源期刊
Revista de Teledeteccion
Revista de Teledeteccion REMOTE SENSING-
CiteScore
1.80
自引率
14.30%
发文量
11
审稿时长
10 weeks
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