Modelling seagrass blue carbon stock in seagrass-mangrove habitats using remote sensing approach

Modelling seagrass blue carbon stocks are essential to complement the satellitebased remote sensing in detecting the underground seagrass carbon stocks. The green carbon initiatives have for long reported the detailed mapping and estimation procedural as well as the audit protocol of the global terrestrial carbon stocks. Research on the blue carbon mapping and its related modelling and estimation, on the other hand, is rarely if ever published as part of its importance is realised but remained scattered. Therefore, this study aimed at investigating blue carbon stocks in seagrass habitats by estimating the total carbon stored in seagrass using the satellite-based technique. The specific objectives are to : 1) assess and adapt some selected models for deriving seagrass total above-ground carbon (STAGC); 2) formulate new approach based-on selected models to combine with in-situ data, to model and estimate blue carbon stocks from seagrass total below-ground carbon (STBGC); 3) develop a novel technique using the selected models with soil organic carbon (SOC) to model and estimate the blue carbon stocks from seagrass total soil organic carbon (STSOC); and 4) integrate all the models (STAGC, STBGC, and STSOC) to produce a framework for the mapping and estimation of seagrass total blue carbon stock (STBCS). Suitable logistic functions were selected and applied on the satellite images to investigate seagrass, and soil carbon stocks along the seagrass meadows of Peninsular Malaysia (PM) coastline All the Landsat ETM+’s shortwave visible bands (blue, green, red) were employed for detecting and mapping seagrass stocks boundary within the coastline of PM. The derivation of STAGC was adopted from the existing bottom reflectance index (BRI) based technique via establishing a strong relationship between BRI with seagrass total aboveground biomass (STAGB). While for STBGC estimation, the STAGB^ (STAGB obtained from BRI image) were correlated with seagrass total below-ground biomass derived from insitu measurement (STBGB^^ro). Both these STAGB^ and STBGB^.^ro were converted into STAGC and STBGC using a conversion factor. Furthermore, the derivation of seagrass total soil organic carbon derived via laboratory test (STSOCi^b) was achieved through correlating BRI values with corresponding in-situ samples of soil organic carbon (SOC) obtained from the laboratory analysis by the Carbon-Hydrogen Nitrogen Sulphur (CHNS) analyser. These models were generated from the three major sample areas (Johor, Penang, and Terengganu), which were used to estimate the entire seagrass carbon stocks in the coastline of PM. The models revealed a robust correlation results for BRI versus STAGB (R2 = 0.962, p< 0.001), STAGB^, versus STBGB/A,wro (R2 = 0.933, p< 0.001,), and BRI and STSOC (R2 = 0 .989, p< 0.001) respectively. The STBCS for the whole seagrass meadows along the coastline of PM was finally realised, demonstrating a good agreement in accuracy assessment (Root Mean Square Error (RMSE) = +- <1MtC/ha\). It is, therefore, concluded that the new approach introduced by this research on STBGC and STSOC estimation was tested and proved significant on the entire STBCS quantification for the PM coastline. The contributions are critical to fast-track the United Nations Framework Convention on Climate Change (UNFCCC) agreement to report the STBCS contents. Hence, this study has managed to propose a new fundamental initiative for estimating STBCS for speedy realisation of 2020 agenda on targets 14.2 and 14.5 of United Nations’ Sustainable Development Goal 14th (life below the water)

Strategic use of GIS in controlling pipeline vandalism of oil and gas industry in Nigeria

Nigeria is among the top ten nations of the world that is endowed and blessed with oil and gas. However, the oil and gas industry has contributed a lot in generating revenue to the country but unfortunately that has not impacted much to the social and structural developments of the people in Nigeria. Level of poverty increased which led to high rates of crime and criminal behaviors like petroleum pipeline vandalism that is common in the oil communities in delta state of Nigeria. This type of crime is mostly committed by the jobless youth who are looking for alternative means to success. The aim of this study is to investigate the potential use of GIS as a strategic tool for oil and gas industry for controlling pipeline vandalization in the oil communities of Jesse, Ekakpamre, and Oviri in delta state of Nigeria with objectives set to support the aim of study. GIS techniques were used and it abilities were demonstrated in controlling petroleum pipeline vandalism using ArcGIS 10.2 software. The analysis used includes hotspot analysis, kernel density analysis and proximity analysis, and hyper link to show the photographs of the vandalism incidents. In addition, pattern of vandalism incidents in the form of pie and bar charts. The results of this study proven that GIS can be used as a strategic tool for oil and gas industry as well as it can be a useful tool for decision makers to plan, control and monitor the pipeline vandalism in Nigeria

Multi-sensor mapping and estimation of seagrass aboveground blue carbon stocks using Landsat OLI and ETM+ along merambong coastal water

Multi-sensor mapping and estimation of aboveground seagrass blue carbon stocks are essential to address the extreme deterioration of seagrass meadows. Resulting from climatic fluctuation and related anthropogenic activities throughout the globe. However, the critical role played by seagrass blue carbon pool in the ocean carbon cycle makes it crucial in fast-tracking sustainable development goal (SDG) 14th. Therefore, this study used multi-spectral sensors of Landsat OLI and ETM+ to derive seagrass total aboveground carbon (STAGC) in seagrass meadows of Merambong coastal water along Peninsula Malaysia (PM). A logistic model was employed to establish a relationship between the bottom reflectance index (BRI) with in-situ of seagrass total aboveground biomass (STAGB). The revelation of this developed model proved an agreeable correlation (R2 0.96, p==0.001 and 0.60% STAGC per hectare (MtC/ha1)). Equally, accuracy assessment revealed an excellent RMSE +- 0.62 result. Hence, this study shall support the realisation of SDG 14th targets 14.2 and 14.5 established by United Nations (UN), to prompt the success of the 2020 agenda

Appraisal of seagrass aboveground biomass changes using satellite data within the tropical coastline of Peninsular Malaysia

Seagrass habitats are crucial marine ecosystem component that affects the biophysical and chemical environment, providing nursery beds to various invertebrates, juvenile fish, and dugongs. This study focuses on mapping and monitoring changes in seagrass total above-ground biomass (STAGB) within the coastline of Peninsula Malaysia. The retrieval of the substrate leaving radiance was realized via was realized via Bottom Reflected Index (BRI) on Landsat ETM + visible bands. A strong relationship was established between BRI and seagrass biomass from in-situ samples (R2 > 0.8, p < 0.001), hence enable mapping and detection of changes in STAGB. Other related coastal changes caused by natural and human activities, namely total fish landing and erosion were also correlated with STAGB, to demonstrate the impacts of these variables on the habitat. The results offer inputs for coastal zone management, apart shall fast-track the achievements of target 14.2 of SDG 14

Recent advancement on estimation of blue carbon biomass using satellite-based approach

History revealed that people had been discharging a large proportion of carbon into the atmosphere through fossil fuel consumption and the marine environment. These have prompted atmospheric carbon fixations that have proved to be larger than at any other point throughout the human survival. Due to the critical role of blue carbon in the ocean carbon cycle, it is essential to pay extra attention to these habitats (mangrove, seagrass meadows, salt marshes, and coral reefs). Hence, this article reviews the recent developments in blue carbon biomass estimation using a geospatial approach and highlighted the blue carbon components achievements and gaps. Biomass and soil carbon estimation, using change detection analysis, were reviewed. Analysis of the carbon conversion factors, used in converting biomass to carbon, was demonstrated. The review shall act as support for the realization of the target 14.2 and 14.5 of the 14th sustainable development goal established by the United Nations, to fast track the achievement of the 2020 agenda

Assessment of coastal sustainable development along the maritime silk road using an integrated natural-economic-social (NES) ecosystem

Understanding spatial change and its driving factors behind coastal development is essential for coastal management and restoration. There is an urgent need for quantitative assessments of sustainable development in the coastal ecosystems that are most affected by anthropogenic activities and climate change. This study built a theme-based evaluation methodology with the Natural-Economic-Social (NES) complex ecosystem and proposed an evaluation system of coastal sustainable development (CSD) to understand the complex interactions between coastal ecosystems and anthropogenic activities. The approach revealed the levels of coastal natural, economic, and social sustainable development in the countries along the Maritime Silk Road (MSR) from 2010 to 2020. The results showed (1) a decreasing trend for coastal sustainable development between 2010 and 2015 and a rapid increasing trend between 2015 and 2020; (2) spatially varied CSD, with higher levels in Europe and Southeast Asia and lower levels in South and West Asia and North Africa; and (3) a strong influence on CSD by a combination of economic and social factors and relatively little influence by natural factors. The study further assessed the natural, economic, and social development scores for 41 countries and compared them with the mean scores (MSR) to classify coastal development patterns into three stages (favorable, transitional, and unfavorable). Finally, in the context of the 2030 Agenda for Sustainable Development, the study highlighted the importance of more refined global indicators for CSD assessments

Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor

The increasing concentration of greenhouse gas (GHG) emissions due to increased fossil fuel consumption for manufacturing activities to support population growth is worrisome. Carbon dioxide (CO2) and methane (CH4) remain the two GHGs that contribute to the impact of global warming, and inventorying their concentrations is important for monitoring their changes, which can be used to infer their emissions over time. Hence, this article highlights sniffer4D, an unmanned aerial vehicle (UAV)-based air pollutant mapping system that visualise and analyse three-dimensional (3D) air pollution data in real time, for mapping GHGs concentrations within industrial areas. Consequently, GHGs concentrations for two industrial and adjacent residential areas in Johor, Peninsular Malaysia were mapped. The GHGs concentrations were validated using a ground-based portable gas detector. The results revealed that CO2 has the highest concentration mean of 625.235 mg/m3, followed by CH4 with a mean of 249.239 mg/m3. The mapped UAV GHG concentration also reported good agreement with the in situ observations with an RMSE of 7 and 6 mg/m3 for CO2 and CH4 concentration, respectively. Ozone and nitrogen dioxide mixture (O3 + NO2) with a mean concentration of 249 μg/m3 and an RMSE of 9 μg/m3 are the remaining significant concentrations reported. This approach shall assist in fast-tracking the United Nations climate change mitigation agenda