Evaluation of Low-Cost Radiometer for Surface Reflectance Retrieval and Orbital Sensor’s Validation

Abstract

This paper evaluates the Arable Mark 2 sensor, an automated and low-cost radiometer, for its potential to retrieve surface reflectance data and validate orbital sensors such as the Landsat-8 (L8) Operational Land Imager (OLI) Level 2 product. While orbital sensors are widely used for monitoring solar radiation changes, managing natural resources, and understanding climatic trends, atmospheric effects can make it challenging to obtain accurate measurements. Equipped with multiple sensors, including long-wave and short-wave radiometers, the Arable Mark 2 sensor can measure upwelling and downwelling irradiance to calculate surface reflectance. To assess the accuracy and consistency of the Arable Mark 2 sensor, the study performed a cross-calibration using a ground truth measurement collected with the Analytical Spectral Device (ASD) as the reference point. Additionally, a spectral band adjustment factor (SBAF) was applied across the calibrated Arable surface reflectance to compare it against the orbital sensor. An automated library aided in calculating SBAF for the days with unavailable hyperspectral data. The study found that the Arable Mark 2 sensor can provide accurate surface reflectance data that can be used for orbital sensor validation. The Arable sensor was successfully calibrated against the ASD FieldSpec with an average difference of less than 1/10 reflectance unit (reflectance unit = 0.01) for the blue, green, yellow, and red bands. The red-edge and NIR-1 bands showed an average difference of less than 1/2 reflectance units, while the NIR-2 band had an average difference of less than 1/10 reflectance unit of calibration accuracy. The calibrated Arable surface reflectance data was then compared against orbital sensor surface reflectance data, and the results showed good agreement between the two datasets. The study concludes that the low-cost and automated nature of the Arable Mark 2 sensor makes it a promising tool for surface reflectance retrieval and orbital sensor validation.

Study on potential application of brightness temperature models in passive remote sensing

“…An analysis from open sources shows that, due to their advantages, passive systems are often used to solve various problems (both theoretical and practical), in particular, to restore the parameters of the studied surface or to analyze the results of practical experiments [9,10]. At the same time, the accuracy and suitability of the obtained results depend on the fit of the chosen surface description model to the real conditions of the studied surface [11]. Currently, there are difficulties in choosing optimal models of brightness temperatures.…”

Relation Models of Surface Parameters and Backscattering (or Radiation) Fields as a Tool for Solving Remote Sensing Problems

“…One of the most effective modern methods of earth surface exploration is through the use of remote sensing systems. In modern science and technology, remote sensing and measuring is one of the main methods of analysis in many fields: natural science [1][2][3][4][5][6][7][8], agriculture [9][10][11][12][13][14][15], climatology [16][17][18][19][20][21], etc. At the same time, models of these surfaces are necessary to relate the parameters of the studied surfaces (or objects) to the electromagnetic fields that these surfaces radiate or reflect.…”