## 2 Materials and Methods
### Study Area and Data Sources
#### Overview and Pre-Processing of Remotely Sensed Image Data  
The main data source for this study was Sentinel-2 and MODIS remote sensing image data, which were accessed from the GEE cloud platform. These images were used to find the cultivated area of maize and track its growth in Huinong District, Shizuishan City. The Sentinel-2 mission has two satellites, namely, Sentinel-2A and Sentinel-2B, which are identical in nature. However, it is worth noting that there exists a slight disparity in the spectral widths of Sentinel-2A and Sentinel-2B. The resolution of each band exhibits variation. There is a lot of information about the Sentinel-2 satellite band in Table 1. It has  
Figure 1: Overview map of the study area. the band name, the center wavelength, the bandwidth, the resolution, and the signal-to-noise ratio. By deploying two satellites, the constellation is able to achieve a revisit time of five days for any given point on the Earth's surface. At an altitude of 786 km, every satellite is equipped with a Multispectral Instrument (MSI) that captures photographs of the Earth. These images have a resolution of up to 10 meters per pixel and cover a field of view spanning 290 kilometers. The MSI operates throughout thirteen bands, encompassing both the visible and infrared spectrum [37]. The MOD09 product is a surface reflectance dataset derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). It has a temporal resolution of 1 day and a spatial resolution of 250 m. In general, the Sentinel-2 satellite has a very high level of geometric positioning accuracy and data quality, which enables scientists make accurate observations for the purpose of identifying crops. The MODIS sensor exhibits a notable temporal resolution that enables the continuous monitoring of maize growth. The selection of the imagery period was based on the growth cycle of maize in order to enhance the availability of images, as depicted in Table 2. The use of QA60 band tagging enabled the acquisition of cloud-free Sentinel-2 remote sensing imagery. This approach facilitated the retrieval of images that exhibited a cloud content of less than 30%. To enhance the legibility of remote sensing images, it is imperative to engage in preprocessing of the image data. This preprocessing encompasses various techniques such as image fusion, image mosaicing, image cropping, radiometric calibration, atmospheric correction, image enhancement, de-clouding, and shading processing, as well as projection transformation. As per the provided description on the GEE platform, the product grade of Sentinel-2 remote sensing image data encompasses two levels: 1C and 2A. The 2A level data, in particular, show the bottom reflectance values that have been corrected for \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Sentinel-2A**} & \multicolumn{2}{c}{**Sentinel-2B**} & \\ \cline{2-5}
**Sentinel-2 Bands** & \begin{tabular}{c} **Central** \\ **Wavelength** \\ **(nm)** \\ \end{tabular} & \begin{tabular}{c} **Band Width** \\ **(nm)** \\ \end{tabular} & \begin{tabular}{c} **Central** \\ **Wavelength** \\ **(nm)** \\ \end{tabular} & \
\begin{tabular}{c} **Band Width** \\ **(nm)** \\ \end{tabular} &
\begin{tabular}{c} **Spatial** \\ **Resolution(m)** \\ \end{tabular} \\ \hline Band 1-Coastal & 442.7 & 21 & 442.2 & 21 & 60 \\ aerosol & 492.4 & 66 & 492.1 & 66 & 10 \\ Band 3-Green & 559.8 & 36 & 559 & 36 & 10 \\ Band 4-Red & 664.5 & 31 & 664.9 & 31 & 10 \\ Band 5-Vegetation red edge & 704.1 & 15 & 703.8 & 16 & 20 \\ Band 6-Vegetation red edge & 740.5 & 15 & 739.1 & 15 & 20 \\ Band 7-Vegetation red edge & 782.8 & 20 & 779.7 & 20 & 20 \\ Band 8-NIR & 832.8 & 106 & 832.9 & 106 & 10 \\ Band 8A-Narrow NIR & 864.7 & 21 & 864 & 22 & 20 \\ Band 9-Water Vapor & 945.1 & 20 & 943.2 & 21 & 60 \\ Band 10-SWIR-Cirrus & 1373.5 & 31 & 1376.9 & 30 & 60 \\ Band 11-SWIR & 1613.7 & 91 & 1610.4 & 94 & 20 \\ Band 12-SWIR & 2202.4 & 175 & 2185.7 & 185 & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Spectral bands for the Sentinel-2 sensors.