Digital Mapping Approach Research Articles

Assessing landslide susceptibility in northern Morocco: A geostatistical mapping approach in Al Hoceima-Ajdir

Landslides are a significant global risk due to their impact on nature, society, and the economy. The Al Hoceima-Ajdir region is highly susceptible to geohazards such as earthquakes and ground instabilities caused by local tectonic movements and specific climatic and geomorphological conditions. This study aims to assess landslide susceptibility in Al Hoceima-Ajdir using a digital mapping approach that integrates the geostatistical Frequency Ratio tool, geomatic tools, and field observations. The frequency ratio method, a widely used technique in geospatial analysis, evaluates the relative frequency of landslides based on the spatial distribution of conditioning factors such as slope, lithology and land use – land cover. This method calculates the ratio of the frequency of landslides within specific classes of these factors to their respective frequencies in the entire study area. This research introduces a novel susceptibility map highlighting major threats to several natural and touristic sites crucial to the region's socio-economic activities. The susceptibility map was developed by analyzing 40 historical landslides along various predisposing factors, including topographic, geo-hydrological, and anthropogenic parameters. The results identify areas prone to landslides and classify their susceptibility into five levels ranging from very high to very low, with each level indicating a different degree of risk and requiring a specific set of preventive measures. The reliability of this map was evaluated using the Receiver Operating Characteristics (ROC) method, demonstrating a high accuracy of 89%, further validated by field visits. This high-precision susceptibility map is significant for pre- and post-risk management, enhancing prevention and mitigation strategies. It also protects society, the economy, and the environment by providing a reliable regional planning and hazard management tool. The findings of this study offer a significant advancement in the methodology for landslide susceptibility assessment and present a model that can be adapted to other regions facing similar geohazards. The research underscores the importance of integrating geostatistical tools with field data to produce accurate and actionable susceptibility maps, benefitting the global scientific community by improving hazard prediction and management strategies.

Land-surface quantitative analysis for mapping and deciphering the construction processes of piedmont alluvial fans in the Anti-Lebanon Mountains

Land-surface quantitative analysis based on digital elevation model (DEM) has been applied for improving the geomorphological mapping of piedmont alluvial fans. Indeed, these fans are frequently along a mountain front, where a series of coalescing fans may eventually occur. The margins of adjacent fans are rather difficult to map, thus preventing accurate and meaningful quantification of fan morphometric properties such as fan area, length, and slope. These morphometric properties are essential for informing on the influence of climatic conditions and tectonic factors on the fan-building processes. Therefore, in this paper, we propose a quantitative digital mapping approach along a stretch of about 50 km in the southern front of the Anti-Lebanon Mountains. Here, the Geomorphological Map of Syria at 1:1,000,000 scale (1963) reported at least nine piedmont alluvial fans, but these were poorly characterized in terms of geomorphometric characteristics and construction processes. Adopting the 1-arcsec SRTMv3 DEM, we propose a four-step workflow to analyse the feeding catchments morphology and fan morphometry. In this manner, the identification and geomorphological mapping of coalescent piedmont fans as well as the recognition of the main construction process have been improved. The proposed approach can support geomorphological investigations of wide and inaccessible areas—especially where arid and semi-arid climate conditions prevail—as well as where socio-political issues may prevent effective field work.

Carbon Storage Patterns and Landscape Sustainability in Northeast Portugal: A Digital Mapping Approach

This study investigated the impact of regional land abandonment in northeast Portugal. It specifically focused on carbon sequestration opportunities in the Upper Sabor River Watershed, situated in the northeast of Portugal, amidst agricultural land abandonment. The study involved mapping the distribution of soil organic carbon (SOC) across four soil layers (0–5 cm, 5–10 cm, 10–20 cm, and 20–30 cm) at 120 sampling points. The quantification of SOC storage (measured in Mg C ha−1) allowed for an analysis of its relationship with various landscape characteristics, including elevation, land use and land cover (LULC), normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), topographic wetness index (TWI), and erosion risk (ER). Six statistical tests were employed, including multivariate approaches like Cubist and Random Forest, within different scenarios to assess carbon distribution within the watershed’s soils. These modeling results were then utilized to propose strategies aimed at enhancing soil carbon storage. Notably, a significant discrepancy was observed in the carbon content between areas at higher elevations (>1000 m) and those at lower elevations (<800 m). Additionally, the study found that the amount of carbon stored in agricultural soils was often significantly lower than in other land use categories, including forests, mountain herbaceous vegetation, pasture, and shrub communities. Analyzing bi- and multivariate scenarios, it was determined that the scenario with the greatest number of independent variables (set 6) yielded the lowest RMSE (root mean squared error), serving as a key indicator for evaluating predicted values against observed values. However, it is important to note that the independent variables used in set 4 (elevation, LULC, and NDVI) had reasonably similar values. Ultimately, the spatialization of the model from scenario 6 provided actionable insights for soil carbon conservation and enhancement across three distinct elevation levels.

Mapping perception. Innovative digital mapping approaches as urban investigation methods

This paper presents translation methods of innovative mapping approaches, from paper-based techniques from historical periods to the digital realm for 3 case studies: Bucharest, Lisbon and Rome. Such paper-based techniques are the 18th century’s city map of Rome (by Giambattista Nolli), the 1950s-60s psycho-geographical maps developed by situationists (Guy Debord) and novel visual layouts from architects and urban planners (Kevin Lynch, Saverio Muratori). A previous mapping developed by Bostenaru and Panagoupoulos (2014) of the 18th century Lisbon earthquake, based on a chronicle azulejos engraving of the event, is also considered as a base point for a more modern perception visualization of this location. Digital techniques include story maps and layered mapping. Several story maps types were investigated for walking or cycling tours. These kinds of tours are a method of investigation, more suitable in architecture than in geography, as reviewed for Rome. Photography is another such instrument and the path taken in the story map is suitable for this. The charted buildings span from 20th century heritage, to sites relevant for the effects of earthquakes, the latter for Bucharest and Lisbon. The Rapid Visual Screening method (RVS) focuses on the structural material in Bucharest, while heritage habitat approaches emphasize the role of green materials, for Lisbon and Rome. Innovations in the paper maps as well as scenario thinking (Helmuth Kahn) permit differentiating between emblematic and common buildings, which can be achieved digitally through story maps. As the example of Lisbon shows, a further step may be creating VR and 3D models or video content. In conclusion, these story map tools are useful to investigate layers of the city, for writing urban places.

Soil salinization monitoring method evolution at various spatial and temporal scales in arid context: a review

All across the world, and particularly in arid and semi-arid zones, the negative effects of agricultural productivity and unsustainable development have led to soil salinization, which is one of the critical environmental issues. Since the problem of salinization evolves at the scale of space and time, it is necessary to develop a comprehensive strategy for the sustainable development of irrigated areas. First, it is required to adopt a good evaluation of the spatiotemporal distribution. Several approaches and techniques have been developed to study this distribution under the effect of several natural and anthropogenic factors. The result gives emphasis to the techniques used for predicting and monitoring soil salinity throughout different regions in the world. There are two categories of laboratory methods: destructive methods and non-destructive methods. The field methods are non-destructive unless we keep the need to dig holes for instrumentation or sampling for the calibration of measurements and the validation of results. However, we can distinguish between fixed instruments (point method) and mobile instruments (spatial method) which were used for different purposes. Toward the late 1980s, several works have been undertaken in order to understand the spatial and temporal variabilities of soil salinity. There are methods of geophysical prospection and geostatistical analysis. The combination of these two methods remains effective until today. The latest results show that spatial methods were better than punctual methods. Also, there was a complementarity between digital mapping approaches and geophysical techniques for monitoring the spatiotemporal variation of soil salinity.

Digital Mapping of Techno-Economic Performance of a Water-Based Solar Photovoltaic/Thermal (PVT) System for Buildings over Large Geographical Cities

Solar photovoltaic thermal (PVT) is an emerging technology capable of producing electrical and thermal energy using a single collector. However, to achieve larger market penetration of this technology, it is imperative to have an understanding of the energetic performance for different climatic conditions and the economic performance under various financial scenarios. This paper thus presents a techno-economic evaluation of a typical water-based PVT system for a single-family house to generate electricity and domestic hot water applications in 85 locations worldwide. The simulations are performed using a validated tool with one-hour time step for output. The thermal performance of the collector is evaluated using energy utilization ratio and exergy efficiency as key performance indicators, which are further visualized by the digital mapping approach. The economic performance is assessed using net present value and payback period under two financial scenarios: (1) total system cost as a capital investment in the first year; (2) only 25% of total system cost is a capital investment and the remaining 75% investment is considered for a financing period with a certain interest rate. The results show that such a PVT system has better energy and exergy performance for the locations with a low annual ambient temperature and vice versa. Furthermore, it is seen that the system boundaries, such as load profile, hot water storage volume, etc., can have a significant effect on the annual energy production of the system. Economic analysis indicates that the average net present values per unit collector area are 1800 and 2200 EUR, respectively, among the 85 cities for financial model 1 and financial model 2. Nevertheless, from the payback period point of view, financial model 1 is recommended for locations with high interest rate. The study is helpful to set an understanding of general factors influencing the techno-economic performance dynamics of PVT systems for various locations.

Digital mapping of soil ecosystem services in Scotland using neural networks and relationship modelling—Part 1: Mapping of soil classes

AbstractA digital mapping approach was applied to soils in Scotland, producing maps at 100‐m resolution and different levels of classification. This used neural networks to predict fuzzy soil class weightings based upon site descriptors from existing soil survey data. The intention of this work was to produce a set of soil maps for Scotland, which provide greater spatial resolution mapping than currently available, and provide fuzzy data to be used in mapping of ecosystem services using a novel approach explained in a second paper. When selecting the class with the highest weighting for test data points, Producer's Accuracy of 70.7% was achieved in mapping the broadest classification (five classes), while Producer's Accuracy levels of 59.9% and 43.7% were achieved for 11 and 30 classes, respectively. Evaluation of confusion matrices generated from the neural network model tests showed that, particularly for the classification systems with 11 and 30 classes, misclassification errors were more common between similar soil classes than between classes that were very different from one another. This implies that straightforward estimation of classification accuracy that measures “correct” and “incorrect” gives misleading results, and that the fuzzy classification maps are more useful than the crisp classification accuracy values. These fuzzy classification maps are therefore potentially useful for evaluating ecosystem services relating to soil type. We conclude that the mapping approach used here provides a classification accuracy comparable to other approaches and that the outputs can be used for mapping soil properties, processes, functions and ecosystem services.

Prediction of soil organic carbon stock using digital mapping approach in humid India

There is a need of information on soil organic carbon data for global environmental management and food security. However, the difficulty lies in obtaining soil carbon data, especially in fragile mountainous regions like Northeast India which is complex in nature and difficult to access. The present study aims to model the distribution of soil carbon stock using digital mapping approach, to predict and generate continuous spatially explicit soil carbon map in Northeast India. Firstly, negative exponential depth function has been used to fit the vertical distribution of soil carbon data, and then Random Forest model has been trained and tuned to predict the parameters of the exponential function using climate data and satellite images. The obtained parameters were finally interpolated using ordinary Kriging method and spatial distribution map across the study area has been generated. Results indicate that the negative exponential function fits the data accurately with 94% of data having R2 > 0.7. Land use and topographic factors particularly elevation was found to have the most influence on SOC distribution in Northeast India. The findings from this study indicate good results for the application of this technique to predict and monitor soil carbon of the study area as a function of topographic factors and changes in land use and climate variables. The obtained results can also be connected to global carbon models to improve the understanding of carbon dynamics.

Control of Tungiasis in Absence of a Roadmap: Grassroots and Global Approaches.

Tungiasis is a tropical skin disease caused by the sand flea Tunga penetrans. It inflicts misery upon tens of millions of people, mostly children, across Central and South America and sub-Saharan Africa, and yet there is no globally accepted roadmap for its control. Here we review how research in the last 15 years has developed control methods and report on new grassroots and digital mapping approaches. Treatment is now possible with a two-component dimethicone, used for the treatment of headlice in Europe, Asia and Canada, but not yet available in most tungiasis-endemic areas. Prevention is possible through the daily use of repellents based on coconut oil. A Kenyan coastal community has successfully controlled tungiasis using a neem and coconut oil mix produced locally to treat cases, combined with spraying floors with neem solution and distributing closed shoes. Development of affordable hard floor technology is underway, although not yet widely available, but is a priority to control off-host stages in the floors of homes. A new web-based digital mapping application will enable researchers and health officials to collaborate, share data and map the prevalence of tungiasis. We conclude that tungiasis can be controlled through a multi-disciplinary, One Health approach.

Digital soil assessment of agricultural suitability, versatility and capital in Tasmania, Australia

Digital soil assessment (DSA) is the application of interpretations to digital soil mapping (DSM). Since 2010, an operational DSA program has been underway in Tasmania, Australia, primarily for the assessment of agricultural land suitability for 20 different crops in newly commissioned irrigation schemes. This involves development of functional soil attribute and climate grids, initially undertaken in two pilot areas totalling 70,000ha, with comprehensive soil sampling and temperature sensor networks. Through the Tasmanian State Government ‘Water for Profit Program’, this pilot land resource assessment has become operational and applied to the entire State (68,401km2), covering a total of 19 irrigation schemes. Using a combination of newly collected and legacy soil data and a suite of spatial explanatory covariates, a total of 218 80m resolution 3D soil attribute grids were produced using the digital mapping approach, together with quantified prediction uncertainties. These grids have contributed to the ‘Soil and Landscape Grid of Australia’ and the ‘GlobalSoilMap’ projects. Using a similar approach, functional climate grids were generated for chill-hours, growing degree-days and frost risk. The digital soil and climate grids were applied to pre-defined enterprise suitability rulesets to produce 20 different maps of enterprise suitability, including opium poppies, and a range of perennial horticultural, cereal and vegetable crops, uploaded to a publically accessible spatial internet portal (Land Information Services Tasmania; LISTmap), which includes functionality to identify soil and climate limitations, as an indication of potential land management inputs. The suitability surfaces provide a regional indication of potential areas to expand or diversify into a range of cropping enterprises. However, some informative supplementary products were also developed to provide an overall spatial guide to the more versatile agricultural areas. This included an enterprise versatility index (by combining all suitability surfaces to identify areas more suited to more enterprises); and application of individual commodity ‘financial gross-margins’ to identify the highest-valued agricultural land in terms of earning potential. These products demonstrate the utility of functional soil property grids and the collective capacity of DSA to answer questions of agricultural potential; this can ensure the appropriate land is targeted for appropriate uses to stimulate agricultural markets and maintain food security.

A colorimetric sensor array for detection and discrimination of biothiols based on aggregation of gold nanoparticles

Developments of sensitive, rapid, and cheap systems for identification of a wide range of biomolecules have been recognized as a critical need in the biology field. Here, we introduce a simple colorimetric sensor array for detection of biological thiols, based on aggregation of three types of surface engineered gold nanoparticles (AuNPs). The low-molecular-weight biological thiols show high affinity to the surface of AuNPs; this causes replacement of AuNPs’ shells with thiol containing target molecules leading to the aggregation of the AuNPs through intermolecular electrostatic interaction or hydrogen-bonding. As a result of the predetermined aggregation, color and UV–vis spectra of AuNPs are changed. We employed the digital mapping approach to analyze the spectral variations with statistical and chemometric methods, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). The proposed array could successfully differentiate biological molecules (e.g., cysteine, glutathione and glutathione disulfide) from other potential interferences such as amino acids in the concentration range of 10–800μmolL−1.

Mapping site-level microtopography with Real- Time Kinematic Global Navigation Satellite Systems (RTK GNSS) and Unmanned Aerial Vehicle Photogrammetry (UAVP)

AbstractMicrotopographic mapping has a long history in archaeology and has gained prominence recently owing to the proliferation of digital technologies. With such proliferation, it becomes necessary to compare and contrast different approaches based on a common set of criteria. This article compares the implementation and efficiency of two methods of mapping microtopography – ground-based Real-Time Kinematic Global Navigation Satellite System (RTK GNSS) and Unmanned Aerial Vehicle Photogrammetry (UAVP) survey – assessing the pros and cons of each, including those related to data quality. ‘Off-the-shelf’ solutions for methods were used to create the comparative dataset of microtopographic maps of six Middle and Late Bronze Age sites over the course of four seasons between 2007 and 2013 in the study area of the Central Lydia Archaeological Survey in western Turkey. Comparison of results demonstrate that the methods are similar with respect to ease of implementation, cost efficiency, and the (in)significance of data defects, while, unsurprisingly, UAVP survey can be greater than one order of magnitude more labor efficient than RTK GNSS survey and over two orders of magnitude more detailed as measured by data density. The accuracy of both methods is high, within typical error budgets for site-level mapping, and comparable to other recent digital mapping approaches. Accordingly, the results suggest that, given site suitability, UAVP is the more labor and cost-efficient method in the long run, with significant data quality benefits.

Ongoing Dynamics of a Digital Mapping Approach: ABSTRACT

Ongoing Dynamics of a Digital Mapping Approach: ABSTRACT

Digital mapping of multi-parameter contrast functions in magnetic resonance (MR) imaging using a standard MR computer system and digital display

A technique is described which utilises the full analysis and display capabilities of a commercial MRI system to produce digital maps of multi-parameter functions produced byMR contrast theory. The technique is utilised to determine the effects of nominating specific overall scan times on the optimum solutions as produced by the theory and it is shown that different solutions are obtained when the theory is applied using typical clinical constraints. The digital mapping approach is potentially of great value in prospectively determining pulse timing parameters to produce optimum contrast images, in producing contrast maps to aid retrospective image interpretation, and as a training aid for clinicians inexperienced in the interpretation MR images.