A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations
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DICATECh, Politechnic of Bari, Via Orabona 4, 70125, BARI, Italy
GeoSNav Lab, University of Trieste, p.le Europa 1, 34127, TRIESTE, Italy
Online publication date: 2016-05-31
Publication date: 2016-06-01
Reports on Geodesy and Geoinformatics 2016;100:27-38
Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.
Balacco, G., Figorito, B., Tarantino, E., Gioia, A., & Iacobellis, V. (2015). Space-time LAI variability in Northern Puglia (Italy) from SPOT VGT data. Environmental Monitoring and Assessment, 187(7), 1-15.
Bank, W. (2003). Sustainable Development in a Dynamic World: Transforming Institutions, Growth, and Quality of Life: Oxford University Press.
Brandt, C. J., & Thornes, J. B. (1996). Mediterranean desertification and land use: John Wiley & Sons Ltd.
Caradonna, G., Figorito, B., & Tarantino, E. (2015). Sharing Environmental Geospatial Data Through an Open Source WebGIS. In Computational Science and Its Applications--ICCSA 2015 (pp. 556-565). Springer International Publishing.
Chang, G., & Caneday, L. (2012). Web-Based GIS in Tourism Information Search: An analysis of the effect of socioeconomic characteristics on perception and behavior. Loisir et Société/Society and Leisure, 35(1), 155-174.
Chen, W., Sakai, T., Moriya, K., Koyama, L., & Cao, C. (2013). Estimation of vegetation coverage in semi-arid sandy land based on multivariate statistical modeling using remote sensing data. Environmental Modeling & Assessment, 18(5), 547-558.
Coscarelli, R., Caloiero, T., Minervino, I., & Sorriso-Valvo, M. (2015). Sensitivity to desertification of a high productivity area in Southern Italy. Journal of Maps, 1-9.
Figorito, B., Mancini, F., Novelli, A., & Tarantino, E. (2014). Monitoring land cover changes at watershed scale using LANDSAT imagery. Score@Poliba.
Han, L., Zhang, Z., Zhang, Q., & Wan, X. (2015). Desertification assessments in the Hexi corridor of northern China’s Gansu Province by remote sensing. Natural Hazards, 75(3), 2715-2731.
Harris, A., Carr, A., & Dash, J. (2014). Remote sensing of vegetation cover dynamics and resilience across southern Africa. International Journal of Applied Earth Observation and Geoinformation, 28, 131-139.
Hu, X., & Weng, Q. (2009). Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks. Remote Sensing of Environment, 113(10), 2089-2102. Retrieved from http://www.sciencedirect.com/s....
Im, J., Jensen, J. R., Jensen, R. R., Gladden, J., Waugh, J., & Serrato, M. (2012). Vegetation cover analysis of hazardous waste sites in Utah and Arizona using hyperspectral remote sensing. Remote Sensing, 4(2), 327-353.
Kavzoglu, T., & Mather, P. (2003). The use of backpropagating artificial neural networks in land cover classification. International journal of remote sensing, 24(23), 4907-4938.
Kosmas, C., Kirkby, M. J., & Geeson, N. (1999). The Medalus Project: Mediterranean Desertification and Land Use: Manual on Key Indicators of Desertification and Mapping Environmentally Sensitive Areas to Desertification: Directorate-General Science, Research and Development.
Ladisa, G., Todorovic, M., & Trisorio Liuzzi, G. (2012). A GIS-based approach for desertification risk assessment in Apulia region, SE Italy. Physics and Chemistry of the Earth, Parts A/B/C, 49, 103-113. doi: http://dx.doi.org/10.1016/j.pc....
Lam, D. K., Remmel, T. K., & Drezner, T. D. (2010). Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach. Remote Sensing, 3(1), 1-13.
Lamchin, M., Lee, J.-Y., Lee, W.-K., Lee, E. J., Kim, M., Lim, C.-H., Kim, S.-R. (2016). Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia. Advances in Space Research, 57(1), 64-77.
Liu, Y., Gao, J., & Yang, Y. (2003). A holistic approach towards assessment of severity of land degradation along the Great Wall in Northern Shaanxi Province, China. Environmental Monitoring and Assessment, 82(2), 187-202.
Maisongrande, P., Duchemin, B., & Dedieu, G. (2004). VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products. International Journal of Remote Sensing, 25(1), 9-14.
Mathiyalagan, V., Grunwald, S., Reddy, K., & Bloom, S. (2005). A WebGIS and geodatabase for Florida's wetlands. Computers and electronics in agriculture, 47(1), 69-75.
Meyer, W. B., & Turner, B. L. (1992). Human population growth and global landuse/ cover change. Annual review of ecology and systematics, 23, 39-61.
Muthumanickam, D., Kannan, P., Kumaraperumal, R., Natarajan, S., Sivasamy, R., & Poongodi, C. (2011). Drought assessment and monitoring through remote sensing and GIS in western tracts of Tamil Nadu, India. International journal of remote sensing, 32(18), 5157-5176.
Orellana, F. J., Del Sagrado, J., & Del ÁGuila, I. M. (2011). SAIFA: A web-based system for Integrated Production of olive cultivation. Computers and electronics in agriculture, 78(2), 231-237.
Perovic, V., Jaramaz, D., Zivotic, L., Cakmak, D., Mrvic, V., Milanovic, M., & Saljnikov, E. (2016). Design and implementation of WebGIS technologies in evaluation of erosion intensity in the municipality of NIS (Serbia). Environmental Earth Sciences, 75(3), 1-12.
Sepehr, A., Hassanli, A., Ekhtesasi, M., & Jamali, J. (2007). Quantitative assessment of desertification in south of Iran using MEDALUS method. Environmental Monitoring and Assessment, 134(1-3), 243-254. Retrieved from http://link.springer.com/artic....
Sharma, S. A., & Mishra, S. (2012). Web-GIS based monitoring of vegetation using NDVI profiles. Journal of Geomatics, 6(2), 109-112.
Simeoni, L., Floretta, C., & Zatelli, P. (2011). Spatial database and web-GIS for managing and validating river embankment monitoring data. In Proc. of the 8th International Symposium on Field Measurements in Geomechanics.
Simeoni, L., Zatelli, P., & Floretta, C. (2014). Field measurements in river embankments: validation and management with spatial database and webGIS.Natural hazards, 71(3), 1453-1473.
Sombroek, W., & Sene, E. (1993). Land degradation in arid, semi-arid and dry subhumid areas: rainfed and irrigated lands, rangelands and woodlands. Paper presented at the Inter-Governmental Negotiating Committee for the Preparation of a Convention to Combat Desertification and Drought. Substantive Sess. 1, Nairobi (Kenya), 24 May-4 Jun 1993.
Soto-Garcia, M., Del-Amor-Saavedra, P., Martin-Gorriz, B., & Martínez-Alvarez, V. (2013). The role of information and communication technologies in the modernisation of water user associations’ management. Computers and electronics in agriculture, 98, 121-130.
Tan, K. C., San Lim, H., MatJafri, M. Z., & Abdullah, K. (2012). A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery. Environmental monitoring and assessment, 184(6), 3813-3829.
Tarantino, E., Novelli, A., Aquilino, M., Figorito, B., & Fratino, U. (2015). Comparing the MLC and JavaNNS Approaches in Classifying Multi-Temporal LANDSAT Satellite Imagery over an Ephemeral River Area. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 6(4), 83-102.
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150.
Turner, B. L., Skole, D., Sanderson, S., Fischer, G., Fresco, L., & Leemans, R. (1995). Land-use and land-cover change. Science/Research Plan. Global Change Report (Sweden).
Van der Knijff, J., Jones, R., & Montanarella, L. (2000). Soil erosion risk assessment in Europe: European Soil Bureau, European Commission Belgium.
Varghese, N., & Singh, N. P. (2016). Linkages between land use changes, desertification and human development in the Thar Desert Region of India. Land Use Policy, 51, 18-25.
Weiers, S., Bock, M., Wissen, M., & Rossner, G. (2004). Mapping and indicator approaches for the assessment of habitats at different scales using remote sensing and GIS methods. Landscape and Urban Planning, 67(1), 43-65.
Wheeler, D. A. (2007). Why Open Source Software/Free Software (OSS/FS)? Look at the Numbers! http://www.dwheeler.com/oss_fs....
Zalidis, G., Stamatiadis, S., Takavakoglou, V., Eskridge, K., & Misopolinos, N. (2002). Impacts of agricultural practices on soil and water quality in the Mediterranean region and proposed assessment methodology. Agriculture, Ecosystems & Environment, 88(2), 137-146.
Zhang, J., & Foody, G. (2001). Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and artificial neural network approaches. International journal of remote sensing, 22(4), 615-628.
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