ISPRS Int. J. Geo-Inf.2014, 3(3), 1139-1153; doi:10.3390/ijgi3031139 - published 19 September 2014 Show/Hide Abstract
Abstract: Recent studies indicate that positive relationships between invasive plants and soil can contribute to further plant invasions. However, it remains unclear whether these relations remain unchanged throughout the growing season. In this study, spatial sequences of field observations along a transect were used to reveal seasonal interactions and spatially covarying relations between one common invasive shrub (Tartarian Honeysuckle, Lonicera tatarica) and soil moisture in a tall grassland habitat. Statistical analysis over the transect shows that the contrast between soil moisture in shrub and herbaceous patches vary with season and precipitation. Overall, a negatively covarying relationship between shrub and soil moisture (i.e., drier surface soils at shrub microsites) exists during the very early growing period (e.g., May), while in summer a positively covarying phenomenon (i.e., wetter soils under shrubs) is usually evident, but could be weakened or vanish during long precipitation-free periods. If there is sufficient rainfall, surface soil moisture and leaf area index (LAI) often spatially covary with significant spatial oscillations at an invariant scale (which is governed by the shrub spatial pattern and is about 8 m), but their phase relation in space varies with season, consistent with the seasonal variability of the co-varying phenomena between shrub invasion and soil water content. The findings are important for establishing a more complete picture of how shrub invasion affects soil moisture.
ISPRS Int. J. Geo-Inf.2014, 3(3), 1122-1138; doi:10.3390/ijgi3031122 - published 19 September 2014 Show/Hide Abstract
Abstract: Analysis of land cover change is one of the major challenges in the remote sensing and GIS domain, especially when multi-temporal or multi-sensor analyses are conducted. One of the reasons is that errors and inaccuracies from multiple datasets (for instance caused by sensor bias or spatial misregistration) accumulate and can lead to a high amount of erroneous change. A promising approach to counter this challenge is to quantify and visualize uncertainty, i.e., to deal with imperfection instead of ignoring it. Currently, in GIS the incorporation of uncertainty into change analysis is not easily possible. We present a concept for uncertainty-aware change analysis using a geovisual analytics (GVA) approach. It is based on two main elements: first, closer integration of change detection and analysis steps; and second, visual communication of uncertainty during analysis. Potential benefits include better-informed change analysis, support for choosing change detection parameters and reduction of erroneous change by filtering. In a case study with a change scenario in an area near Hamburg, Germany, we demonstrate how erroneous change can be filtered out using uncertainty. For this, we implemented a software prototype according to the concept presented. We discuss the potential and limitations of the concept and provide recommendations for future work.
ISPRS Int. J. Geo-Inf.2014, 3(3), 1118-1121; doi:10.3390/ijgi3031118 - published 16 September 2014 Show/Hide Abstract
Abstract: This special issue of the ISPRS International Journal of Geographic Information about “Coastal GIS” is motivated by many circumstances. More than one-half of the world’s human population lives in coastal areas (within 200 kilometers of coast) as of 2000 . The trend toward coastal habitation is expected to continue in the US with the total being 75 percent by 2025, meaning that coastal human–environment interactions will likely increase and intensify . Geographic information systems (GIS) are being developed and used by technical specialists, stakeholder publics, and executive/policy decision makers for improving our understanding and management of coastal areas, separately and together as more organizations focus on improving the sustainability and resilience of coastal systems. Coastal systems—defined as the area of land closely connected to the sea, including barrier islands, wetlands, mudflats, beaches, estuaries, cities, towns, recreational areas, and maritime facilities, the continental seas and shelves, and the overlying atmosphere—are subject to complex and dynamic interactions among natural and human-driven processes. Coastal systems are crucial to regional and national economies, hosting valued human-built infrastructure and providing ecosystem services that sustain human well-being. This special issue of IJGI about coastal GIS presents a collection of nine papers that address many of the issues mentioned above. [...]
ISPRS Int. J. Geo-Inf.2014, 3(3), 1101-1117; doi:10.3390/ijgi3031101 - published 10 September 2014 Show/Hide Abstract
Abstract: Growing food in urban areas could solve a multitude of social and environmental problems. These potential benefits have resulted in an increased demand for urban agriculture (UA), though quantitative data is lacking on the feasibility of conversion to large-scale practices. This study uses multiple land use scenarios to determine different spaces that could be allocated to vegetable production in Montréal, including residential gardens, industrial rooftops and vacant space. Considering a range of both soil-bound and hydroponic yields, the ability of these scenarios to render Montréal self-sufficient in terms of vegetable production is assessed. The results show that the island could easily satisfy its vegetable demand if hydroponics are implemented on industrial rooftops, though these operations are generally costly. Using only vacant space, however, also has the potential to meet the city’s demand and requires lower operating costs. A performance index was developed to evaluate the potential of each borough to meet its own vegetable demand while still maintaining an elevated population density. Most boroughs outside of the downtown core are able to satisfy their vegetable demand efficiently due to their land use composition, though results vary greatly depending on the farming methods used, indicating the importance of farm management.
ISPRS Int. J. Geo-Inf.2014, 3(3), 1077-1100; doi:10.3390/ijgi3031077 - published 26 August 2014 Show/Hide Abstract
Abstract: Spatial information for coastal risk assessment is inherently uncertain. This uncertainty may be due to different spatial and temporal components of geospatial data and to their semantics. The spatial uncertainty can be expressed either quantitatively or qualitatively. Spatial uncertainty in coastal risk assessment itself arises from poor spatial representation of risk zones. Indeed, coastal risk is inherently a dynamic, complex, scale-dependent, and vague, phenomenon in concept. In addition, representing the associated zones with polygons having well-defined boundaries does not provide a realistic method for efficient and accurate representing of the risk. This paper proposes a conceptual framework, based on fuzzy set theory, to deal with the problems of ill-defined risk zone boundaries and the inherent uncertainty issues. To do so, the nature and level of uncertainty, as well as the way to model it are characterized. Then, a fuzzy representation method is developed where the membership functions are derived based on expert-knowledge. The proposed approach is then applied in the Perce region (Eastern Quebec, Canada) and results are presented and discussed.