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Remote Sens. 2017, 9(3), 238; doi:10.3390/rs9030238

Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions

1
Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, 310058 Hangzhou, China
2
Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Natural Resources and Environmental Science, Zhejiang University, 310058 Hangzhou, China
3
Institute of Remote Sensing and Information Technology Application, Zhejiang University, 310058 Hangzhou, China
4
Department of Land Management, School of Public Affairs, Zhejiang University, 310058 Hangzhou, China
5
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, 311121 Hangzhou, China
*
Author to whom correspondence should be addressed.
Academic Editors: Jan Dempewolf, Jyotheshwar Nagol, Min Feng, Clement Atzberger and Prasad Thenkabail
Received: 7 November 2016 / Revised: 20 February 2017 / Accepted: 28 February 2017 / Published: 4 March 2017
View Full-Text   |   Download PDF [4662 KB, uploaded 4 March 2017]   |  

Abstract

Oilseed rape (Brassica napus L.) is one of the three most important oil crops in China, and is regarded as a drought-tolerant oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB) of oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the oilseed rape at the experimental plots. Several representative vegetation indices (VIs) obtained from multiple satellite sensors were compared with the simultaneously-collected oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI) with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77), the smallest root mean square error (RMSE = 104.64 g/m2), and the relative RMSE (rRMSE = 21%). It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the winter oilseed rape growth stages, and can be applied to map the variability of winter oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture. View Full-Text
Keywords: mapping above-ground biomass; high spatial resolution satellite data; parcel scale; waterlogging condition; vegetation indices mapping above-ground biomass; high spatial resolution satellite data; parcel scale; waterlogging condition; vegetation indices
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MDPI and ACS Style

Han, J.; Wei, C.; Chen, Y.; Liu, W.; Song, P.; Zhang, D.; Wang, A.; Song, X.; Wang, X.; Huang, J. Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions. Remote Sens. 2017, 9, 238.

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