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Land
Special Issues
Building Climate-Resilient Farms: Navigating Risks and Adaptation in Agriculture
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Building Climate-Resilient Farms: Navigating Risks and Adaptation in Agriculture

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Water, Energy, Land and Food (WELF) Nexus".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2841

Special Issue Editor

Dr. Nasir Abbas Khan

E-Mail Website
Guest Editor
School of Environmental Design and Rural Development, University of Guelph, Guelph, Canada
Interests: climate change risks and adaptation in agriculture; ICT in agricultural extension; institutional capacities evaluation; climate change vulnerability; impacts in agriculture

Special Issue Information

Dear Colleagues,

The agricultural and associated sectors are increasingly vulnerable to the multifaceted impacts of climate change, which pose significant risks to food security, livelihoods and environmental sustainability. From unpredictable weather patterns and extended droughts to more frequent extreme events, the challenges farmers face are intensifying. As these threats grow, the need for climate-resilient farming practices becomes more urgent.

This Special Issue aims to explore innovative approaches and strategies that enhance the resilience of farms in the face of these climatic uncertainties. By focusing on both the risks associated with climate change and the adaptive measures that can mitigate these risks, this collection of research seeks to provide actionable insights for farmers, policymakers and researchers alike.

The Special Issue will cover a broad spectrum of topics, including the adoption of climate-resilient crop varieties, sustainable soil and water management techniques, and the integration of advanced technologies such as precision agriculture. Additionally, it will examine the role of policy frameworks, institutional arrangements and capabilities, and community-based initiatives in supporting farm-level resilience. Through a combination of empirical studies, theoretical frameworks and case studies from diverse geographic regions, this Special Issue will contribute to a deeper understanding of how agricultural systems can adapt to the changing climate while ensuring long-term productivity and sustainability.

This Special Issue aims to explore and disseminate research on enhancing farm resilience in the face of climate change. It seeks to identify effective strategies for mitigating climate-related risks, improving farm efficiency and ensuring food security through innovative adaptation techniques. By addressing both the vulnerability and resilience of agricultural systems, this Special Issue aligns with the journal’s scope, which focuses on sustainable land management and the integration of environmental, economic and social dimensions in land use. The Special Issue will contribute valuable insights into creating more resilient and sustainable agricultural landscapes.

This Special Issue will welcome manuscripts that link the following themes:

  • Strategies for building climate-resilient farms;
  • Vulnerability and resilience in agricultural systems;
  • Climate-smart agricultural practices and adaptation strategies;
  • Climate change adaptation and food security;
  • Disaster Risk Management in Agriculture.

We look forward to receiving your original research articles and reviews.

Dr. Nasir Abbas Khan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change
  • agricultural adaptation
  • vulnerability and resilience
  • climate-smart practices
  • food security
  • sustainable land management

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

15 pages, 4536 KiB  
Article
A Machine Learning Approach to Generate High-Resolution Maps of Irrigated Olive Groves
by Rosa Gutiérrez-Cabrera, Ana M. Tarquis and Javier Borondo
Land 2025, 14(5), 1001; https://doi.org/10.3390/land14051001 - 6 May 2025
Viewed by 286
Abstract
The increasing severity of water scarcity in southern Europe, caused by climate change, requires advanced and more efficient approaches to agricultural water management. In particular, in this paper, we address this problem for olive groves—a cornerstone of the region’s economy. We propose a [...] Read more.
The increasing severity of water scarcity in southern Europe, caused by climate change, requires advanced and more efficient approaches to agricultural water management. In particular, in this paper, we address this problem for olive groves—a cornerstone of the region’s economy. We propose a novel framework for generating high-resolution maps of irrigated olive groves that integrates remote sensing imagery and machine learning. Our approach leverages multi-temporal Sentinel-2 data, specifically the Normalized Difference Vegetation Index (NDVI), to capture seasonal vegetation dynamics. For classification, we explore two distinct models: (1) A Dynamic Time Warping (DTW)-based approach (with and without the Sakoe–Chiba Band constraints), where DTW aligns temporal NDVI sequences to enable robust comparisons of irrigation regimes, followed by a K-Nearest Neighbor classifier (KNN) that classifies plots as irrigated or rainfed. (2) An eXtreme Gradient Boosting (XGBoost) model that directly uses temporal NDVI profiles. Additionally, we compare the dependence of model performance on the length of the NDVI time series (ranging from one to seven seasons), finding that XGBoost requires a shorter time series to achieve optimal results, while KNN with DTW can benefit from longer historical records. Indeed, XGBoost nearly reaches its maximum accuracy using only data based on three seasons, achieving 0.79 compared to its peak performance of 0.80. Hence, our results indicate that this approach can accurately differentiate between irrigated and rainfed plots, enabling the generation of high-resolution irrigation maps for southern Spain. Finally, we argue that the results of this paper go beyond mere mapping: they lay the foundation for a comprehensive management guide that can optimize water use, with broad implications. Such implications range from empowering precision agriculture to providing a roadmap for land management, ensuring both the sustainability and productivity of olive groves in drought-affected regions. Full article
(This article belongs to the Special Issue Building Climate-Resilient Farms: Navigating Risks and Adaptation in Agriculture)
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17 pages, 2313 KiB  
Article
Investigating the Technical Efficiency and Balanced Development of Climate-Smart Agriculture in Northeast China
by Viet Ha Trinh Thi and Wenqi Zhou
Land 2025, 14(3), 547; https://doi.org/10.3390/land14030547 - 5 Mar 2025
Viewed by 598
Abstract
Climate warming poses a significant threat to China’s national food security as grain production encounters the daunting challenge of climate change. Thus, promoting the shift of agriculture toward climate-smart practices has become an inevitable choice. This study investigated climate-smart agriculture (CSA) practices using [...] Read more.
Climate warming poses a significant threat to China’s national food security as grain production encounters the daunting challenge of climate change. Thus, promoting the shift of agriculture toward climate-smart practices has become an inevitable choice. This study investigated climate-smart agriculture (CSA) practices using agricultural and environmental indicators that affect the technical efficiency of grain farming in Northeast China. The study employs the stochastic frontier analysis approach to estimate the efficiency of the production function and highlight the significant factors that affect efficiency. The entropy weight method was also used to analyze the climate-smart agricultural development index (CSA-DI) and climate-smart balanced development index (CSA-BDI) in Northeast China. The provincial panel data from 1980 to 2017 revealed an increasing trend for the CSA-DI and CSA-BDI. Although the region has achieved initial results in systematicity and coordination, there is still room for improvement in food security and climate change adaptation. Based on these results, this study proposes policy recommendations for CSA technologies and the promotion of comprehensive projects to endorse climate-smart agriculture for regional shared benefits and responsibilities. Full article
(This article belongs to the Special Issue Building Climate-Resilient Farms: Navigating Risks and Adaptation in Agriculture)
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16 pages, 768 KiB  
Article
Part-Time Farming, Agricultural Socialized Services, and Organic Fertilizer Use: Implications for Climate Change Mitigation
by Qi Huang, Saman Mazhar, Jingjing Chen, Ghulam Mustafa and Guanghua Lin
Land 2024, 13(11), 1900; https://doi.org/10.3390/land13111900 - 13 Nov 2024
Viewed by 1092
Abstract
The adoption of organic fertilizers is essential for advancing China’s green agricultural transformation, ensuring food security, and supporting agricultural adaptations. However, several challenges hinder its widespread use in rural areas. This study examines how part-time farming and agricultural service provision influences organic fertilizer [...] Read more.
The adoption of organic fertilizers is essential for advancing China’s green agricultural transformation, ensuring food security, and supporting agricultural adaptations. However, several challenges hinder its widespread use in rural areas. This study examines how part-time farming and agricultural service provision influences organic fertilizer use, employing fixed and random effects models on data from 523 households in Shaanxi Province, one of China’s main apple-producing regions. The results reveal: (1) Part-time farming reduces organic fertilizer use by 7.6%, primarily due to labor shortages; (2) Higher non-farm income exacerbates this decline, particularly for Type II part-time farmers; and (3) Mechanized fertilization services help mitigate this reduction. These findings offer valuable policy insights for promoting organic fertilizer adoption in the context of shifting rural labor dynamics and highlight the complex interactions between farming practices and labor migration in the broader trajectory of organic fertilizer use. Moreover, this study highlights the role of organic fertilizer use in enhancing food security while also helping to reduce the carbon footprint of the crop sector in China. Full article
(This article belongs to the Special Issue Building Climate-Resilient Farms: Navigating Risks and Adaptation in Agriculture)
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