Abstract. Urbanization has played an important part in the development of the society, yet it is accompanied by environmental concerns including the increase of local temperature compared to its immediate surroundings. The latter is known as Urban Heat Islands (UHI). This research aims to model UHI in Quezon City based on Land Surface Temperature (LST) estimated from Landsat 8 data. Geospatial processing and analyses were performed using Google Earth Engine, ArcGIS, GeoDa, and SAGA GIS. Based on Urban Thermal Field Variance Index (UTFVI) and the normalized mean per barangay (village), areas with strong UHI intensities were mapped and characterized. high intensity UHIs are observed mostly in areas with high Normalized Difference Built-up Index (NDBI) like the residential regions while the weak intensity UHIs are noticed in areas with high Normalized Difference Vegetation Index (NDVI) near the La Mesa Reservoir. In the OLS regression model, around 69% of LST variability is explained by Surface Albedo (SA), Sky View Factor (SVF), Surface Area to Volume Ratio (SVR), Solar Radiation (SR), NDBI and NDVI. OLS yield relatively high residuals (RMSE = 1.67) and the residuals are not normally distributed. Since LST is non-stationary, Geographically Weighted Regression (GWR) regression was conducted, proving normally and randomly distributed residuals (average RMSE = 0.26).

Urbanization can be observed through the occurrence of land-use changes as more land is being transformed and developed for urban use. One of the Philippine cities with high rate of urbanization is Baguio City, known for having a subtropical highland climate. To understand the spatiotemporal relationship between urbanization and temperature, this study aims to analyze the correlation of urban extent with land surface and air temperature in Baguio City using satellite-based built-up extents, land surface temperature (LST) maps, and weather station-recorded air temperature data. Built-up extent layers were derived from three satellite images: Landsat, RapidEye and PlanetScope. Land-use land cover (LULC) maps were generated from Landsat images using biophysical indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI); while RapidEye and PlanetScope built-up extent maps were generated by applying the visible green-based built-up index (VgNIR-BI). Mean LST values from 1988 to 2018 during the dry and wet seasons were calculated from the Landsat-retrieved surface temperature layers. The result of the study shows that the increase in the built-up extent significantly intensified the LST during the dry season which was observed in all satellite data-derived built-up maps: RapidEye+PlanetScope (2012 r = 0.88), Landsat 8 (2012 r = 0.88), Landsat 8 ( -2018 r = 0.63) and Landsat 5,7,8 (1988-2018; r = 0.61). The main LST hotspots were detected inside the Central Business District where it expanded gradually from year 1998 (43ha) to 2011 (83ha), but have increased extensively within the years 2014 to 2019 (305 ha). On average, 98.5% of the hotspots detected from 1995 to 2019 are within the equivalent built-up area.

Abstract. Laguna Lake is significant to its surrounding cities and municipalities as it serves multiple purposes: flood basin, aquaculture, water source for irrigation and domestic use, among others. Monitoring the lake’s water quality is an integral part ensuring that the lake would continue to serve its purposes. Bio-optical modelling is a type of empirical model that relates the inherent optical properties of water to different biological properties like chlorophyll-a. The BOMBER (Bio-Optical Model Based tool for Estimating water quality and bottom properties from Remote sensing images) tool makes use of the different IOPs apparent optical properties (AOPs) of satellite images to be able to produce water quality maps. To localize the parameters used by the BOMBER tool, the use of WASI (The Water Color Simulator) tool was introduced. Inverting in situ spectral measurements of the lake, WASI tool was able to produce parameters localized for the lake. This research used 2018 Landsat 8 Images to produce images and used a water profiler to validate results. Results show the bio-optical model provided a R-squared value of 0.6912 and an RMSE of 2.43 μg/l which shows good correlation between the in-situ and the bio-optical model results.

Abstract. This paper analyzed both the horizontal and vertical extent of air temperature variations as affected by vegetation leaf area density (LAD) and building area per height threshold. The current microclimate (Scenario 1) and two potential future urbanization scenarios in Lower Session Road, Baguio City were simulated with ENVI-met. The future scenarios include the removal of the Balete trees in the median strip (Scenario 2), and removal of some pine trees and addition of new buildings in the study site (Scenario 3). Remotely-sensed data were used in creating the primary model inputs including the initial built-up layer from PlanetScope green-based built-up index (VgNIR-BI), and digital elevation models (DEM) and normalized difference vegetation index (NDVI) maps derived from unmanned aerial system (UAS) for tree canopy mapping. The horizontal variations in air temperature were observed by selecting three subsites with different proximity to the adjusted variables, while vertical analysis was done by comparing the temperature values from the near-ground up to the 20m height range. Very minimal temperature change (0 °C to −0.01 °C) was observed between the current and simulated scenarios when average temperature of the whole site is obtained. However, temperature variations were better observed with per-subsite analysis as the effects of the adjusted variables are seen to be localized and restricted only to the surrounding thermal condition. Air temperature is highest within 12:00 to 13:00 hours for the three scenarios. In the current scenario, the right region of the study site is cooler in the morning, which gradually became warmer pre-noon up to late afternoon. Removal of Balete trees with Scenario 2 have increased the temperature in the near-ground elevation only, both in Subsites 1 (up to 0.1 °C) and 3 (up to 1.6 °C), attributed to the loss of surface shadow and reduction in total LAD. In contrast, the removal of pine trees and addition of buildings impacted the air temperature across all subsites and across all atmospheric height ranges. Application of Scenario 3 to Subsite 3 which is close to the adjusted variables, gave the highest near-ground air temperature rise across the study site with a mean value of 1.4 °C and a maximum value of 1.9 °C. The ENVI-met model of the current scenario generated high accuracy (R2 = 0.59 to 0.99) which implies that the simulation outputs are reliable for this study.

Abstract. Cities are consistently motivated to come up with technology-driven solutions that aim to reduce the negative impacts of rapid urbanization. This paper explores open-source software as a platform in visualizing and developing a digital twin, which aids in mitigating the problem by running simulations and generating potential improvements through generated insights. The four essential components examined to develop the methodology are: (1) Visualization of Digital Model; (2) Identification of User Interface and Data Management Requirements; (3) User Interface Set-up and Configuration; and (4) Analysis and Simulations. Different tools for visualizing the city such as Unity3D, QGIS2threejs, and TerriaMap were explored and compared. Though Unity3D and QGIS2threejs can visualize 3D city models, TerriaMap was favored for its capability to visualize large areas in 3D and to create customizable user interfaces. User interface components were identified as well as handling and processing geospatial datasets. For the analysis and simulations, the Land Surface Temperature hotspot detection was performed and integrated into the system to demonstrate its potential to include other simulations in the future.