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Remote Sensing of Environment
Elsevier
Remote Sensing of Environment

Elsevier

0034-4257

Remote Sensing of Environment/Journal Remote Sensing of EnvironmentSCIISTPEI
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    Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment

    Zheng, XiaopoLi, Zhao-LiangWang, TianxingHuang, Huabing...
    25页
    查看更多>>摘要：Land surface temperature (LST) is an essential input for modeling the processes of energy exchange and balance of the earth's surface. Thermal infrared (TIR) remote sensing is considered to be the most efficient way to obtain accurate LST, both regionally and globally. Currently, many LST retrieval algorithms have been developed, including the up-to-date SW-TES (SW: split window; TES: temperature-emissivity separation) method, which is claimed to be able to accurately derive LST without the need for atmospheric information and land surface emissivity (LSE) based on the selected multiple TIR channel configuration. However, this hybrid method is actually not applicable to observations with large viewing angles and was only preliminarily evaluated in Australia. In this study, this method was extended for application to global TIR measurements with different viewing angles. Additionally, the performance of this extended SW-TES method was assessed globally for different seasons by using the MODIS LST product as a reference, and was also validated using in-situ LST measurements from the SURFRAD (SURFace RADiation budget network) sites. The results showed that the LST retrievals using the extended SW-TES method were comparable to the MODIS LST product, with discrepancies of <2.7 K and < 1.8 K for global daytime and nighttime observations, respectively. Validations based on the SURFRAD in-situ LST measurements indicated that the extended method could be used to retrieve LST accurately with a root-mean-square error (RMSE) of approximately 3.6 K during the daytime and 2.4 K during the nighttime. However, special attention should be paid when applying the extended method to daytime observations on grasslands and shrublands during hot seasons, considering the relatively large discrepancy when using this method compared with that obtained with the MODIS LST product (>4.0 K). Overall, in this study, the SW-TES method was extended, and the performance was comprehensively evaluated at the global scale, which may help in facilitating its potential applications.
      原文链接:
    • NSTL
    • Elsevier

    Multi-sensor change detection for within-year capture and labelling of forest disturbance

    Cardille, Jeffrey A.Perez, ElijahCrowley, Morgan A.Wulder, Michael A....
    12页
    查看更多>>摘要：Knowledge of forest change type and timing is required for forest management, reporting, and science. Time series of historic satellite data (e.g. Landsat) have resulted in an invaluable record of changes in forest conditions. Natural resource management and reporting typically operate at an annual time step, yet the recent addition of data streams from compatible satellites (e.g., Sentinel-2) offer the possibility of generating frequent, management-relevant forest status assessments and maps of change. Analytical approaches that rely on a time series of observations to identify change often struggle to provide reliable estimates of change events in terminal years of the time series until subsequent, additional observations are available. Methods to meaningfully integrate observations from compatible satellite platforms can provide short-term information to augment and refine estimates of change area and type in those terminal years of the time series. In this research we fuse Landsat-8 and Sentinel-2A and -2B data streams to capture, with reduced latency, stand replacing forest change (harvest and wildfire), tagged to a temporal window of occurrence over an similar to 10,000 km(2) area of central British Columbia, Canada. We introduce a new algorithm, SLIMS (Shrinking Latency in Multiple Streams), to rapidly and reliably detect change, and then use an established Bayesian approach to meaningfully combine changes detected in the Landsat and Sentinel data streams. Our results indicate that the type and timing of stand-replacing disturbances can be identified in these forests with high accuracy. Overall, 13.9% of the study area was disturbed between the end of 2016 and the end of 2017, with the majority of disturbed area attributable to wildfire and a smaller amount attributed to forest harvesting, mostly in the winter 2016-2017 with some limited summer harvest also occurring. Overall accuracy of the change, assessed using independent validation data, was 95% +/- 2.3%. The capacity of these change results to augment a trend-based assessment of change for 2017 was also demonstrated and provides a framework for how short- and long-term change detection approaches provide complementary information that can increase the timeliness and accuracy of change area estimates in the terminal years of a time series. These findings also demonstrate the capacity to regard Landsat and Sentinel-2 sensors as elements of a virtual constellation to obtain forest change information in a timely (i.e., end of growing season) and reliable fashion over large areas.
      原文链接:
    • NSTL
    • Elsevier

    First multi-year assessment of Sentinel-1 radial velocity products using HF radar currents in a coastal environment

    Martin, Adrien C. H.Gommenginger, Christine P.Jacob, BenjaminStaneva, Joanna...
    15页
    查看更多>>摘要：Direct sensing of total ocean surface currents with microwave Doppler signals is a growing topic of interest for oceanography, with relevance to several new ocean mission concepts proposed in recent years. Since 2014, the spaceborne C-band SAR instruments of the Copernicus Sentinel-1 (S1) mission routinely acquire microwave Doppler data, distributed to users through operational S1 Level-2 ocean radial velocity (L2 OCN RVL) products. S1 L2 RVL data could produce high-resolution maps of ocean surface currents that would benefit ocean observing and modelling, particularly in coastal regions. However, uncorrected platform effects and instrument anomalies continue to impact S1 RVL data and prevent direct exploitation. In this paper, a simple empirical method is proposed to calibrate and correct operational S1 L2 RVL products and retrieve two-dimensional maps of surface currents in the radar line-of-sight. The study focuses on the German Bight where wind, wave and current data from marine stations and an HF radar instrumented site provide comprehensive means to evaluate S1 retrieved currents. Analyses are deliberately limited to Sentinel-1A (S1A) ascending passes to focus on one single instrument and fixed SAR viewing geometry. The final dataset comprises 78 separate S1A acquisitions over 2.5 years, of which 56 are matched with collocated HF radar data. The empirical corrections bring significant improvements to S1A RVL data, producing higher quality estimates and much better agreement with HF radar radial currents. Comparative evaluation of S1A against HF radar currents for different WASV corrections reveal that best results are obtained in this region when computing the WASV with sea state rather than wind vector input. Accounting for sea state produces S1 radial currents with a precision (std of the difference) around 0.3 m/s at similar to 1 km resolution. Precision improves to similar to 0.24 m/s when averaging over 21 x 27 km(2), with correlations with HF radar data reaching up to 0.93. Evidence of wind-current interactions when tides and wind align and short fetch conditions call for further research with more satellite data and other sites to better understand and correct the WASV in coastal regions. Finally, 1 km resolution maps of climatological S1A radial currents obtained over 2.5 years reveal strong coastal jets and fine scale details of the coastal circulation that closely match the known bathymetry and deep-water coastal channels in this region. The wealth of oceanographic information in corrected S1 RVL data is encouraging for Doppler oceanography from space and its application to observing small scale ocean dynamics, atmosphere and ocean vertical exchanges and marine ecosystem response to environmental change.
      原文链接:
    • NSTL
    • Elsevier

    NIRvP: A robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales

    Dechant, BenjaminRyu, YoungryelBadgley, GraysonKohler, Philipp...
    20页
    查看更多>>摘要：Sun-induced chlorophyll fluorescence (SIF) is a promising new tool for remotely estimating photosynthesis. However, the degree to which incoming solar radiation and the structure of the canopy rather than leaf physiology contribute to SIF variations is still not well characterized. Therefore, we investigated relationships between SIF and variables that at least partly capture the canopy structure component of SIF. For this, we relied on high-quality SIF observations from ground-based instruments, high-resolution airborne SIF imagery and the most recent satellite SIF products to cover large ranges in spatial and temporal resolution and diverse ecosystems. We found that the canopy structure-related near-infrared reflectance of vegetation multiplied by incoming sunlight (NIRvP) is a robust proxy for far-red SIF across a wide range of spatial and temporal scales. Our findings indicate that contributions from leaf physiology to SIF variability are small compared to the structure and radiation components. Also, NIRvP captured spatio-temporal patterns of canopy photosynthesis better than SIF, which seems to be mostly due to the greater retrieval noise of SIF. Compared to other relevant structural SIF proxies, NIRvP showed more robust relationships to SIF, especially at the global scale. Our results highlight the promise of using widely available NIRvP data for vegetation monitoring and also indicate the potential of using SIF and NIRvP in combination to extract physiological information from SIF.
      原文链接:
    • NSTL
    • Elsevier

    Estimation and calibration of stem diameter distribution using UAV laser scanning data: A case study for larch (Larix olgensis) forests in Northeast China

    Hao, YuanshuoWidagdo, Faris Rafi AlmayLiu, XinQuan, Ying...
    13页
    查看更多>>摘要：Diameter frequency distributions provide essential information for estimating timber assortment, monitoring carbon stocks, and formulating forest management measures. In this study, we estimated diameter distribution utilizing unmanned aerial vehicle laser scanning (ULS) data by applying three Weibull distribution modeling methods: (1) parameter prediction method (PPM); (2) moment-based parameter recovery method (PRMM); and (3) percentile-based parameter recovery method (PRMP). The variables used in Weibull distribution modeling methods were combined with stand density as response groups to be modeled with ULS metrics. Considering the hierarchical structure of ULS data and the autocorrelation among sub-models, mixed-effects seemingly unrelated regression (SURM) were applied to take into account both spatial and cross-model correlations. The experiments were conducted for 11 sites of larch plantations using leave-one-out cross-validation (LOOCV). The diameter distribution was estimated and calibrated by the observed stand density considering the correlations of submodels' random-effects. The results demonstrated that applying a relatively small number of plots (1 to 6) and estimated best linear predictor (EBLUP) for local calibration could improve the prediction performance. The optimal results were obtained from PRMM with six calibrated plots, and the average Reynolds error index was 45.30. Furthermore, simulation applications with different pulse densities were applied and suggested that calibration could also improve the estimation performance but brought little improvement on estimation stability, far lesser than the impact of point cloud density. This study provides an improved approach for diameter distribution estimation and benefits for operational forest applications using remote sensing data.
      原文链接:
    • NSTL
    • Elsevier

    TROPOMI observations allow for robust exploration of the relationship between solar-induced chlorophyll fluorescence and terrestrial gross primary production

    Li, XingXiao, Jingfeng
    13页
    查看更多>>摘要：Solar-induced chlorophyll fluorescence (SIF) observed by satellites has advanced the monitoring of terrestrial photosynthesis regionally and globally. The relationship between SIF and gross primary production (GPP) at leaf, canopy, and ecosystem scales has received tremendous attention in recent years. It remains controversial whether the SIF-GPP relationship at the ecosystem scale is universal or dependent upon vegetation type. New SIF observations from the TROPOspheric Monitoring Instrument (TROPOMI) with unprecedented high spatial and temporal resolution provide a new opportunity to elucidate the SIF-GPP relationship. Here, we examine the SIF-GPP relationship for seven major vegetation types across the U.S. with TROPOMI SIF and in-situ GPP data for 83 eddy covariance flux sites. We find that TROPOMI SIF shows a strong and consistent relationship with tower based GPP at both satellite footprint and grid-cell levels. The slope of the SIF-GPP relationship is similar among all the vegetation types except croplands, demonstrating a nearly universal (converging to similar to 13.5 g C m(-2) d(-1)/W m(-2) mu m(-1) sr(-1)) rather than vegetation type-specific SIF-GPP relationship. This confirms that TROPOMI SIF can be used as a proxy for GPP across a wide variety of vegetation types, and can also be used to quantify GPP by avoiding uncertainty associated with land cover maps. The C-4 crops have a much higher slope than the C-3 crops, and therefore croplands tend to have a higher slope than C-3-dominated vegetation types (e.g., forests, shrublands, savannas). We also find that the TROPOMI SIF is well correlated with GPP under normal or wetter conditions, while their relationship becomes weaker under water stress. Our TROPOMI-based study could improve our understanding of the SIF-GPP relationship at the ecosystem scale and advance the mapping of GPP globally with SIF observations from space.
      原文链接:
    • NSTL
    • Elsevier

    Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data

    Klauberg, CarineSilva, Carlos AlbertoBroadbent, Eben Northdo Amaral, Cibele Hummel...
    19页
    查看更多>>摘要：Quantifying fuel load over large areas is essential to support integrated fire management initiatives in fire-prone regions to preserve carbon stock, biodiversity and ecosystem functioning. It also allows a better understanding of global climate regulation as a potential carbon sink or source. Large area assessments usually require data from spaceborne remote sensors, but most of them cannot measure the vertical variability of vegetation structure, which is required for accurately measuring fuel loads and defining management interventions. The recently launched NASA's Global Ecosystem Dynamics Investigation (GEDI) full-waveform lidar sensor holds potential to meet this demand. However, its capability for estimating fuel load has yet not been evaluated. In this study, we developed a novel framework and tested machine learning models for predicting multi-layer fuel load in the Brazilian tropical savanna (i.e., Cerrado biome) using GEDI data. First, lidar data were collected using an unnamed aerial vehicle (UAV). The flights were conducted over selected sample plots in distinct Cerrado vegetation formations (i.e., grassland, savanna, forest) where field measurements were conducted to determine the load of surface, herbaceous, shrubs and small trees, woody fuels and the total fuel load. Subsequently, GEDI-like full-waveforms were simulated from the high-density UAV-lidar 3-D point clouds from which vegetation structure metrics were calculated and correlated to field-derived fuel load components using Random Forest models. From these models, we generate fuel load maps for the entire Cerrado using all on-orbit available GEDI data. Overall, the models had better performance for woody fuels and total fuel loads (R-2 = 0.88 and 0.71, respectively). For components at the lower stratum, models had moderate to low performance (R-2 between 0.15 and 0.46) but still showed reliable results. The presented framework can be extended to other fire-prone regions where accurate measurements of fuel components are needed. We hope this study will contribute to the expansion of spaceborne lidar applications for integrated fire management activities and supporting carbon monitoring initiatives in tropical savannas worldwide.
      原文链接:
    • NSTL
    • Elsevier

    Review of GPM IMERG performance: A global perspective

    Pradhan, Rajani K.Markonis, YannisGodoy, Mijael Rodrigo VargasVillalba-Pradas, Anahi...
    19页
    查看更多>>摘要：Accurate, reliable, and high spatio-temporal resolution precipitation data are vital for many applications, including the study of extreme events, hydrological modeling, water resource management, and hydroclimatic research in general. In this study, we performed a systematic review of the available literature to assess the performance of the Integrated Multi-Satellite Retrievals for GPM (IMERG) products across different geographical locations and climatic conditions around the globe. Asia, and in particular China, are the subject of the largest number of IMERG evaluation studies on the continental and country level. When compared to ground observational records, IMERG is found to vary with seasons, as well as precipitation type, structure, and intensity. It is shown to appropriately estimate and detect regional precipitation patterns, and their spatial mean, while its performance can be improved over mountainous regions characterized by orographic precipitation, complex terrains, and for winter precipitation. Furthermore, despite IMERG's better performance compared to other satellite products in reproducing spatio-temporal patterns and variability of extreme precipitation, some limitations were found regarding the precipitation intensity. At the temporal scales, IMERG performs better at monthly and annual time steps than the daily and sub-daily ones. Finally, in terms of hydrological application, the use of IMERG has resulted in significant discrepancies in streamflow simulation. However, and most importantly, we find that each new version that replaces the previous one, shows substantial improvement in almost every spatiotemporal scale and climatic condition. Thus, despite its limitations, IMERG evolution reveals a promising path for current and future applications.
      原文链接:
    • NSTL
    • Elsevier

    Seasonal and long-term variations in leaf area of Congolese rainforest

    Sun, YuanhengKnyazikhin, YuriShe, XiaojunNi, Xiangnan...
    13页
    查看更多>>摘要：It is important to understand temporal and spatial variations in the structure and photosynthetic capacity of tropical rainforests in a world of changing climate, increased disturbances and human appropriation. The equatorial rainforests of Central Africa are the second largest and least disturbed of the biodiversly-rich and highly productive rainforests on Earth. Currently, there is a dearth of knowledge about the phenological behavior and long-term changes that these forests are experiencing. Thus, this study reports on leaf area seasonality and its time trend over the past two decades as assessed from multiple remotely sensed datasets. Seasonal variations of leaf area in Congolese forests derived from MODIS data co-vary with the bimodal precipitation pattern in this region, with higher values during the wet season. Independent observational evidence derived from MISR and EPIC sensors in the form of angular reflectance signatures further corroborate this seasonal behavior of leaf area. The bimodal patterns vary latitudinally within this large region. Two sub-seasonal cycles, each consisting of a dry and wet season, could be discerned clearly. These exhibit different sensitivities to changes in precipitation. Contrary to a previous published report, no widespread decline in leaf area was detected across the entire extent of the Congolese rainforests over the past two decades with the latest MODIS Collection 6 dataset. Long-term precipitation decline did occur in some localized areas, but these had minimal impacts on leaf area, as inferred from MODIS and MISR multi-angle observations.
      原文链接:
    • NSTL
    • Elsevier

    Unpacking the drivers of diurnal dynamics of sun-induced chlorophyll fluorescence (SIF): Canopy structure, plant physiology, instrument configuration and retrieval methods (vol 265, 112672, 2021)

    Chang, Christine Y.Wen, JiamingHan, JimeiKira, Oz...
    2页
      原文链接:
    • NSTL
    • Elsevier