2021
DOI: 10.3390/rs13091615
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Detecting Recent Crop Phenology Dynamics in Corn and Soybean Cropping Systems of Kentucky

Abstract: Accurate phenological information is essential for monitoring crop development, predicting crop yield, and enhancing resilience to cope with climate change. This study employed a curve-change-based dynamic threshold approach on NDVI (Normalized Differential Vegetation Index) time series to detect the planting and harvesting dates for corn and soybean in Kentucky, a typical climatic transition zone, from 2000 to 2018. We compared satellite-based estimates with ground observations and performed trend analyses of… Show more

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Cited by 8 publications
(3 citation statements)
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“…The accurate analysis of crop yield is essential for farmers for crop delivery estimates, crop insurance, planning harvest, and financial budgeting [29]. There are several methods to calculate crop yield, but it is generally defined and majored as production per unit of a specific area [30], as shown in Equation ( 2).…”
Section: Crop-yield Analysismentioning
confidence: 99%
“…The accurate analysis of crop yield is essential for farmers for crop delivery estimates, crop insurance, planning harvest, and financial budgeting [29]. There are several methods to calculate crop yield, but it is generally defined and majored as production per unit of a specific area [30], as shown in Equation ( 2).…”
Section: Crop-yield Analysismentioning
confidence: 99%
“…In many previous studies, remote sensing data were used for surface vegetation or crop phenology feature extraction [27,35,36]; various vegetation phenology detection methods have been developed using the MCD12Q2 product as a source of crop phenology or vegetation data. There have been fewer studies using MCD12Q2 as a direct source of vegetation or crop parameter data [37,38].…”
Section: Feasibility Of Using Remote Sensing Phenology Products To Ex...mentioning
confidence: 99%
“…Meroni et al (2019) e Hansen et al (2008 integraram dados MODIS e do satélite Land Remote Sensing Satellite (LANDSAT)para monitorar a mudança da cobertura florestal na Bacia do Congo. Em escala local, Yang et al (2021) utilizaram dados NDVI -MODIS para analisar tendências espaço-temporais dos estágios fenológicos das culturas de milho e soja, em um polígono no estado do Kentucky, nos Estados Unidos da América.…”
Section: Introductionunclassified