NASA Harvest Joins the NISAR Early Adopters Program
NASA Harvest Scientist and South Asia lead Meghavi Prashnani has been selected as a NISAR Early Adopter. NISAR Early Adopters are individuals or organizations with a clear need for NISAR data, have existing applications that can benefit from NISAR, and the resources to demonstrate the utility of NISAR data. They play an important role in informing the NISAR team how NISAR data can fill various application requirements.
Meghavi Prashnani at the 2022 NASA Land Cover and Land Use Change Science Team Meeting
NISAR (NASA-ISRO Synthetic Aperture Radar) is a joint Earth-observing mission between NASA and the Indian Space Research Organization (ISRO). NASA and ISRO are providing two radar imaging systems at L- and S-band wavelengths that together will allow the mission to observe a broader range of land surface changes, making it a first of its kind.
NISAR will monitor Earth’s land and ice-covered surfaces globally with 12-day frequency with ascending and descending passes, sampling the Earth on average every 6 days. NISAR is expected to be launched in January 2024 from Satish Dhawan Space Centre, India into a near-polar orbit and operate for a minimum of three years.
Meghavi’s selection into the NISAR Early Adopter program builds off of her extensive decade long career working in agricultural monitoring, drought assessment, and disaster risk reduction with various agencies including the Indian Space Agency; the Center for Artificial Intelligence & Robotics, Defense Research and Development Organization (DRDO) in Bengaluru, India; and the Mahalanobis National Crop Forecast Center (MNCFC) in New Delhi, India. She has also been engaged with the NISAR development process prior to her selection, attending the 2022 NISAR Science Community Workshop in Pasadena, CA.
Expanding SAR Applications with NISAR
Some key primary applications of the NISAR mission include disaster mitigation, climate change, ecosystem and natural resource assessment and monitoring. Another key application area that Meghavi plans to explore is NISAR’s ability to improve agriculture management and food security by providing information on crop growth, soil moisture, land-use changes and climate change impacts on crop condition.
Meghavi’s proposed project will assess the potential of the NISAR data for improving agriculture monitoring throughout South Asia, especially for monsoon crops, which are difficult to monitor with optical satellite data due to persistent cloud cover. South Asia is home to around 1.9 billion people — nearly a quarter of the world's population. However, food insecurity remains a significant challenge in many countries in the region due to factors such as poverty, inequality, climate change, and conflict. Agriculture is highly dependent on rainfall in this region and hence farmers are vulnerable to the impact of weather extremes and climate change-related problems.
Moreover, the region is dominated by privately-owned smallholder farms making it difficult to monitor using coarser-resolution optical satellite data. Thus, a robust agricultural monitoring system is urgently needed for the region which is capable of monitoring crop conditions throughout the year, thereby helping farmers and policymakers make informed decisions in a timely manner.
Meghavi Prashnani at the 2022 NISAR Science Community Workshop in Pasadena, CA.
How NASA Harvest Will Use NISAR
NISAR will produce unprecedented Synthetic Aperture Radar (SAR) time-series data crucial for ecosystem applications. SAR data can be used for agriculture monitoring, particularly for crop mapping, yield estimation, and monitoring crop growth throughout the growing season. SAR sensors can provide all-weather and day-and-night imaging capabilities, which makes them an effective tool for agriculture monitoring.
NISAR will provide global coverage of SAR data with high temporal and spatial resolutions, large swaths, and with hybrid and full polarimetric capabilities. The Harvest program plans to use the NISAR data for building robust and efficient monitoring techniques for cropland and crop type mapping and yield estimation.
By analyzing the backscatter signals of SAR data, it is possible to estimate the biomass and water content of crops, which can be used to predict yield. Information on crop production estimation using satellite data can be useful for agricultural management and decision-making, including crop insurance and marketing. The NISAR data will be compared with and used in conjunction with the various existing optical and microwave satellite data to monitor key crops in different agro-ecological zones.
The NISAR mission will contribute a tremendous amount of data that will enable development of new (and the enhancement of existing) applications. Harnessing the full potential of the high resolution and high frequency data acquired from the NISAR satellite will require advanced machine learning algorithms and processing platforms to deal with big data challenges.
Harvest scientists will assess the potential of the existing machine learning algorithms and cloud computing platform to monitor agriculture with NISAR data exclusively and combined with other satellite data and also attempt to develop robust and efficient algorithms suitable for the big data generated from remote sensing platforms like NISAR. Within the framework of the international G20 GEOGLAM Initiative, Harvest will be working with regional collaborators on developing effective agricultural monitoring systems using NISAR data.
