Common bean climate niche of Southeastern and Southern Africa
Domain:
agriculturegeospatialRecord type:
dataset
Creator:
PetMes
Editor:
Pet
Publisher:
Har
Host:
Common bean climate niche of Southeastern and Southern Africa
Geospatial dataset of the climate niche for common bean in Southeastern Africa. Temperature and precipitation parameters collected from Beebe et al. (2011). Data sources: NASA MODIS Land Surface Temperature (MOD11A2) (NASA LP DAAC 2015; Wan et al. 2015) and CHIRPS Precipitation (Funk et al. 2015). Growing season months: November–April; temporal range: 2001–2017; precipitation range: 200–710 mm; temperature range: 13.6–25.6°C.
Categories
0 - Non-agriculture
1 - Pessimal
2 - Unsuitable
3 - Marginal
4 - Suitable
5 - Optimal
NASA MODIS Land Surface Temperature (LST) data
NASA LP DAAC, 2015. MODIS Land Surface Temperature (MOD11A2) Version 005. NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
Wan, Z., Hook, S., Hulley, G. (2015). MOD11A2 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed 2020-02-26 from doi.org
CHIRPS precipitation data
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A. and Michaelsen, J., 2015. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2, p.150066.
Common bean temperature and precipitation parameters
Beebe, S., Ramirez, J., Jarvis, A., Rao, I.M., Mosquera, G., Bueno, J.M. and Blair, M.W., 2011. Genetic improvement of common beans and the challenges of climate change. Crop Adaptation to Climate Change, 26, pp.356-369.
Classification methodology
Peter, B.G., Mungai, L.M., Messina, J.P. and Snapp, S.S., 2017. Nature-based agricultural solutions: Scaling perennial grains across Africa. Environmental Research, 159, pp.283-290.
This content is made possible by the support of the American People provided to the Feed the Future Innovation Lab for Sustainable Intensification through the United States Agency for International Development (USAID). The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government. Program activities are funded by USAID under Cooperative Agreement No. AID-OAA-L-14-00006. Google Earth Engine ESRI ArcGIS
Geospatial dataset of the climate niche for common bean in Southeastern Africa. Temperature and precipitation parameters collected from Beebe et al. (2011). Data sources: NASA MODIS Land Surface Temperature (MOD11A2) (NASA LP DAAC 2015; Wan et al. 2015) and CHIRPS Precipitation (Funk et al. 2015). Growing season months: November–April; temporal range: 2001–2017; precipitation range: 200–710 mm; temperature range: 13.6–25.6°C.
Categories
0 - Non-agriculture
1 - Pessimal
2 - Unsuitable
3 - Marginal
4 - Suitable
5 - Optimal
NASA MODIS Land Surface Temperature (LST) data
NASA LP DAAC, 2015. MODIS Land Surface Temperature (MOD11A2) Version 005. NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
Wan, Z., Hook, S., Hulley, G. (2015). MOD11A2 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed 2020-02-26 from doi.org
CHIRPS precipitation data
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A. and Michaelsen, J., 2015. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2, p.150066.
Common bean temperature and precipitation parameters
Beebe, S., Ramirez, J., Jarvis, A., Rao, I.M., Mosquera, G., Bueno, J.M. and Blair, M.W., 2011. Genetic improvement of common beans and the challenges of climate change. Crop Adaptation to Climate Change, 26, pp.356-369.
Classification methodology
Peter, B.G., Mungai, L.M., Messina, J.P. and Snapp, S.S., 2017. Nature-based agricultural solutions: Scaling perennial grains across Africa. Environmental Research, 159, pp.283-290.
This content is made possible by the support of the American People provided to the Feed the Future Innovation Lab for Sustainable Intensification through the United States Agency for International Development (USAID). The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government. Program activities are funded by USAID under Cooperative Agreement No. AID-OAA-L-14-00006. Google Earth Engine ESRI ArcGIS
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