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Open research questions in Remote Sensing in Agriculture

384 unresolved questions extracted from the limitations and future-work sections of 948 Remote Sensing in Agriculture papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • the reference used for training and validation came from the same annual sampling framework, - the study was limited to the area adjacent to Nevado de Colima, - the lack of explicit procedures for validating thematic and area accuracy can lead to biased estimates

    Forest Cover Change in the Nevado de Colima Using Sentinel-2 and an Enriched Random Forest Classifier with Slope and Spectral Indices · 2026 · DOI

  • The lack of explicit procedures for validating thematic and area accuracy can lead to biased estimates. The omission of relevant environmental variables in forest masks can generate biased estimates of forest cover change.

    Forest Cover Change in the Nevado de Colima Using Sentinel-2 and an Enriched Random Forest Classifier with Slope and Spectral Indices · 2026 · DOI

  • the study only analyzed 18 forest sites across Europe, - the sample size was limited to 31 droughts, - the study did not account for other factors that may impact forest productivity

    Evaluating vegetation indices for monitoring drought and post-drought declines in European forest productivity · 2026 · DOI

  • investigate the impact of drought on forest productivity at larger spatial scales, - analyze the response of VIs to drought in different forest types and regions, - develop more accurate models of forest carbon uptake using remote sensing data

    Evaluating vegetation indices for monitoring drought and post-drought declines in European forest productivity · 2026 · DOI

  • Uncontrolled resource overexploitation and open-access grazing pose significant challenges to the management of arid rangelands. The breakdown of traditional community-based management frameworks has led to a lack of effective management strategies. Quantifying the combined effects of season and landform on plant biomass and livestock carrying capacity is a complex task.

    Seasonal and landform effects on plant productivity and carrying capacity at Bisha Rangeland, Saudi Arabia · 2026 · DOI

  • experimental isolation of mechanisms influencing SOC storage, - replication of management–soil combinations, - characterization of continuous SOC dynamics

    Widespread Greening but Uneven Soil Carbon Change: Twenty-Year Evidence from a Semi-Arid Eurasian Steppe · 2026 · DOI

  • The need for accurate assessment of long-term soil organic carbon change. The importance of explicit treatment of temporal differences in soil mass. The lack of consideration of management–soil combinations in SOC change studies.

    Widespread Greening but Uneven Soil Carbon Change: Twenty-Year Evidence from a Semi-Arid Eurasian Steppe · 2026 · DOI

  • Further research is needed to evaluate the performance of the models with more genotypes and seasons - The use of other remote sensing technologies and machine learning algorithms could be explored - Investigation of the relationships between VI values and other grain quality parameters could be conducted

    Estimation of Grain Yield and Quality in Awned and Awnless Wheat Genotypes Using UAV and Proximal Multispectral Sensors · 2026 · DOI

  • Global wheat production is increasingly affected by climate change, including more frequent and severe drought stress events. Precise and periodic monitoring of crop characteristics is necessary. There is a need for advanced remote sensing technologies to monitor and assess vegetation status.

    Estimation of Grain Yield and Quality in Awned and Awnless Wheat Genotypes Using UAV and Proximal Multispectral Sensors · 2026 · DOI

  • The long-term sustainability of restoration-fueled carbon growth remains unclear. Whether ecosystem carbon sinks can maintain continuous enhancement after prolonged restoration remains uncertain. The need for accurate assessment of the spatiotemporal evolution and carbon sequestration potential of regional carbon storage.

    Dynamic Carbon Stock Mapping Reveals a Shift from Rapid Accumulation to Decelerating Carbon Growth After Ecological Restoration on the Loess Plateau · 2026 · DOI

  • While deciduous forests with various leaf forms employ distinct ecological strategies, their vegetation coverage dynamics across the growing season and intra-seasonal periods, as well as their responses to climatic change, remain unclear.

    Divergent impacts of temperature and precipitation changes on leaf area index of deciduous broadleaf and needleleaf forests in the Northern Hemisphere · 2026 · DOI

  • Vegetation dynamics are strongly associated with climate variability, yet large-scale quantification of vegetation's temporal lag responses to climatic drivers remains poorly understood.

    Optimal lag time analysis and relative importance decomposition for insights into ecosystem climate adaptation · 2026 · DOI

  • However, the spatiotemporal extent to which satellite-derived SIF and vegetation traits encode meteorological constraints for prediction of GPP remains insufficiently understood.

    Assessing the Role of Global Satellite-Derived SIF and Vegetation Traits as Proxy Predictors of Gross Primary Productivity · 2026 · DOI

  • However, existing studies are largely limited to the binary classification of immature and mature fruits, lacking dynamic evaluation and precise prediction of maturity states.

    Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model · 2025 · DOI

  • Although numerous techniques have been developed, ranging from traditional field-based measurements to advanced remote sensing and machine learning methods, a comprehensive synthesis that critically evaluates these approaches and explores their convergence is still lacking.

    Advancements in maize yield estimation: a comprehensive review of methods and models · 2025 · DOI

  • Whereas the spatiotemporal variability of vegetation phenology has been studied at regional and continental scales, the spatiotemporal variability in Botswana is still not well understood.

    Uncovering the shifts: land surface phenology in Botswana from satellite observations · 2025 · DOI

  • There has been a growing use of remote sensing, climate data, and their combination to estimate yields, but the optimal indices and time window for wheat yield prediction in arid regions remain unclear.

    Improving Wheat Yield Prediction with Multi-Source Remote Sensing Data and Machine Learning in Arid Regions · 2025 · DOI

  • Previous studies have applied 1D CNN, 2D CNN, LSTM, and GRU, often standalone, but their capacity to jointly process spectral and vegetative features through integrated CNN-RNN structures remains underexplored in mixed agricultural regions.

    Deep Learning Applications for Crop Mapping Using Multi-Temporal Sentinel-2 Data and Red-Edge Vegetation Indices: Integrating Convolutional and Recurrent Neural Networks · 2025 · DOI

  • As a major factor affecting vegetation growth, the role of soil moisture in the impacts of climate change on vegetation is not well understood.

    Impacts of Climate Change and Human Activities on Vegetation Productivity in China · 2025 · DOI

  • Unmanned aerial system (UAS) imagery offers an effective means for high-throughput crop monitoring, yet its performance across spatial resolutions remains insufficiently characterized.

    Effects of Spatial Resolution on Assessing Cotton Water Stress Using Unmanned Aerial System Imagery · 2025 · DOI

  • Future research should explore object-based approaches and advanced classifiers (e.

    Assessment of Vegetation Indices Derived from UAV Imagery for Weed Detection in Vineyards · 2025 · DOI

  • Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence.

    Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change · 2024 · DOI

  • High throughput field phenotyping techniques employing multispectral cameras allow extracting a variety of variables and features to predict yield and yield related traits, but little is known about which types of multispectral features are optimal to forecast yield potential in the early growth phase.

    Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering · 2024 · DOI

  • However, its effectiveness for yield estimation under various data fusion conditions has not been thoroughly explored.

    BO-CNN-BiLSTM deep learning model integrating multisource remote sensing data for improving winter wheat yield estimation · 2024 · DOI

  • In conclusion, in response to the current issues and technological limitations, future research should focus on studying the nitrogen content characteristics of fruit trees during different phenological periods, integrating multi-type data information, and thereby improving the universality of the nitrogen content inversion model for fruit trees.

    Nitrogen monitoring and inversion algorithms of fruit trees based on spectral remote sensing: a deep review · 2024 · DOI

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384 open questions have been extracted from the limitations and future-work passages of 948 Remote Sensing in Agriculture papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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