Understanding Land Use Conflicts With Landsat Time Series

Abstract. Time series analysis of remote sensing data is an efficient method for observing, monitoring, and characterizing land use/cover change (LUCC). However, it is challenging to integrate local knowledge into these estimations to improve the explanation of land use conflicts (LUCs) in terms of LUCC. LUCs are the irrational utilization of land systems (LS) caused by individual stakeholders pursuing their own interests and competing for land resources. The purpose of this study is to understand the relationship between LUCs and LUCC. San Miguel el Grande (SMG), Oaxaca, Mexico, is a case study from 1993 to 2023. The method was two principal phases: 1) Landsat time series analysis and point analysis with the CCDC algorithm (Continuous Change Detection and Classification); and 2) process tracing to explain the causal relationship. The results indicate a classification accuracy of around 88% per year. The breakpoints in the harmonic regression can detect LUCC related to the LUCs reported by the news and local people. These findings provide information about the impact of social drivers on forest lands. They help formulate public policies that consider the local context in rural municipalities with valuable timber resources.