top of page
  • Writer's pictureSindhu Sivakumar

Remote Sensing in Agriculture: Where Remote Sensing meets the humanity at its best

Updated: Jun 28


Agriculture is our livelihood's basic need, since it provides humanity with all the raw materials, fuels, fibers, and food. For ages and ages, farmers have given their lives for farming with fewer resources and technologies. If it is possible to monitor the farming land before hand or test the health of a plant without getting in contact with it, why not? This is where Remote Sensing comes into play. Remotely sensed images captured by satellites and aircraft allow for assessing field conditions from a high altitude without physically touching the ground.


(Remote Sensing Techniques for Diverse Agricultural Applications)



Applications of Remote Sensing in Agriculture:


Agriculture is one of the most essential land-use activities in the world. Apart from changing land cover, agriculture significantly impact the social economy's long-term development, the carbon cycle, climate change, ecosystem services, food security, and so on.


Remote sensing technology has several applications, including forestry, geology, surveying, and photography. However, the most practical application of remote sensing has been in agriculture. The following are a few of the many agricultural and remote sensing uses.


Crop type identification and classification:


  • Crop Type Mapping: Identifying and mapping different crop types over large areas supports agricultural planning and policy-making.

  • Land Use Changes: Monitoring changes in land use and land cover helps understand the environmental impacts of agricultural practices.

  • Crop Type Mapping: Identifying and mapping different crop types over large areas supports agricultural planning and policy-making.


Crop planning and monitoring:


Remote sensing provides farmers with complete information on optimum environmental and weather conditions well into the future, allowing them to better plan their agricultural cycles.

  • Health Assessment: Using vegetation indices like the NDVI (Normalized Vegetation Index), farmers can assess the health and Vigor of crops, identifying stressed or diseased areas early on.

(NDVI range indicating crop conditions)


Yield analysis:


  • Early Yield Estimates: Remote sensing can provide early crop yield estimates, allowing farmers and policymakers to plan and make informed marketing and supply chain management decisions.

  • Monitoring Growth Anomalies: Remote sensing helps understand potential yield impacts, and take corrective actions.


Soil and water management:


  • Soil Moisture Monitoring: Remote sensing technologies can estimate soil moisture levels, aiding in efficient irrigation management and preventing over- or under-watering.

  • Soil Texture and Composition: Hyperspectral sensors can provide detailed information on soil properties such as texture, organic matter content, and nutrient levels.


Pest infestation:


  • Early Detection: Remote sensing can detect early signs of pest infestations and diseases, allowing for prompt intervention and control measures.

  • Spread Monitoring: Tracking the spread of pests and diseases helps implement targeted control strategies.



Conclusion:


Remote sensing revolutionizes agriculture by providing critical insights that enhance productivity, sustainability, and resource management. Through applications such as crop monitoring, soil analysis, yield prediction, and disaster management, remote sensing enables farmers to make informed decisions and optimize their practices. The technology also supports sustainable farming, policy formulation, and market analysis. Despite challenges like data processing complexity and cloud cover interference, the benefits of remote sensing—cost efficiency, timeliness, scalability, and accuracy—make it an invaluable tool for modern agriculture. By leveraging these advancements, the agricultural sector can achieve greater efficiency and resilience, contributing to global food security and environmental sustainability.


Reference:


  • M. Weiss, F. Jacob, G. Duveiller, Remote sensing for agricultural applications: A meta-review, Remote Sensing of Environment, Volume 236, 2020, 111402, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2019.111402.


  • Kumawat, Lalchand & Bala, Biplove & Kumawat, Ganpat & kuldeepKuldeep, Himanshu & Reddy, B. (2023). Remote Sensing Approaches and Application in Agriculture.


  • Wójtowicz, Marek & Wójtowicz, Andrzej & Piekarczyk, J.. (2016). Application of remote sensing methods in agriculture. 11. 31-50.



Recent Posts

See All

Comentários


bottom of page