Geographic Information Systems as a Tool for Viable, Long-Term Farming Solutions in a Time of Climate Change

Annotated Bibliography:

Strong, A. (2019) GIS helps Farmers See the Big Picture, Esri. Available at: https://www.esri.com/about/newsroom/arcuser/gis-helps-farmers-see-the-big-picture/ (Accessed: March 6, 2023).

Environmental Systems Research Institute (Esri) is a geographic information system (GIS) software company whose technology has the potential to answer questions about agriculture in the midst of climate change. For example, their technology has helped farmers in Malawi, Africa to improve crop yields in small farms using climate-smart agriculture (CSA) strategies. CSA uses GIS to monitor the implementation of various strategies and to create maps for stakeholder workshops. Farmers and stakeholders can then access GIS maps that contain customized landscape data. This source is beneficial in understanding how Esri’s technology can help farmers all over the world become more sustainable and knowledgeable about climate related changes in the production of food.

GIS in agriculture – Geospatial Data’s role in water risk mitigation (2022) AQUAOSO. Available at: https://aquaoso.com/gis-in-agriculture/ (Accessed: March 9, 2023).

Water and agriculture go hand in hand. Naturally, a consideration of future water availability is crucial to accurately adapting our agricultural systems. Aquoso is a financial technology company aimed towards building resilient agricultural and food systems. They utilize GIS to interpret water risks using both small data and macro water trends. At a parcel-by-parcel level, GIS is used to map historical and future water availability. This source provides a necessary look into the water supply side of agriculture and how companies are using GIS to make predictions to mitigate water risk.

Hodson, D. and White, J. (2010) “GIS and crop simulation modelling applications in Climate Change Research.,” Climate change and crop production, pp. 245–262. Available at: https://doi.org/10.1079/9781845936334.0245.

Authors David Hodson and Jeffrey White write about the effectiveness of GIS crop simulation models in predicting the effects of climate change on agriculture. The Intergovernmental Panel on Climate Change (IPCC) has even utilized this technology to make predictions under certain emission scenarios and provide relevant recommendations. What makes GIS such a strong tool in assessing climate related agricultural changes is that it is rapid, efficient, understandable, visual, and flexible to regional data. Crop simulation models often use extrapolation to make predictions regarding plant growth and development, and the influence of environmental conditions. Factors considered in a crop simulation model could include: air temperature, precipitation, soil properties, and crop management practices. Hodson and White also provide examples of a crop simulation model for maize and rice in various locations. This journal provides excellent examples of the benefits of the specific tool of crop simulation models within GIS technology.

GIS data for agriculture and the environment (no date) EarthStat. Available at: http://www.earthstat.org/ (Accessed: March 9, 2023).

Earthstat is a website created by the University of British Columbia that compiles valuable geographic data for global crop yields, cropland greenhouse gas emissions, yield gaps, and so much more. Each data set contains maps, articles, and resources that have all been informed by GIS technologies. One of their datasets includes information on varying crop yields for wheat, maize, soybean, and rice under climate change conditions. This data is a prime example of how GIS makes these predictions not only possible, but easily understandable in the form of map visuals. Overall, this resource holds great value in future research as it is evidence that GIS is already being used to document agricultural changes in the midst of climate change.

Seif-Ennasr, M. et al. (2020) “GIS-based land suitability and crop vulnerability assessment under climate change in Chtouka Ait Baha, Morocco,” Atmosphere, 11(11), p. 1167. Available at: https://doi.org/10.3390/atmos11111167.

Morocco is a country that relies heavily on agriculture and is simultaneously seeing the effects of climate change. This study has used GIS technology to assess various indicators that may impact crop suitability, growing seasons, and water demand in Morocco. In order to assess land suitability, GIS considers four major parameters: temperature, soil texture, land use, and slope. These features are looked at under low and high emission scenarios. The results have shown that a decrease in suitable land, growing seasons, and water availability will stress the agriculture industry dramatically. Having these predictions from GIS technology encourages policymakers to use multi-criteria decision making (MCDM) processes to mitigate risks. Overall, this study provides evidence that GIS land suitability models can help farmers choose crops and varieties that will do better in future climate change scenarios.

Kadiyala, M.D.M. et al. (2015) “An integrated crop model and GIS Decision Support System for assisting agronomic decision making under climate change,” Science of The Total Environment, 521-522, pp. 123–134. Available at: https://doi.org/10.1016/j.scitotenv.2015.03.097.  

Geographic Information Systems are being implemented in research regarding the semi-arid tropical (SAT) regions of India. These SAT regions suffer from low agricultural productivity that are exacerbated by the effects of climate change. This study specifically uses an integrated crop model to look at groundnut yields under five global climate models (GCM’s). The results of these models not only can be applied to India, but to other regions that grow groundnuts. It is predicted that groundnut yields are to decrease due to increased pests/diseases, major changes in the hydrological cycle, and increasing temperatures. Scientists and decision-makers use this information to propose and implement resiliency strategies such as drought resistant crops with longer life cycles. This article is another strong piece of evidence the GIS technology is indeed effective in creating resilient, long-term farming practices worldwide.

Kourgialas, N.N. and Karatzas, G.P. (2016) “A flood risk decision making approach for Mediterranean tree crops using GIS; climate change effects and flood-tolerant species,” Environmental Science & Policy, 63, pp. 132–142. Available at: https://doi.org/10.1016/j.envsci.2016.05.020.

In Greece, the island of Crete is particularly prone to flooding and GIS has been used in this study to estimate the flooding risks to fruit tree crops. Factors such as elevation, rainfall intensity, geology, land use, and slope are mapped in a gridded geographic map system. These maps have provided crucial information that depicts the most vulnerable flood regions and allows for agricultural changes to be made before the fact. Additionally, the information in this study can aid farmers in choosing more flood-resilient fruit trees such as apple and quince varieties. Ultimately, this study adds a new outlook to the topic of agriculture in GIS. Not only can GIS be used for crop and land suitability, but it can identify future environmental risks such as flooding.

Chau, V.N. et al. (2013) “Using GIS to map impacts upon agriculture from extreme floods in Vietnam,” Applied Geography, 41, pp. 65–74. Available at: https://doi.org/10.1016/j.apgeog.2013.03.014.

In Vietnam, there is also a risk of massive flooding. This study performed in 2013 aims to identify how increased floods could impact agricultural systems in the Quang Nam Province of Vietnam. Scientists used a digital elevation model (DEM) to create a flood map. With limited remote sensing images, metrological data, and hydrological data, researchers used interpolation to predict raster values. The maps depict rice fields being the most vulnerable to flood damage. Under worst case scenarios, flooded areas cover over forty percent of the province’s rice supply. Having this knowledge is crucial for the Vietnamese government to plan for disasters and impose mitigation strategies. This study specifically is valuable to me because it proves that interpolated data still has the ability to provide very meaningful insights.

Eniolorunda, Nathaniel. (2014). Climate Change Analysis and Adaptation: The Role of Remote Sensing (Rs) a nd Geographical Information System (Gis). International Journal of Computational Engineering Research. 4. 41-51.

In essence, remote sensing (RS) is a way to gather data on Earth’s characteristics and GIS is a way to organize this data into an understandable, analyzable template. The author outlines all of the ways in which RS and GIS can be used to adapt to climate change. Soil quality, water availability/drought stress, and climate change are the three key factors that are necessary to study agricultural resiliency. RS and GIS together can measure all of this in almost all locations. Satellite data, hydrological models, and agricultural census statistics are a few features that can all be used to map areas of high risk to climate change. There is no doubt that these technologies will be very important to human survival as we continue down a climate crisis path. This journal emphasizes the plethora of ways in which GIS can be used, not just in agricultural predictions.

Nyantakyi-Frimpong, H. (2019) “Visualizing politics: A feminist political ecology and participatory GIS approach to understanding smallholder farming, climate change vulnerability, and seed bank failures in northern Ghana,” Geoforum, 105, pp. 109–121. Available at: https://doi.org/10.1016/j.geoforum.2019.05.014.  

Author Hanson Nyantakyi-Frimpong writes about the participatory GIS (PGIS) approach in Northern Ghana as it relates to seed banks. Seed banks are a community-based storage of seeds that are loaned to farmers. However, seed banks often fail to remain active and work in the best interests of the farmers. Nyantakyi-Frimpong uses a PGIS framework to depict the failures of seed banks in her region and to promote new ways to achieve agricultural stability. PGIS is basically a way of incorporating participant knowledge into scientific systems. This is a valuable resource as it shows that GIS can incorporate human observations as data contributing to an outcome.

Peters, C., Bills, N., Lembo, A., Wilkins, J., & Fick, G. (2009). Mapping potential foodsheds in New York State: A spatial model for evaluating the capacity to localize food production. Renewable Agriculture and Food Systems, 24(1), 72-84. doi:10.1017/S1742170508002457

In 2009, researchers used a spatial model to estimate the spatial distribution of food production capacity in the state of New York. There has been increasing research into the ability of states to increase their local food production to feed their own populations- especially in a changing climate. The results of this study proved that it is indeed possible to feed population centers with state-grown food. New York City, due to its size, is one exception. The ability of GIS to map both food production and consumption is beneficial in order to understand how we can grow and feed populations as locally as possible. This model can be applied to other states and cities across the globe. Eating locally not only curbs greenhouse gas emissions related to food transportation but it also increases a community’s resiliency to climate change. This is a valuable source because it expands the idea of food resiliency not just to general food production, but to local eating.

Meenar, M.R. (2017) “Using participatory and mixed-methods approaches in GIS to develop a place-based food insecurity and vulnerability index,” Environment and Planning A: Economy and Space, 49(5), pp. 1181–1205. Available at: https://doi.org/10.1177/0308518×16686352.

Participatory GIS (PGIS) was utilized to create a Place-Based Food Insecurity & Vulnerability Index (PFIVI) in 2017. The index is an assessment tool that is grounded in community food security. It uses thirty different variables to determine levels of food insecurity and vulnerability. In this case, the city of Philadelphia is used as an example. Participants are encouraged to comment on variables that fall under six categories: hunger, low-access, habit, health, engagement, and risk. The index was then created using this data and the ESRI model builder using raster data. The result was a detailed map of all the more vulnerable and food insecure areas in Philadelphia. Having this information can hopefully help these areas to get more support. The PFIVI is also an extraordinary resource because it can be replicable in other cities. The index can also be used to design food environments using spatial planning techniques.

De Silva, C.S. et al. (2007) “Predicting the impacts of climate change—a case study of paddy irrigation water requirements in Sri Lanka,” Agricultural Water Management, 93(1-2), pp. 19–29. Available at: https://doi.org/10.1016/j.agwat.2007.06.003.

A staple crop in Sri Lanka is paddy rice and over seventy percent of paddy rice is grown during the wet season. GIS has been valuable in mapping trends in the hydrological cycle and how this may influence paddy production. It was found that under future climate predictions the irrigation needs of paddy fields will likely increase as average rainfall during the wet season decreases. GIS mapping not only brings attention to the importance of spatial variation in paddy fields, but it identifies site-specific climate conditions that can aid in future planning and agricultural resiliency. Overall, this resource has a focus on hydrological cycles that will be valuable in analyzing agricultural vulnerabilities in various climates.

Rawat, P.K. (2014) “GIS development to monitor climate change and its geohydrological consequences on non-monsoon crop pattern in Himalaya,” Computers & Geosciences, 70, pp. 80–95. Available at: https://doi.org/10.1016/j.cageo.2014.04.010.

In the Himalaya region, climate change is also having an influence on non-monsoon crops. As there is less rainfall during monsoon season, this has created drought conditions that put a strain on non-monsoon crops. The livelihood of people living in the Himalayan region requires food security and water availability. Thus, GIS technology has the potential to look to the future and provide information that helps us to solve foreseeable problems before they occur. In this journal, researchers evaluate GIS and remote sensing (RS) results that map land use and land cover changes in Himalaya. Specifically, researchers used a database management system (DMS) to manage an integrated spatial and attribute database. Within the DMS were four GIS modules with various map layers and attributes. The four modules include: climate, land use, hydro, and agro informatics. The results predict decreased rainfall, deforestation, declining groundwater, increasing temperatures, and other disconcerting environmental changes. At the very least, these results can help farmers and policy makers to be more prepared for the inevitable pressures put on most crops.

Tashayo, B. et al. (2020) “Land suitability assessment for maize farming using a GIS-AHP method for a semi- arid region, Iran,” Journal of the Saudi Society of Agricultural Sciences, 19(5), pp. 332–338. Available at: https://doi.org/10.1016/j.jssas.2020.03.003.            

Land suitability assessments for Maize have proven useful in Iran. Topography, soil properties, and climate (precipitation & temperature) data were used within a GIS framework to determine areas in Iran that are most suitable for growing- now and into the future. Maize is a staple field crop in Iran and it feeds not only people but is a primary ingredient in many animal feeds. A disruption in Maize production will no doubt have global repercussions. Ultimately, researchers were able to identify the prime, sustainable growing locations for Maize in Iran. This data will certainly aid in Iran’s crop resiliency. I find this article especially valuable because it brings up the idea of an analytical hierarchy process (AHP). An AHP classifies factors that are arranged in a hierarchical structure (i.e. ranked and weighted on importance). This will be a valuable skill in future GIS analysis.

Merem, E.C. et al. (2011) “The applications of GIS in the analysis of the impacts of human activities on South Texas watersheds,” International Journal of Environmental Research and Public Health, 8(6), pp. 2418–2446. Available at: https://doi.org/10.3390/ijerph8062418.

This article is a case study of the effects of human activities on watersheds in South Texas and their effect on local agriculture. Researchers used a geographic information system to map anthropogenic influences on local watersheds. Factors such as population, wastewater management, and fertilizer usage were included in the analysis. GIS was utilized to create over eight maps that depict past and present information such as pollutants found in the water and fertilizer usage in Texas counties. The overall results show beyond a doubt that under current conditions watershed ecosystems are in jeopardy. A decline in the health of watersheds means that there is a decline in the ability of South Texas agriculturalists to produce food. The intention of this study is to provide enough information for Texas decision makers to support coordinated watershed protection planning. This source is helpful to me because it is based in the United States and can be compared and contrasted to other watershed protection plans in the country.

Dornich, Kyle.  (2017) “Use of GIS in Agriculture,” Cornell Small Farms. Available at: https://smallfarms.cornell.edu/2017/04/use-of-gis/.

Kyle Dornich offers a clear analysis of how GIS aids in the practice of precision farming. Precision farming is essentially the application of data towards effective farming practices and solutions. Some aspects of precision farming are automated and rely heavily on technology. For example, data regarding the water usage of a specific crop can then be applied to an automated watering system in order to conserve water resources. Dornich also mentions a helpful GIS-based resource called CropScape by the United State Dept. of Agriculture. CropScape depicts the type and locations of various crops across the country. This data can be used for a variety of purposes including: identifying food insecure regions and climate change related growing patterns. This resource also defines unmanned aerial vehicles (UAV’s), thermal infrared radiation (TIR), and variable rate technology (VRT) as tools that provide data that is then analyzed within a geographic information system. This is a valuable resource as it is specific to the technological aspect of precision farming and how GIS contributes to this field of research.

Bates, R. M., Erlien, C. M., Nielsen, G. A., & Montagne, C. (2002). Exposing Agriculture Students to GPS/GIS: Strategies, Outcomes, New Directions. NACTA Journal, 46(4), 24–28. Available at: http://www.jstor.org/stable/43765700

In this journal article, authors share how agriculture students are encouraged to learn about GIS technology as a crucial and developing part of their field. They identify precision farming, or site-specific farming, as a growing practice that combines holistic approaches and information technology. It is predicted that precision farming, and the technological savvy that comes with it, is only going to increase. Thus, educating future agriculturalists is key. There is evidence that these technologies will aid in farmers’ ability to maintain stability through a deeper understanding of the trends and features around them. This journal in particular focuses on how important it is for students to understand this information as well; it is becoming a new normal to be able to use GIS systems in many different fields.