Felix Jose
Biographic Data
| ID | 7486432 |
|---|---|
| NAME | Felix Jose |
| GIVEN NAMES | Felix |
| FAMILY NAME | Jose |
| SIGNATURE | JOSÉ F |
| AFFILIATIONS | Florida Gulf Coast University |
| ORCID | 0000-0002-9892-0950 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Multi-temporal land use/land cover change in a subtropical river watershed of Bangladesh
Coastal watersheds are experiencing rapid transformation driven by increasing anthropogenic pressures and climate change, with profound consequences for ecosystem dynamics and long-term sustainability. Although land use and land cover (LULC) transitions strongly influence ecological resources, these dynamics remain underexplored in the subtropical coastal regions of Bangladesh. To address this gap, this study examined LULC evolution within the Ch…
Exploring ML ‐Driven Insights on the Impact of Rising Soil Salinity on Sundarbans Mangrove Ecosystems and Ecological Sustainability Through Nature‐Based Solutions
Soil salinity is a growing concern for crop productivity and ecosystem resilience, particularly in coastal regions like the Sundarbans mangrove ecosystem, where salinization has worsened since the 1980s due to climate change and diminished freshwater flow. Nonetheless, previous studies have often relied on limited in situ data or remote sensing, lacking comprehensive integrated approaches. This study aims to fill that gap by utilizing the Harmoni…
Potential effects of projected global sea level rise on Sundarbans mangrove wetland ecosystem
Coastal vulnerability assessment for the Sundarbans mangrove ecosystem using InVest and machine learning-based empirical models
Habitat quality and degradation change analysis for the Sundarbans mangrove forest using invest habitat quality model and machine learning
No prominent works on this page.
Habitat quality and degradation change analysis for the Sundarbans mangrove forest using invest habitat quality model and machine learning
Potential effects of projected global sea level rise on Sundarbans mangrove wetland ecosystem
Coastal vulnerability assessment for the Sundarbans mangrove ecosystem using InVest and machine learning-based empirical models
Multi-temporal land use/land cover change in a subtropical river watershed of Bangladesh
Coastal watersheds are experiencing rapid transformation driven by increasing anthropogenic pressures and climate change, with profound consequences for ecosystem dynamics and long-term sustainability. Although land use and land cover (LULC) transitions strongly influence ecological resources, these dynamics remain underexplored in the subtropical coastal regions of Bangladesh. To address this gap, this study examined LULC evolution within the Ch…
Exploring ML ‐Driven Insights on the Impact of Rising Soil Salinity on Sundarbans Mangrove Ecosystems and Ecological Sustainability Through Nature‐Based Solutions
Soil salinity is a growing concern for crop productivity and ecosystem resilience, particularly in coastal regions like the Sundarbans mangrove ecosystem, where salinization has worsened since the 1980s due to climate change and diminished freshwater flow. Nonetheless, previous studies have often relied on limited in situ data or remote sensing, lacking comprehensive integrated approaches. This study aims to fill that gap by utilizing the Harmoni…
Coastal wetland ecosystem dynamics (5 works) · Ecology (4 works) · Environmental resource management (4 works) · Environmental Science (4 works) · Mangrove (4 works) · Biology (3 works) · Ecosystem (3 works) · Mangrove ecosystem (3 works) · Climate change (2 works) · Fishery (2 works)