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Remote Sens. 2016, 8(4), 269; doi:10.3390/rs8040269

Corn Response to Climate Stress Detected with Satellite-Based NDVI Time Series

Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA
Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA
Author to whom correspondence should be addressed.
Academic Editors: Zhongbo Su, Yijian Zeng, Zoltan Vekerdy, Parth Sarathi Roy and Prasad S. Thenkabail
Received: 22 January 2016 / Revised: 23 February 2016 / Accepted: 17 March 2016 / Published: 23 March 2016
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Corn growth conditions and yield are closely dependent on climate variability. Leaf growth, measured as the leaf area index, can be used to identify changes in crop growth in response to climate stress. This research was conducted to capture patterns of spatial and temporal corn leaf growth under climate stress for the St. Joseph River watershed, in northeastern Indiana. Leaf growth is represented by the Normalized Difference Vegetative Index (NDVI) retrieved from multiple years (2000–2010) of Landsat 5 TM images. By comparing NDVI values for individual image dates with the derived normal curve, the response of crop growth to environmental factors is quantified as NDVI residuals. Regression analysis revealed a significant relationship between yield and NDVI residual during the pre-silking period, indicating that NDVI residuals reflect crop stress in the early growing period that impacts yield. Both the mean NDVI residuals and the percentage of image pixels where corn was under stress (risky pixel rate) are significantly correlated with water stress. Dry weather is prone to hamper potential crop growth, with stress affecting most of the observed corn pixels in the area. Oversupply of rainfall at the end of the growing season was not found to have a measurable effect on crop growth, while above normal precipitation earlier in the growing season reduces the risk of yield loss at the watershed scale. The spatial extent of stress is much lower when precipitation is above normal than under dry conditions, masking the impact of small areas of yield loss at the watershed scale. View Full-Text
Keywords: temporal and spatial corn growth variability; corn NDVI-climate stress relation; risky cell detection temporal and spatial corn growth variability; corn NDVI-climate stress relation; risky cell detection

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, R.; Cherkauer, K.; Bowling, L. Corn Response to Climate Stress Detected with Satellite-Based NDVI Time Series. Remote Sens. 2016, 8, 269.

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