1) Cropland Carbon Monitoring System (CCMS): A satellite-based system to estimate carbon fluxes on U.S croplands -NASA CMS program (2016-2019)
The primary goal of this project is to create a prototype of a Cropland Carbon Monitoring System (CCMS) that improves the existing cropland C storage and flux estimates developed under previous NASA CMS activities in terms of spatial and temporal scales as well as completeness. This project will use RS-EPIC developed as part of Global Agricultural Monitoring Program (GEO-GLAM) to estimate, at 500-m resolution, the 2015-2016 seasonal and annual C fluxes of nine major crops (corn, soybean, winter wheat, spring wheat sorghum, cotton, alfalfa, barley, rice, and peas) grown over ~96% of the cropland area in the conterminous United States. The product developed under this project will provide the knowledge base at required spatial and temporal scale to understand complex carbon cycling outcomes under various land use and land management practices and develop joint policies to meet objectives of food and energy security while stabilizing atmospheric CO2. Further, the data product will help improve national inventories and carbon budget reporting.
2) Agricultural Land Use Change in Central and Northeast Thailand: Effects on Biomass Emissions, Soil Quality, and Rural Livelihoods – NASA LCLUC program (2018-2021)
The overall goal of this project is to understand the impacts of recent land use changes in Central and Northeast Thailand on biomass emissions, soil quality, and economic well-being in rural communities. The specific objectives are to: 1) map major cropping system conversions (e.g. rice to sugarcane) from 2010-2014 and 2014-2018 at 30-m spatial resolution using a combination of Landsat 5, 7 and 8, IRS-P6 AWiFS, Sentinel 1 and 2 satellite datasets; 2) implement Environmental Policy Integrated Climate (EPIC) and remote sensing EPIC modeling frameworks to quantify the impacts of residue burning and alternative residue management strategies under rice and sugarcane production on crop productivity, soil erosion and carbon cycling at 1-km spatial resolution; 3) estimate spatially-explicit biomass emissions using an improved bottom-up approach; 4) implement an integrated socio-economic modeling framework to quantify the socio-economic impacts of cropping system conversions and residue management practices; and 5) understand farmers’ willingness to adopt sustainable management practices and barriers and incentives to adaptation of these practices.