To support offshore wind planning, this study assesses and maps the wind resource around Baja California (Mexico) using MERRA-2 reanalysis. Detailed mean wind speed (MWS), wind power density (WPD) and coefficient-of-variation (CoV) are mapped for the recent 2014–2023 period, whereas long-term wind-speed trends are assessed over a complete 1980–2023 record. The analysis employs a geographic information system (GIS) framework and a 140-node spatial grid. Hourly moist-air density is calculated and linear trends are accompanied by autocorrelation-consistent confidence intervals and significance tests. Moreover, wind-speed variability is characterized using CoV, which is compared with a median absolute deviation (MAD)-based robust CoV and complementary Weibull and persistence diagnostics. Spatial interpolation using inverse distance weighting (IDW) is evaluated by spatial block cross-validation, parameter sensitivity, coastline-aware neighbourhoods, and comparison with alternative interpolation methods. The 2014–2023 maps illustrate pronounced wind-resource patterns along the western and northeastern regions of Baja California, providing a regional-scale resource screening framework rather than a project-specific feasibility assessment. A full-period sensitivity analysis identifies 36 baseline resource candidates; after accounting for temporal, reanalysis-product, air-density, and spatial uncertainties, 19 are classified as robust candidates, 17 as sensitivity-dependent, 28 nodes as uncertain, and 76 as robust non-candidates. The results provide a spatially and temporally resolved screening of the Baja California wind resource and quantifies the sensitivity of candidate locations to key methodological and data uncertainties.
The Urban Heat Island (UHI) effect is a significant consequence of urbanization that shapes Land Surface Temperature (LST) patterns and thermal variability through the complex interactions of urban morphology, surface characteristics, and built environment configuration. This study investigates the multi-scale relationship between urban density indicators and LST in the coastal city of Çanakkale, Türkiye, over a 14-year period (2010–2023). Utilizing Landsat thermal data, the research evaluates six indicators, including Building Coverage Ratio (BCR), Floor Area Ratio (FAR), population density, and open space density, across four spatial scales: 30 m grid, building block, neighborhood, and district. Results identify the Building Block scale as the optimal resolution. While the Neighborhood scale initially exhibited higher explanatory power (Radj2 = 0.447), Leave-One-Out Cross-Validation (LOOCV) revealed this as an artifact of spatial overfitting. Instead, the Building Block scale (Radj2 = 0.314) provides robust structural stability, filtering micro-scale noise without overfitting. A critical finding reveals the synergistic impact of physical and demographic densities. Standardized coefficients show Gross Population Density and BCR act jointly. Unstandardized baseline Multiple Linear Regression (MLR) models indicate every 10% BCR increase is associated with an approximately 0.08°C LST rise (Coef = 0.813). This research’s originality lies in its multi-dimensional approach to scale uncertainty, prioritizing ground-level breathing design over mere density control. The Building Block model’s structural stability, confirmed by consistent in-sample (0.92°C) and out-of-sample LOOCV (0.93°C) errors, provides a verified, robust toolkit for resilient urban planning.
The Abuan Watershed in Isabela, Philippines faces increasing hydrologic and environmental pressures from rainfall variability, land-use change, and hazard-sensitive landscape conditions. This study integrated Soil and Water Assessment Tool (SWAT) modeling with GIS-based vulnerability assessment to evaluate watershed response and spatial vulnerability to flood, drought, and soil erosion. A 5 m × 5 m IFSAR-derived digital elevation model, land-use/land-cover data, soil maps, and hydroclimatic and streamflow records supported the analysis. Streamflow performance was acceptable, with calibration values of R2 = 0.61, nRMSE = 22%, and PBIAS = 3.1%, and validation values of R2 = 0.70, nRMSE = 14%, and PBIAS = 10%. Under baseline conditions, the 63,922-ha watershed received 2169.1 mm of annual precipitation, of which 47% became surface runoff, 23% evapotranspiration, and 30% percolation. Wetter scenarios produced the clearest hydrologic response, increasing runoff by up to 15.99% and soil erosion by up to 13.02% under combined land-use and rainfall-change conditions. Under the projected 2050 rainfall scenario, reforestation caused only minor runoff and percolation changes but reduced simulated soil erosion by up to 1.16 t ha−1 yr−1 relative to the urbanized condition. Flood vulnerability was concentrated in downstream agricultural and settlement areas, whereas drought and soil-erosion vulnerability were greater in cultivated and rainfed uplands. Priority actions therefore include flood-risk reduction and runoff moderation in downstream lowlands, together with vegetation recovery, reforestation, and soil-conservation measures in cultivated hilly and rolling terrain. The integrated SWAT–GIS approach provides a practical, spatially explicit basis for watershed prioritization and intervention planning for future watershed management.
The non-stationarity and vertical coupling of the boundary-layer wind field during typhoon passage are key concerns for wind engineering and disaster prevention. Using hourly ERA5 reanalysis data, this study investigates the evolution of the 10 and 100 m wind fields throughout Typhoon Lekima (2019) by combining BFAST breakpoint detection, Hurst exponent analysis, correlation analysis, and segmented linear fitting, together with near-surface temperature, 850 hPa temperature, and mean sea level pressure fields. BFAST detected a structural breakpoint at all 525 grid cells, with breakpoint timing progressing along the storm track (median 26 h at 10 m and 33 h at 100 m) and magnitudes positive in the northeast and negative in the southwest; at the tower, breakpoints at both heights occurred synchronously at 43 h, with a larger jump at 100 m (+2.20 m s−1) than at 10 m (+1.34 m s−1). The two heights remained strongly correlated (domain-mean r = 0.991) with a nearly constant speed ratio of ~1.45 consistent with the logarithmic profile, while wind-direction correlation degraded only within the inner-core region (minimum r = 0.49). The wind-speed Hurst exponent fell from ~1.04 to 0.84 after center passage, whereas the wind-direction exponent rose from 0.88 to 0.91, indicating that turbulent energy injection disrupted wind-speed persistence while wind direction stabilized under the reorganized flow. The pre-to-post transition in non-stationarity is attributed to a shift in boundary-layer forcing from large-scale baroclinic driving to localized thermal perturbations, with the loss of directional coherence in the pressure gradient field weakening the long-range dependence of the wind field.
Urbanization alters land surface characteristics, intensifies urban heat, and degrades air quality, posing significant environmental and public health challenges. This study investigated the relationship between urban land surface temperature (LST) and air pollution in Kano Metropolis, Nigeria, using Earth observation data, geospatial techniques, and correlation analysis. Land use/land cover (LULC) analysis revealed that built-up areas account for 67.4% of the metropolitan area, contributing to elevated land surface temperatures, particularly within the densely urbanized local government areas of Kano Municipal, Gwale, Ungogo, Dala, and Fagge, as demonstrated by the LST and Urban Heat Island (UHI) analyses. To evaluate the relationship between urban heat and air quality, Pearson correlation analysis showed strong and statistically significant positive relationships between LST and particulate matter, with PM2.5 (r = 0.74, p < 0.001) and PM10 (r = 0.61, p < 0.001) exhibiting the strongest associations. In contrast, CO2, TVOC, and HCHO displayed weak and statistically non-significant relationships with LST. Air Quality Index (AQI) assessment further revealed that 53.6% of the metropolitan area experienced unhealthy air quality, with localized very unhealthy conditions concentrated around commercial cooking areas where biomass fuels are extensively used. These findings indicate that particulate pollution is closely associated with urban surface heating, whereas gaseous pollutants are comparatively less influenced by LST. Overall, the results demonstrate that rapid urbanization, increasing impervious surfaces, and anthropogenic emissions collectively contribute to elevated urban temperatures and deteriorating particulate air quality in Kano Metropolis. These findings provide valuable evidence to support sustainable urban planning through urban greening, the use of high-albedo materials, and cleaner cooking technologies to mitigate urban heat, improve air quality, and reduce public health risks in rapidly urbanizing cities.
