Special Issue "Geospatial Monitoring and Modelling of Environmental Change"

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

Deadline for manuscript submissions: closed (31 December 2012)

Special Issue Editor

Guest Editor
Dr. Duccio Rocchini (Website)

GIS and Remote Sensing Unit, Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Fondazione Edmund Mach, Via Mach 1, 38010 San Michele all'Adige (TN), Italy
Fax: +39 3491425786
Interests: ecological Informatics; ecological heterogeneity and biodiversity estimate by satellite imagery; Free and Open Source Software for spatial ecology; statistical analysis of spatial and ecological data

Special Issue Information

Dear Colleagues,

Geospatial modelling came out with a throughput of analysis approaches to monitor environmental change over time considering different fields of research, including computer science, remote sensing, ecology, environmental science, life science, geography. The aim of this special issue is to publish straightforward research or review papers on the matter in order to stimulate further discussion on the potential of geospatial modelling. It is my pleasure to encourage both theoretical and empirical papers on the matter with the support of the International Society for Photogrammetry and Remote Sensing, promoting an advanced forum for the science and technology of geographic information.

Dr. Duccio Rocchini
Guest Editor

Keywords

  • computer science
  • ecology
  • environmental science
  • life science
  • geography
  • geospatial modelling
  • monitoring
  • remote sensing

Published Papers (8 papers)

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Editorial

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Open AccessEditorial Introduction to the Special Issue: Geospatial Monitoring and Modeling of Environmental Change
ISPRS Int. J. Geo-Inf. 2014, 3(1), 206-208; doi:10.3390/ijgi3010206
Received: 22 November 2013 / Accepted: 23 November 2013 / Published: 6 February 2014
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Abstract
Geospatial modeling is an approach to apply analysis to monitor environmental change over time considering different fields of re-search, including computer science, remote sensing, ecology, environmental science, life science, geography (see [1,2] for a critique). The special issue was instigated to publish [...] Read more.
Geospatial modeling is an approach to apply analysis to monitor environmental change over time considering different fields of re-search, including computer science, remote sensing, ecology, environmental science, life science, geography (see [1,2] for a critique). The special issue was instigated to publish straightforward research on the matter in order to stimulate further discussion on the potential of geospatial modelling. Both theoretical and empirical papers are part of the issue with the support of the International Society for Photogrammetry and Remote Sensing, promoting an advanced forum for the science and technology of geographic information. [...] Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)

Research

Jump to: Editorial

Open AccessArticle Geospatial Narratives and Their Spatio-Temporal Dynamics: Commonsense Reasoning for High-Level Analyses in Geographic Information Systems
ISPRS Int. J. Geo-Inf. 2014, 3(1), 166-205; doi:10.3390/ijgi3010166
Received: 15 December 2013 / Revised: 17 January 2014 / Accepted: 28 January 2014 / Published: 6 February 2014
Cited by 8 | PDF Full-text (30503 KB) | HTML Full-text | XML Full-text
Abstract
The modeling, analysis and visualization of dynamic geospatial phenomenahas been identified as a key developmental challenge for next-generation GeographicInformation Systems (GIS). In this context, the envisaged paradigmatic extensions tocontemporary foundational GIS technology raises fundamental questions concerning theontological, formal representational and (analytical) computational [...] Read more.
The modeling, analysis and visualization of dynamic geospatial phenomenahas been identified as a key developmental challenge for next-generation GeographicInformation Systems (GIS). In this context, the envisaged paradigmatic extensions tocontemporary foundational GIS technology raises fundamental questions concerning theontological, formal representational and (analytical) computational methods that wouldunderlie their spatial information theoretic underpinnings. We present the conceptualoverview and architecture for the development of high-level semantic and qualitativeanalytical capabilities for dynamic geospatial domains. Building on formal methods in theareas of commonsense reasoning, qualitative reasoning, spatial and temporal representationand reasoning, reasoning about actions and change and computational models of narrative,we identify concrete theoretical and practical challenges that accrue in the context offormal reasoning about space, events, actions and change. With this as a basis and withinthe backdrop of an illustrated scenario involving the spatio-temporal dynamics of urbannarratives, we address specific problems and solution techniques chiefly involving qualitativeabstraction, data integration and spatial consistency and practical geospatial abduction. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle GeoMemories—A Platform for Visualizing Historical, Environmental and Geospatial Changes in the Italian Landscape
ISPRS Int. J. Geo-Inf. 2013, 2(2), 432-455; doi:10.3390/ijgi2020432
Received: 20 March 2013 / Revised: 25 April 2013 / Accepted: 27 April 2013 / Published: 21 May 2013
Cited by 4 | PDF Full-text (12643 KB) | HTML Full-text | XML Full-text
Abstract
The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize [...] Read more.
The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessCommunication Measuring Scale-Dependent Landscape Structure with Rao’s Quadratic Diversity
ISPRS Int. J. Geo-Inf. 2013, 2(2), 405-412; doi:10.3390/ijgi2020405
Received: 5 March 2013 / Revised: 3 May 2013 / Accepted: 6 May 2013 / Published: 14 May 2013
Cited by 3 | PDF Full-text (465 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we apply a special application of the Rao quadratic diversity for multiscale analysis of land use changes in a mixed agricultural-forest landscape in Central Italy. The proposed approach is similar to a block-size analysis of compositional diversity for which [...] Read more.
In this paper, we apply a special application of the Rao quadratic diversity for multiscale analysis of land use changes in a mixed agricultural-forest landscape in Central Italy. The proposed approach is similar to a block-size analysis of compositional diversity for which a given landscape is overlaid with a series of square grids composed of increasingly larger boxes. The combination of land cover classes in each box is recorded, and the Rao quadratic diversity is computed for the frequency distribution of the land cover classes at each box-size. Plotting compositional diversity versus box-size provides information on the scale-dependent pattern of the landscape. Since the proposed methodology is not severely influenced by the co-registration accuracy of the underlying data sets, it may prove to be reasonably adequate for analyzing historical data sets of varying resolution and quality, like aerial photographs or categorical maps. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches
ISPRS Int. J. Geo-Inf. 2013, 2(1), 220-236; doi:10.3390/ijgi2010220
Received: 1 January 2013 / Revised: 25 February 2013 / Accepted: 26 February 2013 / Published: 13 March 2013
Cited by 6 | PDF Full-text (1596 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in [...] Read more.
We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and object-based approaches. All pairs of species were separable based on spectral reflectance values in at least one band, with Peltophorum pterocarpum being most distinct from other species. Object-based approaches were consistently superior to pixel-based methods, which were particularly low in accuracy for tree species with small canopy sizes, such as Cocos nucifera and Roystonea regia. There was a strong and significant correlation between the number of trees determined on the ground and from object-based classification. Overall, object-based approaches appear capable of discriminating the six most common species in a challenging urban environment, with substantial heterogeneity of tree canopy sizes. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS)
ISPRS Int. J. Geo-Inf. 2013, 2(1), 201-219; doi:10.3390/ijgi2010201
Received: 1 January 2013 / Revised: 21 January 2013 / Accepted: 21 February 2013 / Published: 11 March 2013
Cited by 5 | PDF Full-text (1269 KB) | HTML Full-text | XML Full-text
Abstract
PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, [...] Read more.
PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS), Web Service Definition Language (WSDL)/Simple Object Access Protocol (SOAP)). The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle Quantifying Landscape-Scale Patterns of Temperate Forests over Time by Means of Neutral Simulation Models
ISPRS Int. J. Geo-Inf. 2013, 2(1), 94-109; doi:10.3390/ijgi2010094
Received: 1 January 2013 / Revised: 19 February 2013 / Accepted: 21 February 2013 / Published: 1 March 2013
Cited by 5 | PDF Full-text (547 KB) | HTML Full-text | XML Full-text
Abstract
Several studies attempt to describe changes in the spatial patterns of forests over time, resorting to the comparison of landscape pattern indices (LPI), but new methods for quantifying landscape differences in a statistical context are necessary. In this paper, we quantified and [...] Read more.
Several studies attempt to describe changes in the spatial patterns of forests over time, resorting to the comparison of landscape pattern indices (LPI), but new methods for quantifying landscape differences in a statistical context are necessary. In this paper, we quantified and assessed the statistical significance of the forests pattern changes, which have occurred since the end of WWII in Central Italy (Isernia). To do this; based on the proportion of forest cover (pi) and contagion (H) of three land cover maps (1954–1981–2006); we generated 100 forest maps with predictable results through the midpoint displacement algorithm. Then, for both observed and simulated maps, we computed a set of LPI (number of patches, cohesion, largest forest patch index and area weighted mean shape index) and we derived their empirical distributions; finally, we compared the empirical distributions using the non-parametric Kruskal-Wallis test. Our results show significant changes in the spatial pattern of forests and underline the process of natural forest re-growth, which, in the area, is constrained by “remnants” of traditional activities. The adopted approach could be extended to a large ensemble of landscapes and spatial scales and could become a standard procedure when comparing patterns in time. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
Open AccessArticle Assessing the Geographic Representativity of Farm Accountancy Data
ISPRS Int. J. Geo-Inf. 2013, 2(1), 50-66; doi:10.3390/ijgi2010050
Received: 6 December 2012 / Revised: 25 January 2013 / Accepted: 28 January 2013 / Published: 6 February 2013
Cited by 2 | PDF Full-text (612 KB) | HTML Full-text | XML Full-text
Abstract
The environment affects agriculture, via soils, weather, etc. and agriculture affects the environment locally at farm level and via its impact on climate change. Locating agriculture within its spatial environment is thus important for farmers and policy makers. Within the EU countries [...] Read more.
The environment affects agriculture, via soils, weather, etc. and agriculture affects the environment locally at farm level and via its impact on climate change. Locating agriculture within its spatial environment is thus important for farmers and policy makers. Within the EU countries collect detailed farm data to understand the technical and financial performance of farms; the Farm Accountancy Data Network. However, knowledge of the spatial-environmental context of these farms is reported at gross scale. In this paper, Irish farm accounting data is geo-referenced using address matching to a national address database. An analysis of the geographic distribution of the survey farms, illustrated through a novel 2D ranked pair plot of the coordinates, compared to the national distribution of farms shows a trend in the location of survey farms that leads to a statistical difference in the climatic variables associated with the farm. The farms in the survey have significantly higher accumulated solar radiation values than the national average. As a result, the survey may not be representative spatially of the pattern of environment x farm system. This could have important considerations when using FADN data in modelling climate change impacts on agri-economic performance. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)

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