## 1 Introduction  
Anthropogenic activities, such as Land Use (LU) and Land Cover (LC) changes, are affecting environmental conditions around the world, especially in developing countries [1, 2]. In particular, LU/LC dynamics that involve deforestation and urban expansion boost carbon levels in the atmosphere and worsen climate change [3]. As a result, assessing LU/LC change could potentially offer several advantages concerning sustainable land use and key important drivers in the present and future [2; 4]. According to SDGs (Sustainable Development Goals), Earth Observation (EO) data is a reliable source of information for mapping and monitoring agricultural land. Specifically, it provides valuable and reliable information for economic, social and environmental policies to accommodate LU/LC dynamics caused by population growth, suburbanization and agricultural expansion [5; 6; 7]. Fast progress in remote sensing technology provides a wide spatial distribution and, consequently, enables LU/LC monitoring and mapping over time [8]. Thailand is one of the main agricultural product exporters in the world. The country's agricultural production has significantly contributed to domestic and global market demand, and as a consequence, agricultural activities have become a significant source of economic growth in the past decades [9]. The amount of cultivated area in 2020 was 23.88 billion hectares (about the 46.54% of the nation areas). The northeast region of Thailand is mainly suited to agriculture, and is actually the most highly cultivated area within the country (about 60% characterized by crop plantations). Many small landowners are located in this area and the agricultural business based on rice, cassava, sugarcane and para rubber (the main local crops) represents their main economic activity. Within this context, the Thai government has supported crop cultivation to increase areas and production for market demand, resulting in higher incomes for farmers [10; 11]. Moreover, it is well know that farmers in the northeast region have acquired high adaptability to unfavorable conditions by using different crop management activities, many materials and national policies to increase productivity and production on the one hand, while still leading to intensive planting on the other hand [12; 13]. Thus, this region is an important area for sustainable agricultural land management. Although the northeast region of Thailand has the greatest agricultural areas and production in the country, increasing demands of agricultural production and renewable energy, as well as national policy, have recently influenced LU/LC patterns [11; 13; 14]. Specifically, forest and rice-growing areas have been replaced by other crops. With this premise, several main challenges have arisen including: crop management, food security, low productivity, lack of labor and irrigation management. Related agencies have started to work on these aspects; however, some of them are still present [15; 16]. Remote sensing technology has evolved into a cutting-edge tool for merging multi-source images for high spatiotemporal resolutions for agricultural activity monitoring. EO data have been extensively utilized for mapping and monitoring agricultural crop fields from a variety of perspectives, including crop type, area of coverage, crop calendar, and yield, in different time periods [17; 18; 19]. At the same time, new technologies and EO data cloud platforms have enabled vast data computations by providing great opportunities for mapping land use on a large scale. For instance, the Google Earth Engine (GEE) is increasingly used across borders, mostly for agricultural area mapping [20]. As a result, EO data cloud computing platforms and powerful machine learning methods have undoubtedly improved analysis within the agricultural sector. Moreover, they provide free and open access information for all communities, which is very important in a sector such as this one, which is frequently characterized by climatic and environmentally related difficulties [21; 22; 23].