The development of population growth in Indonesia which continues to increase yearly is in line with the increase in necessities of life such as clothing, food, and boards. One of the impacts of growing living needs is changes in land cover. Changes in land cover are based on many factors, from clearing land for plantations to changing land into settlements. However, land change often occurs in protected areas such as conservation areas. This phenomenon is difficult to detect because it is located in areas that are difficult to access, such as valleys and forests. However, developing geospatial technology, such as remote sensing, effectively monitors land use violations, saving time and costs. One area that is prone to the phenomenon of land cover change is the Kerinci Seblat National Park. The National Park area is close to settlements and plantations, so it has the potential to be affected by land conversion due to the development of the surrounding area. Therefore, this study aims to analyze the results of the detection of indications of the phenomenon of land change occurring in the Kerinci Seblat National Park. Study area In this research, spatial and temporal vegetation analysis will be carried out using the Normalized Difference Vegetation Index (NDVI) and Maximum Likelihood Classification methods for land cover detection. The process uses ArcGIS software and Google Earth Engine machine learning. As a result, there has been a change in land cover in the Kerinci Seblat National Park area, which should have been forested into another land cover, such as open land. This indicates that there has been a violation in the conservation area. This study also validated the location of the breach and found illegal logging in the middle of the Kerinci Seblat National Park area. This result will significantly assist related parties in monitoring violations in the national park conservation area more effectively and efficiently, assisting in efforts to realize the 2030 SDGs.

Keywords: Detection, Land Change, Geospatial Technology, TNKS.