Industry 4.0 has brought transformative changes across economic, environmental, and land use dimensions, driving innovations through IoT, AI, and cloud computing technologies. This revolution fosters economic growth, promotes circular economies, and integrates renewable energy technologies. However, these advancements present challenges, including rising e-waste, energy demands, and socio-economic disparities. The study uses a qualitative research approach, synthesizing insights from recent literature and employing comparative analysis. Sources include peer-reviewed articles, case studies, and industry reports focusing on the impacts of Industry 4.0 on urbanization, sustainability, and economic growth. Data from these studies have been analyzed to identify trends, challenges, and actionable solutions.
Industry 4.0 facilitates the development of new business models and improves operational efficiency through interconnectivity and analytics. Renewable energy technologies, precision agriculture, and real-time emissions monitoring showcase the environmental potential of this revolution. However, the reliance on data centers and rare earth resources highlights the ecological challenges. Figures in the article illustrate Industry 4.0’s cross-industry impacts and propose frameworks for sustainable production processes. Research materials provide details on the contributions of Industry 4.0 in enabling circular economies and improving resource management.
Policymakers and businesses must address the dual nature of Industry 4.0 by implementing e-waste regulations, investing in renewable energy, and ensuring equitable socio-economic benefits. Future research should focus on scalable energy storage, urban planning innovations, and reducing disparities between large corporations and SMEs. Industry 4.0 is reshaping global systems, offering immense potential for sustainable development. Achieving this requires a balanced approach that aligns technological advancements with ecological and social responsibilities.
Today, population growth, high urbanization rates, and global agenda issues have led to the intensive use of land and air and water spaces, and cadastral systems that manage the people–land relationship have evolved into a multi-purpose form that supports various land-based activities. This situation has necessitated the modernization of traditional land administration and cadastral systems to manage the people–land relationship effectively. This study conducts a literature review on current cadastral trends emerging from the perspective of modern land administration systems (LASs). A total of 367 studies published in the Web of Science (WoS) database in the last decade on 3D cadastre, technical infrastructure cadastre, maritime cadastre, public law restriction (PLR) cadastre, fit-for-purpose land management, and disaster-sensitive cadastral trends are analyzed. The study aims to analyze the interest of the land administration community in current cadastral trends and present the results. The analysis results show that the most researched trend is 3D cadastre, and the least researched trends are PLRs cadastre and disaster-responsive cadastre. LADM stands out as a widely used framework across the studies.
Alice Carlotta Tani, Giuseppe Pulighe, Concetta Cardillo
et al.
Agricultural production plays an important role in the global economy, contributing greatly to the supply of food resources and human well-being. Mapping the areas of agricultural coverage and calculating their respective average annual production values is useful for orienting food security strategies, in a context of climate change and a growing global population. Despite their importance, today no complete and updated maps exist for all types of crops. To provide this critical data lack, we have harmonized statistical datasets at a regional level of detail across Europe (EU-27) to develop a unified dataset consisting of the best available data in the context of agricultural monitoring activities carried out by the CREA. This document illustrates the methodologies adopted to create an harmonized database and an open and easy-to-use cartographic atlas of agricultural area and production, based on accessible, interoperable and reusable data available from Eurostat.
The availability of detailed maps of area and crop production at a regional level can help optimize a wide range of agricultural monitoring, ranging from early warning on phytopathological conditions, to assessment of crop conditions, to production forecasts and the assessment of damage caused by extreme weather events, agricultural statistics, agricultural insurance and climate mitigation and adaptation actions.
Building information extraction utilizing remote sensing technology has vital applications in many domains, such as urban planning, cadastral mapping, geographic information censuses, and land-cover change analysis. In recent years, deep learning algorithms with strong feature construction ability have been widely used in automatic building extraction. However, most methods using semantic segmentation networks cannot obtain object-level building information. Some instance segmentation networks rely on predefined detectors and have weak detection ability for buildings with complex shapes and multiple scales. In addition, the advantages of multi-modal remote sensing data have not been effectively exploited to improve model performance with limited training samples. To address the above problems, we proposed a CNN framework with an adaptive center point detector for the object-level extraction of buildings. The proposed framework combines object detection and semantic segmentation with multi-modal data, including high-resolution aerial images and LiDAR data, as inputs. Meanwhile, we developed novel modules to optimize and fuse multi-modal features. Specifically, the local spatial–spectral perceptron can mutually compensate for semantic information and spatial features. The cross-level global context module can enhance long-range feature dependence. The adaptive center point detector explicitly models deformable convolution to improve detection accuracy, especially for buildings with complex shapes. Furthermore, we constructed a building instance segmentation dataset using multi-modal data for model training and evaluation. Quantitative analysis and visualized results verified that the proposed network can improve the accuracy and efficiency of building instance segmentation.
In recent decades, Russia has experienced substantial transformations in agricultural land tenure. Post-Soviet reforms have shaped land distribution patterns but the impacts of these on agricultural use of land remain under-investigated. On a regional scale, there is still a knowledge gap in terms of knowing to what extent the variations in the compositions of agricultural land funds may be explained by changes in the acreage of other land categories. Using a case analysis of 82 of Russia’s territories from 2010 to 2018, the authors attempted to study the structural variations by picturing the compositions of regional land funds and mapping agricultural land distributions based on ranking “land activity”. Correlation analysis of centered log-ratio transformed compositional data revealed that in agriculture-oriented regions, the proportion of cropland was depressed by agriculture-to-urban and agriculture-to-industry land loss. In urbanized territories, the compositions of agricultural land funds were predominantly affected by changes in the acreage of industrial, transportation, and communication lands. In underpopulated territories in the north and far east of Russia, the acreages of cropland and perennial planting were strongly correlated with those of disturbed and barren lands. As the first attempt at such analysis in Russia, the conversion of cadastral classification data into land-rating values enabled the identification of region-to-region mismatches between the cadaster-based mapping and ranking-based distribution of agricultural lands.
Il fondo Michetti dell’Aerofototeca Nazionale prende il nome dal noto pittore abruzzese Francesco Paolo Michetti (1851-1929), attivo nel periodo postunitario. Artista di ingegno, è conosciuto per opere come Il voto (1883), La figlia di Jorio (1895), Le serpi (1900) e Gli storpi (1900), solo per citarne alcune. Michetti fu anche fotografo prolifico e il suo archivio fu oggetto delle ricerche, tra la fine degli anni Sessanta e la prima metà degli anni Settanta, della storica dell’arte Marina Miraglia (1938-2016). Fu proprio in occasione di tali ricerche che venne notato il fondo in questione nella residenza dell’artista, il Convento di Francavilla al Mare.
La riproduzione del fondo, eseguita dall’Aerofototeca nel 1967, costituisce
un prezioso frammento dell’archivio originale, smembrato nel 1985.
Si tratta di 80 scatti eseguiti tra il 1915 e il 1920 ca., tutti accumunati
da soggetti aeronautici (i dirigibili P, P4, P5, P7, P8, M, M1, M9,
M12, M13, M14, V1, V2; hangar e campi d’aviazione di Campalto,
Ciampino, Ferrara, Pescara, Spilimbergo, Vigna di Valle; particolari relativi ad equipaggiamento militare; riprese dall’alto di Asiago, Francavilla al Mare, Milano, Padova, Pavia, Pola, Roma, Torino, Verona e Venezia, Vigna di Valle).
The considerable diffusion of technologies that use drones as the carriers that make it possible to bring photogrammetric sensors to heights for the acquisition of territorial information is arousing interest in a production sector, that of geotopographic information, which like other sectors, needs to find new stimulus in order to renew itself.
The paper here proposed does not seek to analyse technical innovations of the sector, innovations allowed by new and increasingly efficient aircraft, by new sensors, by increasingly high performance software and more or less restrictive limitations imposed by the norms, all activities and regulations in rapid and, in some respects, tumultuous innovation and subject to other and more specific detail.
The authors instead wish to propose a reflection on the actual possibilities, in the not too distant future, of the transposition of these technologies within the sphere of cadastral activities, so as to allow the economies and positive findings on photogrammetric measurement within the procedures of conservation of the Italian Cadastre.
This work was drawn up within the framework of the activities of the CAT-APR Project, a scientific collaboration between the Revenue Agency and the Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio - Inter-university Department of Sciences, Project and Land Policies - (DIST) of the Polytechnic and the University of Turin, which has as its object the testing of surveying methodologies based on the use of remotely piloted aerial vehicles designed for possible use in the cadastral field.
Ivan Blečić, Arnaldo Cecchini, Giovanna Fancello
et al.
We propose a methodology for the evaluation of urban walkability, and the related software tool for decision and planning support. In the introduction, we discuss the relevance of the concept of walkability for urban quality of life, and attempt to place it within the framework of the capability approach. The central part of the article is dedicated to the presentation of the spatial multi-criteria evaluation model for walkability. Our construction of the walkability in the model proposes a certain change of perspective with regard to the methods suggested thus far: rather than evaluating how a place is walkable in itself, the walkability score we calculate reflects how and where to one can walk from that place, in other words, what is the walkability the place is endowed with. Therefore, the walkability score combines three components: (1) the number of available destinations (urban “opportunities”) reachable by foot; (2) their distances; and (3) the quality of pedestrian routes towards those destinations. The quality of pedestrian routes is evaluated on different attributes relevant for walkability, related to the characteristics of the streets and their surrounding environment which contribute to render the route pleasant, secure and attractive. By way of example, in the third part we present an example application on the city of Alghero (Italy).
Maurizio Pollino, Luigi La Porta, Emanuela Caiaffa
GIS methodologies and technologies are able to provide useful tools for the assessment of sea-waves energy potential, by evaluating both the exploitability of such resource, both the environmental/social impacts in open sea and/or
in the coastal areas.
The DSS-WebGIS application developed (called "Waves Energy") is a tool for providing and publishing different geospatial data, sharing information with a wide range of external user, in order to support specific tasks, such as forecasting,
new installations planning and existing infrastructures management.
Sergio Grauso, Vladimiro Verrubbi, Cinzia Crovato
et al.
The present work was aimed to test the operability of the RUSLE prediction model, on the basis of available data, in combination with different interpolation methods in the area of southern Lazio (central
Italy). The work was based on published rainfall, soil, land-cover and elevation data archives and on a quick supplementary soil sampling survey. The RUSLE factors were computed by means of different correlation formulae and algorithms. Despite the lack of information data, the obtained soil erosion map can provide a useful reference frame of the soil loss potential for regional planning purposes.
The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.
The contribution addresses the phenomenon of Voluntereed Geographic Information
explaining these new and burgeoning sources of information offers multidisciplinary scientists an unprecedented opportunity to conduct research on a variety of topics at multiple spatial and temporal scales. In particular the contribution refers to two COST Actions which have been recently activated on the subject which are
particularly relevant for the growing of the European scientific community.
Stefano Bonesso, Guglielmina Mutani, Tatsiana Hubina
et al.
Per pianificare l’utilizzo di tecnologie che sfruttano energia rinnovabile su un territorio, in particolare quelle che riguarda il solare, si possono utilizzare i software GIS (Sistemi Informativi Geografici) che consentono di analizzare e rappresentare un dato geo-riferito.
Potential of photovoltaic technologies on buildings’ roofs using geographic information systems (GIS) - In order to plan the diffusion of renewable energy technologies, geographic information systems (GIS) can be useful. In this study photovoltaic technologies in urban environments were examined, considering the shadows of urban contest and of territory orography evaluated with GIS (ESRI ArcGIS). The results of potential photovoltaic technologies strongly depend on input data but not always roof data are accurate. The aim of this workis to define a tool to improve the results of a GIS simulation on urban scale. To validate the procedure, the results were compared with data monitored by PERSIL project. The analysis was based on the use of geographic information systems, data scanner laser (LiDAR), and software for 3D reconstruction of the buildings.