Estimation of Direct and Indirect Economic Losses Caused by a Flood With Long‐Lasting Inundation: Application to the 2011 Thailand Flood

River floods are common natural disasters that cause serious economic damage worldwide. In addition to direct economic damage, such as the destruction of physical assets, floods with long‐lasting inundation cause direct and indirect economic losses within and outside the affected area. Direct economic losses include loss of opportunity, due to interruption of business activities, and the costs associated with emergency measures such as cleaning, while indirect economic losses affect sectors within the trade and supply network. Few studies have explicitly estimated direct and indirect economic losses in several sectors, due to the difficulty of modeling inundation depth and period at finer scales. Here we developed a global modeling framework to estimate the direct and indirect economic losses associated with floods using a computable general equilibrium model and a global river and inundation model, which can simulate the flood extent, depth, and period. Application of the method to the 2011 Thailand flood demonstrated that the estimated economic losses due to business interruption in the industry and service sectors totaled $14.7 billion, which was about two thirds of the estimated direct economic damage caused by the flood ($22.0 billion). The estimated indirect economic losses reduced the gross domestic product of Thailand by 4.81% in 2011, without considering transboundary effects, and will cause more than 0.5% reduction in gross domestic product even in 2030, resulting in $55.3 billion of total losses from 2011 to 2030. Comprehensive estimation of direct and indirect economic losses facilitates understanding of various types of flood‐related economic risks during and after a flood

Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map

Data fusion represents a powerful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own. This paper focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study, we compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-weighted logistic regression (GWR), as well as classification and regression trees (CART). We ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference between the methods. However, GWR was found to perform better than the other tested methods in areas with high disagreement between the inputs

Development and evaluation of an automated land cover mapping approach in Greece

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

Global analysis of land-use changes in karst areas and the implications for water resources [Globale Analyse von Landnutzungsänderungen in Karstgebieten und deren Auswirkungen auf die Wasserressourcen]

Karstgebiete weisen wertvolle Grundwasserressourcen und eine hohe Artenvielfalt auf, sind jedoch besonders anfällig für den Klimawandel und menschliche Einflüsse. Landnutzungswandel ist Ursache und Folge von globalen Umweltveränderungen. Die Veröffentlichung von Daten wie denen des Land-Cover-Projektes der Climate Change Initiative (CCI-LC) der europäischen Weltraumbehörde ESA und der World Karst Aquifer Map (WOKAM) hat es ermöglicht, weltweite Landnutzungsveränderungen in Karstgebieten zu untersuchen. In dieser Arbeit wird zunächst die globale Verteilung der Nutzung von Karstlandschaften im Jahr 2020 untersucht, sowie die Charakteristika von Landnutzungsübergängen zwischen 1992 und 2020 analysiert. Dann werden zwei Indikatoren vorgeschlagen, um die räumlichen Merkmale von Landnutzungsveränderungen in globalen Karstgebieten zu identifizieren: Der Anteil von Landnutzungsveränderungen und der dominante Typ von Landnutzungsveränderungen. Schließlich werden drei Beispiele für Landnutzungsveränderungen in Karstgebieten im Detail analysiert. Die Landnutzungstypen und ihre Anteile der globalen Karstgebiete (in abnehmender Größe) sind: Wald (31.78%), kahle Flächen (27.58%), Ackerland (19.02%), Grasland (10.87%), Strauchland (7.21%), Feuchtgebiete (1.67%), Eis und Schnee (1.16%) und urbanes Gebiet (0.71%). Die Gesamtfläche der globalen Landnutzungsveränderungen in Karstgebieten beträgt 1.3 Millionen km², etwa 4.85% der globalen Karstfläche. Der Trend des Landnutzungswandels in den weltweiten Karstgebieten wird von Aufforstung dominiert, ergänzt durch vereinzelte Urbanisierung und landwirtschaftliche Rekultivierung. Die tropischen Klimazonen weisen eine höhere Intensität von Landnutzungsveränderungen auf. Regionen mit landwirtschaftlicher Rekultivierung stimmen weitgehend mit der Bevölkerungsdichte überein. Diese Ergebnisse spiegeln den Einfluss menschlicher Aktivitäten und des Klimawandels auf Landnutzungsveränderungen in globalen Karstgebieten wider und dienen als Grundlage für weitere Forschung und Planung im Bereich des Landressourcenmanagements

Methodology for Agricultural Flood Damage Assessment

This chapter describes a method for assessing flood damage to the agricultural sector, specifically focusing on flood damage to rice crops. The chapter also includes the case studies of flood damage assessment conducted in the Asian river basins, the Pampanga River basin of the Philippines, and the Lower Indus River basin of Pakistan. The assessment was performed by defining flood damage to rice crops as a function of flood depth, duration, and growth stage of rice plants and using depth-duration-damage function curves for each growth stage of rice plants. In the case studies, flood characteristics such as flood depth, duration, and distribution were computed using a rainfall-runoff-inundation (RRI) model. Flood damage to rice crops was assessed for the 2011 flood and 100-year flood events in the case of the Pampanga River basin and for the 2010 flood in the case of Lower Indus River basin. The calculated values of agricultural damage were compared with reported data for validation of methodology, and it was found that the calculated damage reasonably agreed with reported data. The rice-crop damage assessment method described in this chapter can also be applied in other areas for flood risk assessment

Integração de SIG para Padronização de Informação de Uso do Solo à Escala Mundial

A análise de ciclo de vida (ACV) é hoje reconhecida como uma ferramenta fundamental para a avaliação da sustentabilidade de bens e serviços. No entanto, os métodos existentes estão principalmente focados nos efeitos da poluição na saúde humana, ecossistemas e alterações climáticas. Os indicadores de uso do solo (LU – Land Use) em ACV estão tradicionalmente centrados num único aspeto ambiental. Os métodos de ACV mais comuns procuram reconhecer alterações no ciclo de carbono e no seu armazenamento, existindo ainda indicadores de LU que se focam na qualidade do solo, na produtividade deste, nas práticas de utilização, nas mudanças de uso do solo e na perda de biodiversidade. A falta de informação global de LU tem limitado a aplicabilidade desses indicadores, influenciado a qualidade da análise em ACV. Com o fenómeno da globalização, uma parte significativa da cadeia de valor de um produto encontra-se frequentemente em lugares distintos, muitas das vezes em continentes diferentes. O conhecimento do uso do solo a nível global aliado à compreensão dos impactos nas funções do solo e das implicações culturais e sociais de cada uso, permitem-nos avaliar na ACV as implicações ambientais associadas aos diversos usos. Nos dias de hoje, devido ao progresso tanto científico como técnico, atingido nas últimas décadas, é muito mais fácil compilar e avaliar informação ambiental a um nível global. Em particular, os avanços na deteção remota e nos sistemas de informação geográfica (SIG) permitem-nos estudar toda a superfície terrestre, aumentando assim, a nossa capacidade de compreender, analisar e prever impactos ambientais em escalas globais e regionais de uma forma sem precedentes. Este estudo apresenta uma compilação de dados de LU à escala regional e a um nível global, que pode facilitar a sua integração e avaliação em ACV. A maioria das fontes de informação são bases de dados abertos disponibilizadas por várias agências. A metodologia da dissertação contém os seguintes tópicos: Pesquisa de informação geográfica relevante para o indicador de uso do solo a nível global e de metodologias de avaliação dos serviços dos ecossistemas; Comparação e análise crítica para selecionar os mapas de LU mais relevantes em relação aos objetivos; Uniformização de diferentes classes de uso do solo, com a função de criar cartografia de LU em todo o mundo para uso em ACV; Revisão das metodologias de uso do solo em ACV e das metodologias de avaliação de serviços dos ecossistemas; Criação de factores de LU para as classes do mapa global e desenvolvimento de um indicador de uso do solo; Teste do novo indicador. Os factores e indicadores de LU partem da abordagem do método EcoBlock (que dá especial ênfase ao LU), porém as classes criadas podem ser facilmente adaptáveis a outros métodos de ACV. Esta abordagem deve permitir simplificar a consideração de indicadores do uso do solo em ACV e dar robustez a análises de cadeias de valor multinacionais

Urban land cover mapping using medium spatial resolution satellite imageries: effectiveness of Decision Tree Classifier

The study is inserted in the framework of information extraction from satellite imageries for supporting rapid mapping activities, where information need to be extracted quickly and the elimination, also if partially, of manual digitalization procedures, can be considered a great breakthrough. The main aim of this study was therefore to develop algorithms for the extraction of urban layer by means of medium spatial resolution Landsat data processing; Decision Tree classifier was investigated as classification techniques, thus it allows to extract rules that can be later applied to different scenes. In particular, the aim was to evaluate which steps to perform in order to obtain a good classification procedure, mainly focusing on processing that can be applied to images and on training set features. The training set was evaluated on the basis of the number of classes to use for its creation, together with the temporal extension of the training set and input attributes, while images were submitted to different kind of radiometric pre and post-processing. The aim was the evaluation of the best variables to set for the creation of the training set, to be used for the classifier generation. Above-mentioned variables were compared and results evaluated on the basis of reached accuracies. Data used for the validation were derived from the Digital Regional Technical Ma

Regional differences in mainland China after the 1970s economic reform

Relevance. In recent years, China’s GDP has continued to grow, however, the regional gap in socio-economic development is still huge. It is, therefore, crucial to investigate the reasons behind regional disparities and the possible solutions to this problem.  Research objective. This paper aims to examine the patterns of regional differences in mainland China after the economic reform of the 1970s.Data and methods. The study relies on the methods of comparative analysis and the data from the National Bureau of Statistics of the People’s Republic of China and the Statistical Yearbook Sharing Platform as well as the information from the national media portal - Xinhua News Agency.  Results. The Chinese government’s application of differentiated measures, strategies and policies to different regions exacerbated the existing disparities. This paper elaborates on the future regional economic adjustments and plans and thus can be of interest to investors and business activists in China and other countries