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Remote Sens. 2013, 5(7), 3190-3211;

Remote Sensing Based Detection of Crop Phenology for Agricultural Zones in China Using a New Threshold Method

Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Olympic Village Science Park, W. Beichen Road, Beijing 100101, China
Author to whom correspondence should be addressed.
Received: 5 May 2013 / Revised: 23 June 2013 / Accepted: 24 June 2013 / Published: 1 July 2013
(This article belongs to the Special Issue Advances in Remote Sensing of Agriculture)
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In recent years, the use of high temporal resolution satellite data has been emerging as an important tool to study crop phenology. Most methods to detect phenological events based on satellite data use thresholds to identify key events in the lifecycle of the crop. In this study, a new method was used to define such thresholds for identifying the start and end of the growing season (SOS/EOS) for 43 different agricultural zones in China. The method used 2000–2003 NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data with a spatial resolution of eight kilometers and a temporal resolution of 15 days. Following data pre-processing, time series for the normalized difference vegetation index (NDVI or N), slope of the NDVI curve (S), and difference (D) between the NDVI value and a base NDVI value for bare land without snow were constructed. For each zone, an optimal set of threshold values for N, D, and S was determined, based on the remote sensing data and observed SOS/EOS data for 2003 at 261 agro-meteorological stations. Results were verified by comparing the accuracy of the new proposed NDS threshold method with the results of three other methods for SOS/EOS detection with remote sensing data. The findings of all four methods were compared to in situ SOS/EOS data from 2000 to 2002 for 110 agro-meteorological stations. Results show that the developed NDS threshold method had a significantly higher accuracy compared with other methods. The method is mainly limited by the observed data and the necessity of reestablishing the thresholds periodically. View Full-Text
Keywords: phenology; remote sensing; crops; crop proportion; NDVI; NOAA AVHRR phenology; remote sensing; crops; crop proportion; NDVI; NOAA AVHRR

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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You, X.; Meng, J.; Zhang, M.; Dong, T. Remote Sensing Based Detection of Crop Phenology for Agricultural Zones in China Using a New Threshold Method. Remote Sens. 2013, 5, 3190-3211.

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