Environmental Challenges最新文献

{"title":"Refining land cover classification and change detection for urban water management using comparative machine learning approach","authors":"Douraied Guizani ,&nbsp;János Tamás ,&nbsp;Dávid Pásztor ,&nbsp;Attila Nagy","doi":"10.1016/j.envc.2025.101118","DOIUrl":"10.1016/j.envc.2025.101118","url":null,"abstract":"<div><div>Accurate land cover (LC) maps are essential for urban water balance modeling, particularly in rapidly urbanizing cities like Debrecen, Hungary, where industrial expansion has intensified since 2019. However, LC classification remains challenging due to limited studies evaluating the optimal combination of classifiers and satellite data. This study builds upon previous research by introducing a comparative analysis of three machine learning classifiers—Support Vector Machine (SVM), Maximum Likelihood Classification (MLC), and Random Forest (RF)—in LC classification using Sentinel-2 and Landsat 8 imagery from 2018, 2020, and 2022.</div><div>Results show that SVM on Sentinel-2 achieved the highest accuracy (F1 score: 0.84 ± 0.11, overall accuracy: 88 ± 2.1 %, kappa: 0.84 ± 0.03) with the lowest total disagreement values (D% = 12.6 in 2020, 13.1 in 2022). Consequently, SVM with Sentinel-2 was selected for LC change detection, employing trajectory analysis to assess urban development dynamics. The quantity gain component accounted for 5 % of the study area, representing net urban expansion, while the exchange component (10 %) indicated bidirectional shifts between developed and non-developed classes. Given Debrecen's rapid industrialization and the lack of a robust LC classification strategy for hydrological applications, this research refines LC change detection methods. It improves water balance calculations by LC type, strengthening the hydrological framework. By demonstrating the value of satellite imagery and GIS in monitoring urbanization, the findings support future urban water balance assessments, sustainable planning, and resource management, providing local authorities with a robust tool to adapt spatial strategies to an evolving landscape.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101118"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Financial access, depth, and efficiency: The key pillars for enhancing energy equity, security, and sustainability","authors":"Mayank Parashar,&nbsp;Ritika Jaiswal","doi":"10.1016/j.envc.2025.101117","DOIUrl":"10.1016/j.envc.2025.101117","url":null,"abstract":"<div><div>Access to affordable, equitable, and sustainable energy is essential for countries to achieve the Sustainable Development Goals through financial resources. In a critical era for sustainable energy, exploring the relationship between financial development and energy trilemma indicators, i.e., energy equity, security, and environmental sustainability, is imperative. To comprehend this, the present study examines the impact of financial market and institution accessibility, depth, and efficiency on energy trilemma indicators in 18 emerging economies between 2011 and 2021 using the Generalized Method of Moments (GMM) model. The study highlights that energy equity is positively impacted by financial market accessibility and institutional efficiency. Furthermore, it confirms that the depth and efficiency of the financial markets, as well as the development and accessibility of financial institutions, significantly reduce greenhouse gas emissions. However, financial market development negatively impacts wind energy. These unfavorable results are caused by uncertain government regulations, inadequate infrastructure, expensive upfront investments, prolonged payback times, and environmental and other economic challenges. These challenges reduce the financial feasibility of energy-efficient projects, especially in developing nations where overcoming financial and technological barriers requires targeted solutions and supportive policies. Hence, policymakers must develop robust strategies that promote alternative energy sources to address climate change.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101117"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative governance mechanism for nuclear contamination data in the Pacific Rim region in the context of transboundary nuclear damage accountability inflicted by Japan","authors":"Shumei Yue,&nbsp;Wenna Fan","doi":"10.1016/j.envc.2025.101110","DOIUrl":"10.1016/j.envc.2025.101110","url":null,"abstract":"<div><div>As a radioactive waste disposal activity for the Fukushima nuclear accident, Japan government discharge multiple rounds of nuclear-contaminated water will ultimately cause irreversible transboundary damage to the public health, fishery economy, and marine ecosystems of Pacific Rim coastal countries. With the gradual implementation of Japan's commitment on the issue of the discharge of Fukushima nuclear-contaminated water into the sea, experts from many countries, including China, have headed to the Fukushima Daiichi nuclear power plant to collect samples. Currently, Facing the absence of an international monitoring mechanism for nuclear-contaminated water has led to low transparency regarding radioactive data from nuclear waste and environmental monitoring data of surrounding marine areas. This article analyses the legal problems faced by the Pacific Rim region in the recovery of transboundary nuclear damage by utilizing literature research method, arguing the feasibility of the construction of a regional synergistic governance mechanism for nuclear contamination data, then advocating a framework for the construction of a regional collaborative governance mechanism for nuclear contamination data, however, the establishment of such mechanism in the Pacific Rim region involves multiple complexities. Regional Nuclear Energy Powers as Lead Countries, seeking to promote the governance mechanism from theory to practice. Therefore, the systematic promotion of the construction of a collaborative governance mechanism for in the Pacific Rim region can remedy the lack of an international monitoring mechanism for nuclear-contaminated water and providing institutional legality for the recovery and compensation of transboundary nuclear damages in the Pacific Rim countries.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101110"},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recursive feature elimination for summer wheat leaf area index using ensemble algorithm-based modeling: The case of central Highland of Ethiopia","authors":"Dereje Biru ,&nbsp;Berhan Gessesse ,&nbsp;Gebeyehu Abebe","doi":"10.1016/j.envc.2025.101113","DOIUrl":"10.1016/j.envc.2025.101113","url":null,"abstract":"<div><div>Accurate and nondestructive monitoring of the wheat leaf area index (LAI) is important for effective agricultural management and production forecasting. However, building a high-performance predictive model faces challenges in selecting suitable machine learning algorithms and identifying important variables. This study explored the use of ensemble algorithm-based recursive feature elimination (RFE) for summer wheat LAI estimation using the Google Earth Engine (GEE) cloud computing platform. Remote sensing datasets, including Sentinel-1/2 and digital elevation models, encompassing spectral bands, vegetation indices, texture metrics, and topographic variables, were used. The preprocessing stage involved creating 136 independent variables in the GEE, whereas the LAI data were collected from 84 systematically selected samples using the ACCUPAR LP-80 Ceptometer. Further processing included feature combination, min–max normalization, extraction of the 136 independent variables to the LAI data, and data partitioning for training and testing. The RFE algorithm was applied using the random forest (RF) and gradient tree boost (GTB) algorithms within the GEE to predict the summer wheat LAI at the Lole State Farm. Model performance validation analysis was evaluated via R-squared (R²), root mean squared error (RMSE), mean squared error (MSE), and mean absolute error (MAE) statistical models. The results indicated that 49 significant variables were selected for the RFE-RF model, whereas 29 were chosen for the RFE-GTB model. The GTB model outperformed the RF model, achieving R² values of 0.968 for training and 0.88 for validation, whereas the R² values of the RF model were 0.961 for training and 0.856 for validation. The GTB model also exhibited superior accuracy, with lower RMSE, MSE, and MAE values. Additionally, a predicted LAI map for summer wheat was generated, ranging from 0.22-2.12 for the random forest model and from 0.24-2.23 for the gradient tree boost model. Overall, this study demonstrated the improvement of the learning algorithm by identifying important variables, evaluating its performance in predicting wheat LAI, and generating a map of the predicted LAI. The results offer valuable insights for the nondestructive and rapid acquisition of summer wheat LAI by employing an ensemble algorithm-based RFE and utilizing Earth observation data in the GEE.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101113"},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New Mexico as a testbed for safe beneficial produced water reuse","authors":"Jamie Cull-Host ,&nbsp;Prashant Sharan ,&nbsp;Jolante Van Wijk ,&nbsp;Mohamed Mehana","doi":"10.1016/j.envc.2025.101116","DOIUrl":"10.1016/j.envc.2025.101116","url":null,"abstract":"<div><div>Produced water is a large waste product associated with the production of oil and gas. It is often either disposed of or partially reused in hydraulic fracturing. If treated properly, this waste product could be used as a non-potable water source in arid regions to lessen the strain on freshwater resources. Across basins, produced water contains different levels of salinity and different potentially toxic constituents. New Mexico is one state in the Intermountain-West that is projected to have water scarcity issues due to increases in evapotranspiration and changes in precipitation, leading to a general increase in aridity. Additionally, New Mexico has a significant and increasing flow of produced water, totaling 2.3 billion barrels in 2023. With this increase in both aridity and produced water, there is active rulemaking around the reuse of produced water outside the oil and gas industry. The combination of these factors makes New Mexico a good candidate as a testbed for beneficial produced water reuse in the United States. This study evaluates the feasibility of produced water reuse in New Mexico, investigating reuse options through the lenses of policy and environmental impacts. Key findings include the suitability of hydrogen production and mineral extraction subject to targeted treatment strategies and continued regulatory adjustments.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101116"},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical and environmental performance evaluation of meta-kaolin and silica fume-modified steel fiber embedded concrete: A sustainable construction","authors":"Nawab Sameer Zada ,&nbsp;Nasir Shafiq ,&nbsp;Muhammad Basit Khan ,&nbsp;Muhammad Imran","doi":"10.1016/j.envc.2025.101104","DOIUrl":"10.1016/j.envc.2025.101104","url":null,"abstract":"<div><div>In this experimental study, mechanical strength, and environmental characteristics of concrete were evaluated. Concrete was prepared by replacing cement with green cementitious material silica fume and meta-kaolin, Additionally, concrete is blended with steel fiber as a means to enhance the concrete characteristics. Response surface methodology was employed for designing the series of experiment and proportions. Two models were constructed in RSM separately, one model consists of meta-kaolin (MK) and steel fiber, while other consists of silica fume (SF) and steel fiber. Findings of both models were compared to each other to study the effects of SF and MK on concrete through the addition of steel fiber. Concrete was tested for compressive strength (CS), split tensile strength (STS), FS (FS), modulus of elasticity (MoE), ultra-sonic pulse velocity (UPV) and symbolized carbon (EC) with eco-strength efficiency (ESE) remained likewise estimated. As per the investigation, it was concluded that addition of 10 % MK with 1 % steel fiber in concrete offers the extreme mechanical strength among the mixes containing MK as a cementitious replacement material and concrete containing 10 % of SF with 1 % of steel fiber exhibits the maximum mechanical strengths among the proportions containing SF in concrete. It was found that concrete containing SF exhibit higher mechanical strength in comparison to concrete in which MK is used as cement supplementary material. Concrete containing 10 % MK or SF reinforced with 1 % steel fiber has the highest ESE. Concrete containing 10 % MK and 1 % steel fiber increases CS, STS, FS and MOE by 14 %, 7.29 %, 8 % and 7.29 % respectively. While concrete mixes containing 10 % SF and 1 % steel fiber enhances the CS, STS, FS and MOE by 19.11 %, 17.23 %, 10 % and 10.06 % respectively in comparison to control mix. Finally, Statistical equations were developed for anticipating the value of each response by using independent variables (MK, SF and steel fiber).</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101104"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of cocoa farm age and slope, and shade rate on cocoa soils fertility","authors":"Jean Baptiste Biloa ,&nbsp;Abossolo Monique ,&nbsp;Mekonnen H. Giweta ,&nbsp;Komi K.M. Fiaboe ,&nbsp;Nanga Nanga Samuel ,&nbsp;Pauline Viviane Mandah ,&nbsp;Jean Daniel Essobo ,&nbsp;Adalbert Onana ,&nbsp;Masso Cargele","doi":"10.1016/j.envc.2025.101115","DOIUrl":"10.1016/j.envc.2025.101115","url":null,"abstract":"<div><div>Under a positive, nature-first cocoa farming development scenario, this study aimed to highlight the multifactorial influence of cocoa tree age, shade rate, and farm slope on soil fertility in cocoa agroforestry systems of the forest-savanna transition zone and tropical rainforest in Cameroon. Using a factorial design, 108 plots were selected, with 54 in each agroecosystem zone. Thirty soil samples were randomly collected from each plot (experimental unit) at depths of 0 to 30 cm to create composite samples. Nutrient availability was significantly impacted by the age-slope-shade interaction (P), age-slope interaction (Mg, CEC), age (C/N, P, Zn, Cu, Mn, and TP), slope (TN, Mg, Fe, CEC, and ECEC), and shade rate (Om, TN). In the forest-savanna transition zone, soils with high fertility were found under cocoa trees aged 10 to 30 years with high shade, while the lowest fertility levels were observed in soils under cocoa trees over 30 years old with low shade. In the dense tropical forest zone, most soils had very low fertility, including soils under cocoa trees over 30 years old on slopes of &lt;5° or 5 to 15° with low shade. Soils with average fertility were identified in cocoa plantations with trees aged 10 to 30 years on slopes over 15° with high shade. Precision nutrient management in cocoa agroforestry systems is crucial and should consider farm age, slope, and shade rate, rather than following fertilization models typically recommended for annual crops.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101115"},"PeriodicalIF":0.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review of surface water and fish monitoring data of the fragrance ingredient, Cashmeran","authors":"J. Bozich ,&nbsp;S.E. Belanger","doi":"10.1016/j.envc.2025.101111","DOIUrl":"10.1016/j.envc.2025.101111","url":null,"abstract":"<div><div>6,7-Dihydro-1,1,2,3,3-pentamethyl-4(5H)-indanone or commonly, Cashmeran® (DPMI) is a prominent fragrance ingredient. Despite its measured low bioconcentration factor (BCF) and risk assessments demonstrating low risk, monitoring studies continue to characterize the presence of DPMI in surface water and fish. To consolidate these findings, a comprehensive literature review and an information synthesis was conducted. The reported levels of DPMI were compared to exposure model estimates using the physico-chemical properties, measured BCF, and representative volumes of use of DPMI. To make use of the fish monitoring data, fish tissue dry weight concentrations were converted to wet-weight concentrations to compare to model estimates. The 90th percentile surface water and fish tissue concentrations of DPMI were 0.052 µg/L and 5.0 µg/kg ww, respectively. DPMI levels were low or non-detectable in surface waters and in fish more distant from sources of pollution. Exposure modeling results using the low end of the volume of use range of DPMI, or 100T, were conservative or comparable to the 90th percentile surface water and fish concentrations of DPMI. This analysis indicates that the levels of DPMI measured in the environment are not elevated, are orders of magnitude below ecotoxicological effect levels and confirm the likelihood that DPMI is not bioaccumulative as indicated by laboratory studies. Should future studies be performed, they should characterize bioaccumulation in the field through simultaneous fish and water sampling in the same location. In addition, fish lipid content and wet weight should be reported. Importantly, samples should be of known origin and methodology be made transparent.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"18 ","pages":"Article 101111"},"PeriodicalIF":0.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical analyses of sunscreen usage survey data for the purpose of factor refinement influencing UV filter exposure in aquatic systems","authors":"Andrea M. Carrao ,&nbsp;Sarah L. Terrell ,&nbsp;Celine N. Schmitt ,&nbsp;Scott D. Dyer","doi":"10.1016/j.envc.2025.101112","DOIUrl":"10.1016/j.envc.2025.101112","url":null,"abstract":"<div><div>Current environmental emissions assessments for UV filters in sunscreens used at the beach assume a uniform application rate. While this approach is both conservative and pragmatic, it fails to take into account consumer behaviors that could lead to a range of application values. This study explored diverse behavior, environmental, and other independent factors that may affect application rates by investigating results from an online survey with &gt;2,000 participants. The survey included visual references that helped participants determine the mass of sunscreen lotion applied to their face and body. The resulting datasets for the face and body required curation to eliminate conflicting responses (e.g., “I don't typically apply sunscreen” and contradictory sunscreen application amount responses). Environmental variables tied to the zip codes of participants were investigated for their links with application rates. Generalized linear models (GLM) were used to assess the multivariate nature of participant attributes (e.g., income, skin tone), environmental factors (e.g., UV radiation by zip code) and others to self-report application rates. Akaike's Information Criterion was used to select highly significant models. An eight-variable model explained application thickness on the body, in order of statistical significance: amount of body submerged in water, time in water, gender identity, age, Fitzpatrick skin type, body reapplication, skin response to the sun, and time at the beach. The statistical analysis demonstrated that a clear, one-size-approach toward exposure assessment of UV filters in sunscreens at the beach may not be appropriate because several independent variables were significantly related to application rates to the face and body. The learnings from this study can be used to refine future online surveys. This can lead to realistic environmental emissions and exposure assessments that include diverse independent factors associated with sunscreen use at the beach as well as the ability to tailor emissions estimates to specific beach and aquatic environments thus providing the ability to better target environmental risk management actions.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"19 ","pages":"Article 101112"},"PeriodicalIF":0.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Empirical and Hybrid Modeling for Advanced Canopy Chlorophyll and Nitrogen Retrieval Technique Using EnMAP Data","authors":"Mir Md Tasnim Alam ,&nbsp;Anita Simic Milas ,&nbsp;Jochem Verrelst ,&nbsp;Qing Tian ,&nbsp;Alia Soleil Kripal ,&nbsp;Henry Poku Osei ,&nbsp;Md Atiqur Rahman","doi":"10.1016/j.envc.2025.101114","DOIUrl":"10.1016/j.envc.2025.101114","url":null,"abstract":"<div><div>This study evaluates empirical and hybrid physical models for estimating canopy chlorophyll content (CCC) and canopy nitrogen content (CNC) using hyperspectral imagery from the Environmental Mapping and Analysis Program (EnMAP) over Michigan's Kellogg Biological Station in summer 2023. In the empirical approach, six machine learning regression algorithms (MLRAs) have been evaluated. In the hybrid modeling approach, each MLRA was combined with the PROSAIL radiative transfer model. Results show the empirical model outperforms the hybrid model for CNC retrieval, while both perform similarly for CCC. In the empirical approach, KRR demonstrated the best performance among MLRAs for both CCC (RMSE = 0.10 g/m², NRMSE = 9.76 %, R² = 0.93) and CNC (RMSE = 0.10 g/m², NRMSE = 8.13 %, R² = 0.94). In the hybrid modeling, GPR performed best for CCC (RMSE = 0.10 g/m², NRMSE = 9.43 %, R² = 0.93), while KRR remained the top performer for CNC (RMSE = 0.17 g/m², NRMSE = 13.67 %, R² = 0.83). Furthermore, the findings indicate that the hybrid model exhibits greater sensitivity in heterogeneous areas where field data are limited, while both approaches effectively distinguish between organic and non-organic treatments. The nitrogen conversion factor refined from 4.43 to 3.03 for corn in this study significantly improves the accuracy of the estimated CNC. This enhancement provides further evidence of the efficacy of EnMAP imagery in estimating biochemical parameters and its potential application in Precision Agriculture.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"18 ","pages":"Article 101114"},"PeriodicalIF":0.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}