The increased frequency of floods, landslides and avalanches recorded across Peru in the last decades suggests that the country is one of the most affected by El Niño-Southern Oscillation and its cascading hazards. Catastrophic floods that happened in Lima in 1997–1998 and 2017–2018 caused hundreds of fatalities and significant economic damage. In this paper, we test the hypothesis that information mined from satellite synthetic aperture radar (SAR) images can provide valuable input into the common workflow of flooding hazard assessment, and thus improve current methods for risk assessment in urban areas. The complete SAR image archives collected over the Rímac River basin by the European Space Agency (ESA)’s European Remote-Sensing (ERS-1/2) missions and the European Commission’s Copernicus Sentinel-1 constellation were screened. SAR backscatter color composites and ratio maps were created to identify change patterns occurred prior, during and after the catastrophic flooding events mentioned above. A total of 409 areas (58.50 km2) revealing change were mapped, including 197 changes (32.10 km2) due to flooding-related backscatter variations (flooded areas, increased water flow in the riverbed, and riverbank collapses and damage), and 212 (26.40 km2) due to other processes (e.g., new urban developments, construction of river embankments, other engineering works, vegetation changes). The areas inundated during the flooding events in 1997–1998 and 2017–2018 mostly concentrate along the riverbanks and plain, where low-lying topography and gentle slopes (≤5°), together with the presence of alluvial deposits, also indicate greater susceptibility to flooding. The accuracy in flood area delineation achieved with the proposed change detection method was assessed by comparison with the potential maximum flood extent map that was produced by Copernicus Emergency Management Service (EMS) in the framework of the Risk and Recovery Activation EMSN-038 during the March 2017 flood. All the observed spatial and temporal backscatter change patterns were interpreted through geospatial integration with ancillary data (topography, geology, permanent and seasonal water bodies, urban footprint, new urban development, roads and infrastructures, and population at the district level) and a risk classification map of Lima was produced. The map highlights the sectors of potential concern along the Rímac River, should flooding events of equal severity as those captured by SAR images occur in the future. Compared to published hazard maps made solely based on geological factors, this product has the advantage to embed event-based information and knowledge of the impacts of urbanization.

Reference

Alvan Romero, N.; Cigna, F.; Tapete, D. ERS-1/2 and Sentinel-1 SAR Data Mining for Flood Hazard and Risk Assessment in Lima, Peru. Appl. Sci. 2020, 10, 6598, doi:10.3390/app10186598

The availability of very high resolution (VHR) satellite imagery (<1m) has opened new vistas in large scale mapping and information management in urban environments. Buildings are the most essential dynamic incremental factor in urban environment and hence their extraction is the most challenging activity. Extracting the urban features particularly buildings using traditional pixel based classification approaches as a function of spectral tonal value produces relatively less accurate results for these VHR Imageries. The present study demonstrates the building extraction using Pleiades panchromatic (PAN) and multispectral stereo satellite datasets of highly planned and dense urban areas in parts of Chandigarh, India. The stereo datasets were processed in photogrammetric environment to obtain the Digital elevation Model (DEM) and corresponding orthoimages. DEM’s were generated at 0.5 m and 2.0 m from stereo PAN and multispectral datasets, respectively. The orthoimages thus generated were segmented using Object Based Image Analysis (OBIA) tools. The object primitives such as scale parameter, shape, textural parameters, DEM derivatives were used for segmentation and indices were used to determine threshold values for building fuzzy rules for building extraction and classification. The rule based classification was carried out with defined decision rules based on object primitives and fuzzy rules. Two different methods were utilized for performance evaluation of the proposed automatic building approach. Overall accuracy, correctness and completeness were evaluated for extracted buildings. It was observed that overall accuracy was higher (> 93%) in areas having larger buildings and sparse built-up as compared to areas having smaller buildings and dense built-up.

Rapid economic development and population growth lead to fast urban expansion in both urban and rural landscapes. Accurate and updated mapping of urban expansions is curtail in urban and territorial planning for sustainable and strategic urban development. Using Earth Observation (EO) technologies, classification of urban areas in a rural landscape is more challenging than big cities. In this regard, in this paper, we aim at assessing the integration of Sentinel-1 and Sentinel-2 satellite data for classifying small urban areas in rural landscape in Google Earth Engine (GEE). Images of close dates from Sentinel-1 and Sentinel-2 were selected, preprocessed, and integrated to develop a machine learning classification through a Support Vector Classification (SVM) classifier. We have also added vegetation indices to the investigated dataset. As a study area, two rural areas in the Republic of North Macedonia has been selected. The results showed that the integration of Sentinel-1 and Sentinel-2 performed better than Sentinel-2 alone, with accuracy higher than 90%. For future studies, we recommend testing the dataset to different study areas and adding different EO data for obtaining even higher accuracy.

Water has always been a critical resource for human groups and climate change could aggravate supply problems.

In this context, groundwater could be an important reservoir of water, especially given the dispersion of places where it can be obtained (namely springs).

Historically, places where groundwater is available have been marked by humans using built structures, with stone materials having a historically major role. These cultural objects tend to become a part of the collective memory and the historical record (when available) and frequently they stay on the original site along time (hence "marking a spot" for groundwater).

However, the development of major water supply structures, especially in the 20th century, promoted an overlook of these ancient water sources.

We present a general defence of the importance of recording and preserving cultural stone related to water sources, preferably in the original sites. Cultural stone could be seen as a potential exploration tool for groundwater. This should converge with historical information on the fountains’ discharge, with geological studies of the terrains and geochemical features of the groundwaters involved, in order to characterize the hydrogeological systems and their potential future use (including the preservation of water quality and properties). These issues should be vital factors in urban planning for the future.

The Biosphere Reserves are laboratories of sustainability that provide local solutions to global challenges such as climate change or the conservation of biodiversity. They promote research, education and the creation of communities of practice that jointly generate knowledge that may be applicable to cooperative decision-making at local scales.

The context of global COVID-19 pandemic posed a great challenge to all teaching and learning processes and so to the co-creation of knowledge. To counteract it, we developed an online teaching environment (webinar) to enhance the value of ecosystems and analyze the perception of youth, a key interest group in participatory governance of the territory, in relation to the provision of ecosystem services in the Biosphere Reserve in Indonesia.

We took the experience of the Programme "Ecosystem Services of Euskadi" as a reference and developed a questionnaire on the perception of the provision of ecosystem services. The results showed that the highest evaluation corresponded to “cultural services” and the most valued environmental unit was “primary and secondary forest”.

Our results contribute to establish a baseline to understand the relationship of youth with the territory within the framework of the MAB Programme and in addition, to set up an international scientific cooperation.

This experience showed that the promotion of online solutions can help counteract the global pandemic negative effects on teaching processes and also empower local actors, specially the youth which have a key present and future role in global sustainability processes, as well as in shared local management of the Biosphere Reserve.