Using Spatial Autocorrelation Techniques and Multi-temporal Satellite Data for Analyzing Urban Sprawl

2012 ◽  
pp. 512-527 ◽  
Author(s):  
Gabriele Nolè ◽  
Maria Danese ◽  
Beniamino Murgante ◽  
Rosa Lasaponara ◽  
Antonio Lanorte
Keyword(s):  
Spatial Autocorrelation ◽  
Urban Sprawl ◽  
Satellite Data ◽  
Multi Temporal

Assessment of Urban Sprawl of Islamabad Metropolitan Area Using Multi-Sensor and Multi-Temporal Satellite Data

2011 ◽  
Vol 37 (1) ◽  
pp. 101-114 ◽  
Author(s):  
Mohsin Jamil Butt ◽  
Ahmad Waqas ◽  
Muhammad Farooq Iqbal ◽  
Gul Muhammad ◽  
M. A. K. Lodhi
Keyword(s):  
Metropolitan Area ◽  
Urban Sprawl ◽  
Satellite Data ◽  
Multi Temporal

Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000

2007 ◽  
Vol 73 (1-2) ◽  
pp. 91-100 ◽  
Author(s):  
Chandra Giri ◽  
Bruce Pengra ◽  
Zhiliang Zhu ◽  
Ashbindu Singh ◽  
Larry L. Tieszen
Keyword(s):  
Satellite Data ◽  
Forest Dynamics ◽  
Mangrove Forest ◽  
Multi Temporal ◽  
The Sundarbans

scholarly journals A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

2016 ◽  
Vol 100 (1) ◽  
pp. 27-38 ◽  
Author(s):  
Grazia Caradonna ◽  
Antonio Novelli ◽  
Eufemia Tarantino ◽  
Raffaela Cefalo ◽  
Umberto Fratino
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Geospatial Data ◽  
Usage Patterns ◽  
Mediterranean Regions ◽  
Multi Temporal ◽  
Using Data ◽  
Set Up

Abstract 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.

Early stage variable rate nitrogen fertilization of silage maize driven by multi-temporal clustering of archive satellite data

2017 ◽  
Vol 8 (2) ◽  
pp. 288-292 ◽  
Author(s):  
R. Casa ◽  
F. Pelosi ◽  
S. Pascucci ◽  
F. Fontana ◽  
F. Castaldi ◽  
...  
Keyword(s):  
Satellite Data ◽  
Nitrogen Fertilization ◽  
Early Stage ◽  
Central Italy ◽  
N Fertilization ◽  
Yield Potential ◽  
Variable Rate ◽  
Landsat Images ◽  
Silage Maize ◽  
Multi Temporal

Nitrogen fertilization of silage maize in Central Italy is typically carried out with two applications at early stages of crop development: 2nd (V2) and 6th (V6) leaf respectively. In such conditions, the crop has not yet fully covered the soil and proximal or remote sensing of the canopy is hindered by the strong soil background signal. There is thus great interest in rapid and inexpensive approaches to N fertilization prescription. Therefore, an indirect method for inferring information on yield potential and soil variability, through a field-based clustering of multi-temporal satellite data, has been developed using archive Landsat images to identify temporally constant patterns. This method is potentially useful for the creation of prescription maps. The usefulness of the method was evaluated during an N fertilisation field trial in Maccarese (Central Italy), in 2016. At the V2 stage, both uniform and variable rate applications were performed and compared. A pseudo-cross variogram and a standardized ordinary co-kriging methodology was used to highlight spatially variable significant differences among the treatments.

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