No abstract

Information about green spaces available in a city is essential for urban planning. Urban green areas are generally assessed through environmental indicators that reflect the city's quality of life and urban comfort. A methodology based on 3D measure and analysis of green urban areas at the city scale is presented. Two products are proposed: (1) measuring current vegetation cover at ground level through object-oriented classification of WorldView-2 imagery; and (2) estimating potential green cover at rooftop level using 3D data obtained by LiDAR sensor. The methodology, implemented in Lisbon, Portugal, demonstrates that: (1) remote sensing imagery provides powerful tools for master planning and policy analysis regarding green urban area expansion; and (2) measures of urban sustainability cannot be solely based on indicators obtained from 2D geographical information. In fact, 2D urban indicators should be complemented by 3D modelling of geographic data.

Aerial photographs have been systematically collected from as early as the 1930s, providing a unique resource to describe changes in vegetation and land cover over extended periods of time. However, their use is often limited by technical constraints, such as the lack of ground control information and precise camera parameters, which hamper an accurate orthorectification of the raw imagery. Here, we describe the historical aerial photographs orthorectification (HAPO) workflow, based on a conventional photogrammetric procedure (the direct linear transformation (DLT) Method), integrated as a geographic information systems (GIS) procedure, in order to perform the image orientation and orthorectification, thereby converting historical aerial imagery into high-definition historical orthoimages. HAPO implementation is illustrated with an application to a rugged landscape in Portugal, where we aimed to produce land-cover maps using an aerial photograph coverage from 1947, as part of a study on long-term socioecological dynamics. We show that HAPO produces highly accurate orthoimages and discuss the wider usefulness of our framework in long-term socioecological research.

Due to strong improvements and developments achieved in the last decade, it is clear that applied research using remote sensing technology such as unmanned aerial vehicles (UAVs) can provide a flexible, efficient, non-destructive, and non-invasive means of acquiring geoscientific data, especially aerial imagery. Simultaneously, there has been an exponential increase in the development of sensors and instruments that can be installed in UAV platforms. By combining the aforementioned factors, unmanned aerial system (UAS) setups composed of UAVs, sensors, and ground control stations, have been increasingly used for remote sensing applications, with growing potential and abilities. This paper's overall goal is to identify advantages and challenges related to the use of UAVs for aerial imagery acquisition in forestry and coastal environments for preservation/prevention contexts. Moreover, the importance of monitoring these environments over time will be demonstrated. To achieve these goals, two case studies using UASs were conducted. The first focuses on phytosanitary problem detection and monitoring of chestnut tree health (Padrela region, Valpaços, Portugal). The acquired high-resolution imagery allowed for the identification of tree canopy cover decline by means of multi-temporal analysis. The second case study enabled the rigorous and non-evasive registry process of topographic changes that occurred in the sandspit of Cabedelo (Douro estuary, Porto, Portugal) in different time periods. The obtained results allow us to conclude that the UAS constitutes a low-cost, rigorous, and fairly autonomous form of remote sensing technology, capable of covering large geographical areas and acquiring high precision data to aid decision support systems in forestry preservation and coastal monitoring applications. Its swift evolution makes it a potential big player in remote sensing technologies today and in the near future.

No abstract

Soil erosion is a serious environmental problem. An estimation of the expected soil loss by water-caused erosion can be calculated considering the Revised Universal Soil Loss Equation (RUSLE). Geographical Information Systems (GIS) provide different tools to create categorical maps of soil erosion risk which help to study the risk assessment of soil loss. The objective of this study was to develop a GIS open source application (in QGIS), using the RUSLE methodology for estimating erosion rate at the watershed scale (desktop application) and provide the same application via web access (web application). The applications developed allow one to generate all the maps necessary to evaluate the soil erosion risk. Several libraries and algorithms from SEXTANTE were used to develop these applications. These applications were tested in Montalegre municipality (Portugal). The maps involved in RUSLE method-soil erosivity factor, soil erodibility factor, topographic factor, cover management factor, and support practices-were created. The estimated mean value of the soil loss obtained was 220 ton km(-2) year(-1) ranged from 0.27 to 1283 ton km(-2) year(-1). The results indicated that most of the study area (80 %) is characterized by very low soil erosion level (<321 ton km(-2) year(-1)) and in 4 % of the studied area the soil erosion was higher than 962 ton km(-2) year(-1). It was also concluded that areas with high slope values and bare soil are related with high level of erosion and the higher the P and C values, the higher the soil erosion percentage. The RUSLE web and the desktop application are freely available.

No abstract

Coastal zones are naturally dynamic and mobile systems exposed to natural factors (river flows, waves and storms) as well as human interventions that continuously reshape their morphology. Erosion phenomena related to extreme weather events and sediment scarcity are common, threatening buildings and infrastructures, as well as beaches, ecosystems and valuable wetland; conditions that pose challenges to coastal security and defence. Regular monitoring of coastal areas, assessment of their morphodynamics and identification of the processes influencing sediment transport are thus increasingly important for a better understanding of changes and evolutionary trends in coastal systems. This demands a multidisciplinary approach involving researchers with expertise in coastal processes and state-of-the-art observation technologies. In this paper state-of-the-art surveying methods for an efficient quantification of changes in coastal environments are described and evaluated, and two NW-Portuguese case studies are presented. Survey methods included: topographic surveys based on terrestrial videogrammetric mobile mapping and aerial photogrammetry; sub-tidal bathymetry with sonar imagery using an Autonomous Surface Vehicle (ASV); as well as field observations, with sediment sampling and beach characterisation. In the first case study, erosion/accretion patterns in the Douro estuary sand spit were analysed, considering its breakwater, river flow, wave and wind effects. Prior to the construction of a detached breakwater, the spit's morphodynamics was related to extreme river flow events, wave and wind conditions; afterwards the spit stabilized its shape and increased its area and volume. In the second case study the coast of Vila Nova de Gaia was broadly analysed, including the shoreface, foreshore and dunes, the characterization of major features and a short-period analysis of installed dynamics. Results obtained from field data, topographical surveys and numerical wave models were combined for an erosion risk assessment, using a methodology specifically developed for the study area. Both monitoring programs achieved their proposed objectives and provided valuable information to the local authorities, as gathered and processed information constitutes a valuable database for coastal planning and for ICZM purposes. They demonstrate the potential of several approaches, supported by advanced technologies, for the study of complex coastal morphodynamic processes.