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A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (10 March 2023) | Viewed by 36303

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Prof. Eufemia Tarantino

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Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Politecnico di Bari, Via Orabona 4, 70125 Bari, Italy
Interests: geomatics; optical remote sensing; pixel-based and geographic object-based image analysis (GEOBIA); UAV applications; digital photogrammetry and spatial analysis for water resource management
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Prof. Dr. Enrico Corrado Borgogno Mondino

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Department of Agricultural, Forest and Food Sciences, University of Turin, L. go Braccini 2, 10095 Grugliasco, Italy
Interests: remote sensing; spatial analysis and landscape planning; GIS; digital photogrammetry; precision farming; lidar
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Prof. Dr. Marco Scaioni

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Department of architecture, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy
Interests: photogrammetry; geomatics for geosciences; remote sensing of the built environment
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Dr. Alessandra Capolupo

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Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Politecnico di Bari, Via Orabona 4, 70125 Bari, Italy
Interests: remote sensing; photogrammetry; vegetation mapping; geoinformation; satellite image processing; spatial analysis for heavy metal detection
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Special Issue Information

Dear Colleagues,

This Special Issue entitled “Geomatics for Resource Monitoring and Management” will assemble high-level contributions related to the application of innovative Geomatics techniques for monitoring natural and artificial resources. Natural hazards and anthropogenic activities, possibly related to the ongoing climate change, are strongly modifying the Earth, with social, environmental and economic impacts at both local and global scales. To tackle them, there is a need for novel resource monitoring and management approaches and protocols, aimed at simplifying the extraction, processing, and accessing of geospatial information derived from remote/near/close-range sensors. A wide variety of data (mainly satellite) can be freely accessed through open archives, exploring a time range that makes them suitable to explore the mid-term effects of climate change. Some others may come from new data acquisition projects that are managed directly by users thanks to the substantial advancements in low-cost systems and sensors, for a more punctual and accurate description of limited areas, as well for validation/integration with spaceborne data sets. Consequently, in this Special Issue, we invite papers focusing on, but are not limited to, the following topics:

Remote and proximal sensors for geospatial data acquisition;
Systems for data processing, analysis and representation;
Multi-source and integrated approaches for monitoring and management of natural resources;
Techniques for 3D data acquisition and objects reconstruction/modelling;
Surveying methods for monitoring and documentation of the built environment;
Tools for geospatial data sharing;
Geomatics for environmental and urban modelling, risk management, and precision agriculture.

Prof. Dr. Eufemia Tarantino
Prof. Dr. Enrico Corrado Borgogno Mondino
Prof. Dr. Marco Scaioni
Dr. Alessandra Capolupo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

remote/proximal sensing
photogrammetry
disaster monitoring
hazards mitigation
monitoring
agriculture
forestry
time series
environmental monitoring
land cover
change detection
urban environment
downstream services
geomatics

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Published Papers (9 papers)

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Research

16 pages, 8982 KiB

Open AccessArticle

Thematic Comparison between ESA WorldCover 2020 Land Cover Product and a National Land Use Land Cover Map

by Diogo Duarte, Cidália Fonte, Hugo Costa and Mário Caetano

Land 2023, 12(2), 490; https://doi.org/10.3390/land12020490 - 16 Feb 2023

Cited by 11 | Viewed by 2776

Abstract

This work presents a comparison between a global and a national land cover map, namely the ESA WorldCover 2020 (WC20) and the Portuguese use/land cover map (Carta de Uso e Ocupação do Solo 2018) (COS18). Such a comparison is relevant given the current amount of publicly available LULC products (either national or global) where such comparative studies enable a better understanding regarding different sets of LULC information and their production, focus and characteristics, especially when comparing authoritative maps built by national mapping agencies and global land cover focused products. Moreover, this comparison is also aimed at complementing the global validation report released with the WC20 product, which focused on global and continental level accuracy assessments, with no additional information for specific countries. The maps were compared by following a framework composed by four steps: (1) class nomenclature harmonization, (2) computing cross-tabulation matrices between WC20 and the Portuguese map, (3) determining the area occupied by each harmonized class in each data source, and (4) visual comparison between the maps to illustrate their differences focusing on Portuguese landscape details. Some of the differences were due to the different minimum mapping unit ofCOS18 and WC20, different nomenclatures and focuses on either land use or land cover. Overall, the results show that while WC20 detail is able to distinguish small occurrences of artificial surfaces and grasslands within an urban environment, WC20 is often not able to distinguish sparse/individual trees from the neighboring cover, which is a common occurrence in the Portuguese landscape. While selecting a map, users should be aware that differences between maps can have a range of causes, such as scale, temporal reference, nomenclature and errors. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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16 pages, 3706 KiB

Open AccessArticle

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

by Dimitris Goussios and Ioannis Faraslis

Land 2022, 11(10), 1657; https://doi.org/10.3390/land11101657 - 25 Sep 2022

Cited by 7 | Viewed by 4772

Abstract

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. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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16 pages, 1246 KiB

Open AccessArticle

Selected Aspects of Carbon Stock Assessment in Aboveground Biomass

by Vilém Pechanec, Lenka Štěrbová, Jan Purkyt, Marcela Prokopová, Renata Včeláková, Ondřej Cudlín, Pavel Vyvlečka, Emil Cienciala and Pavel Cudlín

Land 2022, 11(1), 66; https://doi.org/10.3390/land11010066 - 2 Jan 2022

Cited by 11 | Viewed by 4041

Abstract

Given the significance of national carbon inventories, the importance of large-scale estimates of carbon stocks is increasing. Accurate biomass estimates are essential for tracking changes in the carbon stock through repeated assessment of carbon stock, widely used for both vegetation and soil, to estimate carbon sequestration. Objectives: The aim of our study was to determine the variability of several aspects of the carbon stock value when the input matrix was (1) expressed either as a vector or as a raster; (2) expressed as in local (1:10,000) or regional (1:100,000) scale data; and (3) rasterized with different pixel sizes of 1, 10, 100, and 1000 m. Method: The look-up table method, where expert carbon content values are attached to the mapped landscape matrix. Results: Different formats of input matrix did not show fundamental differences with exceptions of the biggest raster of size 1000 m for the local level. At the regional level, no differences were notable. Conclusions: The results contribute to the specification of best practices for the evaluation of carbon storage as a mitigation measure, as well as the implementation of national carbon inventories. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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22 pages, 13800 KiB

Open AccessArticle

Supporting Pro-Poor Reforms of Agricultural Systems in Eastern DRC (Africa) with Remotely Sensed Data: A Possible Contribution of Spatial Entropy to Interpret Land Management Practices

by Pietro De Marinis, Samuele De Petris, Filippo Sarvia, Giacinto Manfron, Evelyn Joan Momo, Tommaso Orusa, Gianmarco Corvino, Guido Sali and Enrico Mondino Borgogno

Land 2021, 10(12), 1368; https://doi.org/10.3390/land10121368 - 11 Dec 2021

Cited by 15 | Viewed by 3196

Abstract

In the eastern Democratic Republic of Congo, agriculture represents the most important economic sector, and land control can be considered a perpetual source of conflict. Knowledge of the existing production system distribution is fundamental for both informing national land tenure reforms and guiding more effective agricultural development interventions. The present paper focuses on existing agricultural production systems in Katoyi collectivity, Masisi territory, where returning Internally and Externally Displaced People are resettling. We aim to define a repeatable methodology for building evidence-based and updated knowledge concerning the spatial distribution of the two existing production systems: subsistence-oriented agriculture (SOA) and business-oriented agriculture (BOA). To this aim, we used a supervised object-based classification approach on remotely sensed Sentinel-2 imagery to classify land cover. To classify production systems further within the “agriculture” and “pasture” land use classes, binary classification based on an entropy value threshold was performed. An iterative approach was adopted to define the final H_NDVI threshold that minimised commission and omission errors and maximised overall accuracy and class separability. The methodology achieved acceptable observed accuracy (OA equal to 80–90% respectively for agricultural and pasture areas) in the assessment. SOA and BOA respectively covered 24.4 and 75.6% of the collectivity area (34,606 ha). The results conclude that land use and entropy analysis can draw an updated picture of existing land distribution among different production systems, supporting better-adapted intervention strategies in development cooperation and pro-poor agrarian land tenure reforms in conflict-ridden landscapes. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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23 pages, 128140 KiB

Open AccessEditor’s ChoiceArticle

Locating the Italian Radioactive Waste Repository: Issues and Perplexities Arisen from Open Data-Based Analyses about the TO-10 Site (NW Italy)

by Enrico Borgogno-Mondino, Andrea Borgia and Corrado Cigolini

Land 2021, 10(9), 932; https://doi.org/10.3390/land10090932 - 5 Sep 2021

Cited by 1 | Viewed by 4034

Abstract

Recently, Italy has started the procedure for the selection of suitable sites for hosting the National Repository for Low-Medium Activity Radioactive Wastes. Sogin spa, a public company, taking into account the criteria of the ISPRA Technical Guide no. 29, solicited by the EU Directive 2011/70/Euratom, has presented the CNAPI (National Map of the Potentially Suitable Areas) which has become operative since 5 January 2021. Sixty-seven sites were identified in Italy as potentially suitable for hosting the repository. Some criticalities immediately appeared concerning the properness of the selection. An analysis was, therefore, achieved to explore part of the rationales underlying the adopted procedure. A paradigmatic site, namely the TO-10 one (NW Italy), was chosen for the analysis, which highlighted significant anomalies affecting both the procedure rationales and its results. Since the selection process majorly relies on geographical data, attention was particularly paid on the role of official data from open archives. With reference to the most updated and detailed ones, we demonstrated that the Sogin procedure suffers from several critical points. In particular, with reference to the TO-10 site, we found that it cannot be absolutely considered to be suitable for hosting the National Deposit. In fact, it proved to match several exclusion criteria included in the ISPRA Technical Guide n. 29. These include: the potentially high “seismic risk” due to a “seismic gap” and complex tectonics associated with uplift (up to 1–1.5 mm/y); a highly vulnerable and extremely superficial groundwater table; a high permeability (10⁻²–10⁻³ m/s) of the cover sedimentary units; not proper buffer zones around local settlements. In spite of the local specificity of the analysis, results concerning procedure weaknesses are general. Consequently, we expect that they can be a stimulus for Sogin to more properly face the next steps of the selection procedure. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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14 pages, 12841 KiB

Open AccessArticle

Land Cover Mapping from Colorized CORONA Archived Greyscale Satellite Data and Feature Extraction Classification

by Athos Agapiou

Land 2021, 10(8), 771; https://doi.org/10.3390/land10080771 - 22 Jul 2021

Cited by 7 | Viewed by 3643

Abstract

Land cover mapping is often performed via satellite or aerial multispectral/hyperspectral datasets. This paper explores new potentials for the characterisation of land cover from archive greyscale satellite sources by using classification analysis of colourised images. In particular, a CORONA satellite image over Larnaca city in Cyprus was used for this study. The DeOldify Deep learning method embedded in the MyHeritage platform was initially applied to colourise the CORONA image. The new image was then compared against the original greyscale image across various quality metric methods. Then, the geometric correction of the CORONA coloured image was performed using common ground control points taken for aerial images. Later a segmentation process of the image was completed, while segments were selected and characterised for training purposes during the classification process. The latest was performed using the support vector machine (SVM) classifier. Five main land cover classes were selected: land, water, salt lake, vegetation, and urban areas. The overall results of the classification process were then evaluated. The results were very promising (>85 classification accuracy, 0.91 kappa coefficient). The outcomes show that this method can be implemented in any archive greyscale satellite or aerial image to characterise preview landscapes. These results are improved compared to other methods, such as using texture filters. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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20 pages, 7770 KiB

Open AccessArticle

Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR—II: Żelazny Most Tailings Dam

by Paolo Mazzanti, Benedetta Antonielli, Alessandra Sciortino, Stefano Scancella and Francesca Bozzano

Land 2021, 10(6), 654; https://doi.org/10.3390/land10060654 - 18 Jun 2021

Cited by 15 | Viewed by 3399

Abstract

The failures of tailings dams have a major negative impact on the economy, surrounding properties, and people’s lives, and therefore the monitoring of these facilities is crucial to mitigate the risk of failure, but this can be challenging due to their size and inaccessibility. In this work, the deformation processes at Żelazny Most tailings dam (Poland) were analyzed using satellite Ad-vanced Differential SAR Interferometry (A-DInSAR) from October 2014 to April 2019, showing that the dam is affected by both settlements (with a maximum rate of 30 mm/yr), and horizontal sliding in radial direction with respect to the ponds. The load of the tailings is pushing the dam forward along the glacio-tectonic shear planes located at depth, in the Pliocene clays, causing horizontal displacements at a rate up to 30 mm/yr, which could lead to a passive failure of the dam. The measured displacements have been compared with the ones observed by in situ data from the 90s to 2013, available in the literature. The outcomes indicate that intense localized deformations occur in the eastern and northern sectors of the dam, while the western sector is deforming evenly. Moreover, although the horizontal deformation had a slowdown from 2010 until 2013, it continued in 2014 to 2019 with recovered intensity. The upper and the recent embankments are affected by major settlements, possibly due to a lower consolidation degree of the most recent tailings and a larger thickness of compressible materials. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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20 pages, 48801 KiB

Open AccessFeature PaperArticle

Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR—I: Room and Pillar Mine District

by Benedetta Antonielli, Alessandra Sciortino, Stefano Scancella, Francesca Bozzano and Paolo Mazzanti

Land 2021, 10(6), 653; https://doi.org/10.3390/land10060653 - 18 Jun 2021

Cited by 15 | Viewed by 3453

Abstract

Mining exploitation leads to slow or rapid ground subsidence resulting from deformation until the collapse of underground post-mining voids following excavation activities. Satellite SAR interferometry capabilities for the evaluation of ground movements allows the monitoring of intensive surface mine subsidence and can provide new knowledge about the risks in the mining industry. This work integrates both conventional and advanced Differential SAR Interferometry (DInSAR) to study the ground subsidence in the Legnica Glogow Copper District (LGCD, Poland) by processing about 400 Sentinel-1 images from October 2014 to April 2019. Even without field data and information on past and ongoing excavation activities, the DInSAR approach allowed us to identify 30 troughs of subsidence, ranging from 500 m to 2.5 km in diameter, which in some cases, took place several times during the analyzed time span. The cumulative subsidence in 4 years and 7 months exceeds 70 cm in several zones of the LGCD. The sub-centimetric precision achieved by advanced analysis (A-DInSAR), allowed us to monitor the real extent of the mining influence area on the surface, with deformation velocities of up to 50 mm/year. The ground deformation detected at LGCD can be due to both mining-induced tremors and roof subsidence above the underground excavation rooms. As deformations do not occur concurrently with tremors, this can be related to excavation activities or to degradation of abandoned mines. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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17 pages, 9560 KiB

Open AccessArticle

Shoreline Dynamics in East Java Province, Indonesia, from 2000 to 2019 Using Multi-Sensor Remote Sensing Data

by Sanjiwana Arjasakusuma, Sandiaga Swahyu Kusuma, Siti Saringatin, Pramaditya Wicaksono, Bachtiar Wahyu Mutaqin and Raihan Rafif

Land 2021, 10(2), 100; https://doi.org/10.3390/land10020100 - 22 Jan 2021

Cited by 21 | Viewed by 5052

Abstract

Coastal regions are one of the most vulnerable areas to the effects of global warming, which is accompanied by an increase in mean sea level and changing shoreline configurations. In Indonesia, the socioeconomic importance of coastal regions where the most populated cities are located is high. However, shoreline changes in Indonesia are relatively understudied. In particular, detailed monitoring with remote sensing data is lacking despite the abundance of datasets and the availability of easily accessible cloud computing platforms such as the Google Earth Engine that are able to perform multi-temporal and multi-sensor mapping. Our study aimed to assess shoreline changes in East Java Province Indonesia from 2000 to 2019 using variables derived from a multi-sensor combination of optical remote sensing data (Landsat-7 ETM and Landsat-8 OLI) and radar data (ALOS Palsar and Sentinel-1 data). Random forest and GMO maximum entropy (GMO-Maxent) accuracy was assessed for the classification of land and water, and the land polygons from the best algorithm were used for deriving shorelines. In addition, shoreline changes were quantified using Digital Shoreline Analysis System (DSAS). Our results showed that coastal accretion is more profound than coastal erosion in East Java Province with average rates of change of +4.12 (end point rate, EPR) and +4.26 m/year (weighted linear rate, WLR) from 2000 to 2019. In addition, some parts of the shorelines in the study area experienced massive changes, especially in the deltas of the Bengawan Solo and Brantas/Porong river with rates of change (EPR) between −87.44 to +89.65 and −18.98 to +111.75 m/year, respectively. In the study areas, coastal erosion happened mostly in the mangrove and aquaculture areas, while the accreted areas were used mostly as aquaculture and mangrove areas. The massive shoreline changes in this area require better monitoring to mitigate the potential risks of coastal erosion and to better manage coastal sedimentation. Full article

(This article belongs to the Special Issue Geomatics for Resource Monitoring and Management)

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