AN INSTRUCTURAL SYSTEM MODEL OF COASTAL MANAGEMENT TO THE WATER RELATED HAZARDS IN CHINA

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Flood simulation in the coastal lowlands of northern Jiangsu,China

The coastal lowlands in northern Jiangsu Province, China, is characterized by low relief and low water surface gradient in streams. The flooding stages are commonly lower than the high-tide level and the tidal range is relatively small. All these factors prohibit rapid discharge of floodwater and make the flood regimes here extremely sensitive to the sea level rise. The 1991 Plum Rain was examined, when precipitation was significantly higher than normal. The one-dimensional open-channel non-conservative flow model was used to simulate the stream flow in the channel network of studied area. GIS technology was used to delineate the maximum in undated area by analyzing the DEMs.     

Flood simulation in the coastal lowlands of northern Jiangsu, China

The coastal lowlands in northern Jiangsu Province, China, is characterized by low relief and low water surface gradient in streams. The flooding stages are commonly lower than the high-tide level and the tidal range is relatively small. All these factors prohibit rapid discharge of floodwater and make the flood regimes here extremely sensitive to the sea level rise. The 1991 Plum Rain was examined, when precipitation was significantly higher than normal. The one-dimensional open-channel non-conservative flow model was used to simulate the stream flow in the channel network of studied area. GIS technology was used to delineate the maximum in undated area by analyzing the DEMs.     

Flood intensity and land evaluation in the Cauvery delta,Tamil Nadu,applying modern remote sensing techniques

An area of about 7500 km² covering Cauvery delta has been studied from airphotos (1:60,000), Landsats (1:250,000) and survey of India topographic sheets (1:50,000) with a view to delineate various landforms, soils, land use, hydromorphic units, drainage, and flood intensity of the delta. The delta is composed of mainly ancient channels, delta p ains, fossil islands, levees, beach ridges, mangroves marshes and coastal dunes. The various soil types are clayey soils, silty soils, silty loams, sandy loams, coastal sands and alkaline clays. Paddy and sugarcane are dominant crops. The old channels are found to be zones of high ground water potential. The growth of delta seems to be from south to north with twelve abandoned meander lobes and three delta fronts with gradual influx of material into Bay of Bengal. The old rivet courses lying parallel to the present active Coleroon river in third stage of the growth of the delta seem to be severely affected by floods. Moderate to low growth is noticeable in the second stage of the of the delta. The oldest river course which debouched into Bay of Bengal near Adirama-patnam is less affected by floods. The delta plains, fossil islands, disturbed ridges and beach ridges are unaffected. Basing on landforms, soils, land use, hydrogeomorphology and flood intensity the land capability of the delta has been evaluated. About seven classes of land are interpreted.     

基于GIS/AHP集成的浙江省洪涝灾害风险评估

将GIS技术引入洪涝灾害风险评估,可以弥补传统方法评估结果空间化显示不足的缺点。本文针对浙江省洪涝灾害的发生特点,从危险性和易损性两方面选择了浙江省洪涝灾害的影响因素,包括降雨量、地形、河网密度、人口密度和耕地百分比等因子。运用GIS空间分析技术对各因子进行空间化,结合层次分析法（AHP）确定各影响因素的权重,进行浙江省洪涝灾害风险评估和制图,并基于SuperMap iObjects平台设计与开发了浙江省洪涝灾害风险评估系统。研究结果表明：浙江省发生洪涝灾害的风险普遍偏高,高风险区域位于浙北和浙东南的沿海地带,较高风险区域位于浙东、浙南和浙北地区及金衢盆地中间地区,中等风险区位于浙南的西面、浙北及浙西地区。本文分析结果可为浙江省洪涝灾害预防和管理提供决策依据。     

海南岛海岸带土地利用强度与生态承载力分析

随着海南省进一步开放发展,海岸带区域的土地利用强度逐渐加强,生态保护需求日益增强。利用4期（1990、2000、2009、2015年）海岸带土地利用分类数据,研究海岸带土地开发利用强度,并分析了其生态承载力。结果表明：①耕地和林地是海南岛海岸带地区的主要土地类型。②25年间,海南岛海岸带土地利用强度整体较高且逐年上升,2000—2009年土地利用强度增速最高,达2.03%;海口市和澄迈县土地利用强度4期均值最大,分别为300.5和286.1。③25年来海南岛海岸带生态状况呈下降趋势,57%的海岸带市县实际生态承载压力增长了1倍以上。     

A shoreline change analysis along the coast between Kanyakumari and Tuticorin,India, using digital shoreline analysis system

The shoreline is one of the rapidly changing landforms in coastal areas.They are the key element in coastal GIS and provide the most information on coastal land form dynamics.Therefore,accurate detection and frequent monitoring of shorelines is very essential to understand the coastal processes and dynamics of various coastal features.The present study is to investigate the shoreline changes along the coast between Kanyakumari and Tuticorin of south India(where hydrodynamic and morphologic changes occur continuously after the December 2004 tsunami)by using Digital Shoreline Analysis System(DSAS),an extension of ArcGIS.Multidate IRS and Landsat Satellite data(1999,2001,2003,2005,2007,and 2009)are used to extract the shorelines.The data is processed by using the ERDAS IMAGINE 9.1 software and analyzed by ArcGIS 9.2 workstation.The rates of shoreline changes are estimated by three statistical methods,namely,End Point Rate(EPR),Linear Regression Rate(LRR),and Least Me-dian of Squares(LMS)by using DSAS.The study reveals that most of the study area has undergoing erosion.Both natural and an-thropogenic processes along the coast modify the shoreline configuration and control the erosion and accretion of the coastal zones.The coastal zones along the estuary have experienced accretion due to the littoral processes.The zones with headlands have more eroded than other zones along the study area.The study also shows that the coastal zones where sand is mined have relatively more rate of erosion than that of the other zones.Improper and unsustainable sand mining may also lead to severe erosion problem along this area.The shoreline change rates are altered by various geological processes along the coast.Thus,the present study implies that proper beach filling and nourishment projects should be made in the study area to save from hazards.It also indicates the advantage and suitability of DSAS to assess the shoreline changes compared with the traditional manual shoreline change analysis and prom-ising its applications for coastal zone management in other regions.     

Identifying coastal towns and small cities in Denmark using global population data to support climate change adaptation

ABSTRACT

Coastal settlements face many hazards from climate change. Consequently, there has been extensive focus on developing and implementing adaptation. However, these efforts have prodominantly centred on larger cities. Coastal towns and small cities (urban areas between 1000 and 100,000 people) have received little attention, despite experiencing a number of barriers to adaptation. The absence of information on the global scale of the adaptation challenge within coastal towns and small cities may have contributed to these settlements being overlooked. This paper develops a method that can be used to estimate the numbers, sizes, and locations of coastal towns and small cities worldwide from global population data (Global Human Settlement data). Denmark is used as a pilot for this method with settlements over 1000 people classified with relatively high accuracy. The method developed here represents a potentially fruitful approach to supporting coastal adaptation, as coastal towns and small cities are identifiable globally, they can be classified into types. This will support an assessment of their risk to coastal hazards, and could facilitate knowledge and practice sharing between similar coastal towns and small cities.     

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.     

Use of geo-spatial information and technologies for analyzing morphological changes in the Greater Visakhapatnam coastal region,east coast of India

The objective of this study was to investigate the land use/land cover, landforms, shoreline and coastal regulation zone (CRZ) changes of Greater Visakhapatnam coastal region using Indian Remote Sensing-IRS P6 (Resourcesat-I) satellite data and collateral information. Prominent changes have been observed during the past 30 years through land use/land cover analyzes which clearly indicate that thecoastal regulatory zones have altered in respect of both natural and anthropogenic activities. Various geomorphic units were identified and confirmed with appropriate field work. Significant changes have been recognized in the shoreline map, which denote that the area of erosional shoreline is larger than the accretional and stable prone shoreline. The availability of high resolution data has helped to prepare large-scale maps for implementation of CRZ measures. The results were promising and suggest that the modern geo-spatial information and technological tools are extremely helpful for conducting coastal morphological studies.     

潮滩水陆边界计算方法研究

潮滩水陆边界随着潮水的升降不断变化,使潮滩处于周期性的淹没与干出状态.在海岸淹没仿真过程中计算岸线的位置,可以很好地模拟潮滩淹没范围,从而为海岸作战决策服务.针对潮滩水陆边界的动态变化,提出一种基于岸线搜索的水陆边界计算方法.实验证明,该算法可以很好地满足潮滩淹没仿真的需要.     

应用地理信息系统辅助山坡地潜在崩山灾害评估模式之建立

山坡地开发具有潜在的自然危险因子,人工开挖也会触动这些因子,因此,要做好土地管理工作,需从分析潜在崩山灾害类型以及开发区位两方面考虑。地形分析在工程、灾害评估等方面广为应用,本研究以张石角(1987)提出的“简确工程地质灾害调查与评估法”为依据,以山坡地丙种建地作为评估对象,利用地理信息系统所提供的空间分析及数据库功能,完成台湾省中、北部地区大范围的山坡地潜在灾害评估工作,其成果也将为政府部门所采用.     

烟台市海岸地区土地利用变化时空分异研究

海岸线的大规模开发利用活动,加剧了海岸带土地利用/覆被变化,这种变化因离海岸线距离的不同而呈现出明显差异。以烟台市海岸地区为例,利用遥感和GIS空间分析方法揭示这种因海岸区位差异引起的土地利用变化时空格局特征,以期为地方土地资源与海岸线资源合理开发利用提供参考。结果表明:①近20年来烟台海岸地区土地利用变化较为活跃,城镇和其他建设用地扩展明显;海岸区位深刻影响着海岸地区土地利用动态变化率和不同用地类型间的转移特征;②与海岸区位密切相关的自然地理条件和岸线开发利用活动,以及人口增加、经济增长、政策与管理因素是导致烟台海岸地区土地利用变化产生时空分异的主要因素。     

江苏沿海滩涂利用模式遥感影像解译和时空变化分析

为了弄清江苏沿海滩涂利用模式分布情况,定量分析其时空变化趋势,本文基于Google Earth Engine云计算平台和Landsat卫星遥感影像数据,结合随机森林分类方法,通过机器学习建立了滩涂利用模式自动识别分类方法,样本训练后识别准确率达93％以上.利用该方法提取了2002年、2014年和2019年江苏沿海的土地...     

Geomorphology and land use pattern of visakhapatnam urban - industrial area

Geomorphology and land use pattern of Visakhapatnam urban – industrial area have been studied using IRS IB and SPOT data. The geomorphic units under structural landforms, fluvial landforms and coastal landforms were identified and appropriate field confirmations were made. The geomorphic units such as inselbergs/residual hills, rolling plains, colluvial plains, fractures, piedmont fans, pediments were identified under structural landforms. The units wind gap, paleo channels, gully land, alluvial plain and natural levee were identified under fluvial landforms. The coastal landforms include sea cave, sea stack, red sediments, beach sands and marshy area. Study of the land use pattern reveals the land use under various categories of residential, planned and un planned, agricultural land, waste land and others. The data will have high relevance and usefulness for urban, industrial and ground water resource evaluations in the context of rapid urbanization and industrialization.     

Flood risk analysis in the Kosi river basin, north Bihar using multi-parametric approach of Analytical Hierarchy Process (AHP)

The Kosi river in north Bihar plains, eastern India presents a challenge in terms of long and recurring flood hazard. Despite a long history of flood control management in the basin for more than 5 decades, the river continues to bring a lot of misery through extensive flooding. This paper revisits the flooding problem in the Kosi river basin and presents an in-depth analysis of flood hydrology. We integrate the hydrological analysis with a GIS-based flood risk mapping in parts of the basin. Typical hydrological characteristics of the Kosi river include very high discharge variability, and high sediment flux from an uplifting hinterland. Annual peak discharges often exceed the mean annual flood and the low-lying tracts of the alluvial plains are extensively inundated year after year. Our flood risk analysis follows a multi-parametric approach using Analytical Hierarchy Process (AHP) and integrates geomorphological, land cover, topographic and social (population density) parameters to propose a Flood Risk Index (FRI). The flood risk map is validated with long-term inundation maps and offers a cost-effective solution for planning mitigation measures in flood-prone areas.     

一种加入空间关系的海岸带遥感图像分类方法

 海岸带作为海洋、陆地和大气共同作用的地带，其地物混杂度大，变化频繁，单纯利用光谱特征分类难以取得理想的精度。 但海岸带地物滨临水体，而水体与地物存在巨大光谱差异，易于识别。据此，本文尝试提出一种简单的加入空间关系的遥感图像分类 方法，即，先准确识别出海水类，然后统计非海水类的每一个像元到最近海水的空间距离。由于不同的海岸带地类距离海水的空间距 离有其自身的特点，因此，利用这一距离信息辅助分类能提高分类精度，尤其是针对那些光谱特征相近而距离相差较大的地类。     

Pedo-genesis of soils in relation to physiography of part of Yamuna alluvial plain in Sonepat District,Haryana

Air photos coupled with intensive ground check and laboratory analysis have helped in establishing the relationship between physiography and associated soils located in the alluvial tract of Sonepat district Haryana. Four major landform units in the area were1 (i) recent flood plain, (ii) young meander plain, (iii) old meander plain and (iv) ofd alluvial plain. Each of the major units were sub divided on the basis of photo elements, (tone texture and parcelling). In the recent flood plain development in the profile was restricted due to recent deposits and continuous flooding during rainy season. Profile showed little development in the young and old meander plain which are to some extent free from flood activity. The old alluvial plain which showed maximum development in the profile might be attributed to age (Late Placetocene) and topography (occupies low land). Although over all the profile development is slow due to calcareous nature of parent material.     

应用气象卫星识别薄云覆盖下的水体

本文根据地物光谱特性和卫星的信号接收原理，提出了一种利用气象卫星识别水体的简单而有效的方法，使得薄云覆盖下的水体和云影中的水体得到较好的识别效果。在洪水监测中使用该方法，可以充分利用气象卫星数据获取丰富的洪水动态信息．并以１９９１年江淮洪涝灾害为背景，对试验结果进行了分析．     

Multi-hazard assessment using machine learning and remote sensing in the North Central region of Vietnam

Natural hazards constitute a diverse category and are unevenly distributed in time and space. This hinders predictive efforts, leading to significant impacts on human life and economies. Multi-hazard prediction is vital for any natural hazard risk management plan. The main objective of this study was the development of a multi-hazard susceptibility mapping framework, by combining two natural hazards—flooding and landslides—in the North Central region of Vietnam. This was accomplished using support vector machines, random forest, and AdaBoost. The input data consisted of 4591 flood points, 1315 landslide points, and 13 conditioning factors, split into training (70%), and testing (30%) datasets. The accuracy of the models' predictions was evaluated using the statistical indices root mean square error, area under curve (AUC), mean absolute error, and coefficient of determination. All proposed models were good at predicting multi-hazard susceptibility, with AUC values over 0.95. Among them, the AUC value for the support vector machine model was 0.98 and 0.99 for landslide and flood, respectively. For the random forest model, these values were 0.98 and 0.98, and for AdaBoost, they were 0.99 and 0.99. The multi-hazard maps were built by combining the landslide and flood susceptibility maps. The results showed that approximately 60% of the study area was affected by landslides, 30% by flood, and 8% by both hazards. These results illustrate how North Central is one of the regions of Vietnam that is most severely affected by natural hazards, particularly flooding, and landslides. The proposed models adapt to evaluate multi-hazard susceptibility at different scales, although expert intervention is also required, to optimize the algorithms. Multi-hazard maps can provide a valuable point of reference for decision makers in sustainable land-use planning and infrastructure development in regions faced with multiple hazards, and to prevent and reduce more effectively the frequency of floods and landslides and their damage to human life and property.