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Journal of Agricultural, Biological and Environmental Statistics - Call for Papers: Special Issue on New Perspectives in Statistics, Data Science and Econometrics for Agriculture, Land Use and Forestry

The Journal of Agricultural, Biological and Environmental Statistics is seeking submissions to a forthcoming Special Issue on New Perspectives in Statistics, Data Science and Econometrics for Agriculture, Land Use and Forestry. 

Human activities impact terrestrial sinks, through land use, land-use change and forestry (LULUCF), altering the carbon cycle between the terrestrial biosphere and the atmosphere (United Nations Climate Change, 2023). The 6th Intergovernmental Panel on Climate Change report (IPCC - The Intergovernmental Panel on Climate Change, 2023) finds that, on average, Agriculture, Forestry and Other Land Use were responsible for 13 to 21% of global total anthropogenic GHG emissions between 2010 and 2019. However, the report also states that the LULUCF sector offers significant near-term mitigation potential while providing food, wood and other renewable resources as well as biodiversity conservation. Improved and sustainable crop and livestock management, sustainable farming practices, and soil carbon sequestration in agriculture (including soil carbon management in croplands and grasslands, and agroforestry) are the most relevant tools for mitigation policies.

In this context, the development of new data-driven, statistical, and econometric methodologies addressing the socio-economic and environmental challenges of agriculture and soil use are essential. We, therefore, invite methodological and applied contributions for a special issue on the topic of statistics, data science methods and econometrics for the analysis and modelling of agricultural, forestry, land use and land change data.

Submission topics of interest include but are not limited to:

  • Spatio-temporal statistics methods (e.g., geostatistics, spatial point processes, areal models, Bayesian spatial and spatio-temporal models, spatio-temporal prediction) to analyze agricultural data, land use and land cover changes, and forestry data
  • Small Area Estimation and Model-Assisted Estimation models applied to agro-industry surveys, land use and cover, and forestry inventories
  • Econometrics methods, with a particular interest in spatial and spatio-temporal econometrics, focusing on the impact assessment of agricultural-related policies and the economic analysis of the agricultural sector and human-induced land use
  • Statistical machine learning models, especially those accounting for the spatial and temporal dimensions of agricultural, land use and forestry data
  • Data-driven analyses of remote sensing and satellite data related to land use, land cover, and farming
  • Data-driven analyses of policy actions devoted to land and forestry protection, mitigation of human-induced land consumption and climate change
  • Data-driven analyses of structural characteristics of the agro-industry, with particular attention to macro trends and evolution of the industry (e.g., self-sustainability of farms in terms of energy production, waste management and techno-productive innovations)


All papers will undergo a thorough peer-review process, and accepted papers will be published in a special issue of the Journal of Agricultural, Biological and Environmental Statistics. Submission guidelines and deadlines will be announced in due course. We look forward to receiving your submissions and to stimulating discussions.

Guest Editors
Felicetta Carillo, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA-PB), Milano, Italy
email: felicetta.carillo@crea.gov.it (this opens in a new tab)

Paolo Maranzano, Università degli Studi di Milano-Bicocca (UniMiB), Milano, Italy & Fondazione Eni Enrico Mattei (FEEM), Milano, Italy
email: paolo.maranzano@unimib.it (this opens in a new tab)

Philipp Otto, University of Glasgow (UofG), Glasgow, United Kingdom
email: philipp.otto@glasgow.ac.uk (this opens in a new tab)

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