Sensing Approach Research Articles

Deep Learning approach for Co-operative Spectrum Sensing under Congested Cognitive IoT networks

Deep Learning approach for Co-operative Spectrum Sensing under Congested Cognitive IoT networks

Conversational Crowdsensing in the Age of Industry 5.0: A Parallel Intelligence and Large Models Powered Novel Sensing Approach

Conversational Crowdsensing in the Age of Industry 5.0: A Parallel Intelligence and Large Models Powered Novel Sensing Approach

Quantitative Analysis of Soil Erosion in the Kurumanpuzha Sub Watershed of Chaliyar River Basin: A Remote Sensing and GIS Approach for Sustainable Resource Management

Quantitative Analysis of Soil Erosion in the Kurumanpuzha Sub Watershed of Chaliyar River Basin: A Remote Sensing and GIS Approach for Sustainable Resource Management

Precision Mapping of Coastal Wetlands: An Integrated Remote Sensing Approach Using Unoccupied Aerial Systems Light Detection and Ranging and Multispectral Data

Coastal wetlands, crucial for global biodiversity and climate adaptation, provide essential ecosystem services such as carbon storage and flood protection. These vital areas are increasingly threatened by both natural and human-induced changes, prompting the need for advanced monitoring techniques. This study employs unmanned aerial systems (UASs) equipped with light detection and ranging (LiDAR) and multispectral sensors to survey diverse wetland types across 8 sites in North Carolina. Utilizing high-resolution elevation data and detailed vegetation analysis, coupled with sophisticated machine learning algorithms, we achieved differentiated and highly precise classifications of wetland types. Classification accuracies varied by type, with estuarine intertidal emergent wetlands showing the highest classification accuracies due to less complex vegetation structure and clearer spectral signatures, especially when collections account for tidal influence. In contrast, palustrine forested and scrub–shrub wetlands presented lower accuracies, often due to the denser, mixed, and more complex vegetation structure and variable inundation levels, which complicate spectral differentiation and ground returns from LiDAR sensors. Overall, our integrated UAS-derived LiDAR and multispectral approach not only enhances the accuracy of wetland mapping but also offers a scalable, efficient, and cost-effective method that substantially advances conservation efforts and informs policy-making for coastal resilience. By demonstrating the usefulness of small-scale aerial data collection in ecological mapping, this study highlights the transformative potential of merging advanced technologies in environmental monitoring, underscoring their critical role in sustaining natural habitats and aiding in climate change mitigation strategies.

Nanoscale Optical Sensing Approaches for Quantitative Evaluation of Acupuncture and Moxibustion Therapeutic Efficacy

Acupuncture and moxibustion, integral components of traditional medicine, encounter challenges in achieving objective and stable quantitative assessments. This study delves into the utilization of nanoscale optical sensing technology, with a particular emphasis on graphene materials, to quantitatively analyze the therapeutic efficacy of acupuncture and moxibustion. Initially, we examine the properties and synthesis methods of graphene materials, followed by a comprehensive characterization of these materials. Subsequently, the effectiveness of graphene-based optical sensing in quantifying the therapeutic impact of acupuncture and moxibustion is evaluated through meta-analysis, drawing upon data obtained from diverse literature databases. The findings reveal a high level of measurement accuracy, with an Odds Ratio (OR) of 53 within a 95% Confidence Interval (CI) of 27 to 76 and a P-value of 0.75. These results underscore the significant potential of nanotechnologies, specifically graphene-based optical sensing, in enhancing the objectivity and precision of therapeutic assessments within traditional medicine practices.

A Compressive Sensing Approach for the Reconstruction of the Soundfield Produced by Directive Sources in Reverberant Rooms

A Compressive Sensing Approach for the Reconstruction of the Soundfield Produced by Directive Sources in Reverberant Rooms

A Robust Cooperative Sensing Approach for Incomplete and Contaminated Data

A Robust Cooperative Sensing Approach for Incomplete and Contaminated Data

Dynamics of Land Use Land Cover Change and Soil Erosion Rate in Chure Landscape of Sudurpaschim Province

Land use land cover, a dynamic process, has become a central component of current strategies in managing natural resources and monitoring environmental changes. This study adopts an integrated GIS and Remote Sensing approach to assess changes in land use, land cover (LU/LC), and soil erosion rates between 2001 and 2021. Land use maps were generated using supervised classification and the Maximum Likelihood algorithm, while RUSEL factors facilitated soil erosion mapping analysis. The findings underscore a remarkable decrease in 'agricultural land' and 'water,' accompanied by a simultaneous increase in 'settlement area,' 'forest area,' and 'bare land.' Agricultural land witnessed an annual decline of 2.5 percent, while water bodies decreased by 0.65 percent in 2021. Forest areas exhibited a 0.09 percent increment from 2001 to 2021, and settlement areas expanded at a rate of 0.41 percent annually. Notably, agricultural land reduction primarily contributed to the growth of settlement areas. Additionally, soil erosion rates rose from 3.82 (t/ha/year) in 2001 to 4.090 (t/ha/year) in 2021, indicating a correlation between land use change and soil erosion. Factors such as increased settlement, population growth, infrastructure development, riverbank cutting, and erosion were associated with the decline in agricultural land. Effective land use planning in the Churia region is imperative to address these changes. Government intervention and stakeholder cooperation are crucial to curbing forest degradation, unchecked human settlement expansion, and riverbank cutting. Furthermore, the study advocates for the intensified use of GIS and Remote Sensing technologies in monitoring and managing natural resources.

Dynamic Compressed Sensing Approach for Unsourced Random Access

Dynamic Compressed Sensing Approach for Unsourced Random Access

A Novel Capacitive Touch Sensing Approach and Its Application in Gender Classification

A Novel Capacitive Touch Sensing Approach and Its Application in Gender Classification

Milli Mücadele’de Amasya’nın Tercih Edilme Nedenleri ve Amasya Tamimine Giden Süreç

On October 30, 1918, after the signing of the Armistice of Mudros, many parts of Anatolia, especially Istanbul, were occupied by the Allied Powers. The Turkish people, who remained silent about the occupations for a while, threw off the dead soil with the occupation of Izmir by Greece and participated in rallies protesting these occupations in various parts of the country. In the meantime, there were ideas among the Ottoman bureaucrats and intellectuals who accepted the vassalage of various big countries. However, patriotic officers such as Mustafa Kemal Pasha, Kazım Karabekir, Fethi Okyar, Ali Fuat Cebesoy Pasha, and Kazım Karabekir sought ways to start the National Struggle by moving to Anatolia. They were not sure from which province in Anatolia the National Struggle should start. Mustafa Kemal Pasha, Kazım Karabekir Pasha and other patriotic Turkish officers saw Amasya as the place to start the National Struggle. The aim of the study is to reveal the process leading to the Amasya Declaration in the National Struggle, the importance of this declaration and the reasons why Amasya was preferred. In order to convey the information in the article, a literature review was conducted and books, articles and scientific theses on this subject were read and tried to be conveyed to the reader. The aim of the study is to present to the reader the patriotic and common sense approach of the people of Amasya towards the problems of the country in the process leading to the Amasya Declaration.

Remote Sensing and GIS Approach (Benin) to Mapping of the Geospatial Dynamics of Plant Formations in the Upper Ouémé Sub-Catchment, West Africa

This work aims to map the geospatial dynamics of plant formations in the upper Ouémé sub-watershed from 1995 to 2020, i.e. 25 years. To achieve this objective, the combination of different methodological approaches were used. These are the remote sensing and GIS approach, Benaz plant formation inventory techniques, direct field observations and the calculation of the normalized vegetation index. Processing of satellite images from Landsat TM 5 (1995), Landsat 7 ETM+ sensors from 04-23-2002 and 05-14-2005, Landsat 8 OLI/TIRS from 03-04-2015 and 03-06-2015 and finally that of Sentinel-2B of 04-23-2020 enabled the results to be achieved.
 Thus, different classes of forest entities were discriminated (dense forests, gallery forests, open forests and wooded savannas, wooded and shrubby savannas and grassy savannas). Between 1995 and 2020, the rate of plant formations increased from 95.98 to 66.32%, i.e. a plant cover of 611,971 ha in 1995, 591,672 ha in 2005, 561,595 ha in 2015 and 422,528 ha in 2020 with a NDVI which oscillates between -0.076 and 0.315 during this last year. Benaz's method has made it possible to carry out ecological and phytosociological surveys and to measure the diameters and heights of trees in the identified formations.
 Despite the efforts to conserve and protect the natural resources available to the study area, wood resources are in decline, as they are subject to anthropogenic pressure amplified by population growth and uncontrolled activities.

Discussion of “Validation of a Novel Sensing Approach for Continuous Pavement Monitoring Using Full-Scale APT Testing”

Discussion of “Validation of a Novel Sensing Approach for Continuous Pavement Monitoring Using Full-Scale APT Testing”

Urban Forest Cover and LST Change Monitoring Through Optical and Thermal Remote Sensing Approach

Urban Forest Cover and LST Change Monitoring Through Optical and Thermal Remote Sensing Approach

A Remote Sensing Approach for Assessing Daily Cumulative Evapotranspiration Integral in Wheat Genotype Screening for Drought Adaptation.

This study considers critical aspects of water management and crop productivity in wheat cultivation, specifically examining the daily cumulative actual evapotranspiration (ETa). Traditionally, ETa surface energy balance models have provided estimates at discrete time points, lacking a holistic integrated approach. Field trials were conducted with 22 distinct wheat varieties, grown under both irrigated and rainfed conditions over a two-year span. Leaf area index prediction was enhanced through a robust multiple regression model, incorporating data acquired from an unmanned aerial vehicle using an RGB sensor, and resulting in a predictive model with an R2 value of 0.85. For estimation of the daily cumulative ETa integral, an integrated approach involving remote sensing and energy balance models was adopted. An examination of the relationships between crop yield and evapotranspiration (ETa), while considering factors like year, irrigation methods, and wheat cultivars, unveiled a pronounced positive asymptotic pattern. This suggests the presence of a threshold beyond which additional water application does not significantly enhance crop yield. However, a genetic analysis of the 22 wheat varieties showed no correlation between ETa and yield. This implies opportunities for selecting resource-efficient wheat varieties while minimizing water use. Significantly, substantial disparities in water productivity among the tested wheat varieties indicate the possibility of intentionally choosing lines that can optimize grain production while minimizing water usage within breeding programs. The results of this research lay the foundation for the development of resource-efficient agricultural practices and the cultivation of crop varieties finely attuned to water-scarce regions.

Optimization of the Angso Duo Tourism Market Area Based on the Historic Riverfront of the Batanghari River, Jambi City

Angso Duo Market or also known as the Tanah Select Pesako Betuah location is an area that has a long history in the development of the city of Jambi. Angso Duo Market, which is located on the Batanghari River, is one of the development locations for riverside tourist areas which has great potential for development. Many historical events occurred at this location which brought many memories to the people of Jambi. This area has significant historical value as the historic Riverfront Batanghari river site, which has witnessed the cultural and social development of the surrounding community. The aim of this research is to identify and design an optimization strategy for the Angso Duo Tourism Market Area based on the historical heritage of the Batanghari River Riverfront which produces design aspects of the waterfront tourist area which are the basis for determining the design approach, namely the Collective Memory and Sense approaches. of Place (Meaning of Place). The research methods used in this research are literature study, field survey, interviews with related parties, and data analysis. The research results show that the Angso Duo Tourism Market Area has the potential to become an attractive tourist destination. The history of the Batanghari Riverfront, which has existed for many years, is the main attraction. However, efforts are still needed to optimize the use of this area. Based on the research results, several optimization strategies are recommended, including: Historical Heritage Conservation, Preserving and maintaining historical sites around the Batanghari River Riverfront to maintain the authenticity and historical value of the area. Infrastructure Development, Improving regional infrastructure, including road access, parking areas and other public facilities, to increase visitor comfort. Development of tourist facilities, building tourist facilities and facilities that support visitor activities, such as children's play areas, places to eat and places to rest. Environmental Management, Developing a sustainable environmental management plan to preserve the Batanghari River and its surroundings. By implementing this strategy, it is hoped that the Angso Duo Tourism Market Area can become an attractive and sustainable tourist destination, providing economic and social benefits for the local community, as well as preserving the history and environment of the Batanghari River.

Geospatial Analysis of Kurumanpuzha Sub Watershed in the Chaliyar River Basin: A Remote Sensing and GIS Approach for Geomorphological Assessment

Aims: This study aimed to determine geomorphological characteristics of Kurumanpuzha sub-watershed for understanding its hydrological behaviour, erosion susceptibility and geological characteristics.
 Study Design: Morphometric analysis of Kurumanpuzha sub-watershed was carried out using remote sensing and Geographic Information System (GIS) which is pivotal for sustainable resource management.
 Place and Duration of Study: This study was conducted at Kelappaji College of Agricultural Engineering and Technology, Tavanur, Malappuram, Kerala during 2020-2021.
 Methodology: The geomorphological characteristics of Kurumanpuzha sub-watershed were determined using GIS offering precise terrain insights to guide water resource planning, erosion control, infrastructure development and ecological conservation. Morphometric parameters were assessed based on linear, areal, and relief characteristics. USGS Earth Explorer platform was employed to download satellite images from multiple sources, including ISRO Resourcesat, Landsat, Sentinel, RADAR, and others. These images were then used to develop a Land Use Land Cover (LULC) map as well as other maps of the study area.
 Results: The sub-watershed had a dendritic drainage pattern with a mean bifurcation ratio of 2.05, indicating easier flood management due to longer durations of low peak flows. The analysis revealed fine drainage, indicating a prevalence of soft rocks prone to erosion. The watershed had high relief and steep slopes, characterized by hills, breaks, and low mountains. The hypsometric curve indicated an equilibrium stage of geomorphic evolution. Morphometric parameters were grouped into three clusters at the sub-watershed level, demonstrating spatial variability. Forest/dense vegetation were the dominant land use, followed by rubber plantations and scrubland.
 Conclusion: The findings of this study contribute to understanding of the hydrological behaviour, erosion susceptibility and geological characteristics of Kurumanpuzha sub-watershed. It is useful for effective watershed management, erosion control and informed decision-making in land use planning and engineering projects.

Fuel Type Mapping Using a CNN-Based Remote Sensing Approach: A Case Study in Sardinia

Accurate fuel mapping is crucial for effectively determining wildfire risk and implementing management strategies. The primary challenge in fuel type mapping lies in the need to develop accurate and efficient methods for identifying and categorizing the various combustible materials present in an area, often on a large scale. In response to this need, this paper presents a comprehensive approach that combines remote sensing data and Convolutional Neural Network (CNN) to discriminate between fire behavior fuel models. In particular, a CNN-based classification approach that leverages Sentinel-2 imagery is exploited to accurately classify fuel types into seven preliminary main classes (broadleaf, conifers, shrubs, grass, bare soil, urban areas, and water bodies). To further refine the fuel mapping results, subclasses were generated from the seven principles by using biomass and bioclimatic maps. These additional maps provide complementary information about vegetation density and climatic conditions, respectively. By incorporating this information, we align our fuel type classification with the widely used Standard Scott and Burgan (2005) fuel classification system. The results are highly promising, showcasing excellent CNN training performance with all three metrics—accuracy, recall, and F1 score—achieving an impressive 0.99%. Notably, the network exhibits exceptional accuracy in a test case conducted in the southern region of Sardinia, successfully identifying Burnable classes in previously unseen pixels: broadleaf at 0.99%, conifer at 0.79%, shrub at 0.76%, and grass at 0.84%. The proposed approach presents a valuable tool for enhancing fire management, contributing to more effective wildfire prevention and mitigation efforts. Thus, this tool could be leveraged by fire management agencies, policymakers, and researchers to improve the determination of wildfire risk and management.

A Neuro-Fuzzy-Based Sensing Approach for the Classification of Emulated Postural Instability

A Neuro-Fuzzy-Based Sensing Approach for the Classification of Emulated Postural Instability

Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach

Forest fires have significant impacts on economies, cultures, and ecologies worldwide. Developing predictive models for forest fire probability is crucial for preventing and managing these fires. Such models contribute to reducing losses and the frequency of forest fires by informing prevention efforts effectively. The objective of this study was to assess and map the forest fire susceptibility (FFS) in the Indian Western Himalayas (IWH) region by employing a GIS-based fuzzy analytic hierarchy process (Fuzzy-AHP) technique, and to evaluate the FFS based on forest type and at district level in the states of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. Seventeen potential indicators were chosen for the vulnerability assessment of the IWH region to forest fires. These indicators encompassed physiographic factors, meteorological factors, and anthropogenic factors that significantly affect the susceptibility to fire in the region. The significant factors in FFS mapping included FCR, temperature, and distance to settlement. An FFS zone map of the IWH region was generated and classified into five categories of very low, low, medium, high, and very high FFS. The analysis of FFS based on the forest type revealed that tropical moist deciduous forests have a significant vulnerability to forest fire, with 86.85% of its total area having very high FFS. At the district level, FFS was found to be high in sixteen districts and very high in seventeen districts, constituting 25.7% and 22.6% of the area of the IWH region. Particularly, Lahul and Spiti had 63.9% of their total area designated as having very low FSS, making it the district least vulnerable to forest fires, while Udham Singh Nagar had a high vulnerability with approximately 86% of its area classified as having very high FFS. ROC-AUC analysis, which provided an appreciable accuracy of 79.9%, was used to assess the validity of the FFS map produced in the present study. Incorporating the FFS map into sustainable development planning will assist in devising a holistic strategy that harmonizes environmental conservation, community safety, and economic advancement. This approach can empower decision makers and relevant stakeholders to take more proactive and informed actions, promoting resilience and enhancing long-term well-being.