## 1 Introduction  
Despite being the world's largest meat exporter, Brazil primarily practices extensive livestock farming. Pasturelands, occupying approximately 21% of the national territory, are predominantly found in the central savanna environment known as the Cerrado biome [1]. Cultivated and natural pastures cover around 180 million hectares of Brazilian land, with 35% of this area situated in the Cerrado [2]. Satellite imagery from 2018 suggests that about 59% of Brazilian pasturelands experienced some level of degradation [3]. The term \"pasture degradation\" refers to the gradual decline in vigor, productivity, and natural regeneration capacity of a specific pasture [4]. As this process unfolds, the pasture becomes incapable of sustaining the necessary levels of production and quality required by the animals. Additionally, it loses resilience and resistance to the adverse impacts of pests, diseases, and invasive plants. Degradation is commonly linked to inadequate animal stocking practices, insufficient pest control, presence of invasive plants, and lack of fertilization [5]. Given the substantial economic, social, and environmental impacts associated with pasture degradation, there is a significant interest in accurately mapping degraded areas in Brazil. This interest is fueled by the recognition that well-managed and productive pasturelands have the potential to enhance carbon sequestration and reduce carbon emissions [6; 7; 8]. Another compelling reason for mapping these areas is to devise strategies or policies aimed at the potential conversion of degraded pastures into refereed areas or agricultural land [8; 9]. For example, through effective management of degraded pastures, these areas can be transformed into soybean fields, contributing to increased crop production without causing deforestation or clearing of native vegetation in both the Cerrado and Amazon biomes. Traditionally, the assessment of pasture degradation involves extensive fieldwork sampling and labor-intensive laboratory analyses, rendering this method both costly and time-consuming. This is particularly challenging for systematically monitoring vast areas in Brazil, one of the world's largest countries. Realistically, remote sensing emerges as the most suitable approach for systematically covering pasturelands in a short timeframe and providing rapid assessments of their quality with adequate support of field information. Nevertheless, employing remote sensing to discriminate classes of pasture degradation poses challenges in Brazil, particularly in the Cerrado, due to subtle differences in reflectance between degraded and non-degraded sites. Therefore, there is an ongoing need to explore and test various remote sensing approaches and datasets for the systematic mapping of pasture degradation in the Cerrado biome [3]. Most remote sensing investigations on pasture degradation in Brazil have predominantly used data obtained with low-to-moderate (250 to 1000 m) or medium (30 m) spatial resolution, derived from instruments such as the Moderate Resolution Imaging Spectro-radiometer (MODIS)/Terra or satellites such as the Landsat [10; 11; 12; 13; 14]. Various analytical approaches have been employed worldwide to map pastures using these data with advantages and disadvantages. Such approaches involve, for instance, time series analysis of MODIS vegetation indices [11; 15; 16; 17]. However, certain degraded pastures, dominated by invasive plant species or weeds, may, in fact, exhibit an increase in vegetation indices over time when observed by satellites, contrary to the anticipated long-term decline expected for degraded areas. Other methodologies for mapping pasture degradation encompass the use of classification techniques applied to Landsat [18; 19; 20; 21], Synthetic Aperture Radar (SAR) [22], or hyperspectral data [23; 24; 25].