Automatic mapping aquaculture in coastal zone from TM imagery with OBIA approach

IEEE GRSS; The Geographical Society of China<span class="MedBlackText">Aquaculture area monitoring is of great importance for coastal zone sustainable management and planning. This paper focuses on the development and assessment of an automatic approach for aquaculture mapping in coastal zone from TM imagery. The contribution mainly consists of three aspects: first, utilizes the Multi-scale segmentation/object relationship modeling (MSS/ORM) strategy on the object based image analysis (OBIA) of TM imagery; second, evaluates the effectiveness GLCM homogeneity texture feature on pond aquaculture area information extraction; third, compares the analysis results from three different approaches, namely pixelbased maximum likelihood classifier (MLC), One-step supervised OBIA with stand nearest neighbor (SNN) and MSS/ORM OBIA strategy. The final result shows that the MSS/ORM OBIA approach greatly improves the classification accuracy and has good potential for automatic pond aquaculture land mapping in coastal zone from TM imagery.</span

Land Use Change in the Major Bays Along the Coast of the South China Sea in Southeast Asia from 1988 to 2018

Bays are some of the core areas for marine economic development. The South China Sea coast is one of the most developed and dynamic places in the Asia-Pacific. In this study, we focused on the large bays surrounding the South China Sea. The techniques of image segmentation and supervised classification as well as image interpretation were used to acquire land-use data of 41 bays from 1988 to 2018. Then, we quantified the intensity and pattern of land-use and land-cover change during the two periods. Plantation land was the dominant agriculture land type as well as the second land use type after natural forest. Agriculture land cover increased from 29.8% to 40.9% and the growth was driven by plantation expansion. Deforestation was serious, including both natural forests and mangroves. Natural forest cover decreased by 31.6% and mangrove cover decreased by 16.2%. The vast majority of forest loss occurred in Sumatra and western Kalimantan. Commodity-driven deforestation for plantations was the major reason for forest loss

Expansion of construction land in the coastal areas : a case study of the Guangdong - Hong Kong - Macao Greater Bay Area, China

Unprecedented urbanization has taken place in the coastal areas, resulting in the degradation and loss of terrestrial and marine ecosystems. This study explored the spatial and temporal pattern of urbanization, taken the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as the study area. Our results showed that the GBA has experienced dramatic expansion of construction land with the area increasing from 2607.4 km 2 in 1980 to 8243.5 km 2 in 2018. The largest annual increase rate was 279.7 km2/year occurring from 2000–2010, followed by 149.1 km2/year from 1990–2000. Urban residential land has replaced rural residential land and become the main type of construction land since 2000. Throughout the study period, farmland made the dominant contributions to the expansion of construction land with a decreasing trend in the GBA. Construction land expansion was dominated by edge expansion in the past four decades. A clearer unimodal pattern of the area and a monotonic decrease of the density of new increased construction land were observed as the distance from the city center. We suggested the decision-makers to scientifically plan the distribution of construction land to avoid disorderly construction land sprawl in different distance intervals and protect multiple natural ecosystems to realize the local sustainable development

Sea Reclamation Status of Countries around the South China Sea from 1975 to 2010

As a way of turning sea into land for living space for humans, the actions of sea reclamation bring about significant benefits. Nevertheless, it is also an under-recognized threat to the environment and the marine ecosystem. Based on images in two periods, sea reclamation information of countries around the South China Sea was extracted from 1975 to 2010. The spatial state and driven forces of sea reclamation are then discussed. Results show that the overall strength of sea reclamation in the South China Sea was great. New reclaimed land added up to 3264 km2. Sea reclamation for fish farming was the main reclamation type and widely distributed in the whole area, especially on the coast from the Pearl River Delta to the Red River Delta, and the coast of Ca Mau Peninsula. Sea reclamation in China and Vietnam was rather significant, which occupies 80.6% of the total reclamation area. Singapore had the highest level of sea reclamation. New reclaimed land for fish farming holds a key role in China, Vietnam, and Indonesia, while new reclaimed land for construction and docks dominated in Malaysia, Singapore, and Brunei. Areas and use-type compositions of new reclaimed land in countries varied greatly due to the differences of economic factors, policy inclination, and landscapes in the respective countries

Automatic Extraction of Offshore Platforms in Single SAR Images Based on a Dual-Step-Modified Model

The quantity and location of offshore platforms are of great significance for marine oil spill monitoring and offshore oil-gas development. In the past, multiphase medium- and low-resolution optical or radar images have been used to remove the interference of ship targets based on the static position of a platform to extract the offshore platform, resulting in large demands and high image data costs. According to the difference in shape between offshore platforms (not elongated) and ships (elongated shapes) in SAR (synthetic aperture radar) images, this paper proposes an automatic extraction method for offshore platforms in single SAR images based on a dual-step-modified model. First, the two-parameter CFAR (constant false alarm rate) algorithm was used to detect the possible offshore platform targets; then, the Hough transform was introduced to detect and eliminate ship targets with linear structures. Finally, the final offshore platform was obtained. Experiments were carried out in four study areas in the Beibu Gulf basin and the Pearl River estuary basin in the northern South China Sea. The results show that the method has a good extraction effect in the above research area, and the extraction accuracy rate of offshore platforms is 86.75%. A single SAR image can obtain satisfactory extraction results, which greatly saves on image data cost

Research on Safety of Fisheries and Countermeasures in Nansha Islands

86-92In this study, a new accessibility model for spatial analysis and probability statistics are proposed to analyze the safety area and shipping route for fish ships. Accessibility index based on the least accumulative cost distance is proposed which is more suitable than Euclidean distance. Scene of control state is simulated to calculate the average access times between 19 islands or cays of Nansha and 8 surrounding seaports which are belong to 4 countries. The location of bases for fishery and transit are proposed

Novel Semi-Supervised Hyperspectral Image Classification Based on a Superpixel Graph and Discrete Potential Method

Hyperspectral image (HSI) classification plays an important role in the automatic interpretation of the remotely sensed data. However, it is a non-trivial task to classify HSI accurately and rapidly due to its characteristics of having a large amount of data and massive noise points. To address this problem, in this work, a novel, semi-supervised, superpixel-level classification method for an HSI was proposed based on a graph and discrete potential (SSC-GDP). The key idea of the proposed scheme is the construction of the weighted connectivity graph and the division of the weighted graph. Based on the superpixel segmentation, a weighted connectivity graph is constructed usingthe weighted connection between a superpixel and its spatial neighbors. The generated graph is then divided into different communities/sub-graphs by using a discrete potential and the improved semi-supervised Wu&ndash;Huberman (ISWH) algorithm. Each community in the weighted connectivity graph represents a class in the HSI. The local connection strategy, together with the linear complexity of the ISWH algorithm, ensures the fast implementation of the suggested SSC-GDP method. To prove the effectiveness of the proposed spectral&ndash;spatial method, two public benchmarks, Indian Pines and Salinas, were utilized to test the performance of our proposal. The comparative test results confirmed that the proposed method was superior to several other state-of-the-art methods

Impacts of Urbanization on the Ecosystem Services in the Guangdong-Hong Kong-Macao Greater Bay Area, China

Unprecedented urbanization has occurred globally, which has converted substantial natural landscapes into impervious surfaces and further impacted ecosystem services and functioning. In this study, we quantified the spatiotemporal patterns of urbanization and investigated the impacts of urbanization on the ecosystem service value (ESV) in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 1980 to 2018. The results show that the GBA has experienced extensive urbanization, with the urban area increasing from 2607.4 to 8243.5 km2 from 1980 to 2018. Zhongshan, Zhuhai, Dongguan, Shenzhen, and Foshan exhibited the top five highest urban expansion rates. Throughout the study period, edge expansion was the most dominant growth mode, with a decreasing trend, while infilling increased in the GBA. The total ESV loss induced by urban expansion in the GBA reached 40.5 billion yuan over the past four decades. The ESV loss due to the water body decrease caused by urbanization was the largest. Our study suggests that decision-makers should control new urban areas and protect water bodies, wetlands, and forests with high ESVs to promote the sustainable development of urban agglomerations