Environmental Earth Sciences最新文献

{"title":"Assessment of surface water and groundwater quality and their associated human health risks around dumpsites, Cross River State, Southern Nigeria","authors":"Aniekan Edet,&nbsp;Aniediobong Ukpong,&nbsp;Azubuike Ekwere,&nbsp;Oliver Wiche,&nbsp;Therese Nganje,&nbsp;Christopher Adamu,&nbsp;Ebenezer Kudamnya","doi":"10.1007/s12665-025-12186-4","DOIUrl":"10.1007/s12665-025-12186-4","url":null,"abstract":"<div><p>The present study evaluates surface water and groundwater and explores their associated human health risk around dumpsites in four Nigerian cities. Hence, groundwater (GW), surface water (SW), dumpsites leachate (CW) and rainwater (RW) samples were collected and analyzed for physicochemical parameters, major ions trace and rare earth elements using standard field and laboratory methods. Moreover, the study applied multivariate statistics, geochemical modeling, scatter plots and pollution indices. Elevated concentration of TDS, TH, Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, HCO₃⁻, SO₄²⁻, NO₃⁻ and Al were obtained in the different water samples. REE data showed that the LREEs are higher compared to the HREEs, while the plots of REE data normalized to Post Archean Australian Shale (PAAS) revealed a middle REE enrichment relative to LREE and HREEs. Majority of the samples exhibits variable positive Europium, Cerium, Gadolinium and Erbium anomalies. The concentration of aluminum, iron and manganese were higher than MAL in some GW and SW samples, while in CW, Co, Cu and Zn were below their respective MAL. The major hydrochemical facies, were Ca²⁺–HCO₃⁻, Na⁺–Ca²⁺–HCO₃⁻, Na⁺–HCO₃⁻ and Na⁺–Cl⁻. The strong correlation between water pollution parameters suggests that those parameters were derived from common natural and anthropogenic sources. Furthermore, R-mode factor analysis and hierarchal cluster analysis indicated that the water chemistry was controlled by both water-rock interaction and anthropogenic activities. The pollution index for all the samples was low, suggesting that the water samples are suitable for human consumption, except for some samples with pollution index suggesting poor water quality for consumption and irrigation. Though the average daily dose for both adults and children were &lt; 1, elevated hazard quotient &gt; 1 values were observed in some samples, while hazard index values &gt; 1 were also recorded. Carcinogenic values greater than 10⁻⁶ and 10⁻⁴ were observed for some samples due to the high Cd, Cr and Ni concentrations, suggesting potential health risk. The results showed that sustainable management measures are required to control open waste disposal so that water resources contamination can be effectively reduced.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative application of the composite Bezier GSXG hybrid machine learning model for daily evapotranspiration Estimation implementing satellite image data","authors":"Parastoo Amirzehni,&nbsp;Saeed Samadianfard,&nbsp;AmirHossein Nazemi,&nbsp;AliAshraf Sadraddini","doi":"10.1007/s12665-025-12236-x","DOIUrl":"10.1007/s12665-025-12236-x","url":null,"abstract":"<div><p>Estimating reference evapotranspiration (ET₀), a vital hydrological parameter, is particularly challenging in regions with scarce meteorological data, such as developing countries. Remote sensing data is a valuable resource for obtaining climatic and vegetation parameters. By using MODIS data (LST and NDVI), we aim to improve ET0 estimation accuracy. Four interpolation methods (spline, cubic spline, Bezier, and composite Bezier) are used to enhance the temporal resolution of MODIS data for improved daily ET₀ estimation. Conducted at the Yazd station in Iran, using data from 2003 to 2024, this study implements the traditional XGBoost (eXtreme Gradient Boosting) model and its optimized variant, GSXG (GridSearch- XGBoost), which incorporates GridSearch for superior parameter tuning. The results demonstrate the GSXG model’s significant performance enhancements over the base XGBoost, with the Bezier function achieving an RMSE of 0.855 mm/day and R² of 0.531 using only remote sensing data, and the cubic spline method reaching an RMSE of 0.208 mm/day and R² of 0.972 when combining meteorological and remote sensing inputs. These findings underscore the potential of GSXG to minimize errors and improve predictive reliability. This study demonstrates the value of integrating remote sensing data with optimized machine learning for improved ET₀ estimation, providing a valuable approach for hydrological assessments in data-scarce regions.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced urban impervious surface land use mapping using a novel multi-sensor feature fusion method and remote sensing data","authors":"Muhammad Nasar Ahmad,&nbsp;Fahad Almutlaq,&nbsp;Md. Enamul Huq,&nbsp;Fakhrul Islam,&nbsp;Akib Javed,&nbsp;Hariklia D. Skilodimou,&nbsp;George D. Bathrellos","doi":"10.1007/s12665-025-12217-0","DOIUrl":"10.1007/s12665-025-12217-0","url":null,"abstract":"<div><p>The study put forward a data fusion approach for urban remote sensing that combines SAR (Synthetic Aperture Radar) and optical satellite data. By integrating datasets from different sensors and spatial–temporal scales, the technique aims to extract more accurate information. The fusion approach utilizes two methods: feature-based fusion, where relevant features are extracted and fused, and simple layer stacking (SLS), where the original datasets are directly stacked as multiple layers. This study extracted features using SAR textures (using Sentinel-1) and modified indices (using Landsat-8), and then classified these features using an XGBoost algorithm implemented in Python and Google Earth Engine. Researchers examined five cities, each representing a distinct climatic zone and urban dynamic: Cape Town, Guangzhou, Los Angeles, Mumbai, and Osaka. An accuracy assessment was conducted using random validation points, achieving an overall accuracy of 89.5% using the proposed MSFF method. A comparison was also performed with three well-known global products. The proposed approach, outperformed all three global products achived 89% accuracy while ESA (84%), ESRI (81%) and Dynamic World (82%). Additionally, Land surface temperature analysis was accomplished to investigate the relationship between extracted UIS and Land Surface Temperature (LST) across selected cities to show the practical use of proposed MSFF method. Los Angeles, a warm temperate city, showed the highest LST among all five cities. The datasets, along with the GEE and Python codes, are available at https://github.com/mnasarahmad/sls.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Groundwater flow, quality evaluation, and contamination zone mapping in a shallow aquifer, Western Saudi Arabia","authors":"Radhi Abdulaali Alhadi,&nbsp;Natarajan Rajmohan,&nbsp;Hassan M. Albishri,&nbsp;Hamad S. Almutairi,&nbsp;Nassir Alamri","doi":"10.1007/s12665-025-12238-9","DOIUrl":"10.1007/s12665-025-12238-9","url":null,"abstract":"<div><p>Groundwater is a vital resource in Saudi Arabia (KSA). The primary objectives are to explore the water quality status and its application for drinking, agriculture, livestock, and poultry and map the contamination zones (CZ) in the Khulais region, western KSA. Groundwater quality data (<i>n</i> = 53) depicts Ca-Mg-Cl (75%) and Na-Cl water types. The electrical conductivity (EC) and groundwater flow (GF) nexus indicate that EC and major ions increase from upstream to downstream along with GF. In the central region, groundwater is less mineralized with elevated HCO₃⁻ due to geogenic sources. NO₃⁻ and F⁻ distributions pose low values in the northern region. Further, 90% of groundwater samples surpassed the drinking water standards and are unfit for drinking. Irrigation suitability assessment explains that EC (38% of samples), SAR (58%), KR (77%), Na% (94%), PI (100%) and MH (81%) are recommended for irrigation applications. USSL classification suggests that groundwater is usable only for coarse textured (high permeability) soil and salt-tolerant plants. Based on salinity, 68% of samples are usable for livestock and poultry whereas multiple parameters (EC, NO₃⁻, Mg^2+, and F⁻) ensure that only 47% of samples are recommended to use for livestock and poultry. CZ mapping illustrates that groundwater is unsuitable in most of the area except for a few pockets in the southern and northern regions. CZ mapping can aid in locating freshwater zones for groundwater development for future needs in the study site. This study implies that groundwater quality monitoring and CZ mapping are inevitable for sustainable aquifer management in any region.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flood risk assessment of Attabad lake: adopting a scenario-based approach for disaster preparedness","authors":"Muhammad Qamar Javed Pirzada,&nbsp;Junaid Aziz Khan,&nbsp;Muhammad Fahim Khokhar","doi":"10.1007/s12665-025-12237-w","DOIUrl":"10.1007/s12665-025-12237-w","url":null,"abstract":"<div><p>Attabad Lake is a debris-dammed lake formed due to a landslide disaster on 4th January 2010 in Gojal Valley. Multiple villages are located downstream of the lake along Hunza River. As this lake was formed by a massive landslide, there always remain questions about dam’s stability. The lake is in an active seismic zone which makes it prone to future earthquake and landslide disasters. Considering the sensitivity of region and ambiguities about dam’s structural integrity, this study adopts scenario-based approach for flood risk assessment and identification of potential inundation hotspots downstream. Seven hypothetical flow scenarios ranging from 5 to 50% flow were hydrologically modeled using HEC-RAS 6.5. Based on unsteady flow analysis, inundation boundary, depth, velocity, and product of depth and velocity were computed for all scenarios. The inundation boundary was highest (26.1 km²) in 50% flow scenario followed by 35% (19.6 km²), 25% (8.5 km²), 20% (5.1 km²), 15% (3.5 km²), 10% (3.1 km²), and 5% (2.5 km²). Threshold value of depth i.e., 0.35 m surpassed in all scenarios, whereas threshold velocity (1.5 m/s) was exceeded only in 50% flow scenario. In all flow scenarios, mean value of depth times velocity was higher than the threshold value of 0.52 m²/s. Based on analysis of flood critical parameters, flooding hotspots were mapped, and socio-economic impacts were evaluated. Using risk assessment maps, strategies for infrastructure development downstream, timely evacuation of villages in high-risk zones, and extensive disaster management plans can be prepared by administrative authorities to avoid casualties and economic loss.</p><h3>Graphical Abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12237-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS-based multi-criteria decision-making for identifying potential artificial groundwater recharge zones in the Tikurwuha watershed of Ethiopia","authors":"Yisak Mohammed Ababulgu,&nbsp;Mikias Biazen Molla","doi":"10.1007/s12665-025-12220-5","DOIUrl":"10.1007/s12665-025-12220-5","url":null,"abstract":"<div><p>Groundwater extraction has increased significantly by over 30% in urbanizing areas globally due to increasing population growth. Approximately 2 billion people depend on groundwater as their primary source of drinking water, and urban population growth has resulted in aquifer depletion and environmental degradation. This problem also exists in most cities of Ethiopia, including the study area. This study identifies the potential artificial groundwater recharge zones (AGRZs) in the Tikurwuha watershed. A GIS-based multi-criteria decision-making method was used in ArcGIS 10.5 to identify potential artificial groundwater recharge zones. In this process, nine factors were chosen: rainfall, soil texture, geology, normalized difference vegetation index, slope, topographic position index, topographic wetness index, drainage density, and lineament density. The factors were created using rainfall data from national meteorological stations, soil texture data from the FAO soil database, and geology data from the Ethiopia Geological Survey, as well as Landsat images and digital elevation models within ArcGIS 10.5. The weights of all selected factors were derived using the Analytical Hierarchy Process after determining the relative importance between pairs of factors. Suitability classes were generated for all factors, and then a weighted overlay was performed in ArcGIS 10.5. The final output of potential AGRZs was categorized as extremely high (0.5625 hectares (0.001%)), high (20,003.7 hectares (30.959%)), moderate (42,428.17 hectares (65.665%)), poor (2,179.656 hectares (3.373%)), and very poor (1.312 hectares (0.002%)).The NDVI and TPI were the next most important parameters, after drainage density, slope, and rainfall. These factors have a major impact on the processes of groundwater recharge, infiltration, and runoff generation. With an Area Under the Curve of 77.45%, the study showed that it was very capable of using geospatial methodologies and validation against high-resolution data to properly estimate appropriate artificial groundwater recharge zones. Therefore, high-potential locations can be used to use artificial groundwater recharge techniques by decision-makers in charge of the sustainable management of groundwater resources.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the response of calcareous soils to 27 years vs. 16 years of irrigation with treated wastewater: a case study in Eastern Tunisia","authors":"Siwar Kassar Feki,&nbsp;Nebil Belaid,&nbsp;Kamel Zouari,&nbsp;Rim Trabelsi,&nbsp;Rim Benhmid,&nbsp;Wassef Ben Nasser","doi":"10.1007/s12665-025-12233-0","DOIUrl":"10.1007/s12665-025-12233-0","url":null,"abstract":"<div><p>The duration of irrigation with treated wastewater emerges as a key factor influencing the impact of this practice on the properties of calcareous soils in semi-arid regions. This study targets three selected cropland plots of calcisol: two plots are irrigated with treated wastewater for different periods (27 years, 16 years) and the third one is non irrigated (control). A systematic vertical sampling was performed, based on a triangular grid in 8 layers every 10 cm. All soil samples are characterized by their texture, alkalinity, organic matter, carbonates, CEC, salinity, sodicity and total contents of heavy metals such as Cu, Zn, Ni, Mn and Fe. Statistical analyses were performed to compare the variability patterns of physicochemical characteristics between layers, including: Wilcoxon-Mann-Whitney test and PCA analysis. The study revealed different effects of the irrigation durations on soil properties. The soils irrigated since 27 years showed an increase in pH and total CaCO₃ content and became saline sodic soils. These effects are attributed to the sodification process after long-term of irrigation. Conversely, after 16 years of irrigation, soils showed a decrease in pH and CaCO₃ content due to salt inputs from treated wastewater, which substitute Ca in the argilo-humic complex of the soil and become saline-non sodic. Moreover, the both irrigated soils revealed an increase of total heavy metal (Cu, Zn, Mn and Fe). These changes highlighted distinct correlation patterns between parameters for each irrigation period, emphasizing the importance of native calcite alteration.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote sensing techniques for hydrocarbon Micro-Seepage detection in Raman mountain, Turkey","authors":"Mehmet Cetin,&nbsp;Hakan Oktay Aydinli,&nbsp;Mahdi Hasssan Pashaei,&nbsp;Umit Guler,&nbsp;Muge Demir Cakir,&nbsp;Hatice Selin Aydemir,&nbsp;Serhat Aydemir,&nbsp;Mehtap Ozenen Kavlak,&nbsp;Saye Nihan Cabuk,&nbsp;Alper Cabuk","doi":"10.1007/s12665-025-12239-8","DOIUrl":"10.1007/s12665-025-12239-8","url":null,"abstract":"<div><p>Satellite images are valuable resources for detecting surface manifestations of hydrocarbon-induced soils and sediments in potential petroleum reservoirs, particularly in inaccessible areas where field surveys are challenging. This study employed band ratio (BR) and principal component analysis (PCA) techniques to investigate hydrocarbon micro-seepage in low API mature oil fields in Raman Mountain, Türkiye, using Landsat-8 multi-spectral data. The BR and PCA analyses revealed clay and ferrous iron-rich areas within the study boundaries. The results showed that 329 out of 657 existing wells (52%) correlated with hydrocarbon presence, confirming the effectiveness of remote sensing techniques in oil and gas exploration. The study demonstrated that micro-seepage detection in heavy hydrocarbon areas with low permeability is feasible, challenging previous research that primarily focused on light hydrocarbons. Raman Mountain’s heavy oil characteristics include low API gravity values between 7 and 12 and low permeability, complicating direct detection. The study applied band ratios to ferrous iron, clay minerals, and their combinations, using the Crosta Technique to delineate mineral alteration mapping. The eigenvalues and eigenvectors were determined based on existing literature. Overlays of BR and PCA maps with hydrocarbon well locations indicated significant correlations, with a precision score of 52.47%. This suggests that surface anomalies related to hydrocarbon micro-seepage can be reliably identified using Landsat-8 multi-spectral data. These findings support the theory that hydrocarbon micro-seepages are linked to chemical and mineralogical changes in rocks and soils. The results emphasize the importance of integrating RS techniques into hydrocarbon exploration strategies, providing a cost-effective and time-saving approach for detecting subsurface hydrocarbon reserves. Future research should further explore the role of fault systems and structural traps in hydrocarbon migration to refine detection methodologies.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12239-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of force chain during sand liquefaction: perspective from fabric anisotropy and force chain length","authors":"Dongtao Zhang,&nbsp;Kuang Cheng,&nbsp;Hongshuai Liu,&nbsp;Yupeng Shen,&nbsp;Liyun Li","doi":"10.1007/s12665-025-12231-2","DOIUrl":"10.1007/s12665-025-12231-2","url":null,"abstract":"<div><p>The initiation and development of sand liquefaction has been demonstrated to be closely related to the microscopic fabric evolution in previous research. The evolution of force chains and fabric anisotropy plays a critical role in the evolution of sand liquefaction, while a further study on the force chain length and the fabric anisotropy of the strong and weak force chains during sand liquefaction is still needed. To this end, undrained cyclic biaxial simulations were conducted using discrete element method. Various cyclic stress ratios (CSR) and packing densities were considered. The results show that the contact and mechanical anisotropy of the sample increases with the increment of CSR, while the increase of anisotropy is mainly attributed to the strong force chains. The anisotropy of the weak force chains is much smaller compared to that of the strong force chains and it varies little throughout the sand liquefaction. The anisotropy of strong force chains increases obviously with the development of sand liquefaction, which is further demonstrated to be related to the growth of the effective stress ratio. The strong force chain length was calculated as the number of particles participating in the transmission of strong forces. The total number of strong force chains decrease with the development of sand liquefication, while the relative frequency of the strong force chains with a given length always exhibits an exponentially distribution with the growth of force chain length at any stage of sand liquefication.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing sentinel-2 and Landsat 8 spectral reflectance indices for predicting soil organic carbon","authors":"Lin Cheng","doi":"10.1007/s12665-025-12235-y","DOIUrl":"10.1007/s12665-025-12235-y","url":null,"abstract":"<div><p>Soil organic carbon (SOC) significantly improves soil properties, but traditional measurement methods are time-consuming and costly, emphasizing the need for faster, cost-effective alternatives for sustainable soil management. This study aimed to assess the potential of using the standardized spectral reflectance index (ZPC), derived from satellite images, to estimate SOC content. A total of 410 soil samples were collected from agricultural lands in Xuchang County, and the SOC content was measured. To reduce the volume and complexity of the calculations, Principal Component Analysis (PCA) was applied to the band data from both Landsat 8 and Sentinel-2 satellite images. The principal component (PC) with the highest correlation to SOC content was then standardized and considered as the ZPC1 index. Subsequently, a regression relationship between ZPC1 and SOC content was established. The findings revealed a strong correlation between the different bands of the Landsat 8 and Sentinel-2 satellite imagery. Additionally, the PC1 of both satellites, Landsat 8 (<i>r</i> = 0.65) and Sentinel-2 (<i>r</i> = 0.82), demonstrated a high correlation with SOC content and was therefore standardized. A robust and significant regression relationship was established between ZPC1 and SOC content. When comparing the accuracy of SOC content estimation using ZPC1 from the two satellites, Sentinel-2 outperformed Landsat 8, showing higher accuracy (R² = 0.65, RMSE = 0.28, and MBE = 0.08) compared to Landsat 8 (R² = 0.52, RMSE = 0.32, and MBE = 0.10). Overall, the results indicate that the ZPC1 index provides a rapid and accurate method for SOC content monitoring, significantly reducing the complexity of traditional methods. Therefore, it is recommended that future study further validate this method to ensure its accuracy and efficiency for rapid SOC content assessment.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}