Object-based classification of cloudy coastal areas using medium-resolution optical and SAR images for vulnerability assessment of marine disaster

Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation.Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover,coastal areas often encounter significant cloud cover,especially in tropical areas,which makes the classification in those areas non-ideal.To solve this problem,we proposed a framework of combining medium-resolution optical images and synthetic aperture radar(SAR)data with the recently popular object-based image analysis(OBIA)method and used the Landsat Operational Land Imager(OLI)and Phased Array type L-band Synthetic Aperture Radar(PALSAR)images acquired in Singapore in 2017 as a case study.We designed experiments to confirm two critical factors of this framework:one is the segmentation scale that determines the average object size,and the other is the classification feature.Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80,and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features,especially in areas with cloud cover.Based on the land cover generated by this framework,we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km2 over the past decade.To clarify the disaster response plan for different geographical environments,we classified risk based on altitude and distance from shore.The newly increased high-vulnerability regions within 4 km offshore and below 30 m above sea level are at high risk;these regions may need to focus on strengthening disaster prevention construction.This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters,especially those in cloudy coastal areas.

Rural vulnerability,migration,and relocation in mountain areas of Western China:An overview of key issues and policy interventions

Western China features a vast area of mountains and high plateaus where millions of people,including diverse ethnic minority groups,have inhabited for generations.Geographically located in the mountainous,remote,and isolated regions,rural communities are prone to natural hazards and thus become vulnerable to impoverishment.To reduce rural vulnerability,many people residing in mountainous villages opted to out-migrate from their original villages and hometowns while some took in-situ adaptation measures.A host of government-sponsored resettlement programs have been carried out to help rural villagers seek alternative livelihoods elsewhere over the past four decades.To achieve a sustainable future for rural communities in mountainous areas of western China,more effective policies and measures need to be developed and enforced.

Assessing the Vulnerability of Agricultural Production Activities in the Coastal Area of Thua Thien Hue Province, Vietnam by GIS Analysis Tools

Using Geography Information System (GIS) tools and remote sensing data in assessing the level of vulnerability of agricultural production activities in the coastal area has become more efficient in the recent years. This research has identified the sensitivity index (S) (including the traffic access index;the impact of residential areas;the impacts of industrial zones;the community dependence level), exposure index (E) (the sea level rises to 2100;the temperature change to 2100), the adaptable capacity index (AC) (slope;morphology), thereby synthesizing the vulnerability index (V). Based on the indexes to calculate vulnerability, the high to very high vulnerability area is 37,081.44 ha, accounting for 68.09%;the average vulnerability level is 15,286.49 ha, accounting for 28.07%;the low to very low vulnerability level with an area is 2087.82 ha, accounting for 3.84% of the total area. With a high and very high vulnerability accounting for 68.09%, there will be great influences on the lives of resident in the area, especially agricultural production.

Socio-Economic Vulnerability to COVID-19: The Spatial Case of Greater Kampala Metropolitan Area (GKMA)

COVID-19 has presented itself with an extreme impact on the resources of its epi-centres. In Uganda, there is uncertainty about what will happen especially in the main urban hub, the Greater Kampala Metropolitan Area (GKMA). Consequently, public health professionals have scrambled into resource-driven strategies and planning to tame the spread. This paper, therefore, deploys spatial modelling to contribute to an understanding of the spatial variation of COVID-19 vulnerability in the GKMA using the socio-economic characteristics of the region. Based on expert opinion on the prevailing novel Coronavirus, spatially driven indicators were generated to assess vulnerability. Through an online survey and auxiliary datasets, these indicators were transformed, classified, and weighted based on the BBC vulnerability framework. These were spatially modelled to assess the vulnerability indices. The resultant continuous indices were aggregated, explicitly zoned, classified, and ranked based on parishes. The resultant spatial nature of vulnerability to COVID-19 in the GKMA sprawls out of major urban areas, diffuses into the peri-urban, and thins into the sparsely populated areas. The high levels of vulnerability (24.5% parishes) are concentrated in the major towns where there are many shopping malls, transactional offices, and transport hubs. Nearly half the total parishes in the GKMA (47.3%) were moderately vulnerable, these constituted mainly the parishes on the outskirts of the major towns while 28.2% had a low vulnerability. The spatial approach presented in this paper contributes to providing a rapid assessment of the socio-economic vulnerability based on administrative decision units-parishes. This essentially equips the public health domain with the right diagnosis to subject the highly exposed and vulnerable communities to regulatory policy, increase resilience incentives in low adaptive areas and optimally deploy resources to avoid the emancipation of high susceptibility areas into an epicentre of Covid-19.

Ecological vulnerability analysis of Tibetan towns with tourism-based economy： a case study of the Bayi District

This paper provides a generalizable mode for the ecological vulnerability evaluation for tourism planning and development in high mountain areas.The Bayi District located in southeastern Tibet is taken as a typical town to study the conflict between the protection of natural ecological environment and the exploitation of tourism resources. Based on the Sensitivity-Recovery-Pressure(SRP) framework, a set of vulnerability evaluation systems for plateau tourism regions were developed. The spatial principal component analysis(SPCA), remote sensing and GIS technologies were integrated to apply for spatial quantification of evaluation index system. The ecological vulnerability of the Bayi District was divided into five levels: potential, mild, moderate,severe, and extreme, and our results showed that significantly severe and extreme vulnerability areas were mainly distributed throughout the southwestern and central northern alpine pasture and glacial zones.Potential and mild vulnerability areas were mainly distributed in the vicinity of the Yarlung Zangbo River tributary basin. Then three tourism development and environmental protection zones were classified and appropriate measures for the protection were proposed. It also provides a reference for the spatial distribution of a range of areas that require different protection measures according to ecological vulnerability classification.

Aquaculture area extraction and vulnerability assessment in Sanduao based on richer convolutional features network model

Sanduao is an important sea-breeding bay in Fujian,South China and holds a high economic status in aquaculture.Quickly and accurately obtaining information including the distribution area,quantity,and aquaculture area is important for breeding area planning,production value estimation,ecological survey,and storm surge prevention.However,as the aquaculture area expands,the seawater background becomes increasingly complex and spectral characteristics differ dramatically,making it difficult to determine the aquaculture area.In this study,we used a high-resolution remote-sensing satellite GF-2 image to introduce a deep-learning Richer Convolutional Features(RCF)network model to extract the aquaculture area.Then we used the density of aquaculture as an assessment index to assess the vulnerability of aquaculture areas in Sanduao.The results demonstrate that this method does not require land and water separation of the area in advance,and good extraction can be achieved in the areas with more sediment and waves,with an extraction accuracy>93%,which is suitable for large-scale aquaculture area extraction.Vulnerability assessment results indicate that the density of aquaculture in the eastern part of Sanduao is considerably high,reaching a higher vulnerability level than other parts.

Livelihood vulnerability of smallholder farmers to climate change: A comparative analysis based on irrigation access in South Sulawesi, Indonesia

Bulukumba Regency is one of the major rice-producing areas in South Sulawesi,Indonesia and has experienced frequent climate disasters over the past decade.Several downstream villages within the Bettu River irrigation area have been affected by the drought,culminating in reduced lowland rice production and increasing the vulnerability of farmers’livelihoods.This study aims to evaluate the vulnerability of the livelihood system among rice farmers in the Bettu River irrigation area by classifying the area into two zones based on the distance from the main irrigation canal,namely the upstream area and downstream area.The livelihood vulnerability index(LVI)framework and livelihood vulnerability index-Intergovernmental Panel on Climate Change(LVI-IPCC)approach were applied by selecting geographic and socio-demographic indicators that affected the farmer households,including 8 major components and 26 sup-components.The data for LVI-IPCC estimation were collected by randomly selecting 132 households from villages in the two areas.The empirical results showed that farmers in the downstream area were more vulnerable to climate change than farmers in the upstream area.The major components causing the livelihood vulnerability of the downstream farmers were livelihood strategy,food,water,land,and health,as well as natural disasters and climate variability.In particular,the sub-components of agricultural livelihood diversification,consistent water supply for farming,and drought events were important in the downstream area.Farmers in the upstream area were vulnerable to socio-demographic profile and social network components.The LVI-IPCC findings suggested that the government should prioritize farmers in the downstream area to develop resilience strategies,particularly by increasing irrigation infrastructure and the number of reservoirs and drilling holes.Furthermore,to increase their adaptive capacity in terms of diversification of agricultural livelihood systems,the government and donor agencies need to provide trainings on the development of home food industries for poor farmers and vulnerable households that were affected by disasters.

Driving factors and the implications of work choices of rural laborers in ecologically vulnerable areas in North China

Using rural survey data for the year 2009,we provide evidence of work choices of rural laborers in ecologically vulnerable areas in North China,and model these choices as a function of characteristics of individuals,households,and land endowments.The findings reveal large differences between males and females,and between non-farm employment and part-time farming engagement Land scarcity is still an important driving factor in non-farming participation of rural laborers in the study area;and in the current case of land productivity and the total amount of land,there are still surplus rural labor forces in the study area.Diversification of livelihood reduces the pressure on land,thus facilitating ecosystem conservation.So,the paper concludes with the argument that establishing coordination mechanisms among non-farm employment of rural laborers,agricultural production,and restoration of ecosystems are essential for mitigating the conflicts of ecological security,agricultural production,and rural development in mis area.

Livelihood Diversification of Farm Households and Its Impact on Cultivated Land Utilization in Agro-pastoral Ecologically-vulnerable Areas in the Northern China

The relationship between livelihood diversification of farm households and cultivated land utilization has become a core research topic related to global environmental change.Agro-pastoral ecologically-vulnerable areas face challenges such as insufficient ecosystem conservation,low agricultural production,and weak economies.In this study,215 farm households from Zhengxiangbai Banner,Taibus Banner,and Duolun County of Inner Mongolia were surveyed.The sustainable livelihoods framework of the United Kingdom(UK)Department for International Development(DFID)was used to measure the livelihood capital of these farm households.A one-way analysis of variance(ANOVA)was applied to examine the differences in the livelihood capital of different types households,and a correlation analysis was applied to analyze its impact on cultivated land utilization.Results showed that households with non-farming activities accounted for 64.7%of the total surveyed households,and non-farming employment was becoming more prevalent.Physical and financial capital was the driving factors for livelihood diversity.Each livelihood capital had key factors that affected household farmland use behaviors,such as the age of householder,the labor ratio,proportion of income,farmland scale,number of machines,and these had a significantly positive or negative influence on farmland use.Full-time farming households were more likely to transfer the land into cultivation and invest more labor,while non-farming households with high income were likely to transfer farmland out and invest more money to develop efficient farming or improve the employment skills.The results of this study suggest that policymakers need to fully consider livelihood changes of local households.It is effective to strengthen labor training,create farmland market and improve the efficiency of farmland utilization.We hope to achieve a win-win scenario to improve local economies and ecosystem conservation.

Groundwater Quality Analysis and Vulnerability Assessment in Longdong Area

Groundwater is important drinking water source in Longdong area. In recent years,as gradual expanding of industrial and agricultural production scales,seen from change trend of water quality,major impact factors of groundwater in the zone were ammonia nitrogen,COD,sulfate and total dissolved solid. By using specific thought of parameter system method,vulnerability assessment factor system of groundwater and meter point system calculation model in the zone were established. Via calculation and analysis,vulnerability distribution of groundwater in the zone was obtained. According to vulnerability index（ higher,moderate and lower）,zone dividing was conducted,and the areas were respectively 623. 25,4 005. 00 and 6 621. 75 km2,which respectively accounted for 5.54%,35. 60% and 58. 86%. The evaluation provided research basis for prevention,control and protection of groundwater environment in Longdong area.

Ecological Compensation-assisted Relocation in Extreme Poverty-stricken Counties in China’s Ecologically Vulnerable Areas: Taking Dongchuan District of Yunnan Province as an Example

Ecology-oriented poverty alleviation is not only a livelihood project that affects the vast majority of rural people but also a major project to win the fight against poverty. It is also an indispensable income component for the relocation of poor farmers. Dongchuan District,located at the intersection of Jinsha River and Xiaojiang River,is one of the key counties for poverty alleviation and development in China with a wide range of poverty and extreme poverty. The incidence of poverty reached 24. 36%. The ecology is fragile,and earthquake outbreaks frequently. Dongchuan District is a national key monitoring and defense area for earthquakes. A large number of goafs,subsidence areas and geological hazard areas have been formed in the mining area. The number of dangerous houses is large,and ' it has no way of supporting its own inhabitants' is the key point,difficulty and focus of the county’s poverty alleviation. Relocation is a must-have measure to move away from poverty. It is also complex system engineering,which is policy-oriented and difficult. Since 2017,Dongchuan District has regarded relocation has the top priority for poverty alleviation. It has strictly implemented national,provincial and municipal policies,focused on the overall goal of ' moving,securing and getting rich',and strongly promoted the relocation work for poverty alleviation. Obvious social,economic and ecological benefits have been achieved. Successful relocation,combined with ecology-oriented poverty alleviation and other targeted poverty alleviation measures,Dongchuan District’s fight against poverty has achieved a decisive victory. At the end of December 2018,the incidence of poverty in the region fell to 1. 09%,and 129 poor villages( including 86 extremely poor villages) had been successfully lifted out of poverty. This paper analyzes and condenses the specific practices,main achievements,benefits,successful experiences and implications of the region’s relocation combined with ecology-oriented poverty alleviation model,so as to provide necessary reference for the innovation of relocation in poverty-stricken counties of Yunnan Province and similar provinces( cities,districts).

Game Analysis and Mechanism Design of Ecological Protection Red Line for Ecologically Vulnerable Areas in Western China

Drawing the ecological protection red line is to maintain the integrity and benign operation of the ecosystem within the area,and to ensure that the ecological environment is within the boundary of controllable ecological security.Taking the ecologically vulnerable areas in western China as the research object and using the game theory and literature analysis,this paper studied the game behavior of ecological protection red line in these areas.In addition,this paper also analyzed the stakeholders such as government,enterprises and the masses in the drawing of the ecological protection red line,and comprehensively analyzed the game strategies between the government and the masses,the government and enterprises,and the central and local governments and enterprises.On the basis of the analysis,it came up with a safeguard mechanism for the coordination of the interests of the ecological protection red line.

The Research About non-agriculture shift confronting the rural vulnerable farmers in the underdeveloped areas of China

This paper reveals the law of non-agriculture shift of the vulnerable groups in underdeveloped rural areas in china, and put forward the ＂second shift＂ category, namely the vulnerable groups is bound to work in cities; return to participate in local non-agricultural activities; then begin second non-agriculture shift. The paper discusses the ＂second shift＂ feature; Finally, draw policy Implications of the ＂second shift＂.

Understanding livelihood vulnerability:a perspective from Western Sichuan’s ethnic rural settings

To explore the livelihood status and key influencing factors of rural households in the minority areas,we collected flat data from 284 rural households in 32 villages across 12 counties of Western Sichuan from 2021 to 2022.We conducted participatory household survey on the livelihood status of the rural households and try to identify the key factors to influence their livelihood vulnerability using multiple linear regression.The results showed that:the livelihood situation of the rural households is relatively vulnerable.The vulnerability varies significantly with the income levels,education levels,and income sources.The vulnerability of farm households,categorized from low to high livelihood types,follows the sequence:non-agricultural dominant households,non-agricultural households,agricultural dominant households,and pure agricultural households.The degree of damage to the natural environment,education costs,loan opportunities,the proportion of agricultural income to annual household income,and the presence of sick people in the household have significant positive effects on the livelihood vulnerability index(LVI)of rural households;while help from relatives and friends,net income per capita,household size,household education,agricultural land area,participation in industrial organizations,number of livestock,purchase of commercial houses,drinking water source,and self-supply of food have significant negative effects.Based on the findings,we believe that local rural households operate in a complex livelihood system and recommend continuous interventions targeting key influences to provide empirical research support for areas facing similar situations.

Socio-economic vulnerability level in the Jeneberang watershed in Gowa Regency,South Sulawesi Province,Indonesia

Jeneberang watershed is vital,particularly for people living in Gowa Regency(South Sulawesi Province,Indonesia),who benefit from its many advantages.Landslides and floods occur every year in the Jeneberang watershed,so it is imperative to understand the socio-economic vulnerability of this region.This research aims to identify the vulnerability level of the Jeneberang watershed so that the government can prioritize areas with high vulnerability level and formulate effective strategies to reduce these the vulnerability.Specifically,this study was conducted in 12 districts located in the Jeneberang watershed.The primary data were collected from questionnaires completed by community members,community leaders,and various stakeholders,and the secondary data were from the Landsat satellite imagery in 2020,the Badan Push Statistic of Gowa Regency,and some governmental agencies.The socio-economic vulnerability variables were determined using the Multiple Criteria Decision Analysis(MCDA)method,and each variable was weighted and analyzed using the Geographical Information System(GIS).The study reveals that the levels of socio-economic vulnerability are affected by variables such as population density,vulnerable groups(disabled people,elderly people,and young people),road network and settlement,percentage of poor people,and productive land area in the Jeneberang watershed.Moreover,all of the 12 districts in the Jeneberang watershed are included in the medium vulnerability level,with the mean percentage of socio-economic vulnerability around 50.92%.The socio-economic vulnerability of Bajeng,Pallangga,and Somba Opu districts is categorized at high level,the socio-economic vulnerability of Bungaya,Parangloe,and Tombolo Pao districts is classified as medium level,and the remaining 6 districts(Barombong,Bontolempangan,Bontomarannu,Manuju,Parigi,and Tinggimoncong)are ranked as low socio-economic vulnerability.This study can help policy-makers to formulate strategy that contributes to the protection of biodiversity and sustainable development of the Jeneberang watershed,while improving disaster resilience and preparedness of the watershed.

Assessing Multidimensional Vulnerability of Rural Areas to Flooding:An Index‑Based Approach

Vulnerability assessment is essential for understanding and launching effective flood risk reduction strategies.This study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab,Pakistan to external shocks.The concept of vulnerability encompasses a range of dimensions,including physical,social,institutional,environmental,economic,and attitudinal.Using a composite index method,indices were developed for each dimension and combined to create a multidimensional measure of vulnerability.A sample of 365 communities was selected using the Yamane sampling technique,and data were collected through a questionnaire containing 65 indicators across all dimensions.Descriptive statistics and ANOVA tests were used to analyze the data.The results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other communities.High attitudinal vulnerabilities were as sociated with poorly perceived flood risks and low preparedness measures,whereas institutional vulnerabilities were driven by conventional flood protection strategies,lack of institutional trust,and lack of flood risk awareness.This research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.

A Generic Calculation Model for Aircraft Single-hit Vulnerability Assessment Based on Equivalent Target

Aircraft single-hit vulnerability/survivability is usually expressed as the probability of kill or the vulnerable area in case of being given a random threat （e.g. a fragment） hit on the aircraft. In this paper, introducing the ＂equivalent target method＂ in lethality field into the aircraft vulnerability assessment, a generic vulnerability calculation model is proposed. In order for a good representation of reality, the model considers the threat change of state-of-motion during the threat penetrating into the components successively. Application shows that the proposed generic model has solved the Pk/h （probability of kill given by a hit on the component） calculation problem in aircraft vulnerability assessment, and is easier to be computerized than other commonly used models.

Adaptation strategy for sea level rise in vulnerable areasalong China's coast

It can be seen from the calculation that the vulnerable area along China's coast in which the elevation is less than 5 m, is 143 900 km2, accounting for about 11. 3% of the total area of the 11 coastal provinces, municipalities and autonomous regions. These areas are threatened to varying extent by sea level rise. According to prediction, the relative sea level rise (including global sea level rise caused by climate change and local relative as level rise caused by vertical crust movement and ground subsidence) along China's coast will be 4～16 cm by the year 2030 with the optimum estimated value of 6～14cm. It will be 9～26 cm by the year 2050 with the optimum estimated value of 12-23 cm. And it will be 31-74 cm by the year 2100 with the optimum estimated value of 47～65 cm. The calcuation result shows that the percentage of the cost for up-grading (heightening and consolidating) sea dykes/walls in adaptation strategy in the losses of submerged areas varies from area to area: 6. 9% in the Zhujiang (Pearl) River Deta, 1. 3% ～24. 6% in the Changjiang (Yangtze) River Delta, and 0. 9%～2. 0% in the Huanghe River Delta.

Ambient noise as the new source for urban engineering seismology and earthquake engineering: a case study from Beijing metropolitan area

In highly populated urban centers, traditional seismic survey sources can no longer be properly applied due to restrictions in modern civilian life styles. The ambient vibration noise, including both microseisms and microtremor, though are generally weak but available anywhere and anytime, can be an ideal supplementary source for conducting seismic surveys for engineering seismology and earthquake engineering. This is funda- mentally supported by advanced digital signal processing techniques for effectively extracting the useful information out from the noise. Thus, it can be essentially regarded as a passive seismic method. In this paper we first make a brief survey of the ambient vibration noise, followed by a quick summary of digital signal processing for passive seismic surveys. Then the applications of ambient noise in engi- neering seismology and earthquake engineering for urban settings are illustrated with examples from Beijing metro- politan area. For engineering seismology the example is the assessment of site effect in a large area via microtremor observations. For earthquake engineering the example is for structural characterization of a typical reinforced con- crete high-rise building using background vibration noise.By showing these examples we argue that the ambient noise can be treated as a new source that is economical, practical, and particularly valuable to engineering seis- mology and earthquake engineering projects for seismic hazard mitigation in urban areas.

Effects of climate change on potential habitats of the cold temperate coniferous forest in Yunnan province, southwestern China

We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the current and future climates, using seven climate change scenarios, projected over the years of 2070-2099. The accurate CT model on CTCFs showed that minimum temperature of coldest month （TMW） was the overwhelmingly potent factor among the six climate variables. The areas of TMW〈-4.05 were suitable habitats of CTCF, and the areas of -1.35 〈 TMW were non-habitats, where temperate conifer and broad-leaved mixed forests （TCBLFs） were distribute in lower elevation, bordering on the CTCF. Dominant species of Abies, Picea, and Larix in the CTCFs, are more tolerant to winter coldness than Tsuga and broad-leaved trees including deciduous broad-leaved Acer and Betula, evergreen broad- leaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35℃ and -4.05℃, and the warm-side distributions of CTCFs may be controlled by competition to the species of TCBLFs. Under future climate scenarios, the vulnerable area, where current potential （suitable ＋ marginal） habitats （80,749 km^2） shift to non-habitats, was predicted to decrease to 55.91% （45,053 km^2） of the current area. Inferring from the current vegetation distribution pattern, TCBLFs will replace declining CTCFs. Vulnerable areas predicted by models are important in determining priority of ecosystem conservation.