*3.1. Data*

A set of satellite images and ground data were used to evaluate different models and data in RCF modeling. Satellite imagery included the Landsat 8 Collection 2 Surface Reflectance image for 13 October 2020 and the Sentinel 1 Ground Range Detected (GRD)

image for 7 October 2020. The spatial resolution of the Landsat 8 and Sentinel 1 image bands is 30 and 10 m, respectively. The Landsat 8 bands, including Blue, Green, Red, NIR, SWIR 1 and SWIR 2, and Sentinel 1 bands, including VV and VH, were used in this study. Some criteria were considered when selecting the date of the images: (1) a lack of cloud cover in the area during the Landsat 8 overpass time, (2) the absence of precipitation in the study area a few days before the satellite overpass time and (3) proximity to the date of harvest of agricultural products. Landsat 8 image downloaded from https://earthexplorer.usgs.gov/ (accessed on 13 February 2021) and sentinel 1 downloaded from https://scihub.copernicus.eu/ (accessed on 16 February 2021). The land crop map prepared by Agriculture and Agri-Food Canada (AAFC) in 2020 with the spatial resolution of 30 m was used to mask various agricultural products. This data is produced annually and can be downloaded from https://open.canada.ca/data/en/dataset?q (accessed on 2 March 2021) website.

Ground data collection includes determining the RCF in autumn from a number of corn, soybean and wheat fields that were performed after harvest on the 9 October 2020, 10 October 2020 and 9 November 2020 dates. For this purpose, RCF values were determined at 57 land points for wheat, 149 points for corn and 128 points for soybeans. The selection of land areas was carried out in such a way that there was a suitable distribution in the fields of these crops in the whole study area (Figure 1b). The minimum distance between sampling points was 500 m. Additionally, based on the initial and complete field visit of the study area, the suitable distribution of absolute values between the highest and lowest actual values of RCF in the study area was also considered when selecting the sampling points. Little to no rain (less than 0.25 cm) had fallen the week before the sampling, and the soil moisture levels were constantly dry. When field sampling took place, the weather was identical to the weather when taking images the day before. Ordinary camera images were used for sampling. A Phantom 3 SE drone was used to produce images from each selected sampling point. The flight height of the drone for imaging was 20 m, and a digital orthophoto with a spatial resolution of 20 cm was prepared for each sampling point. Then, for each image, the position of product residues was manually digitized. After processing the images taken by the camera, the remaining coverage fraction was calculated for an area of 900 m<sup>2</sup> around each sampling point. Agisoft Metashape 1.8.3, developed by Agisoft LLC (St. Petersburg, Russia) and ArcMap 10.6.1, developed by Esri (Environmental Systems Research Institute), (Redlands, California, United States) software were used to determine the RCF based on the images prepared with the drone (digital orthophoto preparation and digitization).
