Project Funding: 2014 - 2017

NRA: 2012 NASA: Interdisciplinary Research in Earth Science   

Funded by NASA

Abstract:
One of the most immediate and obvious impacts of climate change is on the weather-sensitive agriculture sector. Both local and global impacts on production of food will have a negative effect on the ability of humanity to meet the needs of its growing population. Many factors are affecting agriculture - trends in rainfall and temperature, changes in ecological resilience and the increasing need for ecosystem services such as fresh water provision and cycling of nutrient waste, and, most importantly, changes in economic context with increasing volatility of energy prices and the demand for goods and services at multiple scales. The most vulnerable and food insecure regions of the world such as the Horn of East Africa need financial tools to reduce the risk of food production shortages while enabling productivity increases to meet the needs of a growing population. This project brings together climate assessment, economics, and remote sensing expertise to develop a moisture-based, scalable, sensor-independent remote sensing product that can be used in agriculture insurance programs around the world. We will focus our efforts in Ethiopia and Kenya in East Africa and in Senegal, West Africa, where there are active index insurance pilots that can test the effectiveness of our remote sensing-based approach for use in the insurance industry. This research seeks to provide a multi-resolution, multi-sensor source of weather and climate information that will enable the scaling up of an agriculture insurance program that provides basic weather-risk financial support. Index insurance provides an indemnity payout that depends on the exceedance of a threshold variable such as water level (for floods) or consecutive days without rain (for droughts), could fill that gap. Many insurance companies and non-profit development organizations are working to develop index insurance for smallholder farmers. Index insurance can facilitate the availability of credit and enable wide spread increases in the use of fertilizers and improved seeds. This project will use an energy balance model and satellite remote sensing derived information to provide quantitative and scalable information that meets the index insurance requirements: 30 year historical record, frequent observations, high resolution to accurately estimate risk at the field level, and transparency so that it is understandable by the contract holders. Datasets that will be used include the 30 year time series of vegetation, temperature and precipitation based on the polar orbiting and geostationary sensors, AMSR/E and (after launch) SMAP soil moisture data, MODIS and VIIRS temperature and vegetation index data, ground observations of precipitation, and Landsat 30m data for spatially disaggregating the information for specific farms. We will fund Martha Andersen USDA and Chris Hain at NOAA NESDIS/University of Maryland to use geostationary thermal infrared land surface temperature to create a long time series of evapotranspiration data over the continent of Africa at 10km resolution from 1982 to 2012. Evapotranspiration data can be used together with gridded precipitation and soil moisture data (from microwave sensors) to understand moisture stress in agricultural crops. Hain et al. (2011) shows that since microwave soil moisture is able to penetrate non-precipitating cloud cover, while ALEXI (TIR) deals better with moderate to dense vegetation (the MW signal suffers from attenuation from the overlying canopy), that they can provide complementary information to precipitation. We will determine if using precipitation, soil moisture and ET parameters together may be more valuable than either ET from ALEXI or precipitation information alone.

Publications:

Enenkel, M., Farah, C., Hain, C., White, A., Anderson, M., You, L., Wagner, W., Osgood, D. 2018. What Rainfall Does Not Tell Us--Enhancing Financial Instruments with Satellite-Derived Soil Moisture and Evaporative Stress. Remote Sensing. 10(11), 1819. DOI: 10.3390/rs10111819

Enenkel, M., Osgood, D., Anderson, M., Powell, B., McCarty, J., Neigh, C., Carroll, M., Wooten, M., Husak, G., Hain, C., Brown, M. 2018. Exploiting the Convergence of Evidence in Satellite Data for Advanced Weather Index Insurance Design. Weather, Climate, and Society. 11(1), 65-93. DOI: 10.1175/WCAS-D-17-0111.1

Enenkel, M., See, L., Bonifacio, R., Boken, V., Chaney, N., Vinck, P., You, L., Dutra, E., Anderson, M. 2015. Drought and food security - Improving decision-support via new technologies and innovative collaboration. Global Food Security. 4, 51-55. DOI: 10.1016/j.gfs.2014.08.005

Greatrex H, Hansen J, Garvin S, Diro R, Blakeley S, Le Guen M, Rao K, Osgood D. 2015. Scaling up index insurance for smallholder farmers: Recent evidence and insights. CCAFS Report No. 14. Copenhagen, Denmark: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

Hain, C. R., Anderson, M. C. 2017. Estimating morning change in land surface temperature from MODIS day/night observations: Applications for surface energy balance modeling. Geophysical Research Letters. 44(19), 9723-9733. DOI: 10.1002/2017GL074952

McCarty, J. L., Neigh, C. S. R., Carroll, M. L., Wooten, M. R. 2017. Extracting smallholder cropped area in Tigray, Ethiopia with wall-to-wall sub-meter WorldView and moderate resolution Landsat 8 imagery. Remote Sensing of Environment. 202, 142-151. DOI: 10.1016/j.rse.2017.06.040

Neigh, C. S., Carroll, M. L., Wooten, M. R., McCarty, J. L., Powell, B. F., Husak, G. J., Enenkel, M., Hain, C. R. 2018. Smallholder crop area mapped with wall-to-wall WorldView sub-meter panchromatic image texture: A test case for Tigray, Ethiopia. Remote Sensing of Environment. 212, 8-20. DOI: 10.1016/j.rse.2018.04.025

Osgood, D., Powell, B., Diro, R., Farah, C., Enenkel, M., Brown, M., Husak, G., Blakeley, S., Hoffman, L., McCarty, J. 2018. Farmer Perception, Recollection, and Remote Sensing in Weather Index Insurance: An Ethiopia Case Study. Remote Sensing. 10(12), 1887. DOI: 10.3390/rs10121887

Trnka, M., Hayes, M., Jurecka, F., Bartosova, L., Anderson, M., Brazdil, R., Brown, J., Camarero, J., Cudlin, P., Dobrovolny, P., Eitzinger, J., Feng, S., Finnessey, T., Gregoric, G., Havlik, P., Hain, C., Holman, I., Johnson, D., Kersebaum, K., Ljungqvist, F., Luterbacher, J., Micale, F., Hartl-Meier, C., Mozny, M., Nejedlik, P., Olesen, J., Ruiz-Ramos, M., Rotter, R., Senay, G., Vicente-Serrano, S., Svoboda, M., Susnik, A., Tadesse, T., Vizina, A., Wardlow, B., Zalud, Z., Buntgen, U. 2018. Priority questions in multidisciplinary drought research. Climate Research. 75(3), 241-260. DOI: 10.3354/cr01509

Yin, J., Zhan, X., Hain, C. R., Liu, J., Anderson, M. C. 2018. A Method for Objectively Integrating Soil Moisture Satellite Observations and Model Simulations Toward a Blended Drought Index. Water Resources Research. 54(9), 6772-6791. DOI: 10.1029/2017WR021959

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• Linking remote sensing and climate data for an agriculture index insurance program in Ethiopia   --   (Christopher Neigh, Molly Brown, Dan Osgood, Jessica McCarty, Bristol Mann, Gregory Husak, Martha Anderson, Christopher Hain, Helen Greatrex)   [abstract]

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile