# A Very High-Resolution Urban Green Space from the Fusion of Microsatellite, SAR, and MSI Images
## 2 Methodology
### Satellite Datasets: PlanetScope, Sentinel-1, and Sentinel-2  
The PlanetScope satellite constellation comprises approximately 130 microsatellites, also referred to as CubeSats. These CubeSats have dimensions of 10 cm \(\times\) 10 cm \(\times\) 30 cm,  
Figure 1: Jakarta as the study area overlaid with the Planet dataset. The base map is Google Road. QGIS version 3.22.8-Bialowieża was used to create the map. with a daily temporal resolution, three-meter spatial resolution, 12-bit radiometric resolution, and eight spectral bands [22]. The initial PlanetScope satellites were launched in 2018, featuring only four spectral resolutions. The second generation is known as PS2.SuperDove (PS2.SD) or Dove-R, which became available from 2019 to 2022. The third generation is also referred to as SuperDove or PSB.SD, now boasts eight spectral bands, namely coastal blue (b1), blue (b2), green I (b3), green (b4), red (b5), yellow (b6), red edge (b7), and near-infrared (b8). In this study, the PlanetScope data were obtained through an education and research standards license. These data were captured on 14 August 2023, encompassing three scenes that encompassed the study area. These scenes provide surface reflectance products at the analytic level, comprising eight bands. The data were accessed from [[https://www.planet.com/explorer/](https://www.planet.com/explorer/)]([https://www.planet.com/explorer/](https://www.planet.com/explorer/)) (accessed on 12 December 2023) and imported into QGIS software version 3.22.8-Bialowieza, and they were subsequently merged. The resulting merged dataset was then uploaded to the Google Earth Engine (GEE) platform as an asset for additional processing. In the GEE platform, the PlanetScope data were transformed into the Red-Edge Triangulated Vegetation Index (RTVI) and the Red-Edge Triangulated Wetness Index (RTWI) spectral indices using the first and second equations, respectively, as follows:  
\[RTVI=(100*(NIR-RedEdge)-10*(NIR-Green)) \tag{1}\]  
\[RTWI=(100*(RedEdge-NIR)-10*(Green-Red)) \tag{2}\]  
The RTVI and RTWI were chosen to monitor the red-edge band, which is known to be responsive to subtle variations in vegetation health. This choice enables a unique method to address situations where the Normalized Difference Vegetation Index (NDVI) becomes saturated in regions with extensive, dense vegetation or crops, limiting its effectiveness in capturing changes [23]. Sentinel-1 is a part of the European Space Agency (ESA) and consists of two constellations: Sentinel-1A and Sentinel-1B. This system is equipped with an active remote sensing sensor that gathers data using dual-polarization C-band Synthetic Aperture Radar (SAR). Its spatial resolution is 10, 25, and 40 m, and it captures data every 6 to 12 days [24]. In this study, the Sentinel-1 data in vertical-vertical (VV) and vertical-horizontal (VH) polarizations were used, which were acquired in interferometric wide (IW) swath mode, with ascending properties, during the post-rainy season (April to September 2023). This ensured comprehensive coverage of the study area. The queried Sentinel-1 data were processed to calculate the inter-quartile range (IQR) as a measure of backscatter variability. All of the Sentinel-1 data used in this study were ground-range-detected (GRD) and readily available in the Google Earth Engine (GEE) data catalog. Sentinel-2, like Sentinel-1, is part of the ESA program and consists of two satellite constellations: Sentinel-2A and Sentinel-2B. However, unlike Sentinel-1, Sentinel-2 employs a passive remote sensing sensor equipped with a multispectral imaging (MSI) sensor capable of capturing data in 13 spectral bands. It offers variable spatial resolutions of 10, 20, and 60 m and a temporal resolution of 10 days at the equator with one satellite, and 5 days with two satellites under cloud-free conditions [25]. For this study, Sentinel-2 MSI Level-2A datasets available in the Google Earth Engine (GEE) data catalog were utilized.