Preliminary study of natural reservoirs as sentinels of <i>Anaplasma phagocytophilum</i>and <i>Ehrlichia chaffeensis</i>in Soria, northern Spain

The serum of foxes and red deer from the Province of Soria (northern Spain) was screened in indirect immunofluorescence assays to determine whether these animals could be used as sentinels of the tick-borne pathogens Anaplasma phagocytophilum and Ehrlichia chaffeensis. The results suggest that foxes and red deer would not make good sentinels in epidemiological studies on E. chaffeensis in this region, although red deer could be used as such for the study of A. phagocytophilum transmission.

基于Sentinel-2与时序Sentinel-1 SAR特征的赣南柑橘种植区识别方法

为准确获取柑橘果园空间分布信息,实现柑橘种植结构调整、产量估算和资源管理,以赣南3个柑橘种植主产区(信丰县、安远县及寻乌县)为研究区域,针对南方地区多云多雨导致传统光学影像较为缺乏的问题,使用Sentinel系列数据和PIE-Engine平台,构建和优选了光谱特征、植被水体指数特征、红边波段特征和纹理特征,并引入时间序列Sentinel-1合成孔径雷达(SAR)数据的后向散射系数,共同探讨不同特征组合对柑橘种植园的识别提取效果,基于随机森林算法并融合Sentinel-2与时序Sentinel-1 SAR特征识别提取了赣南柑橘种植区。结果表明:5、9、11月柑橘种植园与其他地物的平均后向散射系数分离性最佳,是识别提取柑橘的关键时期;指数特征及纹理特征参与分类改善了分类效果且提高了分类精度;相较于单一SAR特征及指数、纹理特征,加入时序SAR特征的分类结果中总体精度达90.084%,Kappa系数达0.863,错分、漏分误差较小,符合实际地物分布情况,说明了时序SAR特征的可用性和实用性。本研究可为多云多雨的南方柑橘果园的识别提取提供参考。

基于多源遥感数据的俄亥俄水体污染情况监测

城市水污染监测是当前研究的热点问题。针对美国俄亥俄州东巴勒斯坦镇氯乙烯泄露事件,以多源卫星遥感数据为依托,快速进行事故发生后水质变化的遥感水体指数提取,选取两种黑臭水体指数与一种水质回归模型进行监测试验。试验结果表明,事故发生后,研究区附近综合水质指标值均值显著增大。

融合Sentinel-1特征参数的海冰类型监测研究

本文以Sentinel-1A为实验数据,提取加拿大西北航道部分区域的纹理特征和极化特征,采用相关分析和ReliefF法筛选出对分类具有促进作用的特征参数,将参数进行组合后输入随机森林分类器进行海冰类型的识别。通过对比不同组合特征的分类精度,得到以下结论:融合纹理特征和极化特征的分类精度高达92.01%,分类结果相较其他融合特征组合也更加平滑,加入纹理特征或极化特征使分类精度提高了2.59%——18.75,Kappa系数也相应的得到了提高。实验表明,特征融合对识别不同海冰类型有促进作用,可以弥补单一特征之间的不足,提高海冰分类的精度。

基于Sentinel数据的沅陵县针叶林可燃物载量估测研究

森林可燃物是引发森林火灾的重要因素之一,准确估测森林可燃物载量对于制定火灾防控策略、提高火灾预警能力以及保护生态环境具有重要意义。以湖南省沅陵县Senitnel-1A和Sentinel-2A影像为数据源,通过提取多源数据的不同类型遥感因子,结合地面调查获取的样地可燃物载量信息,采用前向特征筛选法和4种机器学习模型[多元线性回归(multiple linear regression,MLR)、k最近邻(k-nearest neighbor,kNN)、支持向量机回归(support vector regression,SVR)、随机森林(random forest,RF)]构建了针叶林可燃物载量反演模型,并对研究区内针叶林可燃物载量进行反演。结果表明:①基于Sentinel-1A数据提取的VH极化后向散射系数与针叶林可燃物载量有较高的相关性;②相比于单一数据源,联合Sentinel-1A和Sentinel-2A数据可显著提高针叶林可燃物载量估测精度,最优模型R^(2)分别提高了0.19、0.29,rRMSE分别降低4.66、6.94个百分点,RMSE分别降低了6.13、9.13 t/hm^(2),平均rRMSE分别降低了5.17、5.75个百分点,最优模型为SVR模型,其R^(2)=0.5,rRMSE=27.71,RMSE=36.47 t/hm^(2)。Sentinel-1A数据的加入有利于针叶林可燃物载量估测精度的提升。

Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests

Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.

基于雷达和光学遥感数据的云污染区域光谱重建算法

光学遥感影像在农业领域中应用广泛,但易受天气影响,为减少云污染对影像质量的影响并恢复受污染区域的光谱信息,该研究提出了一种基于雷达和光学遥感数据的云污染区域光谱重建方法。该方法通过结合合成孔径雷达数据,将雷达信号与地类信息作为重建区域的约束条件,在雷达影像上计算相应距离矩阵并移植到光学影像上进行替换,在提高像元间匹配精度的同时最大限度地保留原始影像的光谱信息,为后续地表信息的准确提取奠定基础。为了评估所提出方法的性能,该研究采用传统像素替换法、加权线性回归方法以及基于曲率驱动的方法进行对比试验。结果表明,改进算法重建的波段反射率更接近参考影像,其中Band2、Band3相关系数达到了0.925与0.922,均方根误差分别为0.009、0.007,重建影像与参考影像间的质量损失较少,各波段的峰值信噪比与结构相似性均最高,说明该研究算法在重建影像质量、与参考影像的相似性和光谱特征一致性方面取得了较好的结果。

Advances in regional nodal management of early-stage breast cancer

With the continuous improvement of systemic treatment, reasonable local regional control of early-stage breast cancer can be translated into survival benefits. The optimization of regional nodal management in patients with limited sentinel lymph node(SLN) metastasis needs to be weighed by surgical complications, regional recurrence risk, and lymph node status, as well as other escalating treatment(systemic/radiotherapy) that may result from deescalating surgery. With the effective support and supplementation of systemic therapy and radiotherapy, the management of axillary surgery is developing in a de-escalating trend. The widespread application of neoadjuvant therapy has contributed to optimizing the management of patients with clinically node-negative/imaging nodepositive disease. In clinical practice, it is necessary to consider the residual tumor burden of regional lymph nodes when formulating the optimal irradiation fields in patients with limited positive SLN without axillary lymph node dissection. The combined application of genomic tests and American College of Surgeons Oncology Group Z0011/AMAROS criteria could provide patients with a better strategy of dual de-escalation treatment, which includes the de-escalation of both axillary surgery and systemic treatment. In the era of sentinel lymph node biopsy(SLNB), the regional nodal management of breast cancer should adhere to the concept of “updating ideas, making bold assumptions, and carefully seeking proof”, make full use of the benefits of systemic therapy and radiotherapy to reduce the scope of surgery and complications, and expand the “net benefit” of efficacy and quality of life. This review discusses the optimization of regional nodal management in the era of SLNB, in order to provide reference information for clinicians.

基于Sentinel2A影像的干旱区土壤盐渍化监测研究

以渭干河-库车河三角洲绿洲为例,在5种盐分光谱指数(NDSI、SI、SI1、SI2、SAVI)基础上,选择Sentinel2A多光谱影像中的3个红边波段和近红外窄波段进行扩展,提出了新的基于红边和近红外窄波段的光谱指数,用偏最小二乘回归(PLSR)方法构建土壤电导率遥感反演模型。结果表明:相对传统光谱指数,引入红边1波段(B_(5))和近红外窄波段(B_(8a))的光谱指数与土壤电导率相关性显著提高;基于Sentinel2A影像的PLSR的土壤电导率信息建模效果较好(R^(2)=0.77),模型准确、可靠。盐分反演结果表明研究区土壤盐分含量整体较高,盐渍化影响范围广泛。自绿洲内部向外围由非盐渍化向轻度-中度-重度盐渍化过渡,绿洲西部、南部轻度盐渍土分布较多,绿洲东部、东南及西南方向有重度盐渍土及极重度盐渍土分布,盐渍化程度较高。

Application value of indocyanine green fluorescence imaging in guiding sentinel lymph node biopsy diagnosis of gastric cancer: Meta-analysis

BACKGROUND Gastric cancer is a common malignant tumor of the digestive system worldwide,and its early diagnosis is crucial to improve the survival rate of patients.Indocyanine green fluorescence imaging(ICG-FI),as a new imaging technology,has shown potential application prospects in oncology surgery.The meta-analysis to study the application value of ICG-FI in the diagnosis of gastric cancer sentinel lymph node biopsy is helpful to comprehensively evaluate the clinical effect of this technology and provide more reliable guidance for clinical practice.AIM To assess the diagnostic efficacy of optical imaging in conjunction with indocya-nine green(ICG)-guided sentinel lymph node(SLN)biopsy for gastric cancer.METHODS Electronic databases such as PubMed,Embase,Medline,Web of Science,and the Cochrane Library were searched for prospective diagnostic tests of optical imaging combined with ICG-guided SLN biopsy.Stata 12.0 software was used for analysis by combining the"bivariable mixed effect model"with the"midas"command.The true positive value,false positive value,false negative value,true negative value,and other information from the included literature were extracted.A literature quality assessment map was drawn to describe the overall quality of the included literature.A forest plot was used for heterogeneity analysis,and P<0.01 was considered to indicate statistical significance.A funnel plot was used to assess publication bias,and P<0.1 was considered to indicate statistical significance.The summary receiver operating characteristic(SROC)curve was used to calculate the area under the curve(AUC)to determine the diagnostic accuracy.If there was interstudy heterogeneity(I2>50%),meta-regression analysis and subgroup analysis were performed.analysis were performed.RESULTS Optical imaging involves two methods:Near-infrared(NIR)imaging and fluorescence imaging.A combination of optical imaging and ICG-guided SLN biopsy was useful for diagnosis.The positive likelihood ratio was 30.39(95%CI:0.92-1.00),the sensitivity was 0.95(95%CI:0.82-0.99),and the specificity was 1.00(95%CI:0.92-1.00).The negative likelihood ratio was 0.05(95%CI:0.01-0.20),the diagnostic odds ratio was 225.54(95%CI:88.81-572.77),and the SROC AUC was 1.00(95%CI:The crucial values were sensitivity=0.95(95%CI:0.82-0.99)and specificity=1.00(95%CI:0.92-1.00).The Deeks method revealed that the"diagnostic odds ratio"funnel plot of SLN biopsy for gastric cancer was significantly asymmetrical(P=0.01),suggesting significant publication bias.Further meta-subgroup analysis revealed that,compared with fluorescence imaging,NIR imaging had greater sensitivity(0.98 vs 0.73).Compared with optical imaging immediately after ICG injection,optical imaging after 20 minutes obtained greater sensitivity(0.98 vs 0.70).Compared with that of patients with an average SLN detection number<4,the sensitivity of patients with a SLN detection number≥4 was greater(0.96 vs 0.68).Compared with hematoxylin-eosin(HE)staining,immunohistochemical(+HE)staining showed greater sensitivity(0.99 vs 0.84).Compared with subserous injection of ICG,submucosal injection achieved greater sensitivity(0.98 vs 0.40).Compared with 5 g/L ICG,0.5 and 0.05 g/L ICG had greater sensitivity(0.98 vs 0.83),and cT1 stage had greater sensitivity(0.96 vs 0.72)than cT2 to cT3 clinical stage.Compared with that of patients≤26,the sensitivity of patients>26 was greater(0.96 vs 0.65).Compared with the literature published before 2010,the sensitivity of the literature published after 2010 was greater(0.97 vs 0.81),and the differences were statistically significant(all P<0.05).CONCLUSION For the diagnosis of stomach cancer,optical imaging in conjunction with ICG-guided SLN biopsy is a therapeut-ically viable approach,especially for early gastric cancer.The concentration of ICG used in the SLN biopsy of gastric cancer may be too high.Moreover,NIR imaging is better than fluorescence imaging and may obtain higher sensitivity.

基于SBAS-In SAR的地表沉降监测及漏斗拟合分析

近年来,In SAR技术凭借其测量范围广、精度高及便捷高效等优势,已被广泛应用于矿区的沉降监测中。利用InSAR技术研究矿区的沉降漏斗所采用的主要模型有Logistic模型、Knothe模型等,这些多以沉降量预测为主,且模型计算相对复杂,在三维可视化表达方面也相对较少。因此,本文提出一种采用椭圆锥拟合矿区沉降漏斗的方法,用于揭示矿区开采时地表沉降的时空演化特征。首先,基于SBAS-InSAR技术处理Sentinel-1A影像数据获取矿区的时序沉降结果;其次,将不同时期的沉降结果转化为栅格数据,利用椭圆锥模型拟合沉降漏斗,获取椭圆锥参数;最后,采用线性拟合的方式拟合不同时期椭圆锥的参数变化,研究矿区沉降过程中的时空演化规律,并用验证点证实监测结果的可靠性。结果表明,本方法能够用于快速模拟和分析矿区工作面附近的沉降漏斗,从而有效揭示沉降过程中的三维时空演化规律。研究成果能够为地质灾害防治、沉降治理等提供科学的参考依据。

Clinical Study of Double Contrast-Enhanced Ultrasound Combined with Dye Method and Marker Placement to Identify and Locate Sentinel Lymph Nodes in Patients with Breast Cancer

Objective: To explore the value of percutaneous ultrasonography combined with transvenous ultrasonography for accurate localization of sentinel lymph nodes and diagnosis of metastatic lymph nodes in patients with breast cancer. Methods: 18 cases of patients with breast cancer attending the Hainan General Hospital from May 2022 to June 2024 who were proposed to undergo axillary lymph node dissection were selected, and the ultrasonographic agent was injected subcutaneously through the areola on the 1st day before the operation, and the marker localization of the manifestation of the Sentinel lymph nodes and draw the lymphatic vessel alignment for drainage on the body surface, and record the manifestation of SLN by conventional ultrasound and dual ultrasonography. At the time of surgery, intraoperative melphalan localization was used to identify the SLN, the difference between the number of ultrasound and melphalan localization was observed, and resection was performed for pathological examination to determine whether they were metastatic or not. Results: There were 8 metastatic lymph nodes and 18 non-metastatic lymph nodes among 31 SLN. A total of 62 SLN were localized by intraoperative melphalan, of which 31 were consistent with ultrasound localization and 31 were not identified by ultrasound. The diagnostic sensitivity of SLN metastasis diagnosed by transcutaneous ultrasonography was 62.50%, specificity was 91.30%, positive predictive value was 71.43%, negative predictive value 87.50%, accuracy was 83.87%, and the AUC was 0.769;the diagnostic sensitivityof transvenous ultrasonography diagnosed was 75.00%, specificity was 75.00%, and the accuracy was 83.87%, 75.00%, specificity 91.30%, positive predictive value 75.00%, negative predictive value 91.30%, accuracy 87.10%, AUC 0.832;dual ultrasonography diagnostic sensitivity 87.50%, specificity 91.30%, positive predictive value 77.78%, negative predictive value 95.45%, accuracy 90.32%. The AUC was 0.894. Conclusion: Transcutaneous ultrasonography combined with transvenous ultrasonography can accurately localize sentinel lymph nodes and improve the sensitivity and accuracy of the diagnosis of metastatic SLN.

Method of Monitoring Three-dimensional Mining Surface Deformation Based on InSAR

In order to solve the problems of small monitoring range,long time and high cost of existing sedimentation observation methods,based on two-view sentinel No.1 radar images of Guqiao mining area in Huainan City from November 4,2017 to November 28,2017,surface change information was obtained in combination with D-InSAR,and the three-dimensional surface deformation was monitored by two-pass method and single line of sight D-InSAR method.The results show that during the research period of 24 d,the maximum deformation of the mining area reached 71 mm,and the southern subsidence was the most obvious,which was in line with the mining subsidence law.The maximum displacement from the north to the south was about 250 mm,while the maximum displacement from the east to the west was about 80 mm,and the maximum subsidence in the center was 110 mm.It is concluded that D-InSAR technique has a good effect on the inversion of the mining subsidence,and this method is suitable for three-dimensional surface monitoring in areas with similar geological conditions.The monitoring results have certain reference value.

SENTINELS FOR FERIODIC DISTRIBUTED SYSTEMS

For periodic distributed systems the author reduces the "entinels" problem to a problem of controllability type and uses suitable adaptations of of HUM (Hilbert Uniqueness Method) to gives olutions to the original "sentinels" problem.

基于GEE云平台和数据融合的地表覆盖产品制作方法

地表覆盖产品是地理国情监测、生态系统评估、国土空间规划等活动的重要基础数据。GEE、PIE、微软行星云等遥感计算云平台具备丰富的数据源和强大算力。利用GEE云平台融合多套公开产品制作训练样本,可以显著降低产品更新的成本和周期,具有重要研究价值。本文以淮河流域为例,将欧洲航天局(ESA)和美国环境系统研究所(ESRI)存储在GEE平台上的2020年分辨率10 m地表覆盖产品作为训练样本数据源,选用Sentinel-1雷达和Sentinel-2多光谱影像构建特征空间,利用随机森林分类方法制作分辨率10 m的地表覆盖产品。为验证方法效果,进行了2组对比实验。实验1随机抽取1 116个公开产品类别一致的样点作为训练样本,并通过目视解译方式验证本文产品与多套公开产品的精度。结果显示,本文产品总体精度为80.35%,相较于公开产品的总体精度提升2.89~8.94个百分点,局部刻画也更加精细;在Sentinel-2基础上加入雷达影像,总体精度提高3.52个百分点,雷达影像辅助效果明显。实验2设置8组不同数量的训练样本,并分别以人工判读、ESA、ESRI、DW、GlobeLand30为参考数据源,研究不同训练样本量和不同参考数据源对分类产品总体精度的影响。结果显示,随着训练样本不断增加,基于5种不同参考数据源的总体精度的提升幅度逐渐减小并趋于相对稳定。研究结果表明,借助GEE平台上的公开地表覆盖产品和海量遥感影像,可以快速提取高质量的训练样本,获得更高质量的分辨率10 m地表覆盖产品,该方法具有重要的实践推广价值。

基于Sentinel2-L1C的江汉平原水产养殖区水质参数反演

遥感技术已成为监测内陆水域水质的一种有效手段,为研究江汉平原水产养殖区域内水体总磷、总氮和化学需氧量浓度的变化规律,基于Sentinel2-L1C遥感数据建立水体透明度、悬浮物浓度、叶绿素a浓度3种光学活性物质浓度的反演模型,结合推算出的水体透明度、悬浮物浓度和叶绿素a浓度与拟合点水体实测总磷、总氮和化学需氧量浓度分别建立关联,构建江汉平原拟合点水体总磷、总氮和化学需氧量浓度3种非光学活性物质浓度的间接反演模型并进行模型的率定验证。结果表明:水体透明度与水体总磷浓度具有较好相关性,水体透明度越高,水质越好,水体总磷浓度越低;水体悬浮物浓度与水体总氮浓度具有较高相关性,水体悬浮物浓度越高,水质越差,对应水体总氮浓度越高;水体叶绿素a浓度越高,对应水体化学需氧量浓度越高。构建水体总磷浓度、总氮浓度和化学需氧量浓度的间接反演模型,确定性系数均>0.6,并对江汉平原监测点水体的总磷、总氮和化学需氧量浓度进行了模拟和分析,结论与水产养殖区内饲料投喂主要时期的影响规律基本保持一致。研究结果对于探测江汉平原水产养殖区大尺度范围水质参数的时空演变具有一定的实用价值。

融合主被动遥感影像的冬小麦种植面积提取研究

为了快速、准确地获取作物分布信息,探索使用主动遥感影像(Sentinel-1A)和被动遥感影像(Sentinel-2)提取冬小麦空间分布的可行性。首先,根据冬小麦的物候特征,合成冬小麦全生育期的Sentinel-1A影像;并依据各类地物的NDVI(归一化植被指数)时序曲线合成一期高质量的冬小麦越冬后Sentinel-2影像。其次,设计Sentinel-1A影像、Sentinl-2影像和融合Sentinel-1A与Sentinl-2主被动遥感影像3种分类方案,然后在Google Earth Engine(GEE)云平台上基于随机森林算法对冬小麦进行分类。结果表明,基于全生育期Sentinel-1A影像的冬小麦用户精度和生产者精度分别为83.15%和86.44%,提取结果中存在较多的“椒盐”噪声;基于冬小麦越冬后Sentinl-2影像的冬小麦用户精度和生产者精度分别为87.98%和84.75%,提取精度较使用全生育期Sentinel-1A影像有所提高,但分类结果受“异物同谱”的影响,产生许多错分;融合主被动遥感影像的冬小麦用户精度和生产者精度分别为96.57%和95.48%,相较于仅使用单一数据源,冬小麦分类精度有不同程度的提升。

基于5种植被指数的荒漠区植被生物量提取研究

荒漠区植被地上生物量是土地荒漠化监测和荒漠植被遥感信息提取的重要指标。本研究以甘肃民勤县为试验区,以哨兵2号(Sentinel-2)影像为数据源,构建了比值植被指数RVI、归一化植被指数NDVI、差值植被指数DVI、土壤调节植被指数SAVI及优化型土壤调节植被指数OSAVI 5种植被指数与植被实测地上生物量的估算模型(一元线性、指数、对数和二项式模型),并利用所选的最优模型,估算了研究区的地上生物量。结果表明:SAVI相较于RVI、NDVI、DVI和OSAVI指数同地上生物量之间的相关性最高(r=0.79),基于SAVI指数的二项式模型是研究区地上生物量估算的最优模型(R^(2)=0.76),且精度较高(R^(2)=0.73,RMSE=0.12)。民勤县的植被相对密集区主要分布于四大灌区(红崖山、环河、昌宁、南湖)、青土湖周边以及红沙岗镇西北区域,其他地域植被较为稀疏,无植被区[<0.005 kg·(100m^(2))^(-1)]、低植被区[0.005~0.2 kg·(100m^(2))^(-1)]、中植被区[0.2~0.5 kg·(100m^(2))^(-1)]和高植被区[>0.5 kg·(100m^(2))^(-1)]的占比分别为66%、21%、5%和8%。

基于哨兵SAR数据和多光谱数据的水稻识别研究

水稻分布范围与面积监测可为水稻产量估算、农业水资源消耗和评价等提供科学决策依据。目前,对华北单季稻稻作区水稻识别的研究尚少,寻找一种适用该区域的水稻识别方法具有一定的研究价值。以天津为研究范围,以Sentinel-1和Sentinel-2为数据源,基于水稻后向散射系数时序变化特征和水稻不同生长期光谱特征,分别对研究区水稻进行了提取,并对两者的提取精度进行了比较。得出以下结论:(1)利用Sentinel-1移栽期、拔节期、抽穗期影像组合可识别水稻,水稻生产者精度和用户精度均在90%以上;(2)在水稻移栽期和成熟期,Sentinel-2近红外、短波红外和可见光红光等波段组合易识别水稻,水稻生产者精度和用户精度均在96%以上,成熟期B12+B8+B4波段组合效果最优;(3)基于水稻成熟期的Sentinel-2 B12+B8+B4波段组合,采用支持向量机法提取水稻是一种适用于华北单季稻的识别方法。运用该方法计算出研究区2016、2018和2021水稻种植面积分别为399.04、586.67和764.55 km^(2),5 a增加365.51 km^(2),符合天津市实际情况。该方法在技术上简单易行,可为提高我国北方稻作区水稻监测效率与精度提供参考。

基于Sentinel数据的新疆奇台县小麦作物识别和秸秆产量估算

【目的】新疆奇台县小麦作物种植面积大,秸秆资源丰富。监测并获取秸秆资源的分布与产量,对于促进秸秆综合利用、减少环境污染具有重要意义。【方法】以奇台县境内小麦作物为研究对象,融合多时相的Sentinel-2光学和Sentinel-1雷达数据,选择合适的特征,使用三种机器学习方法对奇台县小麦作物进行识别和小麦秸秆估产。【结果】使用随机森林分类器的分类结果最好,在仅使用Sentinel-1的雷达极化特征分类时,总体精度为96%。在使用Sentinel-1的雷达极化特征与Sentinel-2光学波段特征分类时,总体精度为94%。当使用Sentinel-1的雷达极化特征、Sentinel-2光学波段特征以及植被特征指数的组合分类时精度最高,总体精度可达到98%,Kappa系数可达到97%。基于地面抽样调查数据,估算小麦作物秸秆每公顷产量为27007 kg,总产量为100615.5 t。【结论】在小麦抽穗期,特征组为Sentinel-1的雷达极化特征、Sentinel-2光学波段特征以及植被特征指数的组合,使用随机森林分类效果最好。