Remote Sensing of Environment最新文献

{"title":"Measuring topographic change after volcanic eruptions using multistatic SAR satellites: Simulations in preparation for ESA’s Harmony mission","authors":"Odysseas Pappas ,&nbsp;Juliet Biggs ,&nbsp;Pau Prats-Iraola ,&nbsp;Andrea Pulella ,&nbsp;Adam Stinton ,&nbsp;Alin Achim","doi":"10.1016/j.rse.2024.114528","DOIUrl":"10.1016/j.rse.2024.114528","url":null,"abstract":"<div><div>Volcanoes are dynamic systems whose surfaces constantly evolve. During volcanic eruptions, which can pose great threat to local communities, significant changes to the local topography occur as edifices build up and/or collapse and lava, tephra and other eruptive products are deposited. Monitoring such changes in topography is crucial to risk assessment and the prediction of further eruptive behaviour. Multistatic Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing modality particularly suited to this task as it allows for the creation of digital elevation models (DEMs) that can accurately map out three-dimensional changes in the topography, regardless of weather conditions and temporal decorrelation caused by volcanic activity. Few such missions are however currently operational. Harmony is an upcoming ESA mission that will be operating alongside Sentinel-1 and will provide multistatic InSAR capabilities for the measurement of stress and deformation across the cryosphere, the oceans and the solid earth, with the monitoring of topographic change due to volcanic eruptions being one of the specific areas of focus for the mission.</div><div>In this work we demonstrate the use of high resolution bistatic interferometric data from TanDEM-X for the measurement of topographic change after recent eruptions in El Reventador, Ecuador and La Soufrière, St. Vincent and the Grenadines. Additionally, we simulate data at the lower, 20 m resolution of Harmony so as to gain insights into its capability in quantifying topographic change. Our results demonstrate that Harmony’s resolution can be sufficient to resolve and measure accurately topographic change such as the emplacement of lava flows, but may be challenged in areas of steep topography where unwrapping errors can occur. The experimental results highlight the effect of acquisition pass direction with respect to local topography, the challenges arising in areas of steep topography and the importance of masking results based on estimates of precision and resolution. Finally we discuss some of the challenges, as well as implications of the Harmony mission for the future of volcano monitoring.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114528"},"PeriodicalIF":11.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142742486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bushfire recovery at a long-term tall eucalypt flux site through the lens of a satellite: Combining multi-scale data for structural-functional insight","authors":"William Woodgate ,&nbsp;Stuart Phinn ,&nbsp;Timothy Devereux ,&nbsp;Raja Ram Aryal","doi":"10.1016/j.rse.2024.114530","DOIUrl":"10.1016/j.rse.2024.114530","url":null,"abstract":"<div><div>Satellite earth observation (EO) data plays a vital role quantifying vegetation structural and functional metrics across spatio-temporal scales. However, the degree of coupling between satellite derived spectral signals and the rate of photosynthesis, as estimated by Gross Primary Productivity (GPP), both before and after bushfire remain understudied, yet these are a critical part of the global carbon cycle. This study evaluated a combination of passive optical and active LiDAR satellite data to quantify the disturbance and recovery of photosynthesis from a major fire event. The work was completed at the Tumbarumba long-term tall eucalypt flux site following a catastrophic bushfire in December 2019. TROPOMI solar-induced fluorescence (SIF) and Sentinel 2 derived greenness and burn severity metrics (NDVI, EVI, NIRv, and NBR) were investigated, termed ‘spectral metrics’ herewith. Detailed in-situ observations from leaf-to-canopy scales were utilised to examine variations in vegetation structural-functional parameters.</div><div>We found the rate of vegetation spectral metrics recovery largely outpaced GPP recovery at the one- and two-year post-fire mark. Specifically, SIF recovered to 80–90 % compared to pre-fire levels, whereas GPP recovered only 45–50 %. This indicated that separate SIF:GPP functions were required for pre- and post-fire data to account for different recovery trajectories due to changes in canopy structure and species composition. The use of TROPOMI SIF for monitoring canopy productivity at seasonal (monthly) time-scales was advantageous over traditional greenness-based indices, as SIF tracked GPP seasonality both pre- and post-fire. Spaceborne GEDI LiDAR data effectively captured post-fire changes in forest structure, albeit at sparse spatio-temporal sampling intervals, revealing a significant reduction in overstorey vegetation density and a concurrent increase in understorey vegetation density. This contributed to reduced carbon uptake, compared to pre-fire, due to the lower light use efficiency of understorey species, which was verified with in-situ gas exchange measurements. Overall, this study highlights the importance of accounting for disturbance history and the relative abundance of overstorey and understorey vegetation for tracking GPP from satellite platforms. Our results also highlight the crucial role of longitudinal field-based data for calibration and validation of EO data, ultimately enhancing our understanding of forest recovery processes.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114530"},"PeriodicalIF":11.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142735533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimising sub-metre resolution 3D geomorphic change detection over large areas using multitemporal airborne laser scanning with Sentinel-1 InSAR and Sentinel-2 optical observations","authors":"Simon J. Walker ,&nbsp;Scott N. Wilkinson ,&nbsp;Tim R. McVicar ,&nbsp;Pascal Castellazzi ,&nbsp;Sana Khan","doi":"10.1016/j.rse.2024.114522","DOIUrl":"10.1016/j.rse.2024.114522","url":null,"abstract":"<div><div>Airborne laser scanning (ALS) is widely used in studies of Earth surface change and has potential to inform targeted landscape remediation over large areas. Leveraging this capability requires geomorphic change detection methods that exploit the full 3D information contained in ALS point clouds but remains challenging over large areas (i.e., &gt; 10 km²). We developed a methodology for geomorphic change detection over large areas using multitemporal ALS in a multiscale model-to-model cloud comparison (M3C2) framework adapted for volumetric estimation. Time series Sentinel-2 optical observations were used to isolate persistently-bare areas as candidate sites to co-register the ALS point clouds. Geomorphic stability of those sites was determined from coherence change detection using time series Sentinel-1 InSAR, thereby ensuring only geomorphically-stable sites were used for co-registration. Results showed the Sentinel-based co-registration produced a closer vertical alignment (0.00 ± 0.09 m) between ALS point clouds over stable parts of the landscape, while co-registration using an iterative closest-point algorithm contained bias (0.07 ± 0.10 m). The methodology was used to estimate annual sediment yield for a semi-arid catchment in northeastern Australia and results were compared with long-term field-based stream sediment monitoring. The ALS-based geomorphic change detection estimated 2.58 ± 0.54 t·ha⁻¹·a⁻¹ sediment yield and stream sediment monitoring estimated 1.40 t·ha⁻¹·a⁻¹. These similar estimates indicate multitemporal ALS can produce realistic whole-of-catchment sediment yield estimates in ungauged catchments (i.e., with no stream sediment monitoring) and improves the spatial detail of those estimates. Accurately detecting geomorphic change from multitemporal ALS also required a strategy to manage vegetation-related error due to misclassification of ALS point clouds. Combined identification of fine-scale erosion processes and reliable estimation of catchment-scale erosion rates indicates the proposed methodology provides a valuable tool for planning landscape remediation over large areas.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114522"},"PeriodicalIF":11.1,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring northern Greenland proglacial river discharge from space","authors":"Dinghua Chen ,&nbsp;Kang Yang ,&nbsp;Mengtian Man ,&nbsp;Chang Huang ,&nbsp;Yuhan Wang ,&nbsp;Xiaodong Yi ,&nbsp;Yuxin Zhu","doi":"10.1016/j.rse.2024.114529","DOIUrl":"10.1016/j.rse.2024.114529","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Large volumes of meltwater produced on the northern Greenland Ice Sheet (GrIS) are directly routed into proglacial rivers, forming continuous supraglacial-proglacial catchments. Thereby, estimating proglacial river discharge is crucial for better understanding of northern Greenland hydrology and mass balance. We propose a method for estimating proglacial river discharge solely from space by combining Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), ArcticDEM, and Harmonized Landsat and Sentinel-2 (HLS) data. Firstly, we use the modified normalized difference water index to extract proglacial river water masks from 30 m HLS imagery time series and calculate river effective width (&lt;em&gt;W&lt;/em&gt;&lt;sub&gt;&lt;em&gt;e&lt;/em&gt;&lt;/sub&gt;). Secondly, we derive near-dry riverbed cross-sectional curves from ICESat-2 ATL06 data. Thirdly, we intersect proglacial river water masks with riverbed cross-sectional curves to calculate the mean depth, wetted perimeter, cross-sectional area, and hydraulic radius, and combine ArcticDEM to estimate the channel bed slope. Finally, with these hydraulic geometry estimates, we calculate proglacial discharge and analyze its uncertainty via error propagation. We apply this method to estimate the proglacial discharge (&lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt;) of the Denmark catchment (area ∼ 3254 km&lt;sup&gt;2&lt;/sup&gt;) in northern Greenland during the 2020–2021 melt seasons and compare &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt; with the surface meltwater runoff (&lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;m&lt;/em&gt;&lt;/sub&gt;) simulated by two regional climate models (RCMs, including MARv3.12 and RACMO2.3p2), and validate the accuracy and spatial transferability of the method with in-situ proglacial discharge (&lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;in-situ&lt;/em&gt;&lt;/sub&gt;) of the Watson River in southwestern Greenland. The results show that: (1) the satellite-estimated &lt;em&gt;W&lt;/em&gt;&lt;sub&gt;&lt;em&gt;e&lt;/em&gt;&lt;/sub&gt; and &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt; exhibit significant seasonal variations, with the average &lt;em&gt;W&lt;/em&gt;&lt;sub&gt;&lt;em&gt;e&lt;/em&gt;&lt;/sub&gt; of 579 ± 371 m for 2020, 505 ± 394 m for 2021, and a maximum of 2040 m, and &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt; has the average value of 207.6 ± 134.1 m&lt;sup&gt;3&lt;/sup&gt;/s for 2020, 210.4 ± 243.2 m&lt;sup&gt;3&lt;/sup&gt;/s for 2021, and a maximum of 1509.4 ± 190.3 m&lt;sup&gt;3&lt;/sup&gt;/s; (2) the satellite-estimated &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt; is positively correlated with the RCM-simulated &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;m&lt;/em&gt;&lt;/sub&gt; (&lt;em&gt;R&lt;/em&gt;&lt;sup&gt;&lt;em&gt;2&lt;/em&gt;&lt;/sup&gt; = 0.82 and 0.69 for MAR and RACMO, respectively), indicating that RCMs can reflect the overall seasonal variations of proglacial discharge reasonably well; (3) the RCM-simulated &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;m&lt;/em&gt;&lt;/sub&gt; is considerably higher than our satellite-estimated &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;&lt;em&gt;s&lt;/em&gt;&lt;/sub&gt;, with the &lt;em&gt;bias&lt;/em&gt;, &lt;em&gt;RMSE&lt;/em&gt;, and &lt;em&gt;RRMSE&lt;/em&gt; for MAR (RACMO) being 116.6 ± 5.9 m&lt;sup&gt;3&lt;/sup&gt;/s (130.3 ± 5.9 m&lt;sup&gt;3&lt;/sup&gt;/s), 174.7 ± 6.7 m&lt;sup&gt;3&lt;/sup&gt;/s (208.9 ± 6.1 m&lt;sup&gt;3&lt;/sup&gt;/s), and 83 ± 4 % (100 ± 4 %), respectively, and (4) our satellite-based method can b","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114529"},"PeriodicalIF":11.1,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697765","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":"Comprehensive LiDAR simulation with efficient physically-based DART-Lux model (II): Validation with GEDI and ICESat-2 measurements at natural and urban landscapes","authors":"Xuebo Yang ,&nbsp;Cheng Wang ,&nbsp;Tiangang Yin ,&nbsp;Yingjie Wang ,&nbsp;Dong Li ,&nbsp;Nicolas Lauret ,&nbsp;Xiaohuan Xi ,&nbsp;Hongtao Wang ,&nbsp;Ran Wang ,&nbsp;Yantian Wang ,&nbsp;Jean Philippe Gastellu-Etchegorry","doi":"10.1016/j.rse.2024.114519","DOIUrl":"10.1016/j.rse.2024.114519","url":null,"abstract":"<div><div>LiDAR is a developed technology that has been widely used to measure the Earth's surface by acquiring accurate three-dimensional (3D) information. DART (Discrete Anisotropic Radiative Transfer) model developed a new LiDAR modeling method based on the Monte Carlo bidirectional path tracing mode named DART-Lux. Using the DART-RC (Ray Carlo) mode as a reference, DART-Lux shows consistency and efficiency for LiDAR signal modeling. This paper presents a further validation of DART-Lux LiDAR model for simulating actual LiDAR waveform and photon-counting measurements by considering two in-orbit spaceborne LiDAR systems: GEDI (Global Ecosystem Dynamics Investigation) and ICESat-2 (Ice, Cloud, and land Elevation Satellite-2). The validation experiments are conducted on accurate 3D descriptions of an urban landscape in Toulouse, France, and a natural forest landscape in Saihanba, China. The pulse-by-pulse comparisons of GEDI and simulated waveforms yield mean R² = 0.893, mean RMSE = 0.077. The simulated ICESat-2 photon counting shows accuracies of signal photon frequency (R² = 0.950, RMSE = 0.465 pts./pulse) and noise photon frequency (R² = 0.820, RMSE = 0.247 pts./pulse). Results in GEDI and ICESat-2 overlapping footprints illustrate the usefulness of DART-Lux for studying their height retrieval inconsistency. Furthermore, sensitivity studies conducted with DART-Lux reveal performance and limitation of GEDI and ICESat-2 in height measurement. This study confirms the accuracy of DART-Lux for simulating actual LiDAR signals and provides valuable insights for exploitation of GEDI and ICESat-2.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114519"},"PeriodicalIF":11.1,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697893","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":"Comparing methods for solar-induced fluorescence efficiency estimation using radiative transfer modelling and airborne diurnal measurements of barley crops","authors":"Juliane Bendig ,&nbsp;Zbynĕk Malenovský ,&nbsp;Bastian Siegmann ,&nbsp;Julie Krämer ,&nbsp;Uwe Rascher","doi":"10.1016/j.rse.2024.114521","DOIUrl":"10.1016/j.rse.2024.114521","url":null,"abstract":"<div><div>Ability of remotely sensed solar-induced chlorophyll fluorescence (SIF) to serve as a vegetation productivity and stress indicator is impaired by confounding factors, such as varying crop-specific canopy structure, changing solar illumination angles, and SIF-soil optical interactions. This study investigates two normalisation approaches correcting diurnal top-of-canopy SIF observations retrieved from the O₂-A absorption feature at 760 nm (F₇₆₀ hereafter) of summer barley crops for these confounding effects. Nadir SIF data was acquired over nine breeding experimental plots simultaneously by an airborne imaging spectrometer (HyPlant) and a drone-based high-performance point spectrometer (AirSIF). Ancillary measurements, including leaf pigment contents retrieved from drone hyperspectral imagery, destructively sampled leaf area index (LAI), and leaf water and dry matter contents, were used to test the two normalisation methods that are based on: i) the fluorescence correction vegetation index (FCVI), and ii) three versions of the near-infrared reflectance of vegetation (NIR_V). Modelling in the discrete anisotropic radiative transfer (DART) model revealed close matches for NIRv-based approaches when corrected canopy SIF was compared to simulated total chlorophyll fluorescence emitted by leaves (R² = 0.99). Normalisation with the FCVI also performed acceptably (R² = 0.93), however, it was sensitive to variations in LAI when compared to leaf emitted chlorophyll fluorescence efficiency. Based on the results modelled in DART, the NIRvH1 normalisation was found to have a superior performance over the other NIRv variations and the FCVI normalisation. Comparison of the SIF escape fractions suggests that the escape fraction estimated with NIRvH1 matched escape fraction extracted from DART more closely. When applied to the experimental drone and airborne nadir canopy SIF data, the agreement between NIRvH1 and FCVI produced chlorophyll fluorescence efficiency was very high (R² = 0.93). Nevertheless, NIRvH1 showed higher uncertainties for areas with low vegetation cover indicating an unaccounted contribution of SIF-soil interactions. The diurnal courses of chlorophyll fluorescence efficiency for both approaches differed not significantly from simple normalisation by incoming and apparent photosynthetically active radiation. In conclusion, SIF normalisation with NIRvH1 more accurately compensates the effects of canopy structure on top of canopy far red SIF, but when applied to top of canopy in-situ data of spring barley, the effects of NIRvH1 and FCVI on the diurnal course of SIF had a similar influence.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114521"},"PeriodicalIF":11.1,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A physics-based atmospheric precipitable water vapor retrieval algorithm by synchronizing MODIS near-infrared and thermal infrared measurements","authors":"Shugui Zhou ,&nbsp;Jie Cheng","doi":"10.1016/j.rse.2024.114523","DOIUrl":"10.1016/j.rse.2024.114523","url":null,"abstract":"<div><div>This study proposed an innovative joint inversion algorithm that synchronized Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) and thermal infrared (TIR) radiance data for accurate estimates of clear-sky precipitable water vapor (PWV). The algorithm consists of three parts: (1) simplifying the NIR radiative transfer equation by assuming linear reflectance change with wavelength in the 0.85–1.25 μm range, facilitating NIR water vapor absorption channel top-of-atmosphere (TOA) radiance simulation without explicit reflectance; (2) partial derivatives of NIR-TIR TOA radiance with respect to the background fields were derived by applying the one-term variational theorem to the radiative transfer equation; (3) optimization approach was employed to adjust the background fields, minimizing the discrepancy between simulated and observed NIR-TIR TOA radiances. The refined water vapor profile was integrated to derive PWV. Three years in situ measurements from the 473 GPS sites and 122 sun photometers in North America were utilized for PWV validation. Additionally, the MODIS MYD05 and MYD07 PWV products were validated using the same in situ measurements. Validation results indicated that the root mean square error (RMSE) of PWV retrieval using the NIR-TIR joint inversion algorithm ranged from 2.40 mm in summer to 1.67 mm in winter, and the mean bias and RMSE were − 0.55 mm and 2.08 mm, respectively, outperforming MODIS PWV products. The bias and RMSE were 3.84 mm and 4.86 mm for MYD05, and 0.41 mm and 4.60 mm for MYD07. Overall, the NIR-TIR joint inversion algorithm provides an effective way to generate comprehensive, long-term, high-resolution PWV data records.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114523"},"PeriodicalIF":11.1,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142694294","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":"Impact of vegetation phenology on anisotropy of artificial light at night - Evidence from multi-angle satellite observations","authors":"Jinjin Li,&nbsp;Xi Li,&nbsp;Deren Li","doi":"10.1016/j.rse.2024.114525","DOIUrl":"10.1016/j.rse.2024.114525","url":null,"abstract":"<div><div>Anisotropy of artificial light at night (ALAN) has been revealed from satellite observations, as Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) provides multi-angle measurements of ALAN. However, the knowledge behind this phenomenon is very limited. In this study, we hypothesize that vegetation phenology impacts the anisotropy of ALAN, which is defined as the change in radiant intensity with viewing zenith angle (VZA). The time series Normalized Difference Vegetation Index (NDVI) quantifying the vegetation phenology and Change Index (CI) quantifying the ALAN anisotropy were extracted from VNP13A1 and VNP46A2 products, respectively. We analyzed the effect of vegetation phenology by comparing the anisotropy of ALAN at the same location across different seasons in eleven suburban study areas in North America. The anisotropy of ALAN was found to exhibit obvious seasonal dynamic which is consistent with that of NDVI, and these two variables showed significant positive correlation at both pixel scale (0.41 &lt; <em>r</em> &lt; 0.79) and regional scale (0.56 &lt; <em>r</em> &lt; 0.92). Furthermore, we found that the seasonality of the ALAN anisotropy was significantly correlated with the seasonality of vegetation over the eleven study areas (<em>r</em> = 0.75). All these results suggest that vegetation growth can reduce the anisotropy of ALAN. In other words, vegetation growth leads to a more even distribution of emitted light in different directions, which supports our hypothesis. These findings are potentially useful to improve the quality of time series nighttime light data by angular normalization considering vegetation phenology and better build City Emission Function (CEF) for modeling astronomic light pollution.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114525"},"PeriodicalIF":11.1,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating forest litter fuel load by integrating remotely sensed foliage phenology and modeled litter decomposition","authors":"Yanxi Li ,&nbsp;Yiru Zhang ,&nbsp;Xingwen Quan ,&nbsp;Binbin He ,&nbsp;Sander Veraverbeke ,&nbsp;Zhanmang Liao ,&nbsp;Thomas A.J. Janssen","doi":"10.1016/j.rse.2024.114526","DOIUrl":"10.1016/j.rse.2024.114526","url":null,"abstract":"<div><div>Litter on the forest floor, or from a fire perspective the litter fuel load (LFL), is a key driver of the occurrence and spread of surface fires and an important regulator of forest fire behavior. High-quality spatiotemporal LFL data are essential for modeling fire behavior and assessing fire risk in forest ecosystems. Traditionally, LFL is estimated from ground-based measurements, but they are difficult to implement on large spatial scales. While remote sensing techniques have the advantage of large-scale observation, they encounter challenges in retrieving LFL because forest canopies generally block signals from the forest floor. Here we present a new method based on modeled litter accumulation to estimate LFL dynamics, integrating litterfall influx from the forest canopy and decomposition outflux through a mass balance approach. Annual litterfall was estimated based on seasonal changes in foliage fuel load which are retrieved from Landsat imagery and a radiative transfer model, while the decomposition rate was derived from meteorological data. Litterfall and decomposition were quantified over the past 20 years with the difference between the two being LFL accumulating over time. We validated the estimated LFL using 105 ground-based measurements in Liangshan Yi Autonomous Prefecture, China, and this validation demonstrated a reasonably strong performance for estimating LFL (R² = 0.67, root mean squared error (RMSE) = 2.56 Mg ha⁻¹, relative RMSE = 31.61 %). Our method integrates remote sensing-based foliage phenology with the ecological process of LFL accumulation, enabling large-scale LFL monitoring for forest fire risk assessments.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114526"},"PeriodicalIF":11.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684695","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":"Importance of viewing angle: Hotspot effect improves the ability of satellites to track terrestrial photosynthesis","authors":"Haoran Liu ,&nbsp;Jingfeng Xiao ,&nbsp;Dalei Hao ,&nbsp;Fa Li ,&nbsp;Fujiang Ji ,&nbsp;Min Chen","doi":"10.1016/j.rse.2024.114492","DOIUrl":"10.1016/j.rse.2024.114492","url":null,"abstract":"<div><div>The product of near-infrared reflectance of vegetation and photosynthetic active radiation (NIRvP) is a new tool for monitoring gross primary productivity (GPP) dynamics in terrestrial ecosystems, due to the discovered linear correlation between NIRvP and GPP. While remote sensing-based NIRvP is considerably influenced by sensor geometry, such geometry impacts on the NIRvP-GPP relationship remain underexplored. In this study, we calculate NIRvP using observations from the Deep Space Climate Observatory (DSCOVR) that provide unique hotspot observation geometry in which the sensor viewing angle coincides with the sun direction. We evaluated the linear correlation between NIRvP and GPP in both the common nadir direction and the special hotspot direction. The results indicate that NIRvP in the hotspot direction significantly outperforms that in the nadir direction for tracking GPP variations across different ecosystems from diurnal to daily scales. This conclusion is further supported by data from the MODerate resolution Imaging Spectroradiometer (MODIS) and simulations using the Soil Canopy Observation Photosynthesis Energy (SCOPE) model. Our research highlights the value of using the unconventional hotspot-based sun-tracking satellite observations for a more accurate characterization of GPP dynamics in terrestrial ecosystems.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"317 ","pages":"Article 114492"},"PeriodicalIF":11.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690883","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}