Remote Sensing of Environment最新文献

{"title":"Identification and evaluation of nighttime light pollution in residential gathering area of megacities based on SDGSAT-1 glimmer imagery","authors":"Yixuan Wu ,&nbsp;Chenhao Huang ,&nbsp;Yang Ye ,&nbsp;Linlu Mei ,&nbsp;Yalan Liu ,&nbsp;Dacheng Wang ,&nbsp;Weirong Chen ,&nbsp;Jinsong Deng","doi":"10.1016/j.rse.2025.114894","DOIUrl":"10.1016/j.rse.2025.114894","url":null,"abstract":"<div><div>Nighttime light pollution has become an increasingly serious issue in rapidly urbanizing megacities. It not only disrupts circadian rhythms and affects mental health, but also leads to energy waste and undermines the stability of urban and surrounding ecosystems, posing a significant threat to sustainable development. This study evaluated nighttime light pollution in the residential gathering areas of two typical megacities in China (Beijing and Shanghai) using 40-m SDGSAT-1 glimmer imagery (reflecting actual supply) and population grids (reflecting human demand) refined by the high-performance Random Forest model (with R² values of 0.93 for Beijing and 0.81 for Shanghai). By integrating urban functional zoning data to supplement the demand for nighttime lighting, a Nighttime Light Supply-Demand Mismatch Index (NLSDMI) was developed to quantify the imbalance of nighttime light between supply side and demand side. The results showed that Shanghai's nighttime light pollution area covered 78.25 km² (15.10 %), a higher proportion than Beijing's 115.61 km² (11.29 %) of the study area. Shanghai also exhibited higher peak NLSDMI values. In both cities, residential zones were among the primary contributors to nighttime light pollution. Additionally, in Beijing, the largest share was distributed in parks and green spaces, while in Shanghai, the second major distribution was found in industrial zones. The spatial patterns of nighttime light pollution reflected the distinct characteristics of the two megacities: Beijing focuses on cultural and administrative functions, while Shanghai tends to play its role as an economic hub. Accordingly, feasible countermeasures, including targeted lighting strategy formulation, urban land-use planning refinement and energy-saving lighting technology innovation, were proposed to mitigate light pollution and promote urban sustainability. This study demonstrated the promising potential of SDGSAT-1 glimmer imagery in advancing light pollution assessment and urban management. It also provides practical pathways toward the achievement of multiple Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). Future research should focus on enhancing data accuracy, improving validation methods, and exploring the applicability of findings to cities with diverse types and scales, thus providing broader theoretical support and practical guidance for global nighttime light pollution management.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114894"},"PeriodicalIF":11.1,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic and morphological analysis of oceanic vortex streets in the Yellow Sea using SDGSAT-1 imagery","authors":"Linghui Xia ,&nbsp;Baoxiang Huang ,&nbsp;He Gao ,&nbsp;Ge Chen","doi":"10.1016/j.rse.2025.114889","DOIUrl":"10.1016/j.rse.2025.114889","url":null,"abstract":"<div><div>The oceanic Kármán vortex street is a significant fluid dynamics phenomenon resulting from the unsteady separation of the boundary layer behind a bluff body. In this study, multispectral images from the Sustainable Development Goals Science Satellite 1 (SDGSAT-1) were utilized to observe oceanic vortex streets in the Yellow Sea from 2021 to 2024. A statistical analysis of 114 vortex streets was conducted from both dynamic and morphological perspectives. The relationship between vortex streets and ocean currents was explored from multiple perspectives, including single-factor statistical analysis, multi-factor statistical analysis, and case studies. Experimental results indicate that the formation of vortex streets in the Yellow Sea is primarily driven by interactions between tidal currents and islands. Furthermore, the spatiotemporal distribution and characteristic parameters of oceanic vortex streets were analysed using time-series SDGSAT-1 data. The observation frequency of oceanic vortex streets follows a general pattern of higher frequency in winter and lower frequency in summer, with most characteristic parameters being stronger in winter and weaker in summer. The seasonal characteristics of tidal currents have a significant impact on the vortex street characteristics. High-resolution satellite imagery reveals that the average aspect ratio of vortex streets is 2.75 and the Reynolds number is 403.56 in winter, compared to 1.92 and 185.86, respectively, in summer. This research presents the first temporal observations and systematic analysis of oceanic vortex streets across an entire marine area, offering practical significance for advancing and implementing multiple targets under SDG 14.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114889"},"PeriodicalIF":11.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the potential of principal component analysis for the reconstruction of full-spectrum SIF emission and emulated airborne-to-satellite upscaling","authors":"Miguel Morata ,&nbsp;Bastian Siegmann ,&nbsp;José Luis García-Soria ,&nbsp;Juan Pablo Rivera-Caicedo ,&nbsp;Jochem Verrelst","doi":"10.1016/j.rse.2025.114865","DOIUrl":"10.1016/j.rse.2025.114865","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Solar-induced fluorescence (SIF) emitted by plants as a byproduct of photosynthesis provides critical insights into vegetation health and climate regulation. However, detecting the weak SIF signal from small telluric oxygen absorption features remains challenging. ESA’s upcoming Fluorescence Explorer (FLEX) mission will retrieve full-spectrum SIF data at 300 m spatial resolution. In the meantime, we propose an alternative approach to reconstruct full-spectrum SIF from &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; bands using Principal Component Analysis (PCA) and the Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model. Based on 100,000 SCOPE simulations (640–850 nm at 1 nm resolution), the SIF signals in the &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; (760 nm) and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; (687 nm) bands showed high correlations with adjacent spectral regions and the full spectrum (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;89&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;). From this data, we derived linear regression functions linking SIF at the &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; (760 nm) and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; (687 nm) bands to the first two principal components (PCs), enabling inverse PCA transformation to reconstruct full-spectrum SIF with &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;98&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and RMSE &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;&lt;&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;12&lt;/mn&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mtext&gt;mW m&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mtext&gt;nm&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mtext&gt;sr&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. Applying the functions to HyPlant airborne SIF maps (1.7 m resolution) in northeastern Spain, and subsequent PC transformation, successfully reconstructed full-spectrum SIF including peaks and total emitted flux (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;S&lt;/mi&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;) with propagated uncertainties. To transfer this airborne full-spectrum SIF data to the satellite scale, we then trained an emulator with PRecursore IperSpectrale de la Missione Applicativa (PRISMA) Bottom of Atmosphere (BOA) reflectance spectra as input to produce spaceborne synthetic full-spec","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114865"},"PeriodicalIF":11.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monte Carlo uncertainty analysis from top-of-atmosphere reflectance to plant functional type distributions","authors":"R. Quast ,&nbsp;G. Kirches ,&nbsp;C. Brockmann ,&nbsp;M. Böttcher ,&nbsp;R. Shevchuk ,&nbsp;C. Lamarche ,&nbsp;P. Defourny ,&nbsp;C.M.J. Albergel ,&nbsp;O. Arino","doi":"10.1016/j.rse.2025.114875","DOIUrl":"10.1016/j.rse.2025.114875","url":null,"abstract":"<div><div>Uncertainty in the trends and variations of climate variables in climate data records is as important to understand as climate trends and variations themselves. Metrology provides the framework for assessing and budgeting uncertainty but the application of metrology to climate data records derived from Earth Observation is a scientific and technical challenge and a matter of research. We applied Monte Carlo methodology to demonstrate the end-to-end uncertainty budget for the quantitative variables (seasonal land surface spectral reflectance and plant functional type fractional coverage) of the Land Cover project within ESA’s Climate Change Initiative on the example of one year of Sentinel-3 OLCI remote sensing data and study cases in Africa, Europe, and South America. The budget considers most important sources of errors and takes account of uncorrelated and fully correlated random error structures. The interquartile range of relative standard uncertainty per datum of yearly land surface spectral reflectance is 0.050–0.108 at 490 nm, 0.015–0.046 at 560 nm, 0.007–0.062 at 665 nm, and 0.008–0.024 at 885 nm. The uncorrelated random component of seasonal land surface reflectance uncertainty diminishes with the duration of the season. Spectrally anti-correlated errors in seasonal land surface reflectance composites were attributed to a maximum spectral index selection criterion used for daily image composition. The typical range of standard uncertainty per datum of plant functional type fractional area coverage is 0.3 to 30.8 percent and depends on type abundance. Up to 3.5 percent of fractional coverage uncertainty is attributed to random fluctuation, higher uncertainty is caused by the variation of land cover classes. Errors in plant functional type fractional area coverage are typically anti-correlated. Confusion between natural and managed grass drives the uncertainty in African savannah.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114875"},"PeriodicalIF":11.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data processing and acquisition geometry impact the estimation of plant trait-based functional richness from airborne imaging spectroscopy","authors":"Marius Vögtli ,&nbsp;Isabelle S. Helfenstein ,&nbsp;Daniel Schläpfer ,&nbsp;Meredith C. Schuman ,&nbsp;Mathias Kneubühler ,&nbsp;Alexander Damm","doi":"10.1016/j.rse.2025.114846","DOIUrl":"10.1016/j.rse.2025.114846","url":null,"abstract":"<div><div>Functional diversity can be assessed remotely from optical sensors using vegetation index-based plant traits. Without effective corrections, employed reflectance values are affected by absorption and scattering processes in the atmosphere and on the ground, which modify radiance and irradiance values used for the reflectance retrieval. Additionally, the anisotropic nature of vegetation canopies induces observation and illumination angle-dependent reflectance variations. Often, however, the reflectance retrieval is not accurate enough to compensate for these effects in the atmosphere and on the surface, resulting in uncertain reflectance values. Furthermore, the effects in retrieved reflectance values propagate into derived products, like the vegetation indices used for calculating functional diversity, where they manifest as apparent differences between temporally close observations of the same area. A key to compensating for these effects lies in the capacity and consideration of several processing steps, such as atmospheric, topographic, and anisotropy correction.</div><div>To date, it is unknown how these effects and their correction influence the estimation of functional richness. Here, we estimate functional richness based on three differently retrieved reflectance datasets in the overlapping area of three consecutively acquired flight lines with short temporal differences but with three distinct acquisition geometries. We analyze how atmospheric, topographic, and anisotropy effects influence functional richness estimates and how functional richness varies due to different observation and illumination angles.</div><div>We show that reflectance data before correction for atmospheric, topographic, and anisotropy effects yield up to 15% larger median functional richness estimates compared to data after respective corrections. We discuss under which circumstances comprehensive data processing can reduce between-observation differences. Furthermore, we show that resulting functional richness estimates correlate with the number of shaded pixels (r² <span><math><mo>≈</mo></math></span> 0.7). Consequently, observations in the solar principal plane with more or fewer shadows can lead to larger or smaller functional richness estimates and to differences compared to observations perpendicular to the solar principal plane.</div><div>We conclude with recommendations concerning best-suited data processing and acquisition geometry for reliable and repeatable assessments of functional richness from optical remote sensing data and discuss applications to aerial and space-based observations of functional diversity.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114846"},"PeriodicalIF":11.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban recovery patterns after the 2023 Turkey-Syria earthquake revealed by SDGSAT-1 nighttime light data","authors":"Yu Gong ,&nbsp;Xi Li ,&nbsp;Deren Li ,&nbsp;Xubing Zhang","doi":"10.1016/j.rse.2025.114888","DOIUrl":"10.1016/j.rse.2025.114888","url":null,"abstract":"<div><div>The Turkey-Syria earthquake, which struck in February 2023, was the worst earthquake the region had suffered in the last two decades. The post-earthquake reconstruction process remains underway, with local communities continuing to grapple with challenges. In this study, four cities in Turkey (i.e., Antakya, Kirikhan, Samandag, and Nurdagi) were investigated to track the post-disaster recovery process. We employed the power recovery percentage metric, derived from glimmer imagery acquired by the Sustainable Development Science Satellite 1 (SDGSAT-1), which records nighttime light (NTL), to track the spatial-temporal dynamics of power restoration over the year following the earthquake. Clustering on time series NTL data was then utilized to identify pixel-scale recovery patterns. Furthermore, urban morphological variables were measured to explore their relationship with urban recovery at the block level. Our findings reveal three diverse dynamic patterns, characterized by ascending, descending, and stable NTL change trajectories. Notably, grids exhibiting rising NTL trends align closely with post-disaster reconstruction efforts (e.g., newly-built accommodation areas). In addition, blocks with low-density buildings, abundant open spaces, and uniform layouts demonstrate greater resilience and faster recovery pace. Overall, this study highlights that the SDGSAT-1 NTL data is powerful in capturing heterogeneous urban recovery processes following the disaster, thereby showing its contribution to advancing Sustainable Development Goal 11.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114888"},"PeriodicalIF":11.1,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study on detection of human activity using SDGSAT-1 glimmer imager data over urban agglomerations in China","authors":"Lu Zhang ,&nbsp;Huadong Guo ,&nbsp;Dong Liang ,&nbsp;Zhuoran Lv ,&nbsp;Zilu Li ,&nbsp;Yaqi Geng ,&nbsp;Xuting Liu ,&nbsp;Mingyang Lv ,&nbsp;Changyong Dou","doi":"10.1016/j.rse.2025.114886","DOIUrl":"10.1016/j.rse.2025.114886","url":null,"abstract":"<div><div>Sustainable Development Goal (SDG) 11 aims to make cities and human settlements inclusive, safe, resilient, and sustainable. Understanding urban agglomerations, as highly developed products of urbanization, is important for achieving SDG 11. The Sustainable Development Science Satellite (SDGSAT-1), launched in 2021, aims to characterize “human activity traces” at a fine scale to fill data gaps and address incomplete methods in the implementation of the United Nations 2030 Agenda for Sustainable Development. The satellite, with a 10 m glimmer imager, provides a new and valuable data source for research related to urban agglomerations. To better describe the degree of construction and development of urban agglomerations, we established two new indicators—the City Activity Index (<span><math><mi>CAI</mi></math></span>) and the Population Activity Index (<span><math><mi>PAI</mi></math></span>)—based on SDGSAT-1 glimmer imager data. Additionally, we proposed a novel method for extracting the strength of intercity connections using 10 m glimmer imager data to reflect the current status of city linkages. These methods were combined and applied in three urban agglomerations in China: Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The findings not only enhance our understanding of spatial patterns and resource flows within major Chinese urban agglomerations, but also provide actionable data support for urban planning, infrastructure development, and governance. The study fully demonstrates the advantages of SDGSAT-1 high-precision glimmer imager data in depicting urban development, and provides data support for achieving SDG 11.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114886"},"PeriodicalIF":11.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient method for aurora and noise reduction with a harmonized nighttime light dataset","authors":"Mengqing Geng ,&nbsp;Xuecao Li ,&nbsp;Shirao Liu ,&nbsp;Guojiang Yu ,&nbsp;Yuyu Zhou ,&nbsp;Peng Gong","doi":"10.1016/j.rse.2025.114891","DOIUrl":"10.1016/j.rse.2025.114891","url":null,"abstract":"<div><h3>Abstract</h3><div>The availability of long-term, annually harmonized nighttime light (NTL) data is pivotal for monitoring human activities across past decades. The Defense Meteorological Satellite Program (DMSP) has provided over 20 years of NTL observations, facilitating extensive global and regional studies. With the termination of DMSP NTL in 2013 and the subsequent introduction of the Visible Infrared Imaging Radiometer Suite (VIIRS) NTL data, we previously developed the global harmonized NTL dataset (H-NTL-v1), which offers a temporally extended and consistent time series data from 1992 to 2022. Despite its widespread use, the H-NTL-v1 dataset has been affected by noise from auroras and transient lights, particularly in high-latitude areas. In this study, we present an innovative method that employs temporal frequency analysis and Pareto surface optimization to address these challenges, resulting in an improved global harmonized NTL dataset (H-NTL-v2). This enhanced dataset markedly improves the consistency between historical DMSP (1992–2013) and the DMSP-like estimates post-2014. For aurora affected city lights, here we did not implement a specific correction algorithm. Our results indicate that the improved H-NTL-v2, spanning 1992 to 2022, significantly reduces auroral noise and inter-annual variability. Compared to the original H-NTL-v1, the improved H-NTL-v2 demonstrates strong agreement with DMSP observation in 2012 and 2013. It exhibits significantly diminished fluctuation in total lit pixels and digital numbers, particularly for low-luminance pixels. This refined dataset minimizes noise impacts from auroras and other sources, enhancing the application potential of NTL data in studies of light pollution, urban slums, and poverty and inequality in developing regions.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114891"},"PeriodicalIF":11.1,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144516286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-situ and triple collocation-based evaluations of Tianmu-1 global soil moisture products","authors":"Qingyun Wang,&nbsp;Cuixian Lu,&nbsp;Yuxin Zheng,&nbsp;Zhuo Wang,&nbsp;Jiafeng Li,&nbsp;Yini Tan","doi":"10.1016/j.rse.2025.114892","DOIUrl":"10.1016/j.rse.2025.114892","url":null,"abstract":"<div><div>Global Navigation Satellite System-Reflectometry (GNSS-R), as a favorable technology to provide large-scale soil moisture estimates, contributes to studies in climatology, hydrology, and agriculture. The Tianmu-1 Meteorological Mission (TM-1), currently runs 23 satellites in orbit (including one experimental satellite) with multi-GNSS compatibility, achieve shorter revisit periods and higher data acquisition frequencies compared with single-satellite missions. The hourly TM-1 surface soil moisture (SSM) products, offer affluent information for global soil moisture monitoring. This study provides the first comprehensive characterization and performance evaluation of TM-1 SSM products based on in-situ measurements and products of Soil Moisture Active Passive (SMAP), European Space Agency Climate Change Initiative (ESA CCI), and Global Land Data Assimilation System (GLDAS). The TM-1 SSM demonstrates expected spatiotemporal patterns at both regional and global scales. The in-situ validation results reveal its landcover-dependent accuracy, with superior performance over bare soils (unbiased Root Mean Square Error, ubRMSE of about 0.02 m³/m³) compared to vegetated regions (ubRMSE of around 0.07 m³/m³). Furthermore, Extended Triple Collocation (ETC) assessments using (1) TM-1, active, and ground observations and (2) TM-1, model, and ground observations triplets are conducted. The ETC-derived results present that TM-1 SSM achieve global correlation coefficient of 0.75 and random error standard deviation of 0.035 m³/m³. Overall, this study demonstrates the reliable accuracy of TM-1 SSM product, and provides valuable insights for its refinement and potential applications.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114892"},"PeriodicalIF":11.1,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A line-spread kernel function for angular anisotropy in row-dominated heterogeneous scenarios","authors":"Yifan Lu ,&nbsp;Zunjian Bian ,&nbsp;Chandrika Pinnepalli ,&nbsp;Jean-Louis Roujean ,&nbsp;Mark Irvine ,&nbsp;Xinguang Sang ,&nbsp;Xiaobo Luo ,&nbsp;Hua Li ,&nbsp;Yongming Du ,&nbsp;Biao Cao ,&nbsp;Qing Xiao","doi":"10.1016/j.rse.2025.114887","DOIUrl":"10.1016/j.rse.2025.114887","url":null,"abstract":"<div><div>Land Surface Temperature (LST) is a fundamental variable for determining mass (water, carbon) and energy surface fluxes. LST can be obtained from remote sensing but under varying configuration geometries that create directional effects due to the inherent anisotropy properties of most terrestrial targets. Actually, thermal infrared (TIR) measurements obtained from satellites or unmanned aerial vehicles (UAV) are seriously impacted by varying viewing and solar geometries (Cao et al., 2019). In this regard, a computationally efficient approach to handle them is using kernel-driven models (KDM), as they were shown to be an effective solution. However, in high-resolution scenes, the structural features can be very detailed and, in this case, the assumption of homogeneity in considering traditional KDM no longer holds. This is why we propose to develop a novel KDM that is able to handle typical heterogeneous scenes whose structure is dominated by rows. Rather than improving existing point-spread kernels, we propose a line-spread kernel considering the row orientation and radiative occlusion. This new KDM is validated with both airborne measurements and simulated datasets generated by three-dimensional radiative transfer models. Results indicate that: 1) This proposed Heterogenous KDM captures the directional anisotropies of temperatures in row-planted vineyard canopies, whereas the traditional point-spread KDM show limitations. In most cases, root mean squared errors (RMSE) improved up to 0.5 K. 2) A sensitivity analysis based on simulated datasets also showed a better performance of the new proposed KDM under different cases including LAI and row height/width. 3) Further simple validation using UAV and sandbox measurements has demonstrated the effectiveness of the proposed KDM in urban and mountainous areas, where stripe characteristics in thermal radiation directionality are present. In conclusion, this study proposes a novel KDM with significant practical implications for heterogeneous scenarios.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114887"},"PeriodicalIF":11.1,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}