Application of SLEUTH Model to Predict Urbanization Along the Emilia-Romagna Coast (Italy): Considerations and Lessons Learned

Coastal zone of Emilia-Romagna region, Italy, has been significantly urbanized during the last decades, as a result of a tourism development. This was the main motivation to estimate future trajectories of urban growth in the area. Cellular automata (CA)-based SLEUTH model was applied for this purpose, by using quality geographical dataset combined with relevant information on environmental management policy. Three different scenarios of urban growth were employed: sprawled growth scenario, compact growth scenario and a scenario with business-as-usual pattern of development. The results showed the maximum increase in urbanization in the area would occur if urban areas continue to grow according to compact growth scenario, while minimum was observed in case of more sprawled-like type of growth. This research goes beyond the domain of the study site, providing future users of SLEUTH detailed discussion on considerations that need to be taken into account in its applicatio

Meeting of the Ecosystem Approach Correspondence Group on on Pollution Monitoring (CorMon Pollution)

In accordance with the UNEP/MAP Programme of Work adopted by COP 21 for the biennium 2020-2021, the United Nations Environment Programme/Mediterranean Action Plan-Barcelona Convention Secretariat (UNEP/MAP) and its Programme for the Assessment and Control of Marine Pollution in the Mediterranean (MED POL) organized the Meeting of the Ecosystem Approach Correspondence Group on Pollution Monitoring (CorMon on Pollution Monitoring). The Meeting was held via videoconference on 26-27 April 2021. 2. The main objectives of the Meeting were to: a) Review the Monitoring Guidelines/Protocols for IMAP Common Indicator 18, as well as the Monitoring Guidelines/Protocols for Analytical Quality Assurance and Reporting of Monitoring Data for IMAP Common Indicators 13, 14, 17, 18 and 20; b) Take stock of the state of play of inter-laboratory testing and good laboratory practice related to IMAP Ecological Objectives 5 and 9; c) Analyze the proposal for the integration and aggregation rules for IMAP Ecological Objectives 5, 9 and 10 and assessment criteria for contaminants and nutrients; d) Recommend the ways and means to strengthen implementation of IMAP Pollution Cluster towards preparation of the 2023 MED Quality Status Report

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers

Estrazione di linee di riva mediante classificazione multispettrale di immagini satellitari ad alta risoluzione

La linea di riva rappresenta un elemento costiero dinamico e complesso, spesso difficilmente distinguibile, la cui identificazione precisa è ancora un tema aperto per gli esperti del settore. Il principale scopo di questo lavoro è di valutare il potenziale di un approccio semiautomatico di estrazione di linee di riva, mediante analisi multispettrali di immagini satellitari ad alta risoluzione. L’analisi è stata effettuata utilizzando un’immagine WorldView-2 relativa a circa 40 km di costa lungo il litorale Ravennate, nel Nord Adriatico. Da decenni questo tratto di costa è interessato da significativi arretramenti della linea di riva e fenomeni di erosione in genere, dovuti principalmente a ridotti apporti sedimentari di origine fluviale, subsidenza, storm surges e opere di difesa inefficaci. Mediante classificazioni multispettrali delle diverse coperture del suolo lungo la fascia costiera, è stato possibile identificare la linea di separazione tra sabbia asciutta e sabbia bagnata. Le oscillazioni di marea sono state prese in considerazione al fine di valutare i possibili scostamenti dal livello medio mare. Sono state applicate tecniche di classificazione unsupervised (ISODATA) e supervised (Parallelepiped, Gaussian maximum likelihood, Minimum-distance-to-means and Mahalanobis distance). Al fine di valutare l’affidabilità di questi metodi per l’estrazione della linea di riva, sono state calcolate le distanze medie tra le varie linee ottenute ed una linea di riferimento digitalizzata manualmente dall’utente. I valori della mediana della distanze non superano i 6 m, e per alcune classificazioni come ISODATA e Mahalanobis sono di circa 2 m, indicando un alto grado di compatibilità tra la linea di riferimento e quelle calcolate. Inoltre la correlazione tra i diversi valori di scostamento e le tipologie di costa presenti, ha evidenziato l’influenza di particolari elementi geomorfologici e delle opere di difesa. I risultati indicano come gli ambienti costieri più omogenei ed antropizzati siano facilmente classificabili, al contrario di ambienti più naturali, eterogenei e discontinui. L’elevata congruenza tra la linea di riferimento e le linee derivanti dalle classificazioni, suggerisce un possibile utilizzo di questo metodo di estrazione della linea di riva per attività di monitoraggio costiero. La procedura di analisi semiautomatica permette un risparmio considerevole di tempi e costi. Inoltre, rispetto alla digitalizzazione manuale, il livello di soggettività nell’identificazione della line di riva è sensibilmente ridotto

Image classification methods applied to shoreline extraction on very high-resolution multispectral imagery

Comprehension of vulnerability to coastal erosion in dynamic coastal environments strongly depends on accurate and frequent detection of shoreline position. The monitoring of such environments could benefit from the semi-automatic shoreline delineation method, especially in terms of time, cost, and labour-intensiveness. This article explores the potential of using a semi-automatic approach in delineating a proxy-based shoreline by processing high-resolution multispectral WorldView-2 satellite imagery. We studied the potential and differences of basic and easily accessible standard classification methods for shoreline detection. In particular we explored the use of high spatial and spectral resolution satellite imagery for shoreline extraction. The case study was carried out on a 40 km coastal stretch facing the Northern Adriatic Sea (Italy) and belonging to the Municipality of Ravenna. In this area a frequent monitoring of shoreline position is required because of the extreme vulnerability to erosion phenomena that have resulted in a general trend of coastal retreat over recent decades. The wet/dry shorelines were delineated between the classes of wet and dry sand, resulting from different supervised (Parallelepiped, Gaussian Maximum Likelihood, Minimum-Distance-to-Means, and Mahalanobis distance) image classification techniques and the unsupervised Iterative Self-Organizing Data Analysis Technique (ISODATA). In order to assign reliability to outcomes, the extrapolated shorelines were compared to reference shorelines visually identified by an expert, by assessing the average mean distance between them. In addition, the correlation between offset rates and different types of coast was investigated to examine the influence of specific coastal features on shoreline extraction capability. The results highlighted a high level of compatibility. The average median distance between reference shorelines and those resulting from the classification methods was less than 5.6 m (Maximum likelihood), whereas a valuable distance of just 2.2 m was detected from ISODATA and Mahalanobis. Heterogeneous coastal stretches exhibited a larger offset between extracted and reference shorelines than the homogeneous ones. To finally evaluate the coastal evolution of the area, results from Mahalanobis classification were compared to a shoreline derived from airborne light detection and ranging (lidar) data. The fine spatial resolution provided by both methodologies allowed a detailed Digital Shoreline Analysis System (DSAS) comparison, detecting an erosive trend within a wide portion of the study area

Coupling scenarios of urban growth and flood hazards along the Emilia-Romagna coast (Italy)

The extent of coastline urbanization reduces their resilience to flooding, especially in low-lying areas. The study site is the coastline of the Emilia-Romagna region (Italy), historically affected by marine storms and floods. The main aim of this study is to investigate the vulnerability of this coastal area to marine flooding by considering the dynamics of the forcing component (total water level) and the dynamics of the receptor (urban areas). This was done by comparing the output of the three flooding scenarios (10, 100 and > 100 year return periods) to the output of different scenarios of future urban growth up to 2050. Scenario-based marine flooding extents were derived by applying the Cost–Distance tool of ArcGIS^® to a high-resolution digital terrain model. Three scenarios of urban growth (similar-to-historic, compact and sprawled) up to 2050 were estimated by applying the cellular automata-based SLEUTH model. The results show that if the urban growth progresses compactly, flood-prone areas will largely increase with respect to similar-to-historic and sprawled growth scenarios. Combining the two methodologies can be useful for identification of flood-prone areas that have a high potential for future urbanization, and is therefore crucial for coastal managers and planners

Integrating ecosystem services and climate change responses in coastal wetlands development plans for Bangladesh

This study explores the integration of ecosystem services and climate change adaptation in development plans for coastal wetlands in Bangladesh. A new response framework for adaptation is proposed, based on an empirical analysis and consultations with stakeholders, using a modified version of the DPSIR (Driver-Pressure-State-Impact-Response) framework. The framework is tested in the Narail district of Bangladesh, where temperature has increased by about 1 0C in the summer in combination with an increase in rainfall of 0.70 mm day-1 yr-1 in the last decade. Calibrated model (MAGICC/SENGEN) projections forecast, on average, a temperature increase of up to 5 0C and an increase in rainfall of 25% by the end of this century. Water diversion in the upstream regions of the Ganges delta contributes to increase water scarcity in the dry season. Enhanced rainfall and the immense pressure of water discharges from upstream water sources are increasing the risk of floods and river erosion in the dry season. An increase in the water holding capacity of rivers, wetlands and canals by dredging is urgently required. The empirical model of this study is intended to support adaptation planning in Bangladesh and can be used in other data-poor areas which will suffer from climate change