Intra-arterial microguidewire electrocoagulation to treat intracranial vascular diseases.

OBJECTIVE: To investigate the therapeutic effect of intra-arterial microguidewire electrocoagulation on intracranial vascular diseases. METHODS: Data from 10 patients with cerebral aneurysms between May 2018 and September 2022 were analysed. Patients were treated with endovascular coil embolisation and microguidewire electrocoagulation. XperCT scans were conducted to identify new intracranial haemorrhage, infarction and hydrocephalus. Follow-up examinations were conducted 1, 3, 6 and 12 months after discharge. RESULTS: After the patients received electrocoagulation for different durations, Raymond Grade 1 embolisation was achieved in all 10 patients. No complications, such as haemorrhage, infarction or hydrocephalus, were found during or after surgery. Ten patients were followed up for 6-12 months, and none had any symptoms or new neurological dysfunction 1 month after their operation. Among them, nine were followed up for 12 months, and digital subtraction angiography showed no recurrence of aneurysms or occlusion of parent arteries. CONCLUSION: Intra-arterial microguidewire electrocoagulation can be used as a supplementary treatment for cerebral aneurysms. In cases of incomplete lesion embolisation and cases where tamponade treatment cannot continue, immediate thrombosis may occur. Thus, intra-arterial microguidewire electrocoagulation can help achieve patients' treatment goals.

Non-symmetric responses of leaf onset date to natural warming and cooling in northern ecosystems.

The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks.

Local temperature responses to actual land cover changes present significant latitudinal variability and asymmetry.

Land cover changes (LCCs) affect surface temperatures at local scale through biophysical processes. However, previous observation-based studies mainly focused on the potential effects of virtual afforestation/deforestation using the space-for-time assumption, while the actual effects of all types of realistic LCCs are underexplored. Here, we adopted the space-and-time scheme and utilized extensive high-resolution (1-km) satellite observations to perform the first such assessment. We showed that, from 2006 to 2015, the average temperature in the areas with LCCs increased by 0.08 K globally, but varied significantly across latitudes, ranging from -0.05 to 0.18 K. Cropland expansions dominated summertime cooling effects in the northern mid-latitudes, whereas forest-related LCCs caused warming effects elsewhere. These effects accounted for up to 44.6% of overall concurrent warming, suggesting that LCC influences cannot be ignored. In addition, we revealed obvious asymmetries in the actual effects, i.e., LCCs with warming effects occurred more frequently, with stronger intensities, than LCCs with cooling effects. Even for the mutual changes between two covers in the same region, warming LCCs generally had larger magnitudes than their cooling counterparts due to asymmetric changes in transition fractions and driving variables. These novel findings, derived from the assessment of actual LCCs, provide more realistic implications for land management and climate adaptation policies.

Case report: emergent endovascular treatment for carotid cavernous fistulas presenting as intracranial hemorrhage.

Objectives: This study aimed to discuss the clinical characteristics and emergent endovascular treatment of carotid cavernous fistulas presenting as intracranial hemorrhage. Methods: The clinical data of five patients with carotid cavernous fistulas, who presented with intracranial hemorrhage and who were admitted from January 2010 to April 2017, were analyzed retrospectively, and the diagnoses were confirmed by head computed tomography. Digital subtraction angiography was carried out in all the patients for the diagnosis and further emergent endovascular procedures. All patients were followed up to assess the clinical outcomes. Results: In total, five patients harbored five mono-lateral lesions; two of them were obliterated by detachable balloons, two by detachable coils, and one by detachable coils and Onyx glue. Only one patient was cured by another detachable balloon in the second session, and the other four patients were cured in the first session. At the 3- to 10-year follow-up, there was no intracranial re-hemorrhage in any of the patients; there was no recurrence of symptoms; and delayed occlusion of the parent artery was noted in one case. Conclusion: Emergent endovascular therapy is indicated for carotid cavernous fistulas presenting as intracranial hemorrhage. Individualized treatment according to the characteristics of different lesions is safe and effective.

Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming.

Vegetation change can alter surface energy balance and subsequently affect the local climate. This biophysical impact has been well studied for forestation cases, but the sign and magnitude for persistent earth greening remain controversial. Based on long-term remote sensing observations, we quantify the unidirectional impact of vegetation greening on radiometric surface temperature over 2001-2018. Here, we show a global negative temperature response with large spatial and seasonal variability. Snow cover, vegetation greenness, and shortwave radiation are the major driving factors of the temperature sensitivity by regulating the relative dominance of radiative and non-radiative processes. Combined with the observed greening trend, we find a global cooling of -0.018 K/decade, which slows down 4.6 ± 3.2% of the global warming. Regionally, this cooling effect can offset 39.4 ± 13.9% and 19.0 ± 8.2% of the corresponding warming in India and China. These results highlight the necessity of considering this vegetation-related biophysical climate effect when informing local climate adaptation strategies.

Assessing early changes in plasma HER2 levels is useful for predicting therapeutic response in advanced breast cancer: A multicenter, prospective, noninterventional clinical study.

BACKGROUND: Early prediction of treatment response is crucial for the optimal treatment of advanced breast cancer. We aimed to explore whether monitoring early changes in plasma human epidermal growth factor receptor 2 (HER2) levels using digital PCR (dPCR) could predict the treatment response in advanced breast cancer. METHODS: This was a multicenter, prospective, noninterventional clinical study of patients with advanced breast cancer. All enrolled patients underwent blood testing to measure the HER2 levels by digital PCR before treatment initiation and once every 3 weeks during the study. The primary endpoints werea the diagnostic value of dPCR for detecting HER2 status in the blood andb the relevance of potential changes in the plasma HER2 level at 3 weeks from baseline for predicting treatment response. RESULTS: Overall, 85 patients were enrolled between October 9, 2018, and January 23, 2020. dPCR had a specificity of 91.67% (95% CI: 80.61% to 97.43%) for detecting HER2 amplification, and the area under the receiver operating characteristic (ROC) curve was 0.84 (p < 0.01). A clinically relevant specificity threshold of approximately 90%, which was equivalent to a ≥15% decrease in the plasma HER2 ratio at 3 weeks from baseline, showed a positive predictive value of 97.37% (95% CI: 77.11% to 98.65%) in terms of predicting clinical benefit. Patients whose plasma HER2 ratio was reduced by ≥15% had a longer median progression-free survival (PFS) than those whose ratio was reduced by <15% (9.20 months vs. 4.50 months, p < 0.01). CONCLUSIONS: Early changes in the plasma HER2 ratio may predict the treatment response in patients with advanced breast cancer and could facilitate optimal treatment selection.

Cross-wired metal stents for endoscopic bilateral stent-in-stent deployment in malignant hilar biliary obstruction: A multicenter, single-arm, prospective study.

Objectives: The endoscopic bilateral stent-in-stent (SIS) deployment is a challenging procedure. Such difficulty is mainly caused by sticking of the tip of the delivery sheath into the self-expandable metal stents (SEMSs) mesh, requiring an additional dilating procedure. Herein, we assessed the clinical results of using cross-wired metal stent for endoscopic bilateral SIS deployment (BONASTENT M-Hilar) in patients with malignant hilar biliary obstruction (MHBO) in both high-volume and non-high-volume centers. Methods: We prospectively enrolled consecutive patients with MHBO between February 2016 and December 2018 at eight centers. Results: Forty-six patients were enrolled during the study period. The proportions of technical success were 93.5% (43/46) and clinical success (CS) on intention-to-treat and per-protocol analyses were 91.3% (42/46) and 93.0% (40/43), respectively. The proportion of an additional dilating procedure during the primary procedure was 50.0% (23/46). Recurrent biliary obstruction (RBO) on intention-to-treat analysis occurred in 32.6% (15/46) of cases. Almost all of the events were caused by stent ingrowth (14/15). The median survival time and time to RBO were 255 and 349 days, respectively. The probability of stent patency at 3, 6, and 12 months was 86.5%, 63.9%, and 47.6%, respectively. Conclusions: The cross-wired metal stent had excellent technical and CS, although non-high-volume centers were included in this study (UMIN000021441).

Prediction of vegetation phenology with atmospheric reanalysis over semiarid grasslands in Inner Mongolia.

Vegetation phenology is a sensitive indicator of climate change and vegetation growth. In the present study, two phenological phases with respect to vegetation growth at the initial and mature stages, namely, the start of the season (SOS) and the peak of the season (POS), were estimated from a satellite-derived normalized difference vegetation index (NDVI) dataset over a long-term period of 32 years (1983 to 2014) and used to explore their responses to atmospheric variables, including air temperature, precipitation, solar radiation, wind speed and soil moisture. First, the forward feature selection method was used to determine whether each independent variable was linear or nonlinear to the SOS and POS. In addition, a generalized additive model (GAM) was used to analyze the correlation between the phenological phases and each independent variable at different temporal scales. The results show that soil moisture and precipitation are linearly correlated with the SOS, whereas the other variables are nonlinearly correlated. Meanwhile, soil moisture, wind speed and solar radiation are found to be nonlinearly correlated with the POS. However, air temperature and precipitation reveal a significant negative correlation with the POS. Furthermore, it was concluded that the aforementioned independent variables from the previous year could contribute to approximately 63%-85% of the SOS variations in the present year, whereas the atmospheric variables from April to June could contribute to approximately 70%-85% of the POS variations in the same year. Finally, the SOS and POS predicted by the GAM exhibit significant agreement with those derived from the satellite NDVI dataset, with the root mean square error of approximately 3 to 5 days.

Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite.

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.

Lagged precipitation effect on plant productivity is influenced collectively by climate and edaphic factors in drylands.

Lagged precipitation effect explains a large proportion of annual aboveground net primary productivity in some dryland ecosystems. Using satellite-derived plant productivity and precipitation datasets in the Northern Hemisphere drylands during 2000-2018, we identify 1111 pixels mainly located in the Tibetan Plateau, the western US, and Kazakhstan where productivities are significantly correlated with previous-year precipitation (hereafter, the lagged type). Differences in climatic and edaphic factors between the lagged and unlagged (pixels where productivities are not correlated with previous-year precipitation) types are evaluated. Permutational multivariate analysis of variance shows that the two types differ significantly regarding six climatic and edaphic factors. Compared to unlagged type, water availability, soil organic carbon, total nitrogen, field capacity, silt content and radiation are more sensitive to changes in precipitation in lagged type. Water availability is the most important factor for distinguishing the two types, followed by soil organic carbon, total nitrogen, field capacity, soil texture, and radiation. Our study suggests that the altered sensitivities of several climatic and edaphic factors to precipitation collectively affect the lagged effect of precipitation on productivity in drylands.

Utility and Safety of a Novel Fully Covered Metal Stent in Unresectable Distal Malignant Biliary Obstruction.

BACKGROUND: Self-expandable metal stents (SEMSs) are widely used in patients with distal malignant biliary obstruction. A SEMS that can avoid occlusion as much as possible is desirable. AIMS: The aim of this multicenter single-arm prospective study was to assess the clinical effectiveness and safety of a novel fully covered braided SEMS. METHODS: We enrolled consecutive patients with distal malignant biliary obstruction between February 2016 and November 2017 at ten tertiary-care medical centers. RESULTS: We included 79 patients with a median age of 76 years; 47 (59.5%) patients were men. The technical and clinical success rate was 98.7% and 93.6%, respectively. Recurrent biliary obstruction occurred in 14 patients (17.9%); stent ingrowth, overgrowth, migration, and other occurred in five (6.4%), four (5.1%), four (5.1%), and one (1.3%) patients, respectively. All reinterventions in patients with recurrent biliary obstruction were successful via the transpapillary approach. Adverse events occurred in 15 patients (19.2%); cholangitis, pancreatitis, and others occurred in ten (12.8%), three (3.8%), and two (2.6%) patients, respectively. The stent patency probability at 6 months was 48.5%. Median time to stent patency was 171 days, median time to recurrent biliary obstruction was 536 days, and median survival time was 195 days. CONCLUSIONS: We confirmed the utility and safety of a novel fully covered braided SEMS with low axial force and high radial force in patients with malignance biliary obstruction. This novel SEMS is recommended in patients with distal malignant biliary obstruction.

An Improved Linear Spectral Emissivity Constraint Method for Temperature and Emissivity Separation Using Hyperspectral Thermal Infrared Data.

The linear spectral emissivity constraint (LSEC) method has been proposed to separate temperature and emissivity in hyperspectral thermal infrared data with an assumption that land surface emissivity (LSE) can be described by an equal interval piecewise linear function. This paper combines a pre-estimate shape method with the LSEC method to provide an initial-shape estimation of LSE which will create a new piecewise scheme for land surface temperature (LST) and LSE separation. This new scheme is designated as the pre-estimate shape (PES)-LSEC method. Comparisons with the LSEC method using simulated data sets show that the PES-LSEC method has better performance in terms of accuracy for both LSE and LST. With an at-ground error of 0.5 K, the root-mean-square errors (RMSEs) of LST and LSE are 0.07 K and 0.0045, respectively, and with the scale factor of moisture profile 0.8 and 1.2, the RMSEs of LST are 1.11 K and 1.14 K, respectively. The RMSEs of LSE in each channel are mostly below 0.02 and 0.04, respectively, which are better than for the LSEC method. In situ experimental data are adopted to validate our method: The results show that RMSE of LST is 0.9 K and the mean value of LSE accuracy is 0.01. The PES-LSEC method with fewer segments achieves better accuracy than that of LSEC and preserves most of the crest and trough information of emissivity.

[A new aurone with anti-inflammatory activity from Cleistocalyx operculatus flower buds].

A new compound(Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone was isolated from Cleistocalyx operculatus flower buds. Its structure was identified by spectroscopic data including MS, ¹H-NMR, ¹³C-NMR HSQC and HMBC. A known compound, 2',4'-dihydroxy-6'-methoxy-3'5'-dimethylchalcone (DMC), was also isolated and identified,and used as material to synthesize (Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone.Anti-inflammatory activities of the two compounds were tested in vitro. The results showed that (Z)-6-hydroxy-4-methoxy-5,7-dimethylaurone possesses much stronger PGE2 inhibitory activity (IC50 6.12 nmol·L⁻¹) than the positive control ibuprofen （68.66 nmol·L⁻¹ï¼‰.

Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach.

Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

New method to estimate surface upwelling long-wave radiation from MODIS cloud-free data.

As an important component in the surface radiation budget, surface upwelling longwave radiation (SULR) is an outcome of the land surface energy exchange and mainly represents the capability of thermal radiation from the surface of the Earth. Existing satellite-derived SULR products are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this study, an equivalent temperature is introduced through which a "split-window" atmospheric correction algorithm is developed for MODIS data to estimate the instantaneous clear-sky SULR. It is a simple and feasible method that is particularly applicable to MODIS data to acquire relatively high precision SULR under clear skies from which qualified water vapor contents (WVC) and thermal channel brightness temperatures are available. The root mean square errors (RMSEs) are less than 13 W/m2 for all WVC sub-ranges with the viewing zenith angle (VZA) less than 30°, or for all sub-ranges with the VZA less than 60° and the WVC less than 3.5 g/cm2. Also, applications and comparisons with the LST-emissivity method are made by using ground measurements which are collected from the network of surface radiation budget network data (SURFRAD) at the moment of MODIS overpass. Results show that the proposed model has high computational efficiency to estimate SULR from MODIS cloud-free data.

Atmospheric correction for retrieving ground brightness temperature at commonly-used passive microwave frequencies.

An analysis of the atmospheric impact on ground brightness temperature (Tg) is performed for numerous land surface types at commonly-used frequencies (i.e., 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz and 89.0 GHz). The results indicate that the atmosphere has a negligible impact on Tg at 1.4 GHz for land surfaces with emissivities greater than 0.7, at 6.93 GHz for land surfaces with emissivities greater than 0.8, and at 10.65 GHz for land surfaces with emissivities greater than 0.9 if a root mean square error (RMSE) less than 1 K is desired. To remove the atmospheric effect on Tg, a generalized atmospheric correction method is proposed by parameterizing the atmospheric transmittance τ and upwelling atmospheric brightness temperature Tba↑. Better accuracies with Tg RMSEs less than 1 K are achieved at 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz and 36.5 GHz, and worse accuracies with RMSEs of 1.34 K and 4.35 K are obtained at 23.8 GHz and 89.0 GHz, respectively. Additionally, a simplified atmospheric correction method is developed when lacking sufficient input data to perform the generalized atmospheric correction method, and an emissivity-based atmospheric correction method is presented when the emissivity is known. Consequently, an appropriate atmospheric correction method can be selected based on the available data, frequency and required accuracy. Furthermore, this study provides a method to estimate τ and Tba↑ of different frequencies using the atmospheric parameters (total water vapor content in observation direction Lwv, total cloud liquid water content Lclw and mean temperature of cloud Tclw), which is important for simultaneously determining the land surface parameters using multi-frequency passive microwave satellite data.

Non-Contact Measurement of the Spectral Emissivity through Active/Passive Synergy of CO2 Laser at 10.6 µm and 102F FTIR (Fourier Transform Infrared) Spectrometer.

In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic related to quantitative thermal infrared remote sensing. The academic research and practical applications based on the temperature-emissivity retrieval algorithms show that directly measuring the emissivity of objects at a fixed thermal infrared waveband is an important way to close the underdetermined equations for thermal infrared radiation. Based on the prior research results of both the authors and others, this paper proposes a new approach of obtaining the spectral emissivity of the object at 8-14 µm with a single-band CO2 laser at 10.6 µm and a 102F FTIR spectrometer. Through experiments, the spectral emissivity of several key samples, including aluminum plate, iron plate, copper plate, marble plate, rubber sheet, and paper board, at 8-14 µm is obtained, and the measured data are basically consistent with the hemispherical emissivity measurement by a Nicolet iS10 FTIR spectrometer for the same objects. For the rough surface of materials, such as marble and rusty iron, the RMSE of emissivity is below 0.05. The differences in the field of view angle and in the measuring direction between the Nicolet FTIR method and the method proposed in the paper, and the heterogeneity in the degree of oxidation, polishing and composition of the samples, are the main reasons for the differences of the emissivities between the two methods.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method.

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800-950 cm(-1) larger than 0.95 and it has not been extended for off-nadir measurements.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery.

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators-depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance-to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R² = 0.91 for Damm vs. SCOPE SIF; R² = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.