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Mangroves, coastal salt marshes and seagrass beds, as the typical coastal blue carbon ecosystems, have been widely recognized for their remarkable capacity in carbon storage. Vegetation carbon pool and sediment (or soil) carbon pool were considered to be the major carbon pools within the coastal blue ecosystems and their variations determined the overall carbon sequestration of the ecosystems. From a perspective of carbon pool interactions, this study summarized the previous research work based on literature review, including the interactions within various vegetation carbon pools and within various sediment carbon pools, as well as the interactions between vegetation and sediment carbon pools. Interspecific competition, allochthonous carbon input and biogeomorphology were found to be the key to understand the carbon pool interactions. Finally, a perspective on the current state-of-the-art of blue carbon pool study is offered, with challenges and suggestions for future directions.

In order to explore the distribution, formation mechanism and motion law of eddy around Kuroshio in East China Sea, firstly, the eddy distribution around the Kuroshio in the East China Sea during the past 27 years was analyzed by using the mesoscale eddy data set of the AVISO(Archiving, Validation and Interpretation of Satellite Oceanographic Data). The results show that there are 650 eddies generated in the meander of the Kuroshio, and 271 eddies in the middle part of the Kuroshio. The diameters of the most these eddies were between 100 to 150 km, and the amplitudes were between 2 to 6 cm. Secondly, the motion path and eddy motion process of the Kuroshio in the East China Sea are also analyzed. The results show these the cyclonic eddies are easy to be generated in the inner side of the Kuroshio cyclonic bend, with a long path. For example, at the cyclone bend of the Kuroshio axis in the northeast of Taiwan, the average length of the path was 87.6 km. Otherwise, when these anticyclonic eddies are generated, these eddies usually are wandered. In the middle part of the Kuroshio, the eddy showed the polar symmetric distribution characteristics of these cyclonic eddies in the west side of the Kuroshio main axis and these anticyclonic eddies in the east side of the Kuroshio main axis. Both types of eddies moved northeastward along the Kuroshio main axis. Finally, combined with reanalysis data sets of ocean current and sea surface height, the eddy motion law and generation mechanism were discussed. It is concluded that these eddies generation at the curve of the Kuroshio are related to the separation of the boundary layer of the Kuroshio fluid. The Kuroshio countercurrent from the south of Yanmei Island to the west of Okinawa Island played a key role in the polar symmetric distribution of these eddies in the middle part of the Kuroshio. These eddies usually experience three stages of growth, maturation and decay in the process of movement.

Costal ocean receives a bunch of carbon materials and nutrients from terrestrial sources, relates a lot of carbon-involving interactions. Meanwhile, it is normal that sedimentary reservoir-cap systems with good trap conditions beneath coastal ocean, these entrapments have potentials to storage CO₂. This review focuses on the coastal ocean as the research object, and introduces the carbon cycle processes in coastal ocean, their factors which could influence CO₂ fluxes in the carbon cycle processes, and the potential carbon storage mechanisms of the coastal marine sedimentary basins. From the perspective of “carbon peaking and carbon neutrality”, the significance of coastal oceans for “Ocean Negative Carbon Emission (ONCE)”, its potential promotion paths, carbon storage potentials in sedimentary basins and the problems faced by coastal oceans are discussed. Overall, the costal ocean is one of the important blue carbon sink areas. In the coastal marine seawater system, improving the reaction efficiency of microbial carbon pump and carbonate carbon pump have positive significance for CO₂ negative emissions; The suitable reservoir-cap systems for CO₂ storage beneath coastal ocean can not only provide extra spaces, but also guarantee the safety for CO₂ storage. In the future, the main research directions should be to inhibit the conversion process of carbon materials to CO₂ in coastal oceans and ensure the safety of CO₂ storage in sedimentary reservoirs, these could provide theoretical basis and technical guarantee for CO₂ negative emissions.

Alkaline phosphatase activity (APA) is an important indicator of phytoplankton phosphorus limitation status in the marine science study. In the “nitrogen-excess” areas such as the Changjiang Estuary (CJE), phosphorus is a major factor controlling the primary productivity in the sea. However, the extent of phosphorus limitation is often difficult to define and little is known about the effect of phosphorus limitation on phytoplankton at different sizes. In this study, the spatial distribution of phytoplankton (Net: ≥20 μm; Nano: 2~20 μm; Pico: 0.8~2 μm) APA, bacterioplankton APA (0.2~0.8 μm) and dissolved APA (<0.2 μm) in the surface layer of the CJE in the summer of 2020 were given, and the correlation between APA and environmental factors were analyzed. The results showed that size-fractionated phytoplankton APA was negatively correlated with dissolved inorganic phosphate (DIP), indicating that DIP concentration was the main factor affecting the distribution of size-fractionated phytoplankton APA. In the spatial distribution, phytoplankton APA was lower in the light-limitation zone near the mouth, and showed an increasing trend from the mouth to the east, contrary to the distribution of DIP. Net and Nano phytoplankton APA (mean values of (40.28±32.35) nmol/(L·h) and (52.38±34.78) nmol/(L·h), respectively) were significantly higher than Pico phytoplankton APA (mean values of (28.43±20.23) nmol/(L·h)) in the CJE, implying that large size phytoplankton were more susceptible to DIP decline. In this study, the DIP concentration for inducing a rapid increase in phytoplankton APA was 0.159 μmol/L, which was close to the empirical threshold for nearshore phosphorus limitation. This study revealed the characteristics of phytoplankton response to phosphorus distribution in the CJE at different grain levels in summer, and also contributed to the understanding of the environmental regulatory mechanisms of primary production processes in the CJE.

Carbon stock variation observation forms the basis for coastal saltmarsh blue carbon sink accounting. In order to accurately estimate the carbon sequestration rate of coastal saltmarshes over a short-term scale (seasonal to annual), this study carried out field observations and sample collections within a coastal saltmarsh on the south bank of Hangzhou Bay, covering different seasons of 2022. This study was primarily based on high-resolution surface monitoring by Surface Elevation Table (SET) systems. The results revealed a seasonal plant growth pattern between March and September for both the native species Scirpus mariqueter and the exotic species Spartina alterniflora. In terms of belowground biotic carbon stock changes, over the growing season, the carbon stock increase for Scirpus mariqueter reached 11 g C·m^-2 whilst this value was 56 g C·m^-2 for Spartina alterniflora. The SET data indicated a sedimentation rate of 13.02 cm·a^-1 within the Spartina alterniflora saltmarsh, higher than that of the Scirpus mariqueter saltmarsh, 12.30 cm·a^-1. Calculating the sedimentation rate data with sediment bulk density and organic carbon content, the sediment carbon accumulation rate of Scirpus mariqueter saltmarsh was estimated to be 460 g C·m^-2·a^-1, lower than 588 g C·m^-2·a^-1 of the Spartina alterniflora saltmarsh. Combining the biotic carbon stock increase and sediment carbon stock increase, the carbon sequestration rate for the Spartina alterniflora saltmarsh was found to be 644 g C·m^-2·a^-1, higher than the value of Scirpus mariqueter saltmarsh, 471 g C·m^-2·a^-1. Thus, the difference in carbon sequestration abilities of native and exotic species should be considered for future coastal blue carbon management.

The variation characteristics of water and sediment in the Pearl River Basin over the past about 70 years were analyzed by using the runoff and sediment discharge data at three major hydrological stations in the Pearl River Basin, Gaoyao Station (Xijiang River), Shijiao Station (Beijiang River) and Boluo Station (Dongjiang River) from 1954 to 2019, and applying the Mann-Kendall nonparametric test and accumulative anomaly curves. The results showed that the change of the runoff in the Pearl River from 1954 to 2019 was not obvious while the sediment discharge was decrease, among which the sediment discharge at Gaoyao and Boluo Stations changed abruptly in 2003 and 1991, decreasing by 71.3% and 48.88%, respectively, compared with before the abrupt change, while the sediment discharge at Shijiao Station did not change abruptly. On this basis, the change of vegetation cover in the basin and its relationship with the change of water and sediment were studied by using the precipitation data and Normalized Difference Vegetation Index (NDVI) in the basin from 2000 to 2019. The NDVI in the Pearl River Basin showed an overall increasing trend from 2000 to 2019, and the improvement area of vegetations cover accounted for 89.27% of the total basin area. Among which NDVI in the Pearl River Basin was poorly correlated with sediment discharge from 2000 to 2008, NDVI in the Xijiang River Basin and Dongjiang River Basin were positively correlated with precipitation in the basin but not with sediment discharge form 2009 to 2019, and only in the Beijiang River Basin, NDVI was insignificantly negatively correlated with sediment discharge. The influence of human activities on sediment discharge in the Pearl River at different periods was discussed using the double cumulative curve method. Since the 1980s, human activities such as deforestation, reservoir construction, and soil and water conservation had a significant impact on sediment discharge. After 2000, the construction of Longtan Reservoir was the main reason for the decline of sediment discharge in the Xijiang River, but the improvement of vegetation coverage had no significant impact on the sediment discharge in the Pearl River Basin.

Marine gas hydrate deposits are significant temporal reservoirs for hydrocarbons migrating from deep sources. This is crucial to our understanding of ocean carbon cycling. The cold seep, a geological process regarding gas leakage from deep or shallow sources, is usually linked with gas hydrate decomposition. In this thesis, we reviewed the latest applications of in situ monitoring and detecting methods regarding the leakage plumes, migration pathways, and seafloor geomorphologies associated with gas hydrate and cold seep systems, primarily including vessel-and land-based gas plume measurements, surface ocean-lower atmosphere hydrocarbon emission detections, seafloor visualization techniques, and in situ observation networks. The integrated applications of these in situ observation methods provide a nuanced view of the temporal and spatial variability of hydrate and cold seep systems, facilitate understanding of the fate of hydrocarbons, and expand our knowledge of cold-seep biota in a watery desert.

In satellite remote sensing image recognition, compared with ship recognition in a single marine environment, port ship recognition is more difficult due to the presence of a large number of interference targets such as containers and docks. In order to improve the recognition ability of GF-2 satellite data on port ships, five fusion algorithms, i.e. Intensity Hue Saturation (IHS) Transform, Brovey Transform(BT), ESRI panchromatic sharpening Transform, simple mean Transform and Gram-Schmidt Transform (GS) were used to perform the fusion experiment of panchromatic and multispectral images, and the optimal method applicable to port ship images is selected through qualitative and quantitative evaluation. The results show that GS Transform can increase spatial information while maintaining spectral fidelity, and its mean value, root mean square error, peak signal to noise ratio, and structural similarity are superior to the other four fusion algorithms, with high recognition accuracy for port ships.

The East China Sea Shelf Basin is a Mesozoic and Cenozoic superimposed basin with high oil and gas potential. At present, the discovery of oil and gas in the basin comes from the Cenozoic reservoirs, and various aspects of the Mesozoic residual strata are less known. Furthermore, previous qualitative or semi-quantitative studies are usually spatially limited within specific structural units in the western part of the basin and mainly involves Cretaceous and Jurassic. This study collects and sorts out the latest reflection seismic data and well data penetrated into the Mesozoic in the entire study area. Based on seismic sequences of the Cretaceous, Jurassic and Pre-Jurassic, our results show that the Mesozoic residual strata in the East China Sea Shelf Basin suffered from severe denudation in the later period. The Mesozoic residual strata generally thicken to the east and south, and the range of residual strata expanded eastward over time. Comparing the distribution characteristics of the residual strata between different periods, it is further supported that the East China Sea Shelf Basin was a passive continental margin depression basin in the Triassic, and an active continental margin fore-arc basin in the Early-Middle Jurassic, and a continental margin back-arc extensional basin in the late Jurassic to late Cretaceous. Correspondingly, the subduction of the paleo-Pacific plate began in the Late Triassic-Early-Middle Jurassic, and the retreat of the plate began in the Late Jurassic. The east boundary of the Mesozoic proto of the East China Sea Shelf Basin was located on the east side of the Diaoyu Island uplift.

The monitoring of carbon flux dynamics and assessment of carbon sink functions of island forest ecosystems are rarely reported due to their special geographical location and few data sources. In this study, the forest ecosystem of the Nanji Island was used as the research object, the carbon sink potential of island forests and their driving factors were assessed. Based on eddy correlation techniques, the temporal variation characteristics and driving factors of net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (Reco) from 2020 to 2021 were explored. Results showed that the forest ecosystem of Nanji Island was carbon sink. Net CO₂ uptake in 2020 and 2021 were 516 g C·m^-2·a^-1 and 598 g C·m^-2·a^-1, Reco were 1 037 g C·m^-2·a^-1 and 1 646 g C·m^-2·a^-1, and GPP were 1 552 g C·m^-2·a^-1 and 2 244 g C·m^-2·a^-1, respectively. Total solar radiation (Rg), photosynthetically active radiation (PAR), net radiation (Rn) and sensible heat (H) were significantly and positively correlated with NEP and GPP (p≤0.001); air temperature (Tair) and soil temperature (Tsoil) were significantly and positively correlated with Reco(p≤0.001). The photosynthesis time of Nanji Island forest was longer than the carbon sink time on the daily scale. When Tair reached 10.05-27.76 ℃ and PAR reached 110.47-429.44 μmol·m^-2·s^-1, the photosynthesis intensity of island forest was higher than that of ecosystem respiration, which showed CO₂ absorption. The monitoring and assessment of carbon fluxes in the forest ecosystems of Nanji Island will provide an important theoretical support for the establishment of a dynamic monitoring and assessment management system for blue carbon in China.

Mangroves, salt marshes, and seagrass beds are known as the three major coastal blue carbon ecosystems (CBCEs), which play important roles in marine biodiversity maintenance, water purification, nutrient recycling, carbon sequestration and storage. Guangdong Province and Guangxi Zhuang Autonomous Region in China, where the CBCEs are widely distributed, were selected as the research areas, to investigate the spatial relationship between CBCEs and the marine ecological redlines (MERs). The CBCE conservation gap was analyzed, and the recommended priority conservation areas outside the MERs were proposed. The CBCE distribution data obtained from the satellite images in 2019, combined with field survey and UAV remote sensing data collected during 2020 and 2021 showed that the CBCEs in Guangdong totaled 14 481.39 hm² (mangroves 11 928.87 hm², salt marshes 1 258.00 hm², seagrass beds 1 294.52 hm²), whereas the CBCEs in Guangxi totaled 11 751.30 hm² (mangroves 10 171.70 hm², salt marshes 1 450.36 hm², seagrass beds 129.24 hm²). 62.13% of the CBCEs in Guangdong and 59.88% in Guangxi were covered by the MERs. The distribution areas and protection ratios of mangroves and seagrass beds in Guangdong were both larger than those in Guangxi, while the distribution area and protection ratio of salt marshes in Guangxi were larger than that in Guangdong. As to the 3 types of CBCEs in Guangdong, 62.13% of the mangroves, 38.16% of the salt marshes and 85.41% of the seagrass beds were under protection. For the CBCEs in Guangxi, 61.44% of the mangroves, 49.58% of the salt marshes and 52.99% of the seagrass beds were protected. This research suggests the coast from Rongmujiang Bay to Maowei Sea, the areas of Tieshan Bay, Leizhou Bay, Zhelin Bay and other related locations as the recommended priority conservation areas outside the MERs.

To solve the problem of insufficient information of offshore oil and gas platform, the method of oil and gas platform identification based on multi-source satellite remote sensing was studied. Based on Landsat-8 remote sensing images of the Bohai Sea (2018-2021), 136, 166 and 113 oil and gas platforms in the Bohai Sea were identified by threshold segmentation, K-means unsupervised algorithm and maximum likelihood classification, respectively. Based on Sentinel-1 SAR images (2018-2021), 338 oil and gas platforms were identified by threshold segmentation method. Based on the decision level fusion of the above results, 428 oil and gas platforms in the Bohai Sea were identified. The ZY-3 high-resolution images were used to verify the identification results of the fusion method. The results showed that the accuracy of the identified oil and gas platforms reached 85.2%, and the error rate and miss rate were 10.9% and 3.9%, respectively. The identified oil and gas platform locations are consistent with literature and public data. The research shows that the decision level fusion method can realize the effective identification and extraction of offshore oil and gas platforms, and has the value of popularization and application.

Coastal bays are greatly affected by human activities and natural changes, and the influence mechanism of variation in seawater carbon source and sink patterns is extremely complex. Due to the small spatial scale of the bay, it is necessary to use wide-bands high-spatial resolution satellite remote sensing for monitoring the air-sea CO₂ flux. Compared with the traditional kilometer-level ocean color satellite data, the retrieval of the sea surface partial pressure of CO₂ (pCO₂), the key parameter to calculate air-sea CO₂ flux, is extremely challenging in small-scale bays. Taking Xiangshan Bay in Zhejiang Province in autumn as an example, a satellite retrieval algorithm for sea surface pCO₂ was proposed based on the in situ pCO₂ data and Sentinel-2 satellite images in the past five years, using the machine learning method of support vector machine (SVM). The algorithm validation results showed a good performance with R² of 0.92 and RMSE of 23.23 μatm, and the satellite-derived results were consistent with the in situ values. On this basis, the satellite products of pCO₂ in Xiangshan Bay in autumn from 2017 to 2021 (September to November) were produced. The results revealed that the pCO₂ of Xiangshan Bay showed a decreasing trend from the top of the bay to the mouth of the bay, with an average value of 514.56 μatm, of which the average pCO₂ in the inner bay was 551.94 μatm and the average pCO₂ in the outer bay was 477.19 μatm, which implied that Xiangshan Bay was a source of atmospheric CO₂ as a whole. There was no significant trend change of pCO₂ in autumn in the past five years. Combined with the analysis of in situ data of multiple parameters, it was found that the sea surface pCO₂ of autumn in Xiangshan Bay in 2021 was jointly regulated by physical mixing and biological activities. Sea surface temperature (SST) had a good positive correlation with pCO₂, which was mainly reflected by the thermodynamic equilibrium of carbonate system. In addition, the normalized pCO₂(NpCO₂) with average temperature had a good negative correlation with seawater salinity and dissolved oxygen saturation. The relationship between NpCO₂ and salinity resulted from the exchange of sea water inside the bay and offshore coastal water under tidal effect. Long-time series satellite data analysis also confirmed that sea surface pCO₂ had a relatively consistent trend with the average tide height inside and outside the bay, and this trend was stronger in the outside bay than that in the inner bay. In this study, a set of pCO₂ remote sensing retrieval methods in the small-scale bay was constructed, which laid a good foundation for the subsequent long-time series satellite monitoring of sea-air CO₂ fluxes.

A knowledge of the effects of major currents, extent of hypoxia, tidal effects, and aquaculture activities on speciation and distribution of particulate phosphorus in surface sediments in the Changjiang Estuary (CJE) and coastal waters of Zhejiang is critical to develop a sustainable strategy for the East China Sea (ECS). Two hypoxic zones are located in this region, one off the CJE in the north and the other in the muddy deposits along the Zhejiang coast of the ECS. Hangzhou Bay is a tide-dominated bay, and Xiangshan Bay is an aquaculture area influenced by tidal mixing. Surface sediments were collected from above four regions during August to September, 2018, and sedimentary phosphorus speciation were quantified using SEDEX method. Under reducing conditions at the mud-water interface in the two hypoxic zones of the ECS, iron bound phosphorus (Fe-P) in the sediments were transformed into exchangeable inorganic phosphorus (Ex-iP) which were immediately bioavailable, as evidenced by low Fe-P and high Ex-iP in the sediments. As the hypoxic zone off the CJE was more oxygen deficit, the contents of Fe-P in the sediments were also lower. Tidal mixing in Hangzhou Bay and Xiangshan Bay led to homogeneous distribution of particulate phosphorus in the surface sediments. All surface sediments in Xiangshan Bay were characterized by very low Fe-P, because tidal mixing caused the hypoxic areal extent, resulted from dense aquacultures, to be further increased to cover the whole bay area. The contents of detrital and refractory phosphorus in the surface sediments in a deserted aquaculture farm were substantially lower than those in non-aquaculture area, most likely due to dilution by biomass accumulated during culturing.

Tidal flat is an important part of coastal wetland, and is of great significance for blue carbon. Remote sensing is the most widely used method for tidal flat monitoring, but due to the influence of tides, the area of tidal flat extracted by remote sensing is often greatly underestimated. In this study, Sentinel-2 satellite images from 2016 to 2021 were used to extract the instantaneous area of tidal flats in Yueqing Bay, and the quantitative relationship between tidal flats area and tidal level or the tidal level correction model for tidal flats area was established. On this basis, Landsat satellite images in 7 years from 1988 to 2020 were selected to extract the instantaneous tidal flat area, and the established correction model was used to obtain the corrected multi-year tidal flat area at low tide level, and the change of tidal flat area in Yueqing Bay in recent 30 years and the main driving factors were analyzed. In recent 30 years, the tidal flat area of Yueqing Bay showed a trend of significant increase from 1988 to 1994, sharp decrease from 1994 to 2010, slight increase from 2010 to 2015, and decrease again from 2015 to 2020. The development and utilization of tidal flat by human activities is the main driving factor of tidal flat area change in Yueqing Bay.

The development of the global chemical industry has led to frequent leakage accidents of hazardous chemicals at sea, which has seriously affected the marine ecological environment. How to carry out rapid and effective emergency response has become an urgent need. The prediction and visualization of hazardous chemicals' future diffusion situation is an important part of the emergency process. At present, related researches on pollution diffusion visualization are still insufficient in the aspects of scene construction, rendering efficiency, scalability and interactive control. A three-dimensional dynamic visualization method for the diffusion process of marine hazardous chemicals based on the Unity3D engine and its particle system was proposed in this study. Based on the construction of three-dimensional scenes around the ocean and the optimization of model data, the visualization of hazardous chemicals diffusion process was achieved by dynamically updating the particles and interactive user interfaces for scene roaming and diffusion process control were provided. Taking Hangzhou Bay as an example, the simulation experiment results show that the performance and effect of this method meet the needs of practical applications. This method can provide information reference and auxiliary decision support for the emergency response of marine hazardous chemical leakage accidents.

Using Argo measured data combined with satellite remote sensing data and moored buoy data, the upper ocean temperature and salinity response caused by super typhoon Rammasun in 2014 was analyzed and studied. The result shows that super typhoon Rammasun resulted in cooling of sea surface temperature and deepening of mixing layer. Meanwhile, mixing length and vertical velocity induced by typhoon were calculated in this research, which explained the causes of temperature changes in the subsurface layer. Strong mixing and weak upwelling led to warming of the subsurface layer, whereas weak mixing and strong upwelling led to cooling of the subsurface layer. Compared with the change of temperature, the response of salinity was more complex. Precipitation first caused the decrease of surface salinity, and then vertical mixing led to a large increase of surface salinity. However, the effect of precipitation could greatly inhibit this process. After the typhoon departed, the vertical mixing was weakened, and the salinity was greatly reduced because of the heavy precipitation, it was even lower than that before the typhoon.

Tidal current energy is the kinetic energy carried in the horizontal movement of tidal water, which has great development prospects. Accurate simulation and characterization of regional tidal currents can help to efficiently evaluate the spatial and temporal distribution of tidal energy resources, which is the key to the development and utilization of tidal current energy resources. In this paper, a high-resolution numerical model of tidal currents is constructed by applying FVCOM ocean model in Zhoushan sea area where has rich tidal current energy, and the reliability of the model is confirmed by tidal level and current verification. According to the simulation results, six waterways with dense tidal current energy resources in the Zhoushan sea area were identified, among which the average energy density of Xihoumen waterway, Cezi waterway and Taohuagang waterway exceeds 2.0 kW/m², and the maximum energy density exceeds 20 kW/m², and the flow speed over 1.0 m/s of the whole month is more than 80%. During tidal current ebb and flow, the reflow is dominant, while the asymmetry and rotation of tidal current are low. The flow stability coefficient is more than 0.98, so it is more suitable for the development and utilization of tidal current energy than other three waterways. The best location for tidal current energy development in these three waterways was then determined by calculating the significant hours and available hours, and the corresponding exploitable tidal current energy resources were evaluated using the Farm method, which were 27.53 MW, 39.96 MW, and 130.26 MW, respectively.

Taking Dazhuzhi Island (Dongtou, Wenzhou) as the research area, UAV equipped with multispectral sensors was used to acquire high-resolution remote sensing images, the optimal spectral band combination was selected to classify the island vegetation, and the vegetation types was divided into arbors, shrubs and herbs by supervised classification. The accuracy of vegetation classification was 99.72%, and the Kappa coefficient was 0.995 4. The spatial distribution of dominant species of arbors and shrubs was obtained by using the deep convolutional neural network (the precision rate was 0.79), and combined with the biomass equations, the spatial distribution of the biomass of dominant species of arbors and shrubs was inversed (arbors’ R²=0.97, shrubs’ R²=0.99). The biomass inversion equations of 3 shrub dominant species (Ficus erecta, Mallotus japonicas, and Eurya emarginata) were constructed by field sampling, and the other dominant species biomass inversion equations were obtained from literature. Based on the biomass and spatial distribution of dominant species, the carbon storage of arbors and shrubbys was 300.36 t and 47.59 t, respectively. Using normalized difference vegetation index (NDVI) to invert the spatial distribution of herb biomass (R²=0.99), combined with the biomass equation of the dominant herb species (Zoysia sinica) constructed from the measured data, the carbon storage of herbs was 21.59 t on Dazhuzhi Island.

Based on the unsupervised pixel-based Spectral Rule-based Classifier (SRC) algorithm, an effective Modified Spectral Rule-based Classifier (MSRC) was proposed considering the influence of atmospheric correction on spectral reflectances of remote sensing images. MSRC modifies rule sets according to ground object spectrum curves and spectral indices, optimizes spectral categories through refined and supplementary rules as well as modified thresholds. The Landsat 8 remote sensing images of islands (Jiapeng, Qi'ao) and coastal zones (Quanwan, Huidong) in the Pearl River Delta were chosen as the experimental data. The band reflectances and ground object spectrum curves before and after atmospheric correction process were contrasted. Classification results and accuracy of the MSRC algorithm were analyzed and compared with those of other six classification algorithms: the original SRC algorithm, Minimum Distance Classification (MDC) algorithm, Maximum Likelihood Classification (MLC) algorithm, Support Vector Machine (SVM) algorithm, Neural Network Classification (NNC) algorithm and spectral indices-based classification methods. The overall accuracy (OA) of MSRC algorithm using experimental data were respectively 87.66%, 82.38%, 77.67% and 80.05%, which were all higher than those of the original SRC algorithm, MDC, MLC and spectral indices-based classification methods, and closed to the accuracy of supervised algorithms (SVM and NNC) without the requirement of manually labelling the training dataset. MSRC performs well in land-cover type scenarios of islands and coastal zones on Landsat 8 multispectral remote sensing images.