Remote and Proximal Sensing for Supporting the Optimization and Adaptation of Cultural Practices in Sustainable Agriculture

Dear Colleagues,

Since the Green Revolution, all sectors of agriculture have experienced tremendous intensification, while new practices increased agricultural productivity. The latter became possible by means of breeding for new varieties, adoption of innovating technologies, and—especially the last years—increased used of inputs and natural resources. Climate change, in combination with the ever-increasing food demand and the realization that natural resources are finite, introduced challenges in this industrialized form of agricultural and underlined the need for a sustainable and resource-efficient agricultural transformation, which will secure production at the same time.

A key concept in this agricultural transformation is the adaptation of new types of cultural practices, exploiting the technological innovations of our era. The digitization of the agricultural sector has gained momentum the last decades, exploiting technological advances such as customized machinery, Internet of Things (IoT) solutions and Artificial Intelligence (AI) workflows. Within this context, remote and proximal sensing play a pivotal role, since they provide a wealth of information that can support the necessary adaptation of cultural practices towards a more sustainable agriculture, with reduced environmental footprint and with care for human health. Various remote sensing applications provide support towards the adaptation of cultural practices: monitoring or estimating current state, predicting risks, identifying deficiencies and diseases, forecasting yield, etc.

The purpose of this Special Issue is thus to collect contributions proposing innovative solutions for supporting cultural practices in all sectors of agriculture, based on remote and/or proximal sensing technologies. Specific topics include, but are not limited to, the following:

• Remote and proximal sensing applications for adapting all levels of cultural practices to ensure sustainability and adaptation to climate change
• Data assimilation and fusion from multiple sources for supporting informed decision making by stakeholders of different levels
• Remote sensing applications that support policy adaptation towards sustainable agriculture
• Machine learning approaches for transforming remote sensing data into relevant information for devising actionable strategies
• Estimation and forecasting of yield at different spatial units
• Assessing crop and livestock status and health risk factors at different temporal intervals
• Agronomic traits and bio-physical crop parameters estimation and monitoring at different spatial scales and temporal intervals
• Holistic approaches for the optimization of the production process at any level
• Methodologies and tools that foster the digitalization of the agricultural sector
• Interoperability and capitalization of specialized sensory systems

Dr. Dimitris Stavrakoudis
Dr. Dimitrios Katsantonis
Guest Editor

Manuscript Submission Information

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• Cultural practices
• Agriculture
• Sustainable agriculture
• Remote sensing
• Proximal sensors
• Agricultural digitization
• Machine learning
• Agronomic traits
• Biophysical parameter estimation