Mineral Element Identification in Remote Sensing Imagery: A Fusion Approach Using CH-Tucker Decomposition and RFDNet DOI Open Access
Xingyu Ding, Wenjun Hu,

Guanbing Hu

et al.

Traitement du signal, Journal Year: 2023, Volume and Issue: 40(4), P. 1501 - 1509

Published: Aug. 31, 2023

In the realm of geological and mineral exploration, remote sensing technology has emerged as a pivotal high-tech instrument.However, effective interpretation images, especially in context heterogeneous data processing, noise, identification fine granularity, remains challenge.In this study, novel method for elements within imagery was introduced.Firstly, feature tensor migration technique anchored on Coupled Heterogeneous Tucker Decomposition (CH-Tucker decomposition) presented.Through technique, multi-source were effectively processed fused.Notably, associated features from varying resolutions angles seamlessly coupled.Subsequently, an optical image processing model founded RFDNet network established.This demonstrated robustness against noise data, thereby enabling with higher degree granularity.The proposed methodology exhibited capacity to extract element information comprehensively remarkable accuracy.Thus, research offers both valuable theoretical insights practical evidence furtherance exploration.

Language: Английский

Spatiotemporal Evolution and Multi-Scenario Prediction of Carbon Storage in the GBA Based on PLUS–InVEST Models DOI Open Access

Ruei-Yuan Wang,

Huina Cai,

Lingkang Chen

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(10), P. 8421 - 8421

Published: May 22, 2023

In the context of sustainable development and dual-carbon construction, in order to clarify future changes land use carbon storage GBA, this study used PLUS InVEST models as well Geoda software simulate predict spatial pattern stocks GBA 2030 under multiple scenarios. The results show that (1) From 1990 2020, decreased year by year. (2) 2030, except for EPS, prediction values remaining scenarios are lower than those especially value EDS, which is lowest at 8.65 × 108 t. (3) distribution has significant heterogeneity. high-value areas distributed east west wings southwest while low-value concentrated middle east. research can provide a reasonable scientific basis territorial space resource planning goal “dual carbon”.

Language: Английский

Citations

25
Assessment of asbestos-cement roof distribution and prioritized intervention approaches through hyperspectral imaging DOI Creative Commons

David Martínez,

Manuel Saba, Leydy K. Torres Gil

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25612 - e25612

Published: Feb. 1, 2024

The discernment of asbestos-cement (AC) roofs within urban areas stands as a pivotal concern pertinent to communal well-being and ecological oversight, particularly in emerging nations where asbestos continues be extensively employed. Conventional methodologies entailing the recognition characterization their degradation status, such tangible examinations laboratory assays, prove temporally protracted, financially demanding, arduous extrapolate comprehensively across expansive domains. In this paper, it is presented novel approach for identifying using hyperspectral airborne acquisition carry out diagnosis that allows identify state thus provide tool competent authorities develop prioritize intervention strategies mitigate problem. Four different were implemented compared, three which are new literature, deterioration roof large areas. This, turn, furnishes AC roofs, control points field allowed validating classification proposed methodology prioritization roofs. Some neighborhoods city showed peaks area 47% total neighborhood, representing practically all present neighborhood. On average around 20% neighborhood Cartagena covered by AC. Furthermore, was found throughout more than 9 km

Language: Английский

Citations

10
MultiRS flood mapper: a google earth engine application for water extent mapping with multimodal remote sensing and quantile-based postprocessing DOI
Zhouyayan Li, İbrahim Demir

Environmental Modelling & Software, Journal Year: 2024, Volume and Issue: 176, P. 106022 - 106022

Published: March 14, 2024

Language: Английский

Citations

4
Application of Supervised Learning Methods and Information Gain Methods in the Determination of Asbestos–Cement Roofs’ Deterioration State DOI Creative Commons
Manuel Saba, David Valdelamar Martínez, Leydy K. Torres Gil

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(18), P. 8441 - 8441

Published: Sept. 19, 2024

This study introduces an innovative approach to evaluate the condition of asbestos–cement (AC) roofs by integrating field data with five distinct supervised learning models: decision trees, KNN, logistic regression, support vector machine, and random forest. A novel methodology for assessing importance 380 reflectance bands was employed, offering fresh insights into key indicators AC roof deterioration. The research systematically organized prioritized based on their information gain, optimizing both selection relevant performance models in differentiating between low high intervention priority (LIP HIP) roofs. tree model, when applied top 10 most bands, achieved highest cross-validation accuracy 76.047%, making it effective tool identifying conditions. Additionally, forest model demonstrated strong across various band groups, further validating its utility. Utilizing open-source software Weka (version 3.8.6), this adeptly executed relevance evaluation implementation, providing a practical scalable solution material characterization, especially regions where resources spectral hyperspectral image analysis are limited. findings offer valuable tools government environmental authorities, particularly developing countries, efficient cost-effective assessment is crucial public health safety. adaptable different urban environments climatic conditions, supporting global efforts asbestos management, countries regulations newly implemented. Organized within CRISP-DM framework, paper details methodological phases, presents compelling results relevance, evaluates machine models, concludes prospects future aimed at enhancing detection removal strategies.

Language: Английский

Citations

4
Multi-scenario carbon storage analysis based on PLUS model and InVEST model: a case study of Zhejiang province, China DOI

Yirong Wang,

Xueqin Jiang, Song Gao

et al.

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Jan. 18, 2025

Language: Английский

Citations

0
Analysis of Asbestos-Cement Roof Classification in Urban Areas: Supervised And Unsupervised Methods with Multispectral and Hyperspectral Remote Sensing DOI Creative Commons
Manuel Saba,

Carlos Castrillón-Ortíz,

David Valdelamar-Martínez

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101464 - 101464

Published: Jan. 1, 2025

Language: Английский

Citations

0
Systematic review and bibliometric analysis of innovative approaches to soil fertility assessment and mapping: trends and techniques DOI

Tarchi Fatimazahra,

Samira Krimissa, Maryem Ismaili

et al.

Applied Geomatics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Language: Английский

Citations

0
Identifying New Oil and Gas Exploration Targets Using Machine Learning in Java Island, Indonesia DOI
Tri Muji Susantoro, Ketut Wikantika, Suliantara Suliantara

et al.

Journal of the Indian Society of Remote Sensing, Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Language: Английский

Citations

0
Spatial and temporal evolution of carbon stocks in Yulin City under changing environments DOI Creative Commons

Guikai Sun,

Yadong Li,

Rui Huang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 10, 2025

Land use changes directly or indirectly affect the regional carbon balance. Investigating spatial and temporal evolution of stock contribution land driving factors is crucial for understanding formation mechanisms ecosystem cycles budget balance.In this study, researchers selected model simulation method after comparing various estimation methods. This paper uses InVEST to calculate Yulin City from 2000 2020. It then applies PLUS predict under different scenarios in 2030 forecasts future stock, providing a theoretical basis city's development planning. The main findings study are as follows: (1) transfer City, Guangxi, 2020, mainly among forest land, arable construction land. net out cultivated 476.9982 km2, 245.5803 km2 231.0048 respectively. (2) area's distribution closely follows elevation pattern. high-carbon areas concentrate mountainous hilly regions at higher elevations. Medium-value lie relatively flat central southern parts. In contrast, low-value located reservoirs rivers within City. (3) Compared with 2000, 2020 increased by 2.16 × 106 t. NDS EPS 0.3214 t 0.3286 t, respectively, decreased CPS 2.1524 Overall, compared expected increase but growth rate declining. trend increasing likely continue decreasing future, may even show reduction.

Language: Английский

Citations

0
Advancements in Regional Geological Surveys: Insights from the 2024 China National Regional Geological Survey Conference and a Six-Year Uranium Exploration Case Study in Shaoguan, Guangdong DOI
Jianan Zhao,

Chonghao Liu

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2025, Volume and Issue: unknown, P. 103953 - 103953

Published: April 1, 2025

Language: Английский

Citations

0