Visual analytics and remote sensing imagery to support community-based research for precision agriculture in emerging areas

Wachowiak, Mark P.; Walters, Daniel F.; Kovacs, John M.; Wachowiak-Smolikova, Renata; James, April L.

doi:10.1016/j.compag.2017.09.035

Cited by 39 publications

(21 citation statements)

References 35 publications

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“…Nevertheless, there is relatively less focus on land suitability and site selection studies, knowledge-based systems, natural resource allocation and impact assessment applications. In addition, this idea is supported by many researchers (Wachowiak et al 2017 ; Zolekar 2018 ; Dedeoğlu and Dengiz 2019 ; Habibie et al 2019 ; Tercan and Dereli 2020 ). Therefore, the information produced by this study also contributes to the literature.…”

Section: Resultsmentioning

confidence: 83%

Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Turkey

Everest

Sungur

Özcan

2020

Int. J. Environ. Sci. Technol.

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This study was carried out in the district of Lapseki in Çanakkale, Turkey. The suitability of land in Lapseki for agriculture was evaluated by using an analytic hierarchy process. In the study, the basic parameters were determined by using the soil map and the Shuttle Radar Topography Mission data. Land use capability classes, soil depth, erosion risk and other soil properties (limiting factors) were obtained from the soil map, while slope, elevation and aspect were obtained from the Shuttle Radar Topography Mission data. To determine the weight of the parameters in the analytic hierarchy process, the opinions of the public institutions and experts were obtained. The obtained data were analyzed with the analytic hierarchy process and mapped with geographic information systems techniques, and a land suitability map was generated. The agricultural land suitability map demonstrated that 2.95% (2557 ha) of the lands in the study area were highly suitable; 10.37% (8989 ha) were moderately suitable; 53.47% (46,336 ha) were marginally suitable; and 33.21% (28,775 ha) were not suitable for agricultural use. The data from the agricultural land suitability map were compared with the Coordination of Information on the Environment 2012 data. As a result of comparison, 14.12% (361 ha) of highly suitable lands for agriculture and 2.25% (202 ha) of moderate suitable lands for agriculture are urbanized. It was seen that 45.71% (24,837 ha) of the lands that are marginally suitable for agriculture and 18.76% (5397 ha) of the not suitable lands had current land use for agriculture.

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Section: Resultsmentioning

confidence: 83%

Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Turkey

Everest

Sungur

Özcan

2020

Int. J. Environ. Sci. Technol.

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“…Users can pan and zoom to explore spatial data such as those presented in the figures of this study via tile packages hosted remotely or locally saved to users’ Apple iOS and iPadOS devices. The ability to easily incorporate and interact with large satellite imagery datasets has been of great benefit to the Arequipa Nexus Institute during conversations with stakeholders in the field, research planning meetings, formal training workshops, and has greatly enhanced engagement and project‐based participation in knowledge co‐production and capacity building (Duncan, Kyle, and Race 2010; Sletto et al 2010; Canevari‐Luzardo et al 2015; Kar et al 2016; Wachowiak et al 2017; Kim 2018; Onencan, Meesters, and Van de Walle 2018). Recent field research activities, pairing the use of historic and contemporary satellite imagery in the field with data collection applications like Epicollect (Aanensen et al 2009) and LandPKS (Herrick et al 2016), have been very successful.…”

Section: Resultsmentioning

confidence: 99%

Using Remote Sensing to Discover Historic Context of Human‐Environmental Water Resource Dynamics

Brecheisen

Hamp-Adams

Tomasek

et al. 2020

Contemporary Water Research

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Analysis of historic and contemporary high‐resolution imagery can help to fill knowledge gaps in land cover and management history in locations where documentation is non‐existent or records are difficult to access. Historic imagery dating back to the 1960s can be used to structure quantitative investigation and mapping of land use and land cover change across space and time to enhance earth science, policy, and social science research. Imagery can further inform municipal planning and implementation in areas of natural resource allocation, infrastructure, and hazard mitigation. For management and public education, historic imagery can help people to understand environmental processes and the impacts of human activity in the local environment. Here we emphasize the value of high‐resolution historic satellite imagery from the Corona and Keyhole satellite programs to inform environmental research, public education, and environmental management. Within the Region of Arequipa in southern Peru we highlight examples of urban development, agricultural expansion, river channelization, and glacial retreat via comparison of historic and modern satellite imagery. By incorporating these types of historic imagery data in formats accessible to non‐professionals, public engagement as well as research into human‐environmental investigations will be greatly enhanced.

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“…Users, therefore, need additional tools for understanding and interpreting their data [6]. Visualisation is a powerful technique to address these issues and has demonstrated its usefulness in PA [7] to communicate uncertainty from both the data and the models [8]. Visualisation techniques have been used to assist users to better interact and understand data by aggregating, filtering, searching or otherwise sifting through and scaling down relevant information.…”

Section: Introductionmentioning

confidence: 99%

A review of visualisations in agricultural decision support systems: An HCI perspective

Gutiérrez

Htun

Schlenz³

et al. 2019

Computers and Electronics in Agriculture

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Decision Support Systems (DSSs) are used in precision agriculture to provide feedback to a variety of stakeholders, including farmers, advisers, researchers and policymakers. However, increments in the amount of data might lead to data quality issues, and as these applications scale into big, real-time monitoring systems the problem gets even more challenging. Visualisation is a powerful technique used in these systems that provides an indispensable step in assisting end-users to understand and interpret the data. In this paper, we present a systematic review to synthesise literature related to the use of visualisation techniques in the domain of agriculture. The search identified 61 eligible articles, from which we established end-users, visualisation techniques and data collection methods across different application domains. We found visualisation techniques used in various areas of agriculture, including viticulture, dairy farming, wheat production and irrigation management. Our results show that the majority of DSSs utilise maps, together with satellite imagery, as the central visualisation. Also, we observed that there is an excellent opportunity for dashboards to enable end-users with better interaction support to understand the uncertainty of data. Based on this analysis, we provide design guidelines towards the implementation of more interactive and visual DSSs.

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Visual analytics and remote sensing imagery to support community-based research for precision agriculture in emerging areas

Cited by 39 publications

References 35 publications

Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Turkey

Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Turkey

Using Remote Sensing to Discover Historic Context of Human‐Environmental Water Resource Dynamics

A review of visualisations in agricultural decision support systems: An HCI perspective

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