Performance evaluation of HY-2 series satellites in marine gravity field recovery

China has successfully launched four Haiyang-2(HY-2)series altimetry satellites.HY-2A has attracted significant attention in gravity field recovery,but the performance of other HY-2 series satellites,including HY-2B/C/D,is seldom discussed.This study evaluated the performance of all the HY-2 series satellites in recovering marine gravity field.First,the crossover discrepancies in sea surface height of the four satellites,HY-2A,HY-2B,HY-2C,and HY-2D,were analyzed to assess their altimetry stability.It was found that HY-2B had the best altimetry quality,followed by HY-2D.Subsequently,different combina-tions of altimetry data were used to calculate vertical deflections and gravity anomalies in the South China Sea(112°E-119°E,12°N-20°N).The results showed that combining data from HY-2B,HY-2C,and HY-2D improved the inversion accuracy of gravity anomalies by 0.3 mGal compared to using HY-2A data alone.HY-2C and HY-2D contributed to enhancing the accuracy of the east component of vertical deflections.

Three-dimensional thermohaline structure estimation derived from HY-2 satellite data over the Maritime Silk Road and its applications

Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems.This study employs a statistic regression reconstruction method,in combination with domestic autonomous sea surface height and sea surface temperature observations from the Haiyang-2(HY-2)satellite fusion data,to establish an operational quasi-realtime three-dimensional(3D)temperature and salinity products over the Maritime Silk Road.These products feature a daily temporal resolution and a spatial resolution of 0.25°×0.25°and exhibit stability and continuity.We have demonstrated the accuracy of the reconstructed thermohaline fields in capturing the 3D thermohaline variations through comprehensive statistical evaluations,after comparing them against Argo observations and ocean analysis data from 2022.The results illustrate that the reconstructed fields effectively represent seasonal variations in oceanic subsurface structures,along with structural changes resulting from mesoscale processes,and the upper ocean’s responses to tropical cyclones.Furthermore,the incorporation of HY-2 satellite observations notably enhances the accuracy of temperature and salinity reconstructions in the Northwest Pacific Ocean and marginally improves salinity reconstruction accuracy in the North Indian Ocean when compared to the World Ocean Atlas 2018 monthly climatology thermohaline fields.As a result,the reconstructed product holds promise for providing quasi-real-time 3D temperature and salinity field information to facilitate fast decisionmaking during emergencies,and also offers foundational thermohaline fields for operational ocean reanalysis and forecasting systems.These contributions enhance the safety and stability of ocean subsurface activities and navigation.

Retrieval of Antarctic sea ice freeboard and thickness from HY-2B satellite altimeter data

Antarctic sea ice is an important part of the Earth’s atmospheric system,and satellite remote sensing is an important technology for observing Antarctic sea ice.Whether Chinese Haiyang-2B(HY-2B)satellite altimeter data could be used to estimate sea ice freeboard and provide alternative Antarctic sea ice thickness information with a high precision and long time series,as other radar altimetry satellites can,needs further investigation.This paper proposed an algorithm to discriminate leads and then retrieve sea ice freeboard and thickness from HY-2B radar altimeter data.We first collected the Moderate-resolution Imaging Spectroradiometer ice surface temperature(IST)product from the National Aeronautics and Space Administration to extract leads from the Antarctic waters and verified their accuracy through Sentinel-1 Synthetic Aperture Radar images.Second,a surface classification decision tree was generated for HY-2B satellite altimeter measurements of the Antarctic waters to extract leads and calculate local sea surface heights.We then estimated the Antarctic sea ice freeboard and thickness based on local sea surface heights and the static equilibrium equation.Finally,the retrieved HY-2B Antarctic sea ice thickness was compared with the CryoSat-2 sea ice thickness and the Antarctic Sea Ice Processes and Climate(ASPeCt)ship-based observed sea ice thickness.The results indicate that our classification decision tree constructed for HY-2B satellite altimeter measurements was reasonable,and the root mean square error of the obtained sea ice thickness compared to the ship measurements was 0.62 m.The proposed sea ice thickness algorithm for the HY-2B radar satellite fills a gap in this application domain for the HY-series satellites and can be a complement to existing Antarctic sea ice thickness products;this algorithm could provide long-time-series and large-scale sea ice thickness data that contribute to research on global climate change.

联合多时相GF-6 WFV和Sentinel-2的森林类型识别

【目的】我国南方地区多云雨,地型较破碎,森林类型精细识别较为困难,探讨联合多源、多时相的遥感数据对森林类型识别具有重要意义。【方法】以江西省信丰县为研究区,基于2019年森林资源二类调查数据,将森林划分为松林、杉木林、阔叶林、针叶混交林、针阔混交林、竹林、灌木林和其他林地等8种类型,利用随机森林算法比较GF-6 WFV和Sentinel-2最佳时相相同波段(紫/深蓝、蓝、绿、红、近红外、红边)和不同波段(黄边、短波红外)的森林类型识别能力,构建联合光谱特征集。联合多时相GF-6 WFV和Sentinel-2,构建多时相植被指数特征集,结合联合光谱特征集、纹理特征和地形特征,通过随机森林和递归消除法构建特征变量优选数据集进行森林类型识别,利用混淆矩阵和森林类型的实际分布对识别结果进行精度验证。【结果】(1)GF-6 WFV蓝、绿和红波段组合的总体精度为58.31%,分别加入紫、近红外、红边、黄边和Sentinel-2短波红外波段后,其总体精度分别提高1.99%、8.90%、10.71%、1.50%和14.10%;Sentinel-2蓝、绿和红波段组合的总体精度为54.68%,分别加入深蓝、近红外、红边、短波红外和GF-6 WFV黄边波段后,其总体精度分别提高3.30%、10.82%、12.92%、17.31%和3.97%。(2)特征变量优选数据集的总体精度和Kappa系数为80.80%和75.56%,贡献程度大小依次为GF-6 WFV多时相植被指数、Sentinel-2多时相植被指数、GF-6 WFV光谱特征、Sentinel-2光谱特征、地形特征和纹理特征,贡献率分别为40.44%、23.23%、18.12%、10.21%、4.61%和3.39%。(3)松林、杉木林、阔叶林、针叶混交林、针阔混交林、竹林、灌木林和其他林地的制图精度分别为86.97%、85.60%、88.61%、9.43%、19.01%、53.60%、86.90%和82.56%,用户精度分别为81.42%、79.79%、77.57%、71.43%、81.82%、67.00%、87.74%和82.88%,识别结果与研究区实际森林类型分布较吻合。【结论】联合多时相GF-6 WFV和Sentinel-2可以综合多时相、多源影像的优点,能够有效提高森林类型的识别精度。

基于GF-1卫星遥感反演排水河沟水体溶存N_(2)O浓度模型对比研究

[目的]探究利用GF-1卫星数据反演水体溶存氧化亚氮(N_(2)O)浓度的可行性,为实现低成本、高效率的水质实时监测提供有效途径。[方法]以宁夏青铜峡灌区第1和第5排水河沟为研究对象,选取与排水河沟水体溶存N_(2)O浓度相关性高的GF-1卫星影像波段反射率和水质参数作为自变量,通过最优子集筛选法确定最优自变量组合,分别构建了多元线性回归、BP神经网络和支持向量机模型,对水体溶存N_(2)O浓度进行预测对比。[结果]水温(T)、溶解性有机碳(DOC)等是影响水体溶存N_(2)O浓度的主要因素,同时近红外(NIR)等卫星波段与水体溶存N_(2)O浓度变化趋势显著相关。当自变量包括T,NIR等7个因素时,模型预测效果最佳。在3种模型中,BP神经网络模型验证结果R^(2)为0.64,具有最高预测精度。[结论]GF-1卫星数据以及水质参数与水体溶存N_(2)O浓度存在复杂的相关性关系,且BP神经网络能够实现利用GF-1卫星数据较高精度地反演水体溶存N_(2)O浓度。

基于GF-2和ASTER数据青海德龙地区构造蚀变信息提取及找矿预测

德龙地区位于青海东昆仑金及多金属成矿带东段,是该成矿带内极具勘查潜力区域之一,受限于偏远的地理位置和崎岖的地形条件,大比例尺地球化学勘查及常规地质调查工作难以直接开展。为此,基于ASTER和GF-2数据,通过分析不同空间分辨率遥感影像的色调、几何结构和纹理特征进行线性和环形构造识别;同时,根据主要蚀变矿物光谱特征分析,利用ASTER可见光—近红外波段和短波红外波段,采用“掩模+主成分分析”方法提取铁化、Al-OH和Mg-OH蚀变信息;在此基础上,结合多元地学信息及野外调查结果,综合分析遥感解译构造蚀变信息与研究区金矿化的内在联系,建立基于区内金矿床的遥感找矿预测模型,并以此为依据划分出找矿远景区3处。通过野外查证,在德龙找矿远景区新发现金矿体多条。研究结果表明,融合遥感数据和地理信息系统技术可有效识别地表热液蚀变和构造空间结构特征,能够为该地区进一步找矿预测提供参考和依据。

基于GF-2影像的武汉市九峰山国家森林公园地上碳储量估算

探究国产高分辨率数据在森林碳储量估算研究中的潜力,为构建森林碳储量估算模型提供新思路。选取武汉市九峰山国家森林公园为研究对象,以GF-2遥感影像为数据源,结合地面实测信息,对研究区森林地上碳储量进行估算,共提取6个植被指数、4个波段值、8种纹理特征,筛选出9个与实测碳储量相关的遥感变量,运用线性与非线性方程对单个高相关变量和多个相关变量进行建模,选出最优模型,为进一步提高预测精度,将模型代入4种纹理窗口(3×3、5×5、7×7、9×9)。结果表明:通过遥感图像提取的植被指数之间,具有较强的共线性,单变量建立的模型精度低于多变量模型;利用均方根误差RMSE与决定系数R^(2)对4个窗口下模型的预测精度进行评价,模型在5×5窗口下预测效果最好(R^(2)=0.73,RMSE=0.5),3×3窗口下预测效果最差(R^(2)=0.64,RMSE=0.8),将所有估测模型进行比较,在纹理窗口下模型精度提高了0.11。利用5×5窗口下构建的多变量模型对研究区碳储量进行估算,九峰山国家森林公园碳储总量为1.06×10^(4) t,总体平均碳密度为84.59 t/hm^(2),具有一定的固碳作用。选用国产高分辨率影像GF-2数据对武汉市九峰山森林公园进行反演研究,能很好地运用在森林植被碳储量定量与生长状况领域。研究结果对“双碳”目标下森林生态系统碳汇监测与管理具有重要科学意义。

级联语义分割和边缘检测的GF-2影像耕地提取

针对山地丘陵区的坡耕地和小面积耕地碎片边界模糊不清、分类提取困难的问题,以GF-2影像为数据源,提出了一种级联语义分割和边缘检测模型的遥感影像耕地信息提取方法。首先,针对不同类型耕地的特点选择级联方式;其次,将耕地边缘作为独立的特征类别,结合改进U-Net、DeeplabV3+和DexiNed模型,融合面特征和线特征,使得耕地边缘特征与语义特征能够进行互补,从而提高耕地提取的准确性,实现对复杂地形背景噪声的抑制和不同类型耕地的提取。实验结果表明,对比单一模型DeeplabV3+和U-Net,级联模型的耕地信息提取的总体精度、Kappa系数和F1值均有大幅度提升,针对不同类型耕地级联模型提取的耕地结果更接近真实耕地标注,漏提、误提区域远低于单一模型。

基于GF-2遥感影像和改进后PSPNet模型的丘陵地区耕地图斑提取方法

针对丘陵地区耕地地块具有边界模糊、覆盖物种类多样、大小和空间位置分布不规则等特点,传统分类方法难以快速准确提取耕地信息的问题,本文以四川省金堂县竹篙镇和高板镇为研究区域,利用高分二号卫星影像和改进后的PSPNet语义分割网络模型进行耕地图斑提取研究。在模型训练中,引入CBAM注意力模块以提高整个网络的特征提取和表达能力,采用余弦退火学习率以加快模型的收敛速度。结果表明,改进后的PSPNet模型在丘陵地区耕地提取精度方面取得了显著提高,耕地识别精度达到了95.69%,比标准PSPNet模型提高了1.07%,比Unet++,DeepLabv3+和支持向量机方法方法提高了1.32%,1.75%和6.33%。基于改进后的PSPNet模型具有更强的特征提取和表达能力,可以更准确地提取丘陵地区的耕地信息,为农业决策提供更准确的数据支持,促进农业智能化和精准化,提高农作物产量和质量,推动农业现代化进程。

血清TGF-β1、Nesfatin-1、SFRP5与2型糖尿病胰岛素抵抗关系探究

目的:探讨血清转化生长因子-β1(TGF-β1)、Nesfatin-1、分泌型卷曲相关蛋白-5(SFRP5)与2型糖尿病胰岛素抵抗的关系。方法:选取我院2021年4月-2023年4月收治的148例2型糖尿病患者为研究对象,根据稳态模型胰岛素抵抗指数(HOMA-IR)检测结果将患者分为轻度胰岛素抵抗组(91例,HOMA-IR<2.5)和中重度胰岛素抵抗组(57例,HOMA-IR≥2.5)。比较两组入院时血清TGF-β1、Nesfatin-1、SFRP5水平,分析入院时血清TGF-β1、Nesfatin-1、SFRP5水平与HOMA-IR的相关性,分析发生中重度胰岛素抵抗的影响因素、联合检测的诊断价值及危险度。结果:入院时,中重度胰岛素抵抗组血清TGF-β1、Nesfatin-1水平高于轻度胰岛素抵抗组,SFRP5水平低于轻度胰岛素抵抗组(P<0.05);入院时,HOMA-IR与血清TGF-β1、Nesfatin-1水平呈正相关,与SFRP5水平呈负相关(P<0.05);入院时,血清TGF-β1、Nesfatin-1、SFRP5水平为2型糖尿病患者发生中重度胰岛素抵抗的影响因素(P<0.05);入院时血清TGF-β1、Nesfatin-1、SFRP5水平联合诊断中重度胰岛素抵抗的AUC为0.808,最佳诊断敏感度为91.23%,特异度为70.33%;入院时血清TGF-β1、Nesfatin-1、SFRP5高水平患者发生中重度胰岛素抵抗的危险度是低水平的3.560、2.134、0.341倍(P<0.05)。结论:血清TGF-β1、Nesfatin-1、SFRP5水平与2型糖尿病胰岛素抵抗密切相关,可作为临床诊断病情的参考依据。

Cloud Top Pressure Retrieval Using Polarized and Oxygen A-band Measurements from GF5 and PARASOL Satellites

Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.

Comparative investigation of microstructure and high-temperature oxidation resistance of high-velocity oxy-fuel sprayed CoNiCrAlY/nano-Al_(2)O_(3) composite coatings using satellited powders

Satellited CoNiCrAlY–Al_(2)O_(3)feedstocks with 2wt%, 4wt%, and 6wt% oxide nanoparticles and pure CoNiCrAlY powder were deposited by the high-velocity oxy fuel process on an Inconel738 superalloy substrate. The oxidation test was performed at 1050℃ for 5, 50, 100,150, 200, and 400 h. The microstructure and phase composition of powders and coatings were characterized by scanning electron microscopy and X-ray diffraction, respectively. The bonding strength of the coatings was also evaluated. The results proved that with the increase in the percentage of nanoparticles(from 2wt% to 6wt%), the amount of porosity(from 1vol% to 4.7vol%), unmelted particles, and roughness of the coatings(from 4.8 to 8.8 μm) increased, and the bonding strength decreased from 71 to 48 MPa. The thicknesses of the thermally grown oxide layer of pure and composite coatings(2wt%, 4wt%, and 6wt%) after 400 h oxidation were measured as 6.5, 5.5, 7.6, and 8.1 μm, respectively.The CoNiCrAlY–2wt% Al_(2)O_(3)coating showed the highest oxidation resistance due to the diffusion barrier effect of well-dispersed nanoparticles. The CoNiCrAlY–6wt% Al_(2)O_(3)coating had the lowest oxidation resistance due to its rough surface morphology and porous microstructure.

GF-2正射影像融合方法的比较与分析

基于高分二号卫星(GF-2)多光谱影像和全色影像,采用5 m数字高程模型(digital elevation model,DEM)影像进行正射校正,选用无波段限制的7种影像融合方法对正射影像进行融合,通过定性和定量分析,探究不同影像融合结果的差异性。结果表明,施密特全色锐化(GramˉSchmidt pan sharpening, GS)融合方法能够较为真实地反映原有地物信息,地物细节处理效果比其他影像融合方法好;小波变换(wavelet transform, WT)和最近邻扩散(nearest neighbor diffusion, NND)方法对植被的区分度较差;不同的影像融合方法有其各自的特性,在实际应用中,应根据不同的需求,选择适宜的影像融合方法。

基于GF-2影像的德阳城市黑臭水体遥感监测研究

黑臭水体地面监测覆盖范围有限,受人为因素影响较大,监测结果具有局限性。以德阳市城市建成区内主要黑臭水体为研究对象,采用2017~2022年4幅高质量的GF-2遥感影像,通过ENVI 5.3对GF-2遥感影像进行正射校正、影像融合、辐射定标、图像裁剪、几何校正等预处理后进行遥感监测研究。分析了黑臭水体与一般水体的光谱特征,发现不同波段黑臭水体反射率与一般水体反射率变化差异明显。基于这一特点提出了取不同波段斜率比值作为遥感识别指数。采用水体清洁指数模型,识别黑臭水体与具有黑臭风险的水体。本文基于德阳黑臭水体的光谱特征提出的WCI,仅对德阳市丁家堰进行了验证,还需扩大范围检测其适用性。

On-orbit Geometric Calibration and Preliminary Accuracy Evaluation of GF-14 Satellite

GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Points(GCPs).In fact,space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links,of which on-orbit geometric calibration is one of the most critical links.In this paper,the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field,and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection.On this basis,the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world.The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters(RMS)in plane and 1.97 meters(RMS)in elevation.

On simulation of precise orbit determination of HY-2 with centimeter precision based on satellite-borne GPS technique

The HY-2 satellite carrying a satellite-borne GPS receiver is the first Chinese radar altimeter satellite, whose radial orbit determination precision must reach the centimeter level. Now HY-2 is in the test phase so that the observations are not openly released. In order to study the precise orbit determination precision and procedure for HY-2 based on the satellite- borne GPS technique, the satellite-borne GPS data are simulated in this paper. The HY-2 satellite-borne GPS antenna can receive at least seven GPS satellites each epoch, which can validate the GPS receiver and antenna design. What＇s more, the precise orbit determination processing flow is given and precise orbit determination experiments are conducted using the HY-2-borne GPS data with both the reduced-dynamic method and the kinematic geometry method. With the 1 and 3 mm phase data random errors, the radial orbit determination precision can achieve the centimeter level using these two methods and the kinematic orbit accuracy is slightly lower than that of the reduced-dynamic orbit. The earth gravity field model is an important factor which seriously affects the precise orbit determination of altimeter satellites. The reduced-dynamic orbit determination experiments are made with different earth gravity field models, such as EIGEN2, EGM96, TEG4, and GEMT3. Using a large number of high precision satellite-bome GPS data, the HY-2 precise orbit determination can reach the centimeter level with commonly used earth gravity field models up to above 50 degrees and orders.

Comparison on Winter Wheat Yield Estimating Models Based on Radarsat-2 and HJ Satellite in Huaihe River Region

The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model. With Shou County and Huaiyuan County of Anhui Province as the experimental fields of winter wheat producing areas, the linear winter wheat yield estimating models were established by adopting backscattering coefficient and Normalized Difference Vegetation Index（NDVI） based on images from the synthetic aperture radar（SAR）—RDARSAT-2 and HJ satellite photographed in mid-April and early May, 2014, and then comparisons were conducted on the accuracy of the yield estimating models. The accuracies of the yield estimating models established using co-polarized（HH） and cross-polarized（HV） modes of SAR in Jiangou Town, Shou County were 68.37% and 74.01%, respectively, while the accuracies in Longkang Town, Huaiyuan County were 63.10%and 69.10%, respectively. Accuracies of yield estimating models established by HJ satellite data were 69.52% and 66.43% in Shou County and Huaiyuan County, respectively. Accuracies of winter yield estimating model based on HJ satellite data and that based on SAR were closed, and the yield difference of winter wheat in the lodging region was analyzed in detail. The model results laid the foundation and accumulated experience for the verification, parameters correction and promotion of the winter wheat yield estimating model.

基于ICESat-2多波束激光测高数据的全球海洋重力异常反演分析

卫星测高技术是获取精细海洋重力数据的重要技术手段之一。常规卫星测高反演海洋重力异常主要是利用沿轨测高数据,而跨轨数据因较长的时间间隔或者稀疏的地面轨间距往往不能用于海洋重力异常反演,进而影响了海洋重力异常模型精度的进一步改善。新型激光测高ICESat-2能够同时获得3对光束观测数据,相邻激光束的地面间距约为3 km,为结合跨轨数据改善海洋重力异常模型提供了可能。本文首先给出了集成沿轨和跨轨数据反演海洋重力异常的处理策略;然后,分别利用沿轨数据和集成的数据构建了ICESat-2全球海洋重力异常模型(IS2Gra_alo和IS2Gra_alo_acr),结果表明通过补充跨轨数据能够有效提高沿轨数据反演海洋重力异常的精度,并验证了ICESat-2测高数据反演全球海洋重力异常的可靠性。此外,本文还探讨了ICESat-2不同跨轨数据组合对海洋重力异常模型反演精度的影响,在沿轨数据的基础上集成适当距离的跨轨观测数据能够有利于改善海洋重力异常模型的精度。本文研究为后续SWOT宽刈幅测高数据和我国双星跟飞模式测高数据反演海洋重力异常模型提供了参考意义。

运动联合益生菌干预2型糖尿病大鼠糖脂代谢、氧化应激及骨骼肌卫星细胞成肌分化水平的变化

目的观察运动联合益生菌干预2型糖尿病大鼠糖脂代谢、氧化应激及骨骼肌卫星细胞表达的影响。方法8周龄SPF级SD雄性大鼠60只,随机选择10只大鼠为正常对照组(NC组),造模组大鼠腹腔注射链脲佐菌素,建立2型糖尿病大鼠模型,随机分为模型组(TN组)、运动+糖尿病组(YTN组)、益生菌+糖尿病组(GTN组)、运动+益生菌+糖尿病组(YGTN组),6周的递增负荷有氧跑台运动(第1周跑台速度为15 m/min,持续30 min;第2周跑台速度为15 m/min,持续60 min;第3~6周跑台速度为19.3 m/min,运动时间持续60 min,持续训练到第6周,每周5 d);GTN组和YGTN组在训练前1 h灌胃10.0 mL/(kg·d)的Lactibiane Iki益生菌溶液(浓度为10~7 CFU/mL)。最后,测定大鼠糖脂代谢指标、氧化应激指标及骨骼肌卫星细胞蛋白的表达。结果(1)TN组、YTN组、GTN组和YGTN组大鼠空腹血糖(fasting plasma glucose,FBG)、血清胰岛素(fasting serum insulin,FINS)、糖化血红蛋白(hemoglobin A1c,HBA1C)和胰岛素抵抗指数(homeostasis model assessment-insulin resistance index,HOMA-IR)水平均高于NC组(P<0.01),其中,YGTN组大鼠FBG水平均低于TN组、YTN组、GTN组(P<0.05);YTN组、GTN组和YGTN组大鼠血清FINS水平均与TN组比较均有所下降(P<0.01);YGTN组大鼠血清HBA1C水平均低于TN组、YTN组和GTN组水平(P<0.01);YGTN组大鼠HOMA-IR指数与TN组、YTN组和GTN组比较下降较显著(P<0.01)。结果表明有氧运动联合益生菌干预组大鼠FBG、FINS、HBA1C和HOMA-IR含量下降较明显。(2)TN组大鼠血清总胆固醇(total cholesterol,T-CHO)、甘油三酯(triglyceride,TG)、低密度脂蛋白胆固醇(low density lipoprotein cholesterol,LDL)和游离脂肪酸(free fatty acid,FFA)水平均高于NC组(P<0.05),YGTN组大鼠血清T-CHO、TG、LDL和FFA水平均低于TN组(P<0.05),基本上恢复到NC组的水平。TN组大鼠血清高密度脂蛋白胆固醇(high density lipoprotein cholesterol,HDL)水平低于NC组(P<0.05),YGTN组大鼠血清HDL水平高于TN组(P<0.05),基本上恢复到NC组水平。结果表明有氧运动联合益生菌干预糖尿病大鼠,可降低糖尿病大鼠血清T-CHO、TG、LDL、FFA含量,提高HDL水平较明显。(3)TN组大鼠血清丙二醛(malondialdehyde,MDA)和游离8-异前列腺素F2α(8-iso-prostaglandin F2α,8-isoPGF2α)水平均高于NC组(P<0.05或P<0.01),YGTN组大鼠血清MDA和8-isoPGF2α水平均低于TN组(P<0.05或P<0.01);TN组大鼠血清过氧化氢酶(catalase,CAT)、超氧化物歧化酶(superoxide dismutase,SOD)、谷胱甘肽过氧化物酶(glutathione peroxidase,GSH-Px)和总抗氧化能力(total antioxidant capacity,T-AOC)水平均低于NC组(P<0.01),YGTN组大鼠血清CAT、SOD、GSH-Px和T-AOC水平均高于NC组(P<0.01),但基本上恢复到NC组的水平。(4)TN组大鼠骨骼肌卫星细胞配对盒基因7(paired box gene 7,Pax7)、成肌分化因子(myogenic determination gene,MyoD)、肌细胞生成素(myogenin,MyoG)和生肌因子5(myogenic factor 5,Myf5)蛋白表达均低于NC组(P<0.05或P<0.01),YGTN组大鼠骨骼肌Pax7、MyoD、MyoG和Myf5蛋白表达均高于TN组(P<0.05或P<0.01);基本上恢复到NC组水平。TN组大鼠骨骼肌生成抑制素(myostatin,MSTN)蛋白表达高于NC组(P<0.05),YGTN组大鼠骨骼肌MSTN蛋白表达低于TN组(P<0.05),基本上恢复到NC组水平。结论益生菌和有氧运动具有减轻胰岛素抵抗,改善血脂和氧化激的作用,在改善2型糖尿病大鼠血糖和胰岛素水平具有协同作用。此外,有氧运动联合益生菌干预促进了肌细胞的分化,可能对防止T2DM引起肌肉质量的流失和力量下降以及肌肉组织的并发症发挥一定的作用。

遥感影像融合方法对GF-2影像土地利用分类的影响

选择新郑城镇区域为研究区,以高分二号(GF-2)影像为数据源,首先分别利用HSV算法、Brovey算法、PCA算法及Gram-Schmidk(GS)算法进行影像融合;然后在eCognition软件平台上,基于面向对象多尺度分割技术,利用随机森林算法对影像进行土地利用分类,并对分类结果进行精度评价。试验结果表明:不同融合算法影像融合效果明显不同,其中,GS算法融合后的影像质量最好,且分类精度最高,PCA与HSV算法次之,Brovey算法融合影像在4种融合算法中分类精度最低。