Spatial Analysis for Environmental Applications

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 November 2014) | Viewed by 53720

Special Issue Editor

International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
Interests: citizen science, crowdsourcing and volunteered geographic information (data collection, quality assessment, creating added value products with VGI, motivation and engagement, etc.); land cover/land use validation; creation of hybrid land cover products; serious gaming; sustainable development goals (SDGs)
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Special Issue Information

Dear Colleagues,

The last few decades have seen increasing greenhouse gas emissions, unprecedented losses in species, deforestation, degradation of soil through erosion and agricultural practices, and many issues related to water and air pollution. These environmental problems require sustainable solutions but inevitably involve tradeoffs between multiple competing objectives. This is further impacted by rising populations, increasing urbanization, wealthier populations and changing diets, all of which create a rising demand in natural resources, agriculture and other ecosystem services.

At the same time, developments in computing power/storage, the ubiquity of mobile phones and sensor networks, higher resolution satellite imagery (both spatially and temporally), and the movement towards open data and Volunteered Geographic Information (VGI) means that we have more environmental data at our disposal than ever before. This special issue will examine the state-of-the art in spatial analysis for solving the types of pressing environmental challenges outlined above, given the current technological and data rich era in which we find ourselves.

Papers in the special issue might consider questions such as: Are current methodologies sufficient or do we need to make a step change in the way we integrate, analyze and visualize environmental data? What new methods need to be developed in order to make optimal use of VGI? Are collaborative spaces with access to big data streams and contributed algorithms opening up new ways of doing research? What approaches outside of the more traditional spatial sciences can we apply to these problems? Papers can focus on applications, methods or more conceptual issues around solving environmental problems with spatial analysis.

Dr. Linda See
Guest Editor

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Keywords

  • spatial statistics
  • data mining
  • GeoComputation
  • visualization
  • volunteered geographic information
  • collaborative environments
  • cyberinfrastructure
  • ubiquitious and mobile sensing
  • environmental data streams (big and little)
  • ecosystem services
  • Digital Earth

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Published Papers (7 papers)

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Editorial

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106 KiB  
Editorial
Spatial Analysis as a Transformative Technology for Decision-Making in Environmental Domains
by Linda See
ISPRS Int. J. Geo-Inf. 2015, 4(3), 1770-1773; https://doi.org/10.3390/ijgi4031770 - 16 Sep 2015
Viewed by 4158
Abstract
Mankind is faced with many ongoing environmental challenges including climate change, losses in biodiversity, deforestation, increased soil erosion, and air and water pollution, to name but a few. [...] Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)

Research

Jump to: Editorial

6105 KiB  
Article
The Spatiotemporal Dynamics of Forest–Heathland Communities over 60 Years in Fontainebleau, France
by Samira Mobaied, Nathalie Machon, Arnault Lalanne and Bernard Riera
ISPRS Int. J. Geo-Inf. 2015, 4(2), 957-973; https://doi.org/10.3390/ijgi4020957 - 3 Jun 2015
Cited by 7 | Viewed by 6068
Abstract
According to the EU Habitats Directive, heathlands are “natural habitats of community interest”. Heathland management aims at conserving these habitats threatened by various changes, including successional processes leading to forest vegetation. We investigate the dynamics of woody species to the detriment of heathland [...] Read more.
According to the EU Habitats Directive, heathlands are “natural habitats of community interest”. Heathland management aims at conserving these habitats threatened by various changes, including successional processes leading to forest vegetation. We investigate the dynamics of woody species to the detriment of heathland over a period of 60 years in the Fontainebleau forest and we examine the effects of soil types, soil depth and topography parameters on heathland stability. We assess changes in forest cover between 1946 and 2003 by comparing vegetation maps derived from aerial photographs coupled to GIS analyses. The results show the loss of more than 75% of heathland during 1946–2003 due to tree colonisation of abandoned heathland. We detected differences in the dynamics of colonisation between coniferous and deciduous trees. The colonisation of heathland by coniferous species was faster over the last 20 years of our study period. Tree encroachment was faster in north-facing areas and in areas of acidic luvisols. While this dynamic was very slow in acid sandstone soils, heathland stability was more important in shallow soils on flat and south facing areas. Our study has the potential to assist land managers in selecting those heathland areas that will be easier to conserve and/or to restore by focusing on areas and spatial conditions that prevent forest colonisation and hence favour the long-term stability of heathland. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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3954 KiB  
Article
Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
by Paul Holloway and Jennifer A. Miller
ISPRS Int. J. Geo-Inf. 2015, 4(2), 783-798; https://doi.org/10.3390/ijgi4020783 - 5 May 2015
Cited by 15 | Viewed by 6698
Abstract
In this paper we explore relationships between bird species richness and environmental factors in New York State, focusing particularly on how spatial scale, autocorrelation and nonstationarity affect these relationships. We used spatial statistics, Getis-Ord Gi*(d), to investigate how [...] Read more.
In this paper we explore relationships between bird species richness and environmental factors in New York State, focusing particularly on how spatial scale, autocorrelation and nonstationarity affect these relationships. We used spatial statistics, Getis-Ord Gi*(d), to investigate how spatial scale affects the measurement of richness “hot-spots” and “cold-spots” (clusters of high and low species richness, respectively) and geographically weighted regression (GWR) to explore scale dependencies and nonstationarity in the relationships between richness and environmental variables such as climate and plant productivity. Finally, we introduce a geovisualization approach to show how these relationships are affected by spatial scale in order to understand the complex spatial patterns of species richness. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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4694 KiB  
Article
An Environmental Assessment of School Shade Tree Canopy and Implications for Sun Safety Policies: The Los Angeles Unified School District
by April Moreno, John Tangenberg, Brian N. Hilton and June K. Hilton
ISPRS Int. J. Geo-Inf. 2015, 4(2), 607-625; https://doi.org/10.3390/ijgi4020607 - 16 Apr 2015
Cited by 8 | Viewed by 9610
Abstract
In an effort to reforest school sites with limited resources, communities and non-profits have implemented projects on Los Angeles Unified School District (LAUSD) school sites, often without thought for the best location, long-term maintenance, or appropriateness of the tree type. Although studies exist [...] Read more.
In an effort to reforest school sites with limited resources, communities and non-profits have implemented projects on Los Angeles Unified School District (LAUSD) school sites, often without thought for the best location, long-term maintenance, or appropriateness of the tree type. Although studies exist related to sun safety policies in schools, there has been little emphasis on the environmental public health benefits of trees in public schools. The LAUSD School Shade Tree Canopy Study was a response to this issue in which data was analyzed (a total of 33,729 trees in the LAUSD were mapped) regarding tree canopy coverage, pervious/impervious areas, and buildings for 509 elementary schools to assess urban forestry management issues and environmental injustices within communities of the district. The results of these analyses indicate that there is a wide range of school site size, tree canopy coverage as a percentage of school site size, tree canopy coverage as a percentage of play area, and percentage of unpaved surface play areas (e.g., (~20%) of the schools have both (0.0%) tree canopy coverage play areas and 100% paved surfaces). This finding alone has implications in how the LAUSD may implement sun safe polices which would aid in preventing skin cancer and other adverse health outcomes for students within the school district. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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4348 KiB  
Article
Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management
by Marcelo Curtarelli, Joaquim Leão, Igor Ogashawara, João Lorenzzetti and José Stech
ISPRS Int. J. Geo-Inf. 2015, 4(1), 220-235; https://doi.org/10.3390/ijgi4010220 - 2 Feb 2015
Cited by 72 | Viewed by 9183
Abstract
The generation of reliable information for improving the understanding of hydroelectric reservoir dynamics is fundamental for guiding decision-makers to implement best management practices. In this way, we assessed the performance of different interpolation algorithms to map the bathymetry of the Tucuruí hydroelectric reservoir, [...] Read more.
The generation of reliable information for improving the understanding of hydroelectric reservoir dynamics is fundamental for guiding decision-makers to implement best management practices. In this way, we assessed the performance of different interpolation algorithms to map the bathymetry of the Tucuruí hydroelectric reservoir, located in the Brazilian Amazon, as an aid to manage and operate Amazonian reservoirs. We evaluated three different deterministic and one geostatistical algorithms. The performance of the algorithms was assessed through cross-validation and Monte Carlo Simulation. Finally, operational information was derived from the bathymetric grid with the best performance. The results showed that all interpolation methods were able to map important bathymetric features. The best performance was obtained with the geostatistical method (RMSE = 0.92 m). The information derived from the bathymetric map (e.g., the level-area and level-volume diagram and the three-dimensional grid) will allow for optimization of operational monitoring of the Tucuruí hydroelectric reservoir as well as the development of three-dimensional modeling studies. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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2214 KiB  
Article
Accuracy and Effort of Interpolation and Sampling: Can GIS Help Lower Field Costs?
by Greg Simpson and Yi Hwa Wu
ISPRS Int. J. Geo-Inf. 2014, 3(4), 1317-1333; https://doi.org/10.3390/ijgi3041317 - 5 Dec 2014
Cited by 25 | Viewed by 7943
Abstract
Sedimentation is a problem for all reservoirs in the Black Hills of South Dakota. Before working on sediment removal, a survey on the extent and distribution of the sediment is needed. Two sample lakes were used to determine which of three interpolation methods [...] Read more.
Sedimentation is a problem for all reservoirs in the Black Hills of South Dakota. Before working on sediment removal, a survey on the extent and distribution of the sediment is needed. Two sample lakes were used to determine which of three interpolation methods gave the most accurate volume results. A secondary goal was to see if fewer samples could be taken while still providing similar results. The smaller samples would mean less field time and thus lower costs. Subsamples of 50%, 33% and 25% were taken from the total samples and evaluated for the lowest Root Mean Squared Error values. Throughout the trials, the larger sample sizes generally showed better accuracy than smaller samples. Graphing the sediment volume estimates of the full sample, 50%, 33% and 25% showed little improvement after a sample of approximately 40%–50% when comparing the asymptote of the separate samples. When we used smaller subsamples the predicted sediment volumes were normally greater than the full sample volumes. It is suggested that when planning future sediment surveys, workers plan on gathering data at approximately every 5.21 meters. These sample sizes can be cut in half and still retain relative accuracy if time savings are needed. Volume estimates may slightly suffer with these reduced samples sizes, but the field work savings can be of benefit. Results from these surveys are used in prioritization of available funds for reclamation efforts. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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4022 KiB  
Article
Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio
by Diana Mitsova
ISPRS Int. J. Geo-Inf. 2014, 3(4), 1256-1277; https://doi.org/10.3390/ijgi3041256 - 4 Dec 2014
Cited by 31 | Viewed by 8717
Abstract
This research examines the impact of climate and land use change on watershed hydrology. Seasonal variability in mean streamflow discharge, 100-year flood, and 7Q10 low-flow of the East Fork Little Miami River watershed, Ohio was analyzed using simulated land cover change and climate [...] Read more.
This research examines the impact of climate and land use change on watershed hydrology. Seasonal variability in mean streamflow discharge, 100-year flood, and 7Q10 low-flow of the East Fork Little Miami River watershed, Ohio was analyzed using simulated land cover change and climate projections for 2030. Future urban growth in the Greater Cincinnati area, Ohio, by the year 2030 was projected using cellular automata. Projected land cover was incorporated into a calibrated BASINS-HSPF model. Downscaled climate projections of seven GCMs based on the assumptions of two IPCC greenhouse gas emissions scenarios were integrated through the BASINS Climate Assessment Tool (CAT). The discrete CAT output was used to specify a seed for a Monte Carlo simulation and derive probability density functions of anticipated seasonal hydrologic responses to account for uncertainty. Sensitivity analysis was conducted for a small catchment in the watershed using the Storm Water Management Model (SWMM) developed U.S. Environmental Protection Agency. The results indicated higher probability of exceeding the 100-year flood over the fall and winter months, and a likelihood of decreasing summer low flows. Full article
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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