Research

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

Divergent local responses to globalization: Urbanization, land transition, and environmental changes in Southeast Asia

Dr. Brad G. Peter, Researcher (2020–Present)
PIs: Dr. Peilei Fan (Michigan State University) and Joseph Messina (Co-PI; University of Alabama); http://seagul.info/
Funding: NASA Land-Cover and Land-Use Change Program

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“Southeast Asia, a vast area of 4.5 million sq km with more than 641 million people, experienced rapid urbanization, doubling the urbanization ratio from 24% in 1976 to 48% in 2016, with several cities doubling urban built-up land in just two decades (HCMC, Hanoi, and Yangon from 1990 to 2010) coincident with severe degradation of the urban environment. Globalization has been recognized as one of the most significant driving forces of land transitions in Southeast Asia. It includes flows of commodity (international trade), capital (foreign direct investment (FDI)), money (remittance and overseas aid), and people (rural-urban migration, and international workers, and tourists). Our objective is to examine how diverse local responses to globalization affected land transitions, particularly urbanization, and urban environmental changes across 7 SEA countries, i.e., Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Thailand, and Vietnam and 12 case cities, with 3 particular tasks of data processing and hypothesis testing: Task 1. Urban land transition and its relationship to other land transitions; Task 2. Urban environmental changes (air pollution) patterns, drivers, and impacts; Task 3. Divergent local responses to globalization.”

WaterServ: A Cyberinfrastructure for Analysis, Visualization and Sharing of Hydrological Data

Dr. Brad G. Peter, Co-PI, Postdoctoral Researcher
PI: Dr. Sagy Cohen (University of Alabama); https://waterserv.ua.edu/
Funding: University of Alabama CyberSeed Grant

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“Accessibility to hydrological measurements, model predictions and Earth observing imagery has never been greater. This has led to rapid acceleration in the development, by government and international agencies, private companies, and academic researchers, of new systems for predicting and analyzing extreme hydrological events (floods and droughts). Examples include the NOAA National Water Center (NWC) National Water Model (NWM), the European Union Joint Research Center (JRC) Global Flood Awareness System (GloFAS), and Google flood forecasting system (under development). While these types of emerging systems are poised to greatly improve social resilience to flood and drought, their impact remains quite limited. This is mainly due to the disparity of their end-user access points and difficulties in utilizing their products.”

Precision agriculture for smallholder farming systems in Africa

B. Peter, Graduate Assistant Researcher
PI: Dr. Joseph Messina (Michigan State University); https://www.k-state.edu/siil/whatwedo/pastprojects/malawi/index.html
Funding: USAID Feed the Future

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“The purpose of this project is to collect and integrate multi-scale data and analytic techniques to generate inter- and intra-seasonal decision support guidance capable of improving Malawian smallholder farmers’ agricultural productivity. Recent advances in data management and modeling and in the commercialization of remote sensing tools are leading to dramatic improvements in our understanding of the multi-scale spatial patterns of soils, weather and climate, and agricultural productivity. These types of data are now increasingly available in Africa to combine with farm survey data on farm management, input use, and soil characteristics to provide inter- and intra-seasonal decision support guidance for agricultural extension systems for the benefit of smallholder farmers. In essence, the project seeks to demonstrate how to make agriculture in developing countries ‘smarter’ through newly available tools for collecting and and analyzing large volumes of data on productivity, suitability, and producer behavior.”

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

Perennial grain crops for African smallholder farming systems

B. Peter, Graduate Assistant Researcher (2014–2018)
PI: Dr. Joseph Messina (Michigan State University); https://pgrainsforafrica.psm.msu.edu/
Funding: Bill & Melinda Gates Foundation

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“Cultivation of perennial grain crops such as wheat, rice and sorghum, by smallholder African farmers potentially has many benefits, such as alleviation or reversal of soil degradation, increased soil health, reclamation of marginal land, and increased crop profitability. However, there has been little research devoted to the development of these crops for use in the tropics, particularly for marginal lands, and adoption by farmers may be difficult, especially without seeing immediate benefits and profits from soil conservation…One of the most common and most commonly overlooked development tasks is targeting. In this sense we are referring here to proactively determining the appropriate location and scaling potential for any development innovation. We faced three distinct problems with targeting and scaling perennial grains. 1) where is the agriculture, 2) where is a perennial grain innovation appropriate and scalable given biophysical constraints, current or future, and 3) how do we disentangle social factors driving poorly producing agricultural regions.”