A statistical and machine learning methodology to model rural depopulation risk and explore its attenuation through agricultural land use management

Jato-Espino, Daniel; Mayor-Vitoria, Fernando

doi:10.1016/j.apgeog.2023.102870

Cited by 16 publications

(7 citation statements)

References 63 publications

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“…Jato-Espino and Mayor-Vitoria (2023) developed a statistical and ML methodology to model the risk of rural depopulation and investigate its mitigation through agricultural land use management. The expansion of the Brazilian sugarcane industry has been associated with deforestation in the Amazon rainforest (Benites-Lazaro et al , 2018).…”

Section: Thematic Areasmentioning

confidence: 99%

Machine learning for sustainable development: leveraging technology for a greener future

Kagzi,

Khanra,

Paul

2023

JSIT

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Purpose From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries. Design/methodology/approach This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development. Findings ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals. Originality/value This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

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Section: Thematic Areasmentioning

confidence: 99%

Machine learning for sustainable development: leveraging technology for a greener future

Kagzi,

Khanra,

Paul

2023

JSIT

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“…For example, researchers have studied the feasibility of early prediction of yield per coffee tree based on multispectral aerial imagery in Colombia (Sousa et al, 2020;Giang et al, 2022;Jato-Espino & Mayor-Vitoria, 2023). This type of classification can be useful for determining areas with an agricultural vocation to expand crop areas according to the specific soil and climate needs of the crops.…”

Section: Group Search Stringmentioning

confidence: 99%

Assessing the impact of emerging technologies on sustainable fruit production: A systematic review of the literature

Pardo-Pardo,

Cuervo-Bejarano

2023

Agron. Colomb.

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Agriculture 4.0 refers to innovations in technological tools used in agriculture to achieve different objectives, such as adapting the supply chain to avoid waste, increasing productivity and collecting mass data through ICT (Information and Communication Technologies) to meet the growing food demand of the population. The objective of this study is to conduct a systematic literature review to evaluate the impact of emerging technologies on sustainable fruit production. Initially, a bibliographic search was conducted on the technologies currently implemented in agriculture; the Bibliometrix library of the R Studio software was used, and then an analysis of relevant scientific publications published in the last ten years was carried out through the VOSviewer® software, which allowed the construction and visualization of bibliometric networks. The results show Europe and China as the leading regions in technological development, while developing countries face economic and research limitations; in Colombia, the use of Agriculture 4.0 is focused on the implementation of satellite images for monitoring agro-climatic conditions. In summary, Agriculture 4.0 aims to achieve economic, social, and environmental sustainability in the agri-food sector through data-generating technologies to improve production, reduce costs, and ensure food safety and quality. However, there is a technology gap between developed and developing countries that affects the adoption of these innovations. More support is therefore needed from governments, academia, and the private sector to drive innovation, training, and adoption of these technologies, which can contribute to the economic, social, and environmental development of the country.

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“…Исељавање из руралних подручја резултира ефектом снежне грудве при чему се објекти и услуге које су потребне градским становницима прогресивно смањују. Напуштање руралних заједница је посебно акутно у случају младих одраслих, што се упарује са старењем становника који остају у том подручју, што доводи до смањене самоаутономије (Jato−Espino & Mayor−Vitoria, 2023).…”

Section: уводunclassified

“…Рурална депопулација је важан проблем глобалних размера. Стога би требало креирати моделе користећи глобалне отворене податке за груписање ширих региона у складу са њиховим ризиком од руралне депопулације и покретачима у различитим контекстима (Jato-Espino & Mayor-Vitoria, 2023). Главни фактори процеса депопулације и демографског старења су: емиграција, као и директне и индиректне последице процеса емиграције и процес индустријализације у коме је дошло до концентрације индустрије у градским насељима ван проучаване територије.…”

Section: закључакunclassified

Population dynamics of settlements of the City of Prokuplje in 1991-2022 period

Mihajlović,

Novović

2023

Demografija

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Depopulation and the emptying of settlements are a global process, which is largely represented in our country as well. Demographic changes in the structure of the population are more pronounced and intense in the settlements, which are far from the city centers and are located at higher altitudes. Depopulation, which is strongly present in the area of Southern Serbia, has the effect that some settlements are almost empty or have an older population and a very small share of young people. The aim of this paper is to present the population dynamics of the settlements of the City of Prokuplje in relation to their altitude in the period 1991-2022. For this reason, research was conducted based on the distribution of settlements in the City of Prokuplje into three groups according to altitude. The findings indicate a noticeable difference in the population dynamics of three groups of settlements and show to what extent the negative indicators of the number of inhabitants in the settlements are related to the altitude based on comparative and correlation analysis. The results provide insight into the state of demographic development and could help to create a more complete demographic picture of the City of Prokuplje.

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A statistical and machine learning methodology to model rural depopulation risk and explore its attenuation through agricultural land use management

Cited by 16 publications

References 63 publications

Machine learning for sustainable development: leveraging technology for a greener future

Machine learning for sustainable development: leveraging technology for a greener future

Assessing the impact of emerging technologies on sustainable fruit production: A systematic review of the literature

Population dynamics of settlements of the City of Prokuplje in 1991-2022 period

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