This PDF file contains the front matter associated with SPIE Proceedings Volume 8525, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

A passive and active L-band microwave sensor, Aquarius, developed by NASA to observe the global sea surface salinity (SSS) distribution, was launched on 10 June 2011. The SSS observed by Aquarius (v.1.3) was evaluated by comparison with in-situ salinity data from various sources. The Aquarius SSS generally agreed well with salinity measurements by Argo floats in moderate to high sea surface temperature (SST) regions. However, the Aquarius SSS highly deviated in low SST and high wind regions. Typical root-mean-squared difference between the Aquarius and in situ SSS observations under a condition of sea surface temperature higher than 5°C were 0.7 psu for snapshot observations and 0.35~0.4 psu for monthly 1° x 1° averages.

The Great East Japan Earthquake occurred at March 11, 2011 and caused massive tidal wave. The tsunami swept away a large quantity of rubble and vessels to the sea and they become so-called marine debris. To assess damage situation and protect marine environment, it is essentially required to investigate the status of those marine debris. The technique based on spaceborne synthetic aperture radar (SAR) can be a strong candidate to achieve this ultimate goal, because of its wide observation area and higher resolution with flexible operability: regardless of the day and night and regardless of the weather. We have monitored marine debris on huge amount of spaceborne SAR imagery right after the great disaster and investigated an effective observation of marine debris to predict future direction. In this paper, we firstly define three types of debris as large debris, small debris, and cluster by considering how marine debris looks like on the SAR imagery. Then, an automatic but accurate detection and classification of a large amount of debris on SAR imagery is proposed. Based on those results, resolution and swath width for efficient marine debris monitoring are obtained. Velocity of marine debris is additionally estimated from multi-temporal SAR images to derive optimum swath width.

Ship detection in marine area is an important task for the security and monitoring of coastlines. In this paper, a new physically-based method has been developed to detect ships in marine area with polarimetric SAR data. The method is based on the difference of the scattering mechanisms between sea clutters and ships. Experiments, accomplished over Single Look Complex (SLC) RADARSAT-2 Quad Mode data, demonstrate the effectiveness of the method for ship detection purposes. The proposed method provides a better performance compared with HH-CFAR detector, SPAN detector, and widely used PWF detector.

With the globalization there is an increasing degree of concern on the ship traffic monitoring. Civilian ship classification is an important research area, as it can help to improve sea traffic surveillance and control activities. By making use of the new generation SAR satellites like COSMO-SkyMed, civilian ship classification in high resolution SAR images is a hotspot and preceding problem in SAR applications. This paper presents a ship classification method that uses single-pol COSMO-SkyMed images to categorize civilian ships into three types, including bulk carriers, container ships and oil tankers. The experimental results based on ship structure features show that the whole classification accuracy is above 80%.

This paper presents a novel normalized scanning algorithm for detecting ship wakes in SAR (Synthetic Aperture Radar) images. Unlike most of wake detection algorithm is based on Radon transform, the proposed algorithm is based on normalized scanning. The technique takes advantage of the displacement between the ship and perspective wake in azimuth direction. The proposed algorithm can determine the offset in azimuth direction and the movement direction of ship. Then we can get the velocity vector of the ship. Although the computational complexity is very small, the normalized scan algorithm is robust in high noise environment. Experiment work outs are carried over in real SAR images. Results show that the ship wake detection based on normalized scan is better than traditional technique.

The overall objective of this study is to gain an improved understanding of the sea surface temperature (SST), sea surface wind speed (WS) and sea surface wind direction (WD) variability in the Eastern part of Indonesian Sea in response to the seasonal and inter-annual variations. The statistical properties and monthly average data for the 10-year period from December 1999-November 2009 in the Eastern part of Indonesian Sea are investigated by integrated use of TRMM Microwave Imager (TMI) of the Tropical Rainfall Measuring Mission (TRMM) and SeaWinds on the Quik Scatterometer (QuikSCAT) satellite remote sensing data. The time series shows a high variability (unstable areas) of SST and WS in the southern equatorial (120o-135oE and 3oS-18oS) in contrast with the stable SST condition around equatorial and other regions. This condition related to the effect of the Indonesian throughflow (ITF) and the prevailing winds in the Indonesian inland seas, which is WD varies seasonally. North-south (zonal) change of SST and WS are observed. These overall analyses confirm several characteristics of the Eastern part of Indonesian Sea.

Hyperspectral remote sensing reflectance (Rrs) was measured by a TriOS radiometer system along the East Coast of New Caledonia during the R/V Alis 03-13 October 2011 CALIOPE cruise. The TriOS system consists of radiance and irradiance sensors measuring in the spectral range 320-950 nm, at a spectral resolution of about 10 nm (sampled by every 3.3 nm), and within a 7-degree field-of-view for the radiance sensor. The method developed by Froidefond and Ouillon (2005) was used to determine Rrs, i.e., the radiance sensor was mounted on a small raft to measure upwelling radiance just below the surface, and Rrs was calculated by normalizing water-leaving radiance with downward solar irradiance measured on the ship deck. Inherent Optical Properties (IOPs), i.e., absorption coefficients of phytoplankton and detritus+dissolved substances (a_ph and a_dg, respectively), and particulate backscattering coefficient (b_bp) were estimated from the hyperspectral Rrs data by applying linear matrix inversion (Hoge and Lyon, 1996). The IOP inversion algorithm was adapted to MODIS data and applied to Level 1b imagery at 500 m resolution to demonstrate the feasibility of regular IOP monitoring from space in the study area. Local characteristics of the IOP spectra were used for the candidate spectra in the algorithm. The estimated MODIS Rrs and IOPs were evaluated using TriOS Rrs and in-situ IOP measurements obtained concomitantly during the cruise.

Total suspended matter concentration (TSM) algorithms for ocean color sensors use empirical relationship between satellite-retrieved remote sensing reflectances and TSM. However the estimated-TSM has no enough accuracy because the reflectance at visible bands has error after atmospheric correction in high turbid area. The purpose of this study is to estimate simultaneously total suspended matter concentration, aerosol optical thickness and Angstrom exponent using three bands at near infrared from MODIS/Aqua and SeaWiFS data. We applied this scheme to MODIS/Aqua and SeaWiFS data, and satellite-derived TSM were compared with ship-observed TSM dataset in Yellow Sea and East China Sea. RMSE of TSM was 0.338 in log-log coordinates and correlation coefficient was 0.850. The scheme was better than Clark’s or Tassan’s TSM algorithm.

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

The Sea-Viewing Wide Field-of-view Sensor (SeaWiFS)-derived chlorophyll-a (Chl-a) data within 13-year full SeaWiFS mission were analysed to understand the spatial and temporal variations of phytoplankton biomass in the Malacca Straits. Other data from multi-sensors were also exploited to understand probable factors governing SeaWiFS Chl-a variation. SeaWiFS Chl-a showed remarkable seasonal variation which was high and low during northeast monsoon and southwest monsoon, respectively, especially in the north and middle regions of the Malacca Straits. Analysis results on the long-term trend showed that SeaWiFS Chl-a has experienced long-term increase especially in the south region of the Malacca Straits. In the north region on the other hand, SeaWiFS Chl-a was relatively stable within the SeaWiFS full mission period. The observed seasonal variation and long-term increasing trend of SeaWiFS Chl-a in the south region of the Malacca Straits however might not be associated with real phytoplankton biomass. High suspended sediment due to both bottom sediment re-suspension and sediment loaded from the land by river discharge might lead to incorrect Chl-a retrieval by SeaWiFS ocean color sensor. SeaWiFS Chl-a spatial and temporal variations in the north region of the Malacca Straits seemed to be more determined by wind-driven physical forcing such as water column mixing and/or upwelling.

The suitability of a handheld spectrometer and ASTER satellite data for monitoring water quality in coastal waters of Sri Lanka and inland waters of Japan was tested in November 2010 to March 2012. In-situ Chlorophyll-a (Chl-a), turbidity, total suspended solid, secchi depth and reflectance data were measured at ASTER overpass times in Negombo estuary, Trincomalee bay, Puttalam and Chilaw lagoons, Sri Lanka, and in Lake Senba and Lake Kasumigaura, Japan. ASTER based Chl-a retrieval algorithms were developed support with in-situ Chl-a and MODIS OC3 Chl-a. The original MODIS Chl-a and the in-situ Chl-a were regressively analyzed for determination of a MODIS Chl-a correction equation because it may overestimate in tropical coastal waters. Then, three ASTER VNIR band ratios were compared for correlation with the corrected MODIS Chl-a and in-situ Chl-a. Finally, the regression equation of the ASTER band ratio, B1/B2, with highest correlation was used for generation of high-resolution Chl-a distribution maps. Significant correlation between the ratio of the reflectance peak at 705 nm and the Chl-a absorption at 678 nm and the in-situ Chl-a content was observed and these reflectance ratios were used to establish spectrometric Chl-a estimation algorithms. The proposed algorithms successfully determined localized environmental effects in the study areas. ASTER-based high resolution Chl-a distribution maps will be derived more precisely by further correction of these algorithms, which will be useful in mitigate impacts of the environment change in those coastal and inland water environments.

The assessment of lemuru fish (Sardinella lemuru) using remote sensing and Geographical Information System (GIS) has provided preliminary information on the habitat of lemuru fish at the South waters of Malang Regency, Indonesia. Lemuru fish catch data, mangrove mapping, Sea Surface Temperature (SST) and chlorophyll-a concentration derived from MODIS/Aqua images have been used in this study. The average of SST during the study was 26.1 °C, the highest average was on December and August was the lowest. The average of chlorophyll-a concentration was 0.55 mg/m3, July was the highest and the lowest concentration of chlorophyll-a was on March. Most of the lemuru fish migrated to the west part of Malang waters during northwest monsoon (December-February), and moved toward eastern part during transitional (March-April-May). In contrast, on the southeast monsoon (June-August), lemuru spread across Malang waters. Habitat suitability of lemuru around coastal waters of Malang Regency related to their migration has different criteria for each month depend on the oceanographic factors and primary productivity. Based on the levels of habitat suitability, lemuru predicted to spawn on June. Sumbermanjing area was the most suitable area (72.39%). Lemuru moved away from Malang waters during transitional until the beginning of northwest monsoon. Primary productivity in coastal waters around Sumbermanjing increased in the southeast monsoon. It represented by January (0.7 mg/m³) in the northwest monsoon and increased reaches 3 mg/m3 in the southeast monsoon on July. It was followed by the increasing of lemuru catch.

The chlorophyll-a concentration (Chla) of surface waters is commonly retrieved from space using an empirical polynomial function of the maximum band ratio (MBR), i.e., the maximum ratio of remote sensing reflectance in selected spectral bands in the visible. Recent studies have revealed significant deviations in the relation between MBR and Chla across the oceans. The present work aims at accessing the main sources of MBR variability across the Southern Atlantic and South-east Pacific, using in situ data. The data was collected at 19 bio-optical CTD stations and 40 flowthrough stations during a cruise onboard the R/V Melville, from South Africa to Chile (February-March, 2011). The MBR was derived from modeled remote sensing reflectance using absorption and backscattering measurements. The second order MBR variations (MBR*) were obtained after subtraction of a global polynomial fit for CChla and Chla biases. Multivariate analyses were used to explain the variations with bio-optical properties and phytoplankton pigments. Chla overestimations were associated to high specific phytoplankton absorption (0.73), specific particle backscattering coefficient (0.42) and colored dissolved and particle organic matter (CDM) absorption normalized by non-water absorption (0.38), and vice-versa. The overestimations occurred at stations with dominance of small picoplankton, high concentration of bacteria, and high CDM, while underestimations were in microplankton dominated waters and low CDM. The results reveal important relations of the MBR* with the specific coefficient and associated phytoplankton community structure.

Coral reefs support enormous diversity of species and economical values for human being. However, they are seriously declining at an alarming rate in all tropical oceans. In 2007, one of environmental negative impacts, sea surface temperature rise, was triggered massive coral bleaching and consequential coral mortality in Japan. This study aims to detect massive coral bleaching with change detection by multispectral sensor images and validate the results based on reference materials at a study area - Sekisei Lagoon. It is located between Iriomote-island and Ishigaki-island in Okinawa, is the most abundant coral reef species in Japan. To detecting coral bleaching uses bottom-typed index by Lyzenga (1978) generates constant index values from same habitats without affect by the water depth. After processing several corrections of data products, bleaching areas are extracted with change detection from different time periods. The results are spatially and temporally validated with referenced materials though a report and a websites under the Ministry of Environment in Japan. As a result, the results are determined to detect coral bleaching by the process.

Coral reefs worldwide are now facing so great threat due to various impacts that their monitoring is urgently required for conservation and management. To understand status of coral reef ecosystem and find out indicator fish species for health of ecosystem, mapping seabed habitats with remote sensing and in situ visual survey of fish assemblage by snorkeling were conducted in coral reefs in Spermonde Archipelago, Indonesia. ALOS AVNIR-2 multi-band imagery on 14 October 2010 was analyzed to map four habitats: live coral, dead coral, seagrass and sand-rubble. Groundtruth data were obtained using towed video camera and sidescan sonar in May and June 2011. Depth-Invariant indices (DI-indices) based on ratios of radiance values between bands were applied as a water column correction. Overall classification accuracy in Tau-coefficient of mapping with the DI-indices (0.66) didn’t differ significantly (p<0.05) from that with the radiance values (0.63). Concerning visual fish survey, 12 fish groups were identified and numbers of individuals belonging to each group were counted along a transect of approximately 100m at 18 sites. We calculated Spearman’s rank correlation between abundance (Ind. /100m) of every fish group along a transect and the ratio of each habitat area mapped with DI-indices inside the circle with 50m-diameter which includes the fish transect. We detected significant correlations between abundance of five fish groups and specific habitats, especially butterflyfish and live coral. This result corresponds to the past reports that butterflyfish was a good indicator of healthy corals, suggesting meaningfulness of studying relationships between fish abundance and spatial distribution of habitats in larger scale.

Seaweed forests are important habitats for many fishery species. However, decrease in seaweed forests is reported in all over Japan. Mapping and monitoring seaweed forest distribution is necessary for understanding their present status and taking measures for their conservation. Since traditional diving visual observation is not efficient for large scale mapping, alternative method is required. Although satellite remote sensing is one of the noteworthy methods, only a few studies have been conducted probably due to two main problems about mapping seaweed forests by remote sensing. The first one is a difficulty to collect field truth data. The second one is a light attenuation effect in water column which makes analysis more difficult. We applied an efficient method to overcome these two problems. We selected the seaweed beds off Shimoda in Izu Peninsula, Japan, as a study area. An IKONOS satellite image was used for analysis because its high spatial and radiometric resolutions are practical for seaweed mapping. We measured spectral reflectance profiles of seaweed and substrates in the study area. The result revealed effective wavelength bands for distinguishing seaweeds from other substrates. Truth data for satellite image analysis and evaluation were collected in the field using the boat and an aquatic video camera. This method allowed us to collect many truth data in short time. Satellite image analysis was conducted using radiometric correction for water column and maximum likelihood classification. The overall accuracy using error matrix reached 97.9%. The results indicate usefulness of the method for seaweed forest mapping.

In this study, image contrast between extracted laver cultivation area and background water was extensively compared using various parameters that can be calculated by dual- and quad-polarization (fully-polarimetric) synthetic aperture radar (POLSAR) data. In our test site of laver cultivation in Tokyo Bay, every year starting from October, laver cultivation nets are placed at approximately 10-20 cm below the sea surface with supporting floats with laver spores attached to the nets, grow during winter, and the grown laver is harvested in next April. Through this process, the nets are sometimes placed above the sea surface to promote photosynthesis. When the nets are placed underwater, the areas become effectively shallow water, and small-scale waves, that are the principal scatterers, are damped, resulting in reduced radar backscatter. This difference from surrounding water can appear in SAR data. Each parameter derived from Pauli decomposition, eigenvalue analysis, coherence analysis, and four-component scattering power decomposition (4-CSPD) has distinctive characteristics and react to different backscatterers differently. Contrast comparison was made using those parameters using the L-band quad-polarization data acquired by Phased-Array L-band SAR (PALSAR) on board Advanced Land Observing Satellite (ALOS) and the X-band dual-polarization data acquired by TerraSAR-X, and experimental results showed that the contrast can be improved using multi-polarization data than using single-polarization data. It has also been found that entropy performs better among dual-polarization methods, and the surface scattering component calculated from 4-CSPD exhibits higher contrast than any other parameters from quad-polarization data.

Seagrass canopy plays a critical role in the ecological functions of coastal zones. They supply nursery and juvenile habitats for fisheries, stabilize sediment and provide direct food for dugongs and green turtles. Lap An is the semienclosed lagoon in the South of Thua Thien Hue province with a large area of mangrove and seagrass. This lagoon significantly supports local aquaculture, and is highly important nursery for economic fisheries. However, the reclamation activities of local farmers have disturbed the aquatic habitats, and diminished the seagrass canopy (more than 60% has disappeared from the lagoon). The objective of this research is to detect the distribution of the seagrass, and propose a seagrass-based protected area for conservation purposes. ALOS AVNIR 2 data was utilized to detect the scattered small patches of seagrass. The use of water column correction, principle component analysis, neural network algorithm and ground control points in the field were undertaken to enhance the classification accuracy of the study. This research provides a new approach for detecting seagrass meadows, and contribute toward better integrated management of the coastal zones.

Seagrass beds/meadows are very productive ecosystems with high biodiversities. However, they have been degraded under high pressures of human activities. Combining depth-invariance index and ground-truthing, distribution of seagrass beds in Cam Ranh Bay was identified by analyses of multi-remote sensing images such as LANDSAT, SPOT and ALOS AVNIR-2. Although coverage of seagrass meadows was1178 ha, the seagrass meadows were being degraded by illegal fishing methods, aquaculture and discharges from industries and living domestics. The reducing ratio of seagrass coverage has been increased in recent years. While the depth-invariance index method would help to detect the areas of seagrass beds, this method requires combination of field trip and absorption library methods to increase classification accuracy. Final maps of the status and changes of seagrass beds could help to integrate the sustainable development of economy with protection of natural resources.

Mangroves that appear in the inter-tidal zones along the coast in most tropical and semi-tropical countries play a vital role in coastal zones and can defend against the impacts of tsunamis. Nevertheless, these forests are under severe threat because of high population growth, weak governance, poor planning, as well as uncoordinated economic development. Hai Phong city is located on the Northern coast of Vietnam where the mangroves are distributed between zone I and zone II among the four mangrove zones in Vietnam. This city is vulnerable to rising sea levels and tropical cyclones, which are forecasted to become more severe in coming next decades. The objectives of this research were to analyze the current status of mangroves using different ALOS sensors in Hai Phong, Vietnam in 2010 and compare the accuracy of the post satellite image processing of ALOS imagery in mapping mangroves. A combination of object-based and supervised classification was used to generate the land cover maps. The results of this research indicate that the total area of mangrove was approximately 2,549 hectares and mangrove is present in the five coastal districts in Hai Phong. The findings of this research showed that ALOS AVIR-2 provides better accuracy than ALOS PALSAR. This research indicates the potential of utilizing image segmentation associated with supervised method for both optical and SAR images to map mangrove forests in coastal zones

The coastline of Cambodia stretches along the Gulf of Thailand including 69 islands. It supports rich diversity of marine species. Distributions of habitats including mangroves, coral reefs and seagrass beds along the pristine Cambodian coast still remains unknown compared to neighboring countries, Thailand and Vietnam. Cambodian seagrass beds form habitats with rich biodiversity and economical value through marine ecosystem services playing as a key role against climate change by reserving large amount of carbon. However, the general status of these seagrass habitats is poorly researched and documented. Satellite image of Advance Visible and Near Infrared Radiometer type 2 (ALOS AVNIR-2) with high resolution (10×10m) provides good information for seagrass habitat mapping. Study site was selected around Rabbit (Koh Tonsay) Island with area of 2 km². The objectives of this study are (1) to know spatial distribution of seagrass beds around this island by ground survey and (2) map seagrass beds using the ALOS AVNIR-2 image with ground truthing data. Ground truth survey was conducted in June 2011. Surveys along three transect lines revealed 8 species of seagrasses belonging to Hydrocharitaceae (4 species) and Cymodoceaceae (4 species) around the island. We analyzed ALOS AVNIR-2 taken on 22 December 2009 to map distribution of seagrass beds around Koh Tonsay Island. Results showed that remote sensing using ALOS AVNIR-2 data provides a practical tool for mapping seagrasses beds around the island and information for future management and conservation of seagrass beds in Cambodia.

The coral ecosystem is sensitive to environmental changes thus accurate, up to date information on their status is critical for effective management of these important marine resources. However, environments containing these habitats are challenging to map due to their remoteness, extent and costs of monitoring. In this research, the capabilities of satellite remote sensing techniques combined with in situ data were assessed to generate coral habitat map of Lang Tengah Island, Terengganu, Malaysia. Several classification techniques were utilized in identifying coral distribution to assess their ability to map different type of benthic habitat associated with coral reefs. Five classifiers were used to classify the study area mainly, Parallelepiped, Minimum distance, Maximum likelihood, Fisher and K-Nearest Neighbour. Using the same training data sets to evaluate their effectiveness, results from the classification shows that each method produced different accuracy based on bottom type. Utilizing the strength of each classifier this study was able to increase per class accuracy of the habitat map through several image processing techniques mainly majority voting, simple averaging and mode combination. Results show that by utilizing these ensemble techniques for classifying benthic habitat the accuracy produced was higher than conventional supervised techniques.

Seagrass beds play important roles for coastal ecosystems as an ecosystem engineer and also as a habitat for fish and mollusks as spawning, nursery and feeding grounds, and provide us important ecological services. On 11 March 2011, huge tsunami hit Sanriku Coast, Japan, after the big earthquakes occurred in Northwestern Pacific Ocean. Seagrass beds were distributed on sandy or muddy bottom in Shizugawa Bay, Sanriku Coast. Thus, remote sensing research was conducted to evaluate impact of the tsunami on seagrass bed in Shizugawa Bay, Sanriku Coast. GeoEye-1 multi-band imageries taken on 4 November 2009 and 22 February 2012 were analyzed to map seagrass beds before and after the tsunami, respectively. Analysis of the former imagery showed seagrass beds were distributed in sheltered bottom against waves along the coast corresponding to seagrass distributions obtained through inquiry to fishermen and references on seagrass bed distributions before the tsunami. Analysis of the latter imagery indicated that seagrass bed distributions on 22 February 2012 were less than on 4 November 2009. Seagrass beds in the bay head disappeared while some seagrass beds remained behind the points along the north coast. This was verified by the field survey conducted in October 2011 and May and October 2012. Since the tsunami waves propagated into the bay along the longitudinal axis of the bay without crossing both sides of the bay, they produced only big sea-level changes during the propagation along the both sides from the center to the bay mouth. Their energy is concentrated the bay head and removes seagrass with sand and mud substrates. On the other hand, the tsunami higher than 12 m could not completely destroy seagrass beds due to topographic effect protecting seagrass from strong force by the tsunami. Thus, all seagrass weren’t destroyed completely in Shizugawa Bay even by the hit of the huge tsunami.

Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral sensor system. It will be launched in 2015 or later as one of mission instruments onboard JAXA's Advanced Land Observation Satellite 3 (ALOS-3). HISUI will consist of a hyperspectral imager and a multispectral imager with 30 m and 5 m spatial resolution and 30 km and 90 km swath, respectively. In order to characterize capability to detect seaweed beds of HISUI multispectral data with 5 m spatial resoution, we comprared classification results between ALOS/AVNIR-2 with spatial resolution of 10 m and simulation data of HISUI produced from WorldView-2. Study site was seletced in Oita Prefecture in Kyushu Island, Japan, where seaweed beds were broadly distributed along the coast. We used AVNIR-2 data taken on 20 February 2007 and simulation data produced from WorldView-2 taken on 18 April 2010. Supervised and unsupervised classifications were applied to these data sets. Miss-classification of analysis using AVNIR-2 was identified in deep waters in offshore waters. Since radiometric resolution of AVNIR-2 is 8 bits, it is considered that low radiometric resolution causes missclassification. Spatial resolution of HISUI multiband data with 5 m permits to detect seaweed beds clearer. Precision of classification using HISUI simulation data was about 90% and 10% higher than that using AVNIR-2. Thus HISUI multiband data are suitable for mapping seaweed beds in coastal waters.

Refractivity happens due to stratification in the lower boundary layer over oceans due to variability of moisture, temperature, wind and sea surface temperature which collectively may lead to generate evaporation duct. The evaporation duct has a significant impact on the spread of electromagnetic waves in the atmosphere over oceans both from the meteorological and military point of view. This ducting sometimes supports normal propagation of radar signals and sometimes may cause distortion and attenuation of signals depending on the height of evaporation duct. This leads to over-estimation and under-estimation of rainfall by weather radar meteorologically and for other targets militarily. The aim of this study was not only to locate evaporation duct height but also to check the efficiency of Weather Research and Forecasting Model (WRF) and Babin’s model so that results may be used in applying correction measures for precise identification of targets by radar. In this study by utilizing the high vertical resolution of WRF for the simulation of different meteorological parameters, the Babin’s method was used for calculating the evaporation duct height over South China Sea for the two months, April and July. Very clear duct heights were calculated at different areas over sea in different time domains. Study reveals that maximum height existed in the month of April although July was rich with different EDHs in different regions in contrast to April. It was found that in most of the cases EDH was higher or maximum when relative humidity was comparatively lower and air temperature and wind speed were comparatively higher. This study paves a way for futuristic study of evaporation duct monitoring and forecasting by assimilation of remote sensing data especially through that of Geostationary satellites by incorporating verification measures from radar.

Seagrasses, marine flowering plants, are widely distributed along temperate and tropical coastlines of the world. Seagrasses have key ecological roles in coastal ecosystems and can form extensive meadows supporting high biodiversity. Till now, fourteen seagrass species belonging to four families were found in Vietnam: Halophila beccarii, H. decipiens, H. ovalis, H. minor, Thalassia hemprichii, Enhalus acoroides, Ruppia maritima, Halodule pinifolia, H. uninervis, Syringodium isoetifolium, Cymadocea rotundata, C. serrulata and Thalassodendron ciliatum. A total area of seagrass beds in Vietnam is estimated to be approximately 17000 ha by satellite images and GIS technology. In recent years, the distribution areas and densities of seagrass beds in Vietnam have been serious decreased compared with those 10-15 years ago. The decline level depended on the impacts by the natural process, the economical activities and the conservation awareness of local people. Thus, it is different at each coastal area. Generally speaking, the distribution areas and densities of seagrass beds were decreased by more than 50%. Seagrasses on tidal flats in some areas such as Quang Ninh, Hai Phong, Phu Quoc seem to be nearly lost. The distribution areas of seagrass beds in 2009 at Tam Giang-Cau Hai lagoon and Cua Dai estuary was decreased by 50-70% of those in early 1990s.

The 2011 off the Pacific coast of Tohoku earthquake (Mw = 9) was one of the most devastating earthquakes in Japanese history. The extremely large and widespread tsunami it generated caused a large amount of debris to flow into the Pacific Ocean. It is important to understand debris flow in the ocean for both environmental research and international relations. In this study, tsunami debris was monitored by satellite remote sensing. As a first step, we propose a method for identifying debris floating on turbid sea areas through thin clouds using two-dimensional scatter diagrams for MODIS spectral bands. Characteristic regions in the images are effectively separated by using the scatter diagram to identify six regions (land, coastal areas, debris, cloud, turbid sea, and clear sea). We report initial results of monitoring debris floating in the Pacific Ocean.

A global, 13-year record of photo-synthetically available radiation (PAR) at the ocean surface (9-km resolution) has been generated from SeaWiFS, MODIS-Aqua, and MODIS-Terra data. The PAR values are essentially obtained by subtracting from the solar irradiance at the top of the atmosphere (known) the solar energy reflected by the oceanatmosphere system (satellite-derived) and absorbed by the atmosphere (modeled). Observations by individual instruments, combinations of two instruments, and three instruments are considered in the calculations. Spatial and temporal biases between estimates from one, two, or three instruments are determined and corrected, resulting in a consistent time series for variability studies. Uncertainties are quantified on daily, weekly, and monthly time scales for the various instrument combinations from comparisons with in situ measurements. The correlative behavior of PAR, sea surface temperature, and chlorophyll concentration in the Equatorial Pacific is examined. PAR monitoring will continue with current and future satellite ocean-color sensors, in particular VIIRS, and the methodology will be extended to generating UV-A and UV-B irradiance.

Coral reefs play important ecological services such as providing foods, biodiversity, nutrient recycling etc. for human society. On the other hand, they are threatened by human impacts such as illegal fishing and environmental changes such as rises of sea water temperature and sea level due to global warming. Thus, it is very important to monitor dynamic spatial distributions of coral reefs and related habitats such as coral rubble, dead coral, bleached corals, seagrass, etc. Hyperspectral data, in particular, offer high potential for characterizing and mapping coral reefs because of their capability to identify individual reef components based on their detailed spectral response. We studied the optical properties by measuring in situ spectra of living corals, dead coral and coral rubble covered with algae. Study site was selected in Spermonde archipelago, South Sulawesi, Indonesia because this area is included in the highest diversity of corals in the world named as Coral Triangle, which is recognized as the global centre of marine biodiversity and a global priority for conservation. Correlation analysis and cluster analysis support that there are distinct differences in reflectance spectra among categories. Common spectral characteristic of living corals, dead corals and coral rubble covered with algae was a reflectance minimum at 674 nm. Healthy corals, dead coral covered with algae and coral rubble covered with algae showed high similarity of spectral reflectance. It is estimated that this is due to photsynthetic pigments.

Seaweed beds are very important for abalones and sea urchins as a habitat. In Sanriku Coast, these animals are target species of coastal fisheries. The huge tsunami hit Sanriku Coast facing Pacific Ocean on 11 March 2011. It is needed for fishermen to know present situation of seaweed beds and understand damages of the huge tsunami on natural environments to recover coastal fisheries. We selected Shizugawa Bay as a study site because abalone catch of Shizugawa Bay occupied the first position in Sanriku Coast. To evaluate impact of tsunami on seaweed beds, we compared high spatial resolution satellite image of Shizugawa Bay before the tsunami with that after the tsunami by remote sensing with ground surveys to know impact of the tsunami on seaweed beds. We used two multi-band imageries of commercial high-resolution satellite, Geoeye-1, which were taken on 4 November 2009 before the tsunami and on 22 February 2012 after the tsunami. Although divers observed the tsunami damaged a very small part of Eisenia bicyclis distributions on rock substrates at the bay head, it was not observed clearly by satellite image analysis. On the other hand, we found increase in seaweed beds after the tsunami from the image analysis. The tsunami broke concrete breakwaters, entrained a large amount of rocks and pebble from land to the sea, and disseminated them in the bay. Thus, hard substrates suitable for attachment of seaweeds were increased. Ground surveys revealed that seaweeds consisting of E. bicyclis, Sargassum and Laminaria species grew on these hard substrates on the sandy bottom.