Understanding geographic variation is an important aspect of agricultural research for development. As an integrative discipline, geography has particular strengths to maintain simultaneously in focus the technological, environmental, and socioeconomic aspects of agricultural development.
The key result of IRRI’s work on mapping is “to provide actionable information to policy-makers.”
In recent years, remote-sensing (RS) technology and geographic information systems (GIS) for spatial analysis have become widespread. These technologies can be used to monitor and evaluate agricultural systems to determine where and when rice is grown, as well as where crops are performing well or where they are not.
Mapping and monitoring of the biophysical and socioeconomic characteristics of rice-producing areas is key for developing effective targeting strategies for the dissemination of new technologies and sustainable crop management and diversification options.
Similarly, the identification of regions where there is an opportunity to expand the area of rice production is necessary as an input for policies that will deal with the growing demand for rice.
Moreover, by placing agricultural systems in the context of a river basin or at a national or regional level, the impact of existing and potential rice production areas on the environment, such as degrading water quality or water availability, can be assessed.
RIICE Project
Understanding geographic variation is an important aspect of agricultural research for development. As an integrative discipline, geography has particular strengths to maintain simultaneously in focus the technological, environmental, and socioeconomic aspects of agricultural development. Check out The RIICE project for more information.
Sentinel-1A Mapping
IRRI and partners use remote sensing imagery from satellites to generate information on the rice crop, such as planted area, seasonality, cropping intensity and damaged area due to flood or drought. Information on crop growth from such imagery can also be used in crop growth simulation models to estimate yield.
In recent years we have been working with partners in the RIICE and PRISM projects to develop and test methods for mapping rice using Synthetic Aperture Radar (SAR) imagery. SAR is particularly suited to rice crop mapping and monitoring because of the unique temporal signature of lowland rice which can be extracted from multiple SAR images through the season. SAR systems can penetrate cloud, which is an additional factor in their favour since most rice in Asia is grown in the cloudy monsoon season.
To date, our work has been limited to pilot or test sites due to both the complexity and cost of obtaining and processing SAR images. Due to a long standing collaboration with sarmap, the “complexity” part of the problem has been addressed through the development of automated processing chains which can be run locally or hosted on cloud computing facilities. The “cost” part of the problem also recently changed. The European Space Agency launched the Sentinel-1A satellite in 2014 and it will become a major source of SAR imagery from 2015 onwards, and will be joined in 2016/17 by Sentinel-1B. Sentinel-1 data is freely available and will cover many of the rice-growing areas of Asia with a spatial resolution of 20 metres.
As a demonstration of the potential of the Sentinel program, sarmap and IRRI have generated mosaics composed from many Sentinel-1A images that cover 7 million square kilometers of South and South East Asia. These cloud free mosaics show the value of SAR imagery for detailed monitoring of agriculture and natural resources across Asia.
The mosaics are composed of images taken during February and March 2015. SAR imagery must be interpreted differently to imagery commonly seen in Google Maps and other mapping services. In these mosaics, we have processed images such that dark blue represents water or other flat surfaces such as airport runways, orange and white represent built up areas and human settlements, light blue represents bare soil, while brown and green show vegetation at different stages of growth.
The mosaics are a snapshot of the earth’s surface, and have not been interpreted for rice mapping purposes. Sentinel-1A will continue to acquire images over the region, and these images will become increasingly useful as they reveal the progress of the rice crop over time, season after season. The ESA Sentinel program has a big role to play in the future of satellite-based remote sensing for rice crop applications.
These mosaics are available for viewing as online maps or can be downloaded and viewed in Google Earth.
Remote sensing-based maps and related publications
Over the past five years, IRRI has been developing remote sensing-based maps of rice systems in Asia as part of our contribution to various projects that need good baseline data on the where, how, and when of rice.
As much as possible IRRI aims to make its data available as global public goods. These provide access to the spatial data behind most of these maps as well as citations, documentation and contact points.
We continue to expand our rice mapping activities and plan to characterize the rice systems of countries in South East Asia in the coming years to complement the existing maps for South Asia.