Cloud-based Multi-temporal Sar-optical Fusion Using Random Forest for Geospatial Intelligence Monitoring of Kipp Ikn Nusantara
Year: 2026
Type: article
Abstract: The development of Indonesia's new capital (IKN) Nusantara drives dramatic land-cover transformation across a strategic 17,599-hectare area under the persistent cloud cover of Kalimantan, where optical remote sensing alone is insufficient for continuous monitoring.This study proposes a cloud-based multi-temporal SAR-optical fusion approach using Random Forest classification for geospatial-intelligence (GEOINT) monitoring of the Core Government Area (KIPP) of IKN.Using Google Earth Engine, we processed 70 Sentinel-1 GRD and 52 Sentinel-2 images for 2022 and 61 and 81 images for 2024, building a 12-band fusion stack (SAR backscatter VV, VH, VV/VH; optical B2, B3, B4, B8, B11, B12; and NDVI, NDBI, NDWI).Six experiments compared SAR-only, optical-only, and fusion configurations.The Random Forest fusion achieved 88.89% overall accuracy and 0.8609 kappa for 2022 and 85.12% and 0.8127 for 2024 (assessed against ESA WorldCover 2021 class definitions; see Section 2.7), outperforming SAR-only (63.20%) and optical-only (86.44%).Change detection revealed 899.64 ha of direct vegetation-to-built-up conversion, a 60% expansion of built-up area driven by IKN construction.This is the first cloud-based multi-temporal fusion framework applied to KIPP IKN monitoring, with implications for spatial planning, security surveillance, and environmental compliance.
Source: Geographia Technica
Authors: Fajar Sidik SUGANDA, Asep Adang SUPRIYADI
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7214434955