Investigating the application of hyperspectral remote sensing in other crop types

The gap

Evidence profile

Sourced from the stated research gap and abstract and future-work section of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 5 journals. Those papers have been cited 15 times in total.

Supporting evidence — 6 representative gaps

• DEVELOPMENT OF A SPATIO-TEMPORAL CHANGE DETECTION APPROACH FOR CROP AND DROUGHT STRESS MONITORING USING SENTINEL-2 IMAGES (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The study identifies a gap in the existing methods for change detection in crop stress and drought stress monitoring. The primary aim of this research is to find an appropriate technique for change detection in crop stress and drought stress monitoring.

  generalstated research gapevidence 5/5
  Keywords: study identifies gap existing methods change detection crop
• Assessing rice genotype dependency in remote sensing: challenges in nitrogen discrimination and yield forecasting (2026) · Precision Agriculture · doi

  The current Remote Sensing models are calibrated for specific varieties, limiting their application across diverse cultivars. There is a need for climate-resilient production systems, adaptive management, and improved technological options.

  generalstated research gapevidence 5/5
  Keywords: current remote sensing models calibrated specific varieties limiting
• Estimation of Grain Yield and Quality in Awned and Awnless Wheat Genotypes Using UAV and Proximal Multispectral Sensors (2026) · Plants · 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.

  generalstated research gapevidence 5/5
  Keywords: global wheat production increasingly affected climate change including
• Modeling soil respiration in summer maize cropland based on hyperspectral imagery and machine learning (2025) · Frontiers in Environmental Science · cited 1× · doi

  However, it remains uncertain whether hyperspectral remote sensing can provide an accurate and efficient method for estimating SR rate in croplands, particularly across different maize growth stages of under varying drought conditions.

  generalabstractevidence 5/5
  Keywords: remains uncertain whether hyperspectral remote sensing provide accurate efficient estimating rate croplands particularly across different
• Inversion of Crop Water Content Using Multispectral Data and Machine Learning Algorithms in the North China Plain (2024) · Agronomy · cited 13× · doi

  Little effort has been devoted to accurately estimating the crop water content of winter wheat in the North China Plain. Traditional methods for estimating CWC are labor intensive, time consuming, and limited in spatial coverage.

  generalstated research gapevidence 5/5
  Keywords: little effort has been devoted accurately estimating crop
• Modeling soil respiration in summer maize cropland based on hyperspectral imagery and machine learning (2025) · Frontiers in Environmental Science · cited 1× · doi

  Investigating the application of hyperspectral remote sensing in other crop types, - Examining the impact of different drought treatments on SR, - Developing more accurate models for predicting SR in croplands

  generalfuture-work sectionevidence 5/5
  Keywords: investigating application hyperspectral remote sensing other crop types

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