Albedo Impacts of Changing Agricultural Practices in the United States through Space-Borne Analysis

Abstract

Using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Bidirectional Reflectance Distribution Function (BRDF) with the U.S. Department of Agriculture’s National Agricultural Statistics Service’s Cropland Data Layer (CDL), the daily albedo of homogenous agricultural fields was derived for 51 common United States field crops by wavelength, sky-type, day of year, crop, and hardiness zone from 2015–2018. This study suggests that crop growth can result in changes in reflectivity up to a factor of 2 at most wavelengths and is unique per crop type in timing and range. Additionally, broadband impacts were studied and found to be less conspicuous than the individual wavelengths, but still significant. The results were used to evaluate a common method of cropland albedo estimation, normalized difference vegetation index (NDVI) as a proxy for albedo, and this method was found to have some significant limitations dependent on wavelength and date. Finally, a database of surface albedo variations as a function of growing period is constructed for common field crops to the United States (as well as additional land-cover types). This database can be used to aid both satellite remote-sensing applications and long-term weather modeling efforts by providing a method for parameter adjustments based on crop driven albedo changes, including changes in cropland composition related to commodity markets and other external factors.

Overlooked cooling effects of albedo in terrestrial ecosystems

“…For example, through in situ measurements, Miller et al (2016) and Lei et al (2023Lei et al ( , 2024 observed comparable surface reflectance of 0.18-0.20 and 0.21-0.23 over a growing season at a sufficiently large corn field, which led to similar RF ∆α cooling of approximately −5.5 W m −2 when converted to a switchgrass landscape. Using Landsat and Sentinel satellite observations, Starr et al (2020), Carrer et al (2018), Shao et al (2014), and Bsaibes et al (2009) also observed similar surface reflectance over the study areas. However, as these orbiting satellites only provide a snapshot of local time at approximately 10:00-10:30 h, RF ∆α and GWI∆α based on satellite measurements are biased compared to those from the continuous in situ measurements (Cai et al 2016, Sieber et al 2019, Sciusco et al 2022.…”

Effects of phenological stages, growth and meteorological factor on the albedo of different crop cultivars

“…There is no network to provide this kind of data for agricultural crops especially in developing countries. Therefore, collecting experimental albedo data is crucial for model development and comparing model results (Starr et al, 2020). Having actual albedo values for plants is also useful in order to validate remote sensing data too (Dexter, 2004).…”

“…In addition, in many applications, the albedo value is taken as a constant for a crop to represent the whole growing period, but it changes during the development period. However, as Dixon (1983) and Starr et al (2020) pointed out, albedo changes over time and many factors affect this change. So albedo is not constant.…”