Remote sensing is a technology that has been utilized extensively in agriculture due to its capacity to provide precise and detailed information on various aspects of agricultural production. Farmers and researchers have utilized this technology to gain valuable insights regarding, among other things, crop phenology, yield prediction, land classification, soil quality, water management, and environmental monitoring. The present dissertation is structured into six chapters, with the first serving as an introduction to remote sensing technology in agriculture and the last chapter offering concluding remarks. The remaining chapters delve into various applications of remote sensing technology in agriculture.

 

The second and third chapters examine the potential of remote sensing to classify maize phenology in Kansas, utilizing three distinct image resolutions. The second chapter identifies the optimal combination of spectral bands, vegetation indices, and weather data for phenology classification using Landsat 8 as a source of spectral information.  In chapter three, greater temporal and spatial resolution was  tested using Sentinel-2 and Planet Fusion, and the classification performance of both sources was compared. The model was tested in different areas, and the results emphasized the significance of temporal and spatial resolution for traits like phenology that can change rapidly.

 

Chapter four explores the use of remote sensing technology to identify areas in Cambodia with traditional management practices where conservation agriculture could play a critical role. The study employs 3-meter daily imagery from Planet Fusion and image segmentation tools to distinguish between burned patches and bare soil after ploughing. The results demonstrate that these images, in conjunction with image segmentation tools, have the potential to identify management practices in areas where obtaining ground-truth data could be challenging. 

 

Finally, chapter five discusses the current state of the art and the necessary changes to integrate soil science methods and remote sensing for determining soil organic carbon. This chapter examines the challenges and opportunities associated with using remote sensing to monitor soil properties and offers viable solutions for bridging these two domains.

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You can find the full document here: https://krex.k-state.edu/handle/2097/42977

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