Geospatial analysis from space: Advanced approaches for data processing, information extraction and interpretation

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Introduction

EO techniques offer cost-effective means to geographers, cartographers, GIS specialists, etc. for obtaining useful data that can be easily and systematically updated for the whole globe and applied to a large variety of investigation fields. In particular, the use of satellite data along with spatial analysis techniques can be very useful for environmental monitoring, planning purposes, risk estimation, disaster management, etc. which require updated information and timely reporting at a very detailed level. Nevertheless, the exploitation of satellite Earth Observation in the field of geospatial analysis is a relatively new tool, although it can provide invaluable information for both traditional and new, strategic, challenging applications. One of the most strategic challenges to be addressed is the importance of monitoring the Earth's surface at multiple temporal and spatial scales, from global down to a local level using multiple sensors along with ancillary data source. Intensive and extensive investigations of the huge amount of EO data today available as well as the integration from multiple missions, and the exploration of long time-series ask for novel solutions for the management, analysis and information retrieval. The current availability of time series, often available free of charge from national and international space agency (see, for example, NASA, CNES, etc.) for the whole globe or large areas of the Earth's surface have created great interest in their use for a number of applications encompassing oceans, land, ice and the atmosphere, focused on environmental monitoring, including climate, biodiversity, natural resource management, agricultural studies, urban sprawl, disaster management, human settlements and archaeological investigations.

In the analysis of satellite data, for a number of different applications, geospatial analysis can examine changes in homogeneity and measure the strength of the spatial relationship between values of the same variables. It is a very useful tool since it not only considers the value of the single pixel (reflectance, temperature, spectral index, etc.), but also the relationships between a given pixel and its surrounding in a fixed or variable window size. Geospatial techniques take into account the spatial attributes of geophysical parameters/geographical objects under investigation, evaluate and describe their relationship and spatial patterns. Thus providing information on the arrangement of individual entities in space and the spatial relationships among them also including the possibility to infer such patterns at different times for a given study area. As such, these techniques provide: (i) indicators of spatial patterns and (ii) key information for understanding the spatial processes underlying the distribution of object/feature/site/patterns and/or a given phenomenon under observation, from a local to a global view. In this context, the inclusion of remote sensing data in geospatial sciences and vice versa can not only provide new tools for a number of investigations, but also improve our knowledge, change our vision of geophysical processes and our perception of the phenomena under observation.

In order to better focalize these issues and strategic challenges, Sections 2 Geospatial analysis: a short overview, 3 Satellite remote sensing data and processing: a short overview provides short notes on the main geospatial tools and EO data and processing, respectively; whereas Section 4 provides a synthetic overview of the eight papers of this special issue.

Section snippets

Geospatial analysis: a short overview

Geospatial analysis and tools in “the modern conception” are available since the sixties and they leaded revolutionary approaches in the field of geospatial science. In the mid-1960s, in Canada and the USA there were the first developments on computer graphics and spatial analysis. In particular, the first modern computerized GIS was developed in Canada and it is known as the Canada geographic information system (CGIS), whereas in the USA both raster (SYMAP) and vector GIS (ODYSSEY) systems

Satellite remote sensing data and processing: a short overview

Over the years, a large number of satellite remote sensing missions have been operative thus providing a large amount of remotely sensed data with continuous improvement in the radiometric, spectral and spatial capabilities of the systems. This leads to the possibility of using satellite data for studying the temporal evolution of environmental and man-made systems on short, medium or long timescales. Moreover, as general considerations compared to other measurements technologies, satellite

The special issue

This special issue is made up of eight papers mainly focused on environmental monitoring which cover different methodological approaches applied to remotely sensed data spanning from satellite time series of MODIS, Vegetation and GPS to Very High Resolution (VHR) data both in space (as quickbird) and spectral (as Hyperion) resolution.

Several papers focus on the assessment of spatio-temporal variability in land surface parameters, to study the spatio-temporal variability in energy fluxes (Van De

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