## 2 Methodology
### SuperDove Data Acquisition and Fieldwork Activities  
Operating in a Sun-synchronous orbit at an altitude of 500 km, the PlanetScope SuperDove satellite constellation captures images across eight spectral bands spanning the 400-900 nm range (\(\copy\) 2024 Planet Labs PBC, San Francisco, CA, USA). The bandwidth varies from 16 nm (red-edge band 7) to 50 nm (blue band 2) (Table 1). The SuperDove bands 1 and 5 are also referred to as the \"Coastal blue\" and \"Yellow\" bands, respectively. The SuperDove has a spatial resolution of 3.7 m, a radiometric resolution of 12 bits, and a temporal resolution of one day (Table 1). The images are obtained in frame sizes of 32 km \(\times\) 20 km [39]. Figure 2: Location of the five sites (\(15\times 15\) km each) selected in the southeastern region of the Brazilian state of Goias in a climatically homogeneous region. The insets show photographs representative of non-degraded pasture (NDP) and of pastures with low-intensity degradation (LID), moderate-intensity degradation (MID), severe agronomic degradation (SAD), and severe biological degradation (SBD). The sites are numbered according to the municipality where they are located: 1. Bela Vista de Goias; 2. Caldas Novas; 3. Piracanjuba; 4. Pontalina; and 5. Trindade. Long-term monthly precipitation (average values between 2001 and 2021) and the dry season period are also indicated for reference. This study employed the surface reflectance product (level 3B) from the PlanetScope SuperDove satellite constellation for data analysis. The product includes images that undergo geometric, radiometric, and atmospheric corrections. The algorithm used for atmospheric correction is based on the 6S radiative transfer code. The algorithm uses lookup tables (LUTs) for standard atmospheric models and ancillary near real-time information from MODIS (e.g., water vapor, ozone, and aerosol data) to convert at-sensor radiance into surface reflectance SuperDove data (& 2024 Planet Labs PBC.). Surface reflectance images were downloaded from the Planet platform ([[https://www.planet.com](https://www.planet.com)]([https://www.planet.com](https://www.planet.com)), accessed on 15 May 2023). An available cloud mask, derived from band threshold values, provided information on areas potentially affected by clouds and their related shadows. However, to reduce uncertainties in the data analysis, we downloaded only images exhibiting a maximum of 20% cloud cover in the scene for subsequent scrutiny of their visual quality. Only cloud-free data were considered for the subsequent analyses. Therefore, our analysis concentrated on 259 cloud-free images acquired across all sites from January to December 2022. This period was characterized by a notably increased availability of SuperDove images compared to the years 2020 and 2021. Figure 3 reveals significant gaps in cloud-free image availability during the initial 50 days of the year and from Day of the Year (DOY) 326 onwards. During these periods, there were extensive intervals of total image absence across all sites, attributed to the prevalence of cloud cover. Field surveys were conducted in the designated sites during the years 2022 and 2023 to assess the presence of both degraded and non-degraded pastures. Employing an existing pasture mask and a meticulous statistical sampling design, which considered the spatial distribution of pastures within each site and their proximity to roads, all five sites were physically visited. A comprehensive total of 109 plots, representing distinct levels of degradation, were systematically sampled during the field surveys. Following the methodology proposed by [PERSON] [40], the field-sampled plots were categorized into five classes: non-degraded pasture (NOD) and pastures exhibiting low-intensity degradation (LID), moderate-intensity degradation (MID), severe agronomic degradation (SAD), and severe biological degradation (SBD). This classification method was designed with the purpose of distinguishing between the type and severity of pasture degradation.