Evaluating Landsat-8 and Sentinel-2 Data Consistency for High Spatiotemporal Inland and Coastal Water Quality Monitoring

The synergy of fine-to-moderate-resolutin (i.e., 10–60 m) satellite data of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2 Multispectral Instrument (MSI) provides a possibility to monitor the dynamics of sensitive aquatic systems. However, it is imperative to assess the spectral consistency of both sensors before developing new algorithms for their combined use. This study evaluates spectral consistency between OLI and MSI-A/B, mainly in terms of the topof-atmosphere reflectance (ρt), Rayleigh-corrected reflectance (ρrc), and remote-sensing reflectance (Rrs). To check the spectral consistency under various atmospheric and aquatic conditions, nearsimultaneous same-day overpass images of OLI and MSI-A/B were selected over diverse coastal and inland areas across Mainland China and Hong Kong. The results showed that spectral data obtained from OLI and MSI-A/B were consistent. The difference in the mean absolute percentage error (MAPE) of the OLI and MSI-A products was ~8% in ρt and ~10% in both ρrc and Rrs for all the matching bands, whereas the MAPE for OLI and MSI-B was ~3.7% in ρt , ~5.7% in ρrc, and ~7.5% in Rrs for all visible bands except the ultra-blue band. Overall, the green band was the most consistent, with the lowest MAPE of ≤ 4.6% in all the products. The linear regression model suggested that product difference decreased significantly after band adjustment with the highest reduction rate in Rrs (NIR band) and Rrs (red band) for the OLI–MSI-A and OLI–MSI-B comparison, respectively. Further, this study discussed the combined use of OLI and MSI-A/B data for (i) time series of the total suspended solid concentrations (TSS) over coastal and inland waters; (ii) floating algae area comparison; and (iii) tracking changes in coastal floating algae (FA). Time series analysis of the TSS showed that seasonal variation was well-captured by the combined use of sensors. The analysis of the floating algae bloom area revealed that the algae area was consistent, however, the difference increases as the time difference between the same-day overpasses increases. Furthermore, tracking changes in coastal FA over two months showed that thin algal slicks (width < 500 m) can be detected with an adequate spatial resolution of the OLI and the MSI

Effects of Subcapsularis Neuro Muscular Reduction (NMR) in Adhesive Capsulitis

Background: To determine the effects of Subscapularis Neuromuscular Reduction (NMR) in Adhesive Capsulitis patients on pain, Range of Motion (ROM) and Quality of life. Methods: In this randomized controlled trail patients with freezing and frozen stage of Adhesive capsulitis and limited range of movement were included. Patients were randomly divided into control (Group A) and experimental group (Group B). The patients of Group A were treated with conventional physical therapy treatment protocol and patients of group B were treated with subscapularis neuromuscular reduction along with conventional physical therapy. The patient outcome measures were assessed using numeric pain rating scale (NPRS), SPADI (shoulder pain and disability index) and ranges via goniometry. Data was analyzed by SPSS 21. Results: Both group showed significant improvement, but the end value comparison showed significant difference. NMR (Neuromuscular Reduction) on Subscapularis muscles improved the pain, ROM and Patient functional status more as compared to the conventional physical therapy group. The NPRS mean value for control group was 2.90±1.09 and mean value for experimental group was 2.05±1.10with p value of 0.021 while the mean value of SPADI for control group was33.52±9.96 and for experimental group was 26.72±8.00 with p value of 0.026. Conclusion: Treatment groups showed improvement by reducing pain, improving range of motion and functional status but neuromuscular reduction of subscapularis muscles was found to be more effective

Temperature change and urbanisation in a multi-nucleated megacity: China’s Pearl River Delta

This paper investigates urbanisation and temperature indices, over four decades in a multi-nucleated megacity, China’s Pearl River Delta (PRD). Daily mean minimum, maximum and mean temperatures (Tmin, Tmax and Tmean) have increased considerably above background warming rates. However, only weak to moderate relationships are observed between trends in local urban surface area surrounding climatic stations, and Tmin used as a proxy for UHI development. While 5 out of 21 stations with high increase in both Tmin and degree of urbanisation, showed moderate relationship (R=0.51), another 8 stations with low urbanisation showed significant increase in Tmin. This suggests warming from factors other than local urban development on Tmin. Since PRD contains 123 cities over 1 million population, and a semi-continuous urbanised area due to merging of urban centres, a regional heat island circulation, or heat dome model is invoked. The observed increase in Tmax above background warming rates for 14 stations, is more difficult to explain as Tmax is not generally affected by urbanisation. This is attributed to high surface energy flux in the afternoon, and anthropogenic energy use in dense urban districts. The regional heat dome circulation over PRD suggests local temperatures will increase further, even without further local developments

The accumulation of species and recovery of species composition along a 70 year successional gradient in a tropical secondary forest

The majority of global forests are secondary and are at different stages of succession. Assessing the dynamics of species richness and similarity, and quantifying the importance of environmental filtering, dispersal limitation and other stochastic processes are essential to understanding the mechanisms of succession for forest restoration. In this article, we explored the accumulation of species, the relative importance of spatial distance, environmental factors and stand age in determining species composition of a tropical secondary forest succession in Hong Kong. Twenty-eight plots with median age of 7, 20, 39, 61 and over 70 years in the secondary forest were established and surveyed, and the indicator species for each age class were identified. Species composition shows large variation both within and between age classes, while species richness in the old growth forest (>70 yr) was significantly lower than in the mid-age classes. Rarefied species richness showed a rapid accumulation during early succession, but species richness levelled off from 20 yrs onwards. Variation partitioning indicated that spatial distance alone explained 33% of the variation in species composition, followed by environmental distance (8%) and stand age (1%). The results of Nonmetric Multidimensional Scaling suggested that idiosyncratic successional pathways and alternative stable states might be prevalent. Our results suggested dispersal limitation was the main limiting factor in explaining the turnover of species during forest succession, while environmental filtering played a lesser role in shaping species distributions. Our results highlight the importance of active restoration in overcoming the barriers of succession in secondary vegetation in the tropics

Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Recently, the marine habitat has been under pollution threat, which impacts many human activities as well as human life. Increasing concerns about pollution levels in the oceans and coastal regions have led to multiple approaches for measuring and mitigating marine pollution, in order to achieve sustainable marine water quality. Satellite remote sensing, covering large and remote areas, is considered useful for detecting and monitoring marine pollution. Recent developments in sensor technologies have transformed remote sensing into an effective means of monitoring marine areas. Different remote sensing platforms and sensors have their own capabilities for mapping and monitoring water pollution of different types, characteristics, and concentrations. This chapter will discuss and elaborate the merits and limitations of these remote sensing techniques for mapping oil pollutants, suspended solid concentrations, algal blooms, and floating plastic waste in marine waters

Comparison of machine learning algorithms for retrieval of water quality indicators in case-II waters: a case study of Hong Kong

Anthropogenic activities in coastal regions are endangering marine ecosystems. Coastal waters classified as case-II waters are especially complex due to the presence of different constituents. Recent advances in remote sensing technology have enabled to capture the spatiotemporal variability of the constituents in coastal waters. The present study evaluates the potential of remote sensing using machine learning techniques, for improving water quality estimation over the coastal waters of Hong Kong. Concentrations of suspended solids (SS), chlorophyll-a (Chl-a), and turbidity were estimated with several machine learning techniques including Artificial Neural Network (ANN), Random Forest (RF), Cubist regression (CB), and Support Vector Regression (SVR). Landsat (5,7,8) reflectance data were compared with in situ reflectance data to evaluate the performance of machine learning models. The highest accuracies of the water quality indicators were achieved by ANN for both, in situ reflectance data (89%-Chl-a, 93%-SS, and 82%-turbidity) and satellite data (91%-Chl-a, 92%-SS, and 85%-turbidity. The water quality parameters retrieved by the ANN model was further compared to those retrieved by “standard Case-2 Regional/Coast Colour” (C2RCC) processing chain model C2RCC-Nets. The root mean square errors (RMSEs) for estimating SS and Chl-a were 3.3 mg/L and 2.7 µg/L, respectively, using ANN, whereas RMSEs were 12.7 mg/L and 12.9 µg/L for suspended particulate matter (SPM) and Chl-a concentrations, respectively, when C2RCC was applied on Landsat-8 data. Relative variable importance was also conducted to investigate the consistency between in situ reflectance data and satellite data, and results show that both datasets are similar. The red band (wavelength ≈ 0.665 µm) and the product of red and green band (wavelength ≈ 0.560 µm) were influential inputs in both reflectance data sets for estimating SS and turbidity, and the ratio between red and blue band (wavelength ≈ 0.490 µm) as well as the ratio between infrared (wavelength ≈ 0.865 µm) and blue band and green band proved to be more useful for the estimation of Chl-a concentration, due to their sensitivity to high turbidity in the coastal waters. The results indicate that the NN based machine learning approaches perform better and, thus, can be used for improved water quality monitoring with satellite data in optically complex coastal waters

Spatial and environmental constraints on natural forest regeneration in the degraded landscape of Hong Kong

Tropical forests are the main reservoirs for global biodiversity and climate control. As secondary forests are now more widespread than primary forests, understanding their functioning and role in the biosphere is increasingly important. This includes understanding how they achieve stability, how they accumulate species and build biodiversity and how they cycle nutrients and carbon. This study investigates how we can restore tropical secondary forests to resemble high biomass, highly biodiverse and stable ecosystems seen today only in primary, undisturbed forests. The study used historic aerial photographs and recent high-resolution satellite images from 1945 to 2014 to map forest patches with five age categories, from 14-years to over 70-years, in Hong Kong's degraded tropical landscape. A forest inventory comprising 28 quadrats provided a rare opportunity to relate patterns of species composition at different stages during the succession with topographic and soil characteristics. The topographic variables accounted for 15% of the variance in species abundance, and age of forest stands explained 29%. Species richness rapidly increased after the first 15 years, but was lower in old-growth, than in medium age forest. This is attributed to the inability of late-successional species to disperse into the young forests as the natural dispersal agents (birds, mammals) have been lost. Light-loving pioneers which are unable to tolerate the shade of older forests, cannot regenerate in their own shade, therefore species diversity declines after a few decades. For ecosystem restoration in tropical secondary forests, introduction of late-successional species is necessary to assist natural succession, given the absence of native fauna, seed dispersal agents, and the surrounding altered environment. We also show that remote sensing can play a pivotal role in understanding the recovery and functioning of secondary forest regeneration as its contribution to the biosphere is increasingly important

Unveiling falling urban trees before and during Typhoon Higos (2020): empirical case study of potential structural failure using tilt sensor

Urban trees in a densely populated environment may pose risks to the public’s safety in terms of the potential danger of injuries and fatalities, loss of property, impacts on traffic, etc. The biological and mechanical features of urban trees may change over time, thereby affecting the stability of the tree structure. This can be a gradual process but can also be drastic, especially after typhoons or heavy rainstorms. Trees may fall at any time with no discernible signs of failure being exhibited or detected. It is always a challenge in urban tree management to develop a preventive alert system to detect the potential failure of hazardous urban trees and hence be able to have an action plan to handle potential tree tilting or tree collapse. Few studies have considered the comparison of tree morphology to the tilt response relative to uprooting failure in urban cities. New methods involving numerical modeling and sensing technologies provide tools for an effective and deeper understanding of the interaction of root-plate movement and windstorm with the application of the tailor-made sensor. In this study, root-plate tilt variations of 889 trees with sensors installed during Typhoon Higos (2020) are investigated, especially the tilting pattern of the two trees that failed in the event. The correlation of tree response during the typhoon among all trees with tilt measurements was also evaluated. The results from two alarm levels developed in the study, i.e., Increasing Trend Alarm and Sudden Increase Alarm indicated that significant root-plate movement to wind response is species-dependent. These systems could help inform decision making to identify the problematic trees in the early stage. Through the use of smart sensors, the data collected by the alert system provides a very useful analysis of the stability of tree structure and tree health in urban tree management

Impact assessment of a super-typhoon on Hong Kong’s secondary vegetation and recommendations for restoration of resilience in the forest succession

Typhoons of varying intensities severely impact ecosystem functioning in tropical regions and their increasing frequencies and intensities due to global warming pose new challenges for effective forest restoration. This study examines the impact of a super-typhoon (Mangkhut) on the regenerating native secondary forest and exotic monocultural plantations in the degraded tropical landscape of Hong Kong. The super typhoon, which hit Hong Kong on 16 September 2018 lasted for 10 hours (09:40 to 19:40) and was the most severe storm affecting Hong Kong over the past 100 years. Hong Kong’s secondary forest is a mosaic of forest patches recovering through natural succession since 1945, and plantation stands of exotic monocultural species. We determine the loss in biomass by performing NDVI (Normalized Difference Vegetation Index) difference analysis using two Landsat-8 multispectral images acquired before and after the typhoon. This the assessment of typhoon impacts according to successional age group, structural stages of vegetation, landscape topography, and on stands of exotic plantations. Results indicate that hilltops, open shrubland and grassland were hard hit, especially on southwest and southeast facing slopes, and almost 90 % of the landscape showed abnormal change. Patches of exotic monoculture plantation (Lophostemon confertus, Melaleuca quinquenervia, and Acacia confusa) were the most severely damaged by the typhoon, showing more than 25 % decrease in NDVI, followed by young secondary forest. Field observations confirmed that in exotic plantations, almost the entire canopy was destroyed and there is no generation of young under story trees to replace those lost. The affected young forests and shrublands are mainly dominated by fast growing, soft wooded early successional species such as Mallotus paniculatus or Machilus chekiangensis as well as weak, multi-trunked, fungus infected, or other structurally deficient trees, which were uprooted or seriously damaged by typhoon gusts. The net effect of typhoons in Hong Kong’s degraded landscape, appears to reinforce the arrested succession of dense, less diverse stands of weaker early successional species due to the absence of late and middle successional species and native dispersal agents. In order to obtain a stronger, more resilient forest, it would be necessary to enhance biodiversity by artificially planting a species mix, which resembles primary forests in the region. This could be achieved by thinning of young secondary forest followed by enhancement planting of pockets of high diversity forest