## 4 Discussion
### Future Research Directions  
Smallholders require options that offer relatively low risk while still providing short term returns on investment. Consequently, building resilient systems is essential for both risk management and long-term sustainability. Achieving this requires investments that go beyond plot-level technologies, extending to policies and institutional measures that facilitate adoption and help reduce risks for small-scale agriculture and farming systems in all means [7; 13; 208]. In this context, RS can play a vital role by providing the data and insights needed to make informed decisions at various levels, from field management to policy-making. The reviewed literature, as displayed in Table 2, already highlights the considerable potential of RS while also acknowledging its current limitations. As the field continues to evolve, advancements in RS data quality, the availability of high-quality reference datasets, and methodological approaches are anticipated. Building on those findings, several research gaps, and opportunities for future development should be emphasized. These areas represent important directions for advancing the field and addressing existing limitations:  
* Integrating multiple data sources from RS and non-RS origins, such as field measurements and socio-economic datasets, will help to overcome the spatial, temporal, and radiometric constraints. This integration enhances crop monitoring, yield predictions, and contextual understanding, enabling more accurate and targeted solutions for small-scale agriculture. * Future research should focus on leveraging advancements in artificial intelligence and data fusion to revolutionize satellite-based applications. By integrating diverse datasets, including high-resolution and multi-sensor data, these methods could enable breakthroughs in precision crop monitoring, yield prediction, and land use analysis. Addressing challenges such as processing efficiency, model scalability, and effective multi-source data fusion will be key to unlocking the full potential of these technologies for more robust and actionable insights [198]. * Advancing crop monitoring and management practices through the development of new methods for the detection of phenology and agricultural interventions, including irrigation plans, number of cropping seasons, and plant residue management. This progress will help optimize resource use and inform targeted interventions [62; 100; 107; 108]. * An increased prominence of radar data, in particular SAR will play a crucial role in overcoming challenges posed by cloud cover in West Africa. The anticipated launch of Sentinel-1C in late 2024 is expected to further expand capabilities for all-weather monitoring of agricultural areas [209]. * Advances in daily high-resolution imagery will support near real-time crop monitoring, enabling timely decision-making for farmers and stakeholders to improve productivity and respond effectively to environmental challenges. * Enhanced retrieval of plant parameters, such as LAI and chlorophyll content, will provide more detailed and frequent information on crop health, growth, and conditions, improving precision agriculture practices. * The evolution of methods to derive field plot properties, such as soil characteristics, landscape organization [71], and field boundaries, will provide critical data to support smallholder farmers. This includes facilitating access to financing and insurance for smallholder cropping systems by offering accurate and actionable insights [203; 210]. * The continued refinement of hyperspectral data will enhance the detection of non-photosynthetic vegetation (NPV), leading to better quantification f crop residues and biochemical traits. This will contribute to a deeper understanding of soil health and sustainable farming practices [211]. * The development of monitoring systems for sustainable intensification practices is set to enhance resource use efficiency, encompassing water, energy, fertilizers, and soil.