Characterizing Land Cover Change in Degraded Urban Watersheds through Temporal Dynamics Pattern Analysis
Yudi Setiawan (a*), Kustiyo (b), Liyantono (a), Rizqi Fahma Sidik (a), Rizki Moch Rijaldi (a))

a) Center for Environmental Research, International Research Institute for Environment and Climate Change, IPB University, Darmaga Campus, Bogor 16680, Indonesia
*setiawan.yudi[at]apps.ipb.ac.id
b) Research Center for Geoinformatics, Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Bandung 40135, Indonesia

Abstract

Urban watersheds in Indonesia face increasing environmental degradation due to unregulated land use change and urban expansion. This study focuses on three critical catchments-Ciliwung, Kali Bekasi, and Citarum-which are frequently exposed to flooding, ecological stress, and land instability. We analyzed land cover change from 1990 to 2024 using multi-temporal Landsat imagery and a temporal dynamics pattern approach previously developed to classify land cover transitions based on change trajectories. This method captures distinct patterns such as gradual vegetation decline, abrupt urban expansion, and cyclic disturbances. Building on earlier results, we applied trajectory grouping and temporal segmentation to improve the detection of persistent and reversible changes. The findings reveal consistent trends of vegetation loss and increasing built-up areas, particularly in riparian and floodplain zones. In Ciliwung and Kali Bekasi, urban expansion often follows short phases of regrowth, while in Citarum, conversion is largely irreversible. These dynamics indicate unstable land management and limited effectiveness of spatial planning. This study demonstrates how temporal-based classification improves understanding of long-term land cover dynamics in complex urban environments. The approach supports targeted restoration and planning strategies for more sustainable watershed management.

Keywords: Temporal dynamics- Landscape degradation- Spatio-temporal analysis

Topic: Topic B: Applications of Remote Sensing