Publications

YearManuscripts
2022Burke, W., Snapp, S., Peter, B. G., and Jayne, T. 2022. Sustainable intensification in jeopardy: Transdisciplinary evidence from Malawi. Science of the Total Environment. doi: 10.1016/j.scitotenv.2022.155758.
2021Peter, B. G., Messina, J. P., Carroll, J. W., and Chikowo, R. 2021. A case for green-based spectral indices: Plot-scale sUAS imagery related to crop chlorophyll content at two maize farms in Malawi. Remote Sensing Letters. doi: 10.1080/2150704X.2021.1938733.
2020Peter, B. G., Messina, J. P., Carroll, J. W., Zhi, J., Chimonyo, V., Lin, S., and Snapp, S. S. 2020. Multi-spatial resolution satellite and sUAS imagery for precision agriculture on smallholder farms in Malawi. Photogrammetric Engineering & Remote Sensing (PE&RS) 86(2):107–119. doi: 10.14358/PERS.86.2.107.
Peter, B. G., Messina, J. P., Lin, Z., and Snapp, S. S. 2020. Crop climate suitability mapping on the cloud: A geovisualization application for sustainable agriculture. Scientific Reports 10(15487). doi: 10.1038/s41598-020-72384-x.
Frake, A. N., Peter, B. G., Walker, E., and Messina, J. P. 2020. Leveraging big data for public health: Mapping malaria vector suitability in Malawi with Google Earth Engine. PLOS ONE 15(8): e0235697. doi: 10.1371/journal.pone.0235697.
Peter, B. G., Cohen, S., Lucey, R., Munasinghe, D., Raney, A., and Brakenridge, G. R. 2020. Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for Rapid and Large Scale Flood Analysis. IEEE Geoscience and Remote Sensing Letters 1–5. doi:
10.1109/LGRS.2020.3031190.
2019Peter, B. G. and Messina, J. P. 2019. Errors in time-series remote sensing and an open access application for detecting and visualizing spatial data outliers using Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12(4):1165–1174. doi: 10.1109/JSTARS.2019.2901404.
Snapp, S. S., Cox, C., and Peter, B. G. 2019. Multipurpose pulse crops for smallholders in Sub-Saharan Africa: Identification of promising ‘scale out’ options. Global Food Security 23:22–32. doi: 10.1016/j.gfs.2019.03.002.
Gauthier, C., Lin, Z., Peter, B. G., and Moran, E. F. 2019. Hydroelectric infrastructure and potential groundwater contamination in the Brazilian Amazon: Altamira and the Belo Monte Dam. The Professional Geographer 71(2):292–300. doi: 10.1080/00330124.2018.1518721.
2018Peter, B. G., Messina, J., and Snapp, S. 2018. A multi-scalar approach to mapping marginal agricultural land: Smallholder agriculture in Malawi. Annals of the American Association of Geographers 108(4):989–1005. doi: 10.1080/24694452.2017.1403877.
Snapp, S., Rogé, P., Okori, P., Chikowo, R., Peter, B. G., and Messina, J. 2018. Perennial grains for Africa: possibility or pipedream? Experimental Agriculture 1–22. doi: 10.1017/S0014479718000066.
2017Peter, B. G., Mungai, L., Messina, J., and Snapp, S. 2017. Nature-based agricultural solutions: Scaling perennial grains across Africa. Environmental Research 159:283–290. doi: 10.1016/j.envres.2017.08.011.
Peter, B. G., Messina, J., Frake, A., and Snapp, S. 2017. Scaling agricultural innovations: Pigeonpea in Malawi. The Professional Geographer 70(2):239–250. doi: 10.1080/00330124.2017.1347798.
Messina, J., Peter, B. G., and Snapp, S. 2017. Re-evaluating the Malawian farm input subsidy programme. Nature Plants 3(4):17013. doi: 10.1038/nplants.2017.13.
Li, G., Messina, J., Peter, B. G., and Snapp, S. Mapping land suitability for agriculture in Malawi. Land Degradation and Development 28(7):2001–2016. doi: 10.1002/ldr.2723.
Rogé, P., Diarisso, T., Diallo, F., Boiré, Y., Goïta, D., Peter, B. G., Macalou, M., Weltzien, E., and Snapp, S. 2017. Perennial grain crops in the West Soudanian Savanna of Mali: Perspectives from agroecology and gendered spaces. International Journal of Agricultural Sustainability 15(5):555–574. doi: 10.1080/14735903.2017.1372850.
2016Luehmann, M. D., Peter, B. G., Connallon, C. B., Schaetzl, R. J., Smidt, S. J., Liu, W., Kincare, K., Walkowiak, T. A., Thorlund, E., and Holler, M. S. 2016. Loamy, two storied soils on the outwash plains of southwestern Lower Michigan: Pedoturbation of loess into the underlying sand. Annals of the American Association of Geographers 106(3):551–572. doi: 10.1080/00045608.2015.1115388.
Rogé, P., Snapp, S., Kakwera, M. N., Mungai, L., Jambo, I., and Peter, B. G. Ratooning and perennial staple crops in Malawi. A Review. 2016. Agronomy for Sustainable Development 36(3):50. doi: 10.1007/s13593-016-0384-8.

EGCL in the news

Anthropology professor deploys drone to fight disease in Africa

Flying high while also helping communities

Using satellite data to help communities on the ground

Michigan drones help crops, fight malaria in Africa

Harvard Dataverse Repositories

SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes

Feed the Future Innovation Lab for Collaborative Research on Sustainable Intensification (SIIL) Malawi

FwDET-GEE: Floodwater Depth Estimation Tool for Google Earth Engine

VectorSuit-GEE: Vector suitability models in Google Earth Engine

YearDatasets
2021Peter, B. G., Messina, J., and Moragoda, N. 2021. Monthly Aggregated NEX-GDDP Ensemble Climate Projections: Historical (1985–2005) and RCP 4.5 and RCP 8.5 (2006–2080). Harvard Dataverse, V1. doi: 10.7910/DVN/ZNEJMS.
2020Li, G., Messina, J. P., Peter, B. G., and Snapp, S. S. 2020. Replication Data for: Mapping land suitability for agriculture in Malawi. Harvard Dataverse, V1. doi: 10.7910/DVN/6E9VLT.
2019Peter, B. G. and Messina, J. P. 2019. Multispectral drone imagery of a trial farm in Ntubwi, Malawi. Harvard Dataverse, V1. doi: 10.7910/DVN/OAWDZC.
Peter, B. G. and Messina, J. P. 2019. Multispectral drone imagery of a trial farm in Nyambi, Malawi. Harvard Dataverse, V1. doi: 10.7910/DVN/QBRJH0.
Peter, B. G. and Messina, J. P. 2019. Linear workflow for relating multispectral remote sensing imagery with on-farm plant measurements. Harvard Dataverse, V1. doi: 10.7910/DVN/CW20DZ.
Peter, B. G. and Messina, J. P. 2019. Replication Data for: Mixed-Method Land Characterizations: Remote Sensing and LULC Survey Data of Malawi. Harvard Dataverse, V1. doi: 10.7910/DVN/IEKP6Z.
Peter, B. G. and Messina, J. P. 2019. Common bean climate niche of Southeastern and Southern Africa. Harvard Dataverse, V1. doi: 10.7910/DVN/FZYU2S.
2018Peter, B. G. and Messina, J. P. 2018. Growing season temperature variability in Malawi (2016–2017). Harvard Dataverse, V1. doi: 10.7910/DVN/XLIKQF.
2017Messina, J., Snapp, S., and Peter, B. G. 2017. Malawi weather station data for the 2014–2015 growing season. Mendeley Data, V1. doi: 10.17632/xczc64xw46.2.
YearSoftware & Applications
2022Hamidi, H., Peter, B. G., Muñoz, D. F., Moftakhari, H, and Moradkhani, H. 2022. Replication data for: Fast flood extent monitoring with SAR change detection using Google Earth Engine. Harvard Dataverse, V1. doi: 10.7910/DVN/WOTC7E.
Peter, B. G., Messina, J. P. 2022. GEE-TED: A tsetse ecological distribution model for Google Earth Engine. Harvard Dataverse, V1. doi: 10.7910/DVN/6JR87X.
2021Boumis, G. and Peter, B. G. 2021. Time-Series Matrix (TSMx): A visualization tool for plotting multiscale temporal trends. Harvard Dataverse, V1. doi: 10.7910/DVN/ZZDYM9.
Peter, B. G., Messina, J. P., Raney, A., Principe, R., and Fan, P. 2021. MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory. Harvard Dataverse, V1. doi: 10.7910/DVN/M4ZGXP.
2020Peter, B. G., Cohen, S., Lucey, R., Munasinghe, D., and Raney, A. 2020. A Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET-GEE). Harvard Dataverse, V2. doi: 10.7910/DVN/JQ4BCN.
2019Peter, B. G. and Messina, J. P. 2019. Spatial data outlier detection and visualization using Google Earth Engine. Harvard Dataverse, V1. doi: 10.7910/DVN/9ZIUGQ.
Peter, B. G. and Messina, J. P. 2019. MODIS product version comparison application for Google Earth Engine. Harvard Dataverse, V1. doi: 10.7910/DVN/OGTUVN.
Peter, B. G., Messina, J. P., and Lin, Z. 2019. Web-based GIS for spatiotemporal crop climate niche mapping. Harvard Dataverse, V1. doi: 10.7910/DVN/UFC6B5.
Peter, B. G. and Messina, J. P. 2019. Mapping marginal agricultural lands reimagined. Harvard Dataverse, V1. doi: 10.7910/DVN/EPEGA2.
Peter, B. G. and Messina, J. P. 2019. Visualizing inconsistencies among global agricultural land cover products using Google Earth Engine. Harvard Dataverse, V1. doi: 10.7910/DVN/LBYWUF.
Peter, B. G. 2019. Geovisualizing the modifiable areal unit problem. Harvard Dataverse, V1. doi: 10.7910/DVN/C2CNEB.
2018Peter, B. G. and Evans, M. G. 2018. Bivariate color matrix. Interactive color picking tool for selecting a bivariate color palette. http://color.cartoscience.com.