Operational Algorithms and Products for Near Real Time Maps of Rice Extent and Rice Crop Growth Stage Using Multi - Source Remote Sensing

Rice is one of the most important crops globally for food production, supporting livelihoods, and its role in the Earth system. Rice agriculture faces major chal lenges in the coming decade due to increasing resource pressures, severe weather and climate change, population growth and shifting diets, and economic development. The overall goal of this proposed project is to develop integrated, seamless algorithms and operationalize multisource SAR and optical products for near real time maps of rice extent, rice calendar, and rice crop growth stage to support food security and land use decision making in South Asia. We propose to fuse moderate resolution, operational Synthetic Aperture Radar platforms (ALOS - 2, Sentinel - 1, RISAT - 1) with Landsat 8 OLI and Senintel - 2 for mapping land use and characterizing rice agricultural conditions at 30m at national scales using a Classification And Regression Tree framework. Operatio nalize multisource algorithms to provide weekly maps of: near real time rice extent, rice cropping calendar and growth (phenological) stage and track risk or deviation from normal as an indicator for crop failure. We will conduct technology transfer with p artners in developing regions using an open and transparent approach and grow institutional capacity to support multi - source land monitoring and food security in coordination with GEOGLAM and AsiaRice. The Group on Earth Observations (GEO) is a coordinat ed effort to build the Global Earth Observation System of Systems (GEOSS). GOESS is the leading framework to integrate Earth Observations and geospatial mapping tools to support Global Agricultural Monitoring (GLAM). NASA is a strong supporter of GEO and G OESS and, in particular, the Agricultural task force (GEOGLAM). The next phase of the GEOGLAM plan is to begin to scale up pilot applications to have national and global monitoring tools within he next decade (fig 2). GEOGLAM was tasked to coordinate sate llite monitoring observation systems in different regions of the world in order to enhance crop production projections and support the Agricultural Market Information System (AMIS) and Crop Monitor. The objective of the Crop Monitor is to provide an intern ational and transparent multi - source, consensus assessment of crop growing conditions, status, and agro - climatic conditions, likely to impact global production. This activity covers the four primary crop types (wheat, maize, rice, and soy) within the main agricultural producing regions. Currently, S. Asia has several gaps that are not well represented in GEOGLAM and this proposal will help fill those gaps.