IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2012 · 72 citations · 16 references
EngineeringAgricultural EngineeringOpticsPhotonicsSensorsEnvironmental SensingOptical InstrumentsOptical SensingOptical SensorsPhysical OpticsSensor Data AcquisitionAgricultural SensorsOptical Measurement SystemsProximal Sensing In Agriculture
Portable proximal active optical sensors are increasingly used in production agriculture for crop and soil mapping and agrochemical application, yet most users lack understanding of their underlying optics and construction. This study documents the electro‑optical principles and mathematical rules that govern the operation of these sensors, focusing on the inverse‑square law and its impact on measurements. It presents how sensor data can be transformed through wavelength‑response manipulation to compute distance variations between sensor and target, enabling more complex analytical functions.
Over the last decade, portable, active optical sensors (AOS) have become tools in production agriculture both for mapping crops and soils and also for applying agrochemicals. These sensors are often referred to as "proximal" active optical sensors, in recognition of their deployment at sensor-target distances in the order of meters. Unfortunately most users have little understanding of the underlying physics (optics) or construction of these sensors. This paper sets out to document the fundamental electro-optical principles by which these devices operate and to document the mathematical rules governing the use of data produced by these devices. In particular, emphasis is placed on the inverse-square law of optics and how it affects AOS measurements. The basis for utilizing sensor measurements in more complex mathematical functions is also presented, including manipulation of the individual wavelength response data to derive information regarding the distance variation between the sensor and the target.
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A soil-adjusted vegetation index (SAVI)
Alfredo Huete · Remote Sensing of Environment · 1988 · 7.7K citations
Derivation of Leaf‐Area Index from Quality of Light on the Forest Floor
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