Rice Crop Monitoring and Yield Assessment

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Introduction

Background

Rice is the second most harvested staple food in the world and the leading staple food in the Asian region. Rice can be contributed to food problems as well as poverty alleviation because millions of small farmers grow millions of hectares of rice in the Asian region and there are landless workers who generate some income by working on these farms. 60% of the global population and 90% of the world rice production is derived from the Asian continent (Geert Claessens).

Rice monitoring and mapping is very important for food security, environmental sustainability, water security, greenhouse gas emission and also economically. Most of the countries in the Asian region use statistical survey method to collect rice paddy data from community level to national level. These statistical data sources have some limitations to meet up the needs of science and policy researchers. They need geospatial databases of rice agriculture with updated spatial and temporal resolution (Xiao, et al., 2006).

Remote Sensing (RS) is becoming an essential tool to monitor, map and observe rice growing over large areas, at repeated time intervals (Son, N.T., et al., 2012). According to review article of Remote Sensing of Rice Crop Areas by Kuenzer, C., & Knauer, K., 2013 Remote Sensing combined with Geographical Information System (GIS), can provide reliable information for a variety of purposes related to rice farming as follows.

Mapping and monitoring the extent of rice growing ecosystems

Monitoring and assessment of rice growth and health status

Assessment of cropping pattern and cropping system efficiency

Estimation of crop-growth related para...

... middle of paper ...

.../isprsarchives-XXXIX-B3-421-2012, 2012.

11. The Landscape ToolBox, Enhanced Vegetation Index (EVI), A joint project of The Nature Conservancy and the USDA Agricultural Research Service.

12. Toshihiro Sakamoto, Masayuki Yokozawa, Hitoshi Toritani, Michio Shibayama, Naoki Ishitsuka, Hiroyuki Ohno, 2005. A crop phenology detection method using time-series MODIS data, Remote Sensing of Environment, Volume 96, Issues 3–4, 30 June 2005, Pages 366-374, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2005.03.008.

13. Xiangming Xiao, Stephen Boles, Steve Frolking, Changsheng Li, Jagadeesh Y. Babu, William Salas, Berrien Moore III, 2006. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images, Remote Sensing of Environment, Volume 100, Issue 1, 15 January 2006, Pages 95-113, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2005.10.004.

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