- freely available
ISPRS Int. J. Geo-Inf. 2014, 3(1), 206-208; doi:10.3390/ijgi3010206
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.
Due to the complexity of the theme being treated, the final issue composes seven heterogeneous and stimulating papers on geospatial monitoring and modeling of environmental change.
Table 1 attempts to summarize the focus of each of the articles published.
|Table 1. Summary of the papers published in the special issue.|
|agriculture||a novel 2D ranked pair plot of coordinates to show and analyze the geographic distribution of farms|
|landscape ecology||natural forest e-growth analyzed by midpoint displacement algorithms|
|computer science||PyGRASS library as an object-oriented Python Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS)|
|urban ecology||application of multi-spectral GeoEye imagery for mapping urban tree species|
|landscape ecology||application of the Rao quadratic diversity for multiscale analysis of land use changes|
|computer science||web based services to digitally preserve historical aerial photographs|
|computer science||conceptual models for representing geospatial events and their changes over time|
The special issue included authors from 11 different institutions from the following countries: Germany, India, Ireland, Italy, Sweden, and USA. I am grateful to the whole Editorial office of the ISPRS International Journal of Geo-Information and to all the reviewers who supported the special issue with their skills, ensuring robust and challenging papers which will stimulate further discussion on geospatial monitoring and modelling of environmental change.
Conflict of Interest
The authors declare no conflict of interest.
- Rocchini, D.; Neteler, M. Let the four freedoms paradigm apply to ecology. Trends Ecol. Evol. 2012, 27, 310–311, doi:10.1016/j.tree.2012.03.009.
- Moss, R.H.; Edmonds, J.A.; Hibbard, K.A.; Manning, M.R.; Rose, S.K.; van Vuuren, D.P.; Carter, T.R.; Emori, S.; Kainuma, M.; Kram, T.; et al. The next generation of scenarios for climate change research and assessment. Nature 2010, 463, 747–756, doi:10.1038/nature08823.
- Green, S.; O’Donoghue, C. Assessing the geographic representativity of farm accountancy data. ISPRS Int. J. Geo-Inf. 2013, 2, 50–66, doi:10.3390/ijgi2010050.
- Frate, L.; Carranza, M.L. Quantifying landscape-scale patterns of temperate forests over time by means of neutral simulation models. ISPRS Int. J. Geo-Inf. 2013, 2, 94–109, doi:10.3390/ijgi2010094.
- Zambelli, P.; Gebbert, S.; Ciolli, M. 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, 201–219, doi:10.3390/ijgi2010201.
- Agarwal, S.; Vailshery, L.S.; Jaganmohan, M.; Nagendra, H. Mapping urban tree species using very high resolution satellite imagery: Comparing pixel-based and object-based approaches. ISPRS Int. J. Geo-Inf. 2013, 2, 220–236, doi:10.3390/ijgi2010220.
- Ricotta, C.; Carranza, M.L. Measuring scale-dependent landscape structure with Raos quadratic diversity. ISPRS Int. J. Geo-Inf. 2013, 2, 405–412, doi:10.3390/ijgi2020405.
- Abrate, M.; Bacciu, C.; Hast, A.; Marchetti, A.; Minutoli, S.; Tesconi, M. GeoMemories—A platform for visualizing historical, environmental and geospatial changes in the Italian landscape. ISPRS Int. J. Geo-Inf. 2013, 2, 432–455, doi:10.3390/ijgi2020432.
- Bhatt, M.; Wallgrn, J.O. Geospatial narratives and their spatio-temporal dynamics: Commonsense reasoning for high-level analyses in geographic information systems. ISPRS Int. J. Geo-Inf. 2014, 1, 166–205, doi:10.3390/ijgi3010166.
© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).