Geospatial Assessment of Mangrove Dynamics in Relation to Climate Variability

Understanding changes in mangrove ecosystems driven by human activities, climate change, and environmental variations is essential for effective ecological management. The study analyze the spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) and their responses to parameters such as sea level (SL), Potential Evapotranspiration (PET), rainfall (RF), Standardized Precipitation Index (SPI-1 month), soil moisture (SM), minimum temperature (TN), and maximum temperature (TX) within the study area. Trends, relative influences, spatial autocorrelation, and relationships between NDVI and climatic-environmental variables, as well as partial correlations, were analyzed using the Mann-Kendall monotonic trend test (MKMT), Relative Weight Analysis (RWA), partial correlation coefficients (PCC), and Multiple Linear Regression (MLR) methods. The spatiotemporal patterns of NDVI, EVI, and SAVI display similar dynamics, showing a reduction in bare soil and an increase in sparse and dense vegetation from 1987 to 2022. Nevertheless, zones of degradation were observed, particularly in southern in 2022 compared to 1987, as indicated by NDVI, EVI, and SAVI. These zones coincide with areas of increased salinity concentration according to the VSSI index over the same period. A notable deterioration in NDVI (> 0.2) was recorded from 2000 to 2012. The interannual trend of NDVI is slightly declining. Additionally, analyses with Mann-Kendall and Theil-Sen slope reveal that TN, TX, PET, and SPI-1 show increasing trends, though not statistically significant, while SM and LST show decreasing trends. For environmental variables, SL indicates an upward trend. Further, partial correlation analysis identifies SL, TN, SPI-1, TX, and PET as the primary climatic factors controlling vegetation dynamics during the JJAS season, with PCC values of -0.89, 0.87, 0.77, 0.76, -0.75, and 0.86 with NDVI, respectively. These findings underscore the significant influence of select environmental factors on the spatiotemporal dynamics of mangrove vegetation, providing insights critical for conservation and management efforts.

🎯 The detailed methodology and results can be accessed through this link:

👉click here now! :  https://www.impactio.com/publication

The Abdi-Basid Courses Institute (tABCi)

Performance evaluation of very high multi-satellite daily precipitation products against Observation in situ weather from 1980 to 2021.

 The study covers a range of datasets, including satellite-based, hybrid (satellite + gauge), and reanalysis products:

• CHIRPS v2 (0.05°, 1981–present): Hybrid product combining infrared satellite data with rain gauge observations.

• GSMaP PRT V6 (0.1°, 2000–present): Satellite-based product using passive microwave and infrared sensors.

• IMERG LR & FR (0.1°, 2000–present): Satellite-based datasets from NASA’s GPM mission; Late Run provides near–real-time data, while Final Run is bias-corrected with gauge data.

• TRMM 3B42 (0.25°, 1998–2019): Satellite-derived dataset from the Tropical Rainfall Measuring Mission.

• MSWEP v2.8 (0.1°, 1979–present): Multi-source hybrid product merging gauge, satellite, and reanalysis data.

• ERA5 (0.25°, 1979–present): Global reanalysis from ECMWF.

• ERA5-Land (0.1°, 1981–present): High-resolution reanalysis optimized for land-surface applications.

• ERA5-Ag (~0.1°, 1979–present): Reanalysis dataset derived from ERA5, tailored for agricultural applications.

Abdi-Basid ADAN, 2023

The Abdi-Basid Courses Institute (tABCi)

Mapping Terrain Elevation through DEMs: Multiple Layouts and Visualizations

 

Abdi-Basid ADAN, 2022

The Abdi-Basid Courses Institute (tABCi)

Hydroclimatic Variability and Its Interactions with Vegetation and Climate Teleconnections: Multi-Scale Analyses of SPI/SPEI, Vegetation Indices (NDVI, EVI, VCI, SEDI), ENSO, and IOD (1961–2021)

This study investigates hydroclimatic variability over the period 1961–2021 using the Standardized Precipitation Index (SPI) across multiple temporal scales. Long-term drought dynamics are assessed through the spatial slope of SPI12 and its relationship with total precipitation, while short- to medium-term variability is explored through SPI3 heatmaps, contrasting monthly and annual patterns as well as seasonal fluctuations (JF, MAM, JJAS, and OND).

A comparative analysis between a station with missing precipitation records (and consequently incomplete SPI3 series) and the corresponding regional SPI3 signal was conducted to evaluate the robustness and representativeness of local trends.

Furthermore, correlations between SPI /SPEI (3, 6, 9, and 12 months) and vegetation-related indices — NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), VCI (Vegetation Condition Index), and SEDI (Standardized Evapotranspiration Deficit Index) — highlight the interactions between climatic drought and ecosystem responses. Finally, the analysis incorporates the influence of major climate teleconnections, namely ENSO (El Niño–Southern Oscillation) and the IOD (Indian Ocean Dipole, particularly during OND), to assess their role in modulating regional SPI variability.

The findings provide an integrated understanding of the links between precipitation variability, vegetation dynamics, and large-scale ocean-atmosphere drivers, with implications for drought monitoring, prediction, and sustainable water resource management.

The Abdi-Basid Courses Institute (tABCi)

@ 2022 Abdi-Basid ADAN

Simulation of Storage Tank Emission Dispersion in a Petroleum Depot Using AEROMET

This study investigates the atmospheric dispersion of volatile emissions from storage tanks in a petroleum depot using the AEROMET software. Emissions from tank facilities, including hydrocarbons and other volatile compounds, were estimated using standard EPA methodologies, with meteorological conditions processed through AERMET and topographic effects incorporated via AERMAP. The dispersion patterns were simulated to evaluate the spatial distribution of pollutant concentrations and identify potential areas of environmental and health risk within the depot zone.

(Jan, Feb, Mar, Apr, May, Jun, Jul Aug, Sep, Oct, Nov and Dec)

The Abdi-Basid Courses Institute (tABCi)

@ 2022 Abdi-Basid ADAN