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Remote Sens. 2014, 6(3), 1938-1953; doi:10.3390/rs6031938
Article

Development of a Remote Sensing-Based “Boro” Rice Mapping System

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Received: 19 November 2013 / Revised: 28 January 2014 / Accepted: 24 February 2014 / Published: 3 March 2014
(This article belongs to the Special Issue Remote Sensing in Food Production and Food Security)
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Abstract

Rice is one of the staple foods across the world, thus information about its production is essential for ensuring food security. Here, our objective was to develop a method for mapping “boro” rice (i.e., cultivated during the months January to May) in a Bangladeshi context. In this paper, we used a Moderate Resolution Imaging Spectroradiometer (MODIS)-derived 16-day composite of normalized difference vegetation index (NDVI) at 250 m spatial resolution in conjunction with ancillary datasets (i.e., land use map, crop calendar, and ground-based rice production information) during the period 2007–2012. The proposed method consisted of three procedures: (i) ISODATA clustering and determining the boro rice signatures in temporal dimension using data from the period 2007–2009; (ii) formulating a mathematical model for extracting the boro rice areas using data from the period 2007–2009; and (iii) model calibration using data from the period 2007–2009 and its validation using data from the period 2010–2012. The implementation of the abovementioned procedures revealed reasonable agreements between the model (i.e., MODIS-based) and ground-based estimates of boro rice area at both country (i.e., percentage error in the range −0.83–1.42%) and district levels (i.e., r2 in the range 0.69–0.89) during the period 2010–2012. Our proposed method demonstrated its effectiveness in mapping rice system at the regional/country scale.
Keywords: Boro rice; MODIS; multi-temporal dataset; normalized difference vegetation index; spatial modelling Boro rice; MODIS; multi-temporal dataset; normalized difference vegetation index; spatial modelling
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.

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Mosleh, M.K.; Hassan, Q.K. Development of a Remote Sensing-Based “Boro” Rice Mapping System. Remote Sens. 2014, 6, 1938-1953.

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