Although successful in protecting planted mangrove plants, the effectiveness of emergent detached offshore structures in increasing vegetation cover has yet to be definitively determined. We selected Tien Giang Province, Vietnam as an appropriate case study to address this question. We analyzed multiyear (2000 and 2022) shoreline changes and calculated the enhanced vegetation index (EVI) together with ground truthing in pursuit of the objectives of the study. Our findings suggest that emergent detached offshore structures have yet to lead to an increase in vegetation cover or promote mangrove growth. The vegetation growth steadily increased, as did the high level of natural mangrove growth with fully grown mangrove trees, even before the structures were constructed. By 2015, all the categories increased slightly except for low vegetation cover (LVC) and medium vegetation cover (MVC). LVC decreased from 390 ha in 2010 to 291 ha in 2015, while MVC decreased from 305 ha in 2010 to 275 ha in 2015. By 2020, all the categories decreased slightly except for non-vegetation cover-Barren lands (NVC2) and MVC. NVC2 decreased slightly from 404 ha in 2015 to 368 ha in 2015. The MVC decreased slightly from 275 ha in 2015 to 212 ha in 2020. Non-vegetation cover-Intertidal mudflats (NVC1)-LVC, and high vegetation cover (HVC) increased slightly from 2015 (326 ha, 291 ha, and 249 ha, respectively) to 2020 (368 ha, 292 ha, and 298 ha, respectively). By 2022, NVC2, MVC, and HVC remained unchanged, while NVC1 and LVC increased slightly from 368 ha and 292 ha in 2015, respectively, to 380 ha and 302 ha, respectively. The increase in vegetation cover and the natural regeneration of mangrove species were partly due to the adaptation of mangrove species to the site (river mouth areas), particularly the protection provided by Ngang Island offshore, and the construction of these structures. In addition, these structures were constructed in a rather stable area (slightly eroded and estuarine area) and therefore have yet to provide any noticeable benefits for mangrove regeneration three to five years after their construction. In the future, the morpho dynamic and hydrodynamic elements of the site should be adequately considered during the design and construction of these structures to increase vegetation cover and promote natural mangrove regeneration.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11856600 | PMC |
http://dx.doi.org/10.3390/life15020136 | DOI Listing |
Vegetation restoration plays a critical role in mitigating urban heat island (UHI) effects and improving local climate conditions, particularly in mining-affected areas. This study analyzes vegetation cover changes and their impact on UHI from 2000 to 2020 in three locations: Dexing City and Qibaoshan Township in China, and Dartford Ebbsfleet Garden City in the UK, using satellite imagery and remote sensing data. In Dexing City, the transition from open-pit to underground mining, combined with reclamation efforts, maintained a stable fractional vegetation cover (FVC) of 0.
View Article and Find Full Text PDFInt J Biometeorol
March 2025
Departamento de Construção Civil, Universidade Tecnológica Federal do Paraná - UTFPR /Campus Curitiba - Sede Ecoville, Rua Deputado Heitor Alencar Furtado, 4900, Curitiba, 81280-340, Brazil.
Studies point to an increase in the frequency of heatwaves, revealing that they are longer lasting and more intense, with noticeable impacts from climate change observed in the south of Brazil. This study evaluates the impact of a heatwave event in Curitiba, Brazil, and investigates whether the excessive heat caused during this period influenced the thermal perception reported by participants in a fieldwork carried out during dynamic microclimatic surveys on a university campus. To this end, volunteers took part in thermal walks accompanied by a researcher carrying a portable equipment for monitoring environmental variables, covering points of interest previously defined in a walking circuit with different morphological and land cover configurations.
View Article and Find Full Text PDFPeerJ
March 2025
Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, Urumqi, Xinjiang Uygur Autonomous Region, China.
is an essential species within the Central Asian desert ecosystem, with its aboveground biomass (AGB) serving as a crucial marker of ecosystem health and desertification levels. Precise and effective methods for predicting AGB are vital for understanding the spatial distributions and ecological roles of desert regions. However, the low vegetation cover in these areas poses significant challenges for satellite-based research.
View Article and Find Full Text PDFNat Commun
March 2025
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resource, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China.
Thermokarst lakes, serving as significant sources of methane (CH), play a crucial role in affecting the feedback of permafrost carbon cycle to global warming. However, accurately assessing CH emissions from these lakes remains challenging due to limited observations during lake ice melting periods. In this study, by integrating field surveys with machine learning modeling, we offer a comprehensive assessment of present and future CH emissions from thermokarst lakes on the Tibetan Plateau.
View Article and Find Full Text PDFJ Environ Manage
March 2025
Department of Agronomy, Kansas State University, Manhattan, KS, USA.
Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important management tool for damage control before the occurrence of fires, which often spread very rapidly. In this context, the current study was undertaken with the aim to map forest areas susceptible to fire in the state of Goa (India) using remote sensing (RS) and geographic information system () derived variables through an analytical hierarchy process (AHP) and machine learning techniques namely random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!