Total aboveground biomass (TAGB) estimation using IFSAR and speckle noises effect on TAGB in tropical

Total Aboveground Biomass (TAGB) estimation is critically important to enhance understanding of dynamics of carbon fluxes between atmosphere and terrestrial ecosystem. For humid tropical forest, it is a challenging task for researchers due to complex canopy structure and predominant cloud cover. Optical sensors are only able to sense canopy crown. In contrast, radar technology is able to sense sub-canopy structure of the forest with penetration ability through the cloud for precise biomass estimation with validation from field data including diameter at breast height (DBH) of trees. This study is concerned about estimation of TAGB through the utilization of Interferometry Synthetic Aperture Radar (IFSAR). Based on this study, it is found that the stand parameters such as DBH and backscattered on IFSAR image has high correlation, R2=0.6411. The most suitable model for TAGB estimation on IFSAR is Chave Model with R2=0.9139. This study analyzes the impact brought by speckle noises on IFSAR image. It is found that filtering process has improves TAGB estimation about +30% using several filtering schemes especially Gamma filter for 11×11 window size. Using field data obtained from a primary tropical forest at Gerik, Perak, TAGBestimation can be validated and the assessment has been carried out

Light penetration ability assessment of satellite band for seagrass detection using landsat 8 OLI satellite data

Seagrass distribution is controlled by light availability, especially at the deepest edge of the meadow. Light attenuation due to both natural and anthropogenically-driven processes leads to reduced photosynthesis. Reliability of satellite-based seagrass mapping under different water clarity that has different attenuation coefficient value is still not fully known. Understanding the minimum light requirements for growth is crucial when light conditions are insufficient to maintain a positive carbon balance, leading to a decline in seagrass growth and distribution. By comparing the seagrass-detected pixels at two different coastal locations with the corresponding depth from the nautical chart, the assessment of seagrass map derived from Landsat 8 OLI satellite data were performed. We presented the assessment of light penetration capability of Landsat 8 OLI bands in typical tropical coastal water of Malaysia, with special attention on the different water clarity that has different amount of light deprivation on the seagrass meadow

Above ground blue carbon sequestration capacity of Sungai Pulai estuary seagrass meadows - a satellite based method

Monitoring blue carbon (C) sequestration potential within coastal ecosystem is essential for enhancing climate change mitigation initiatives. Although remote sensing is known as a useful method for mapping benthic habitat and monitoring changes at large spatial scale compared to field survey methods, it has not been attempted for quantifying seagrass C stock. A satellite-based mapping approach, applied on Landsat imagery (acquired in 2004, 2009 and 2013) and field biomass data obtained from previous studies were used for repeat mapping of above ground seagrass C for the turbid water of the Sungai Pulai estuary, Johor Straits, Malaysia. The mapping approach has demonstrated (1) the ability to determine total above ground seagrass C sequestration capacity and identify the areas of highest C stock cover class from the spatially extensive biomass map, and (2) the spatio-temporal dynamics of seagrass C stocks that can be used to assess and monitor C fluxes and (3) informing costal managers to decide which data to be used and method to apply for monitoring climate change related activities when project demands a spatially explicit maps. According to the estimates, the highest mean C stock was in 2004 (90.68 kg C/pixel) and the lowest in 2013 (18.77 kg C/pixel) - a declining trend of seagrass cover, biomass and C stocks in the Sungai Pulai estuary. Further studies on the Sungai Pulai estuary should be conducted to identify C pools and to estimate total C stocks and fluxes in seagrass ecosystem

Using fisher knowledge, mapping population, habitat suitability and risk for the conservation of dugongs in Johor Straits of Malaysia

In the coastal waters of Johor Straits, Peninsular Malaysia, the dugongs occur and their habitat suitability model has yet not been attempted, while it could be critical information for developing their conservation strategies. This study derived spatially explicit dugong population information on the abundance and distribution of dugongs based on fisher surveys. The survey revealed the highest dugong abundance around eastern areas, followed by southern areas of Johor Straits. Degradation of seagrass habitat, which dugong uses as feeding ground, could be the main reason for reducing dugong sighting around western areas. A habitat suitability map was produced based on dugong presence and interacting environmental factors such as seagrass biomass, distance from shoreline, and water depth. Using ArcGIS mapping capability, the data layers on those environmental factors were fied into MaxEnt. The MaxEnt model output showed seagrass biomass as the highest contributing factor to the likelihood of dugong presence. The model also estimated 20 kg/m2 of seagrass biomass, 3 km distance from shoreline and a water depth of 25 m as the optimum habitat condition for dugong population. The combination of fisher interview, habitat suitability, and risk modeling has the ability to provide adequate information required for monitoring and developing policy strategies for sustainable management and conservation of marine mammals

Mapping snow-algae in Antarctic Peninsula with multi-temporal satellite remote sensing data

This article reports on the use of selected spectral image transform technique for detecting and mapping of snow algae growth using multi-temporal Landsat Thematic Mapper (TM), archived from early 80's to the recent Landsat-8 Operational Land Imager (OLI) acquired in March 2015. In-situ spectral radiometry samples during UTM-Antarctica summer 2015 expedition were used in air-to-ground correlation of the corresponding satellite data sets, later yield to retrieve snow algae occurrences in 2009-2015 summer. Multi-temporal analysis of the snow-vegetation growth extents extracted was then compared to against the climate-change effects of the corresponding area in Antarctic Peninsula. Hence, the indicator for snow-vegetation growth as effects of the climate-change could be inferred. Results indicated good agreement (Pearson's coefficient r=0.85, p<0.01) between snow-vegetation growth extent with the temperature changes measured in the corresponding area. Recent in-situ verification of the selected sites in the region confirmed the agreements