Monitoring urban sprawl using simulated PROBA-V data

Urbanization proceeds currently at a rapid pace and the impact on natural ecosystems cannot be neglected. Consequently, it is important to be able to monitor the expansion of urban areas. Yet the process of extracting them from satellite imagery is not trivial. Urban is a non-uniform class with spectral proximity to barren land. In this article, a method for extracting urban areas from medium-resolution Earth observation data is presented. The information source is simulated data of the PROBA-V sensor. Visual and near-infrared bands are classified by the adaptive neuro-fuzzy inference system (ANFIS) neuro-fuzzy classifier into urban and non-urban classes. The method can overcome the main difficulty in similar efforts, i.e. the extensive commission errors of barren to the class urban. The main novelty relies on exploiting annual spectral variability of each land-use class at the pixel level. The basic assumption is that urban and barren areas may have similar spectral values but they have different phenological cycles. The overall accuracy obtained by the classification is 91.57% with a Cohen's kappa coefficient (khat) of 0.84. Sufficient correlation at the city level is also achieved. Change detection is also possible in terms of hot-spot identification, however marginally suitable for medium-sized cities

Integrated Remote Sensing and 3D GIS Methodology to Strengthen Public Participation and Identify Cultural Resources

In the context of territorial development, the construction of specific and competitive local resources is based on the identification of their intangible and material elements but also their links to the region. The connection between these links and local heritage, along with their spatial dimension, makes the active participation of residents in the entire process necessary. This paper presents the application of an integrated methodology that fosters the involvement of residents in a process of collecting relevant implicit information, with the assistance of experts, in order to identify cultural resources from different historical periods. This methodology is based on the synergy of three components: interdisciplinarity, local community participation, and the use of non-destructive cutting-edge technologies (remote sensing, UAV mapping, ground-penetrating radar, and 3D GIS interactive representations). The use of various methods and tools is organized in successive phases, the objective being the substantial participation of residents through 3D interactive visualisations of their area. 3D representations enable the activation of local memory in conjunction with the collection of information regarding location, type, and traces of cultural resources. The entire process validates the implicit information that guides the competent authorities and experts in the further search for more precise information, both from satellite data (high-resolution images) and images from subsurface mapping (ground-penetrating radar). The proposed methodology significantly accelerates the process of identifying cultural resources and provides a comprehensive picture to local government and cultural institutions about the area’s cultural resources and planning possibilities while reducing the failures and costs of the research process. © 2022 by the authors

The possible use of pilotless aircrafts for operative monitoring of soil productivity

As seen from a comprehensive review of literature sources, at the current stage of technological development and simplicity the pilotless aircrafts should be considered as a reliable tool for operative monitoring of soils and crops on fields and areas of small farms. The possibilities to use the imagery obtained by pilotless aircrafts are predetermined by a type of survey apparatus to a considerable extent. At present, the miniature survey apparatus permits to obtain images, the spectral resolution of which can be compatible with those obtained by satellites. Today, the images of pilotless aircrafts are used to give a visual assessment of any object to be surveyed. There are publications devoted to the computer analysis of images including those used for agricultural purposes. The experience is becoming common to use the imagery obtained by pilotless aircrafts and their computer analysis for constructing digital models of the field relief, monitoring over the soil erodibility and operative valuation of the agricultural crops state. Being compared with satellite imagery, the data of pilotless aircrafts have a number of advantages in aerial surveying. The major limits to use data obtained by pilotless aircrafts consist in insufficient miniaturization of the surveying apparatus and the fact that the monitoring cannot be organized to control over large areas

Urbanization in European regions based on night lights

Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night lights are used as a source to capture urbanization trends in European regions. The data are intercalibrated to form a comparable time series. The Sum of Lights (SoL) index is then calculated per region. To eliminate the problem of annual fluctuation, the overall and the decadal slope of the SoL trend are also calculated. The analysis of the results shows that there exist significantly diverse urbanization patterns within European regions that can be effectively captured by DMSP/OLS data. It is also shown that GDP and population are positively associated with urbanization in Europe, however less strongly at regional than national levels. Overall, the interpretation of SoL changes in the European regions is more complex compared to those in the developing parts of the globe, primarily due to differences in energy saving polices. © 2015 Elsevier B.V

Concentration of populations and economic activities, growth, and convergence in Europe using satellite-observed lighting

Using a unique data set of annual nighttime satellite images from the Defense Meteorological Satellite Program’s Operational Linescan System, this article, under the assumption that the density of sum of lights is a proxy for the concentration of populations and economic activities, provides empirically based evidence on the extent of concentration, growth and convergence in Europe between 1992 and 2012. We find that the concentration of populations and economic activities was associated with the level, density and growth of economic factors. Decomposing these economic factors, the agricultural sector, which was a sector resilient to economic recession, seems to have been the key determinant of concentration. Finally, there is strong evidence of divergence in concentration, implying that socioeconomic activities will continue to be concentrated in European urban areas. © 2019 Informa UK Limited, trading as Taylor & Francis Group

GIS-based weather radar siting procedure in mountainous terrain

This paper describes a weather radar siting procedure for a mountainous region in Greece using GIS. The established radar siting objectives consist of the detection and tracking of storms (rainstorms, hailstorms, and snowstorms) requiring operations at a low elevation angle as well as the detection of the vertical structure and evolution of a storm. Moreover, the objective includes precipitation intensity measurements and areal precipitation analysis, which is related to the incidence of permanent echoes and obstructions as well as to the maximum range achievable. Two types of siting criteria are employed; mainly strategic or regional criteria, and local criteria. The strategic criteria mainly consist of set back and communication considerations and local radar siting criteria include the area, geometry or morphology as well as local logistics and practical considerations. In this study, digitized maps of 1:100,000 scale with 100 m contour interval are used. These digitized contour data are used to build the Digital Terrain Model (DTM, raster image) and produce the three-dimensional visualization of the area. The potential sites for the weather radar installation are identified on this three-dimensional DTM. The potential radar sites are located in complex mountainous areas, which results in additional selection difficulties. The selected site and its alternative fulfill the established purposes using the above-mentioned criteria. (C) 2010 Published by Elsevier Ltd

Very high resolution satellite-based monitoring of crop (olive trees) evapotranspiration in precision agriculture

Remote Sensing contributes through the processing and analysis of very high spatial and spectral resolution time series satellite data to a decision support at field level. In this paper, in the olive tree farms of the Agricultural Association of Messolonghi-Nafpaktia, the extraction of Kc and various vegetation indices, such as chlorophyll and red-edge, are presented aiming at the assessment of crop evapotranspiration and irrigation/fertiliser inflows during a period of 24 months. The methodology includes the generation of red-edge, chlorophyll and FPAR indices based on the second NIR band of WV-2, and clustering. The so-called ETc(satellite) produced by using the reference ETo from FAO-56 Penman-Monteith equation, meteorological data set and Kc(satellite) extracted by NDVI utilising the red-edge and second NIR bands of WV-2, respectively. The dynamic ETd compared with ETc. The applied methodology proved to be very useful for the implementation and verification of AGRO 2.1 and 2.2 standards. Copyright © 2020 Inderscience Enterprises Ltd

Statistical analysis for satellite-index-based insurance to define damaged pasture thresholds

Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used in countries like the USA, Canada and Spain for damaged pasture and forage insurance over the last few years. This type of agricultural insurance is called satellite-index-based insurance (SIBI). In SIBI, the occurrence of damage is defined as normal distributions. In this work a pasture area at the north of the Community of Madrid (Spain) has been delimited by means of Moderate Resolution Imaging Spectroradiometer (MODIS) images. A statistical analysis of NDVI histograms was applied to seek for alternative distributions using the maximum likelihood method and 2 test. The results show that the normal distribution is not the optimal representation and the generalized extreme value (GEV) distribution presents a better fit through the year based on a quality estimator. A comparison between normal and GEV is shown with respect to the probability under a NDVI threshold value throughout the year. This suggests that an a priori distribution should not be selected and a percentile methodology should be used to define a NDVI damage threshold rather than the average and standard deviation, typically of normal distributions. © 2019 Author(s)