Journal Article

Advancement of Remote Sensing for Soil Measurements and Applications: A Comprehensive Review

Abdulraheem, Mukhtar Iderawumi, Moshayedi, Ata Jahangir, Farooque, Aitazaz A., Hu, Jiandong, Li, Shixin, Zhang, Wei

2023

Overview

Remote sensing (RS) techniques offer advantages over other methods for measuring soil properties, including large-scale coverage, a non-destructive nature, temporal monitoring, multispectral capabilities, and rapid data acquisition. This review highlights the different detection methods, types, parts, and applications of RS techniques in soil measurements, as well as the advantages and disadvantages of the measurements of soil properties. The choice of the methods depends on the specific requirements of the soil measurements task because it is important to consider the advantages and limitations of each method, as well as the specific context and objective of the soil measurements, to determine the most suitable RS technique. This paper follows a well-structured arrangement after investigating the existing literature to ensure a well-organized, coherent review and covers all the essential aspects related to studying the advancement of using RS in the measurements of soil properties. While several remote sensing methods are available, this review suggests spectral reflectance, which entails satellite remote sensing and other tools based on its global coverage, high spatial resolution, long-term monitoring capabilities, non-invasiveness, and cost effectiveness. Conclusively, RS has improved soil property measurements using various methods, but more research is needed for calibration, sensor fusion, artificial intelligence, validation, and machine learning applications to enhance accuracy and applicability.

• Publisher: MDPI AG
• Subject: Agricultural management / Agricultural production / Agriculture / Artificial intelligence / Artificial satellites in remote sensing / Data analysis / Data entry / Decision making / Environmental management / Environmental monitoring / Geospatial data / Land use planning / Machine learning / Measurement / Radar / Radiation / Remote sensing / Satellites / Sensors / Soil erosion / Sustainability