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J

Jochem Verrelst

University of Valencia

58H指数
290论文数
1.3W被引数
收录论文 111
发表时间
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Assessing the Role of Global Satellite-Derived SIF and Vegetation Traits as Proxy Predictors of Gross Primary Productivity评估全球卫星遥感太阳诱导叶绿素荧光和植被性状作为总初级生产力的代理预测因子的作用
errRemote Sensing
IF4.1
err2026-09-24
err0
errOAAI
errPablo Reyes-Muñoz; Emma De Clerck; Yuxin Zhang; Dávid D. Kovács; Jochem Verrelst
err分享
err收藏
Dynamic Reconstruction of Vegetation Earth Observation Time Series: Beyond Gap-Filling in Level-3 Products植被地球观测时间序列的动态重建：超越Level-3产品的数据填充
errRemote Sensing
IF4.1
err2026-09-17
err0
errOAAI
errJochem Verrelst
err分享
err收藏
Retrieval of Vegetation Nitrogen from Hyperspectral Remote Sensing: A Critical Review of Recent Methodological Advances基于高光谱遥感的植被氮素反演：近期方法学进展的综述
errRemote Sensing
IF4.1
err2026-09-10
err0
errOAAI
errJochem Verrelst; Anirudh Belwalkar; Kang Yu; Miguel Morata; Manish Kumar Patel
err分享
err收藏
GBOV-trained Gaussian process models for Sentinel-3 SYN vegetation traits with decomposed uncertainty quantification基于GBOV训练的高斯过程模型用于Sentinel-3 SYN植被性状及分解不确定性量化
errISPRS Journal of Photogrammetry and Remote Sensing
IF12.2
err2026-09-08
err0
errOAAI
errPablo Reyes-Muñoz; Emma De Clerck; Yuxin Zhang; José Luis García-Soria; Luke A. Brown; Miguel Morata; Carolina Tenjo; Jochem Verrelst
err分享
err收藏
Earth Observation-Driven Inference for Level-4 Terrestrial Products: Process-Based, Machine Learning, and Hybrid Frameworks地球观测驱动的陆地四级产品反演：基于过程、机器学习和混合框架
errRemote Sensing
IF4.1
err2026-08-19
err0
errOAAI
errJochem Verrelst; Pablo Reyes-Muñoz
err分享
err收藏
Hybrid FAPAR and FVC retrieval from Sentinel-3 SYNERGY with Gaussian processes: Development, validation, and cloud-readiness利用高斯过程从Sentinel-3 SYNERGY中协同反演FAPAR和FVC：方法开发、验证与云适应性
errScience of Remote Sensing
IF5.2
err2026-07-08
err0
errOAAI
errDávid D.Kovács; Emma De Clerck; Luke A. Brown; Pablo Reyes-Muñoz; Jochem Verrelst
err分享
err收藏
Scale-Aware Interpretation of Vegetation Traits and SIF-Based Dynamics in Earth Observation基于地球观测的植被性状与SIF基动态的尺度感知解释
errRemote Sensing
IF4.1
err2026-06-12
err0
errOAAI
errJochem Verrelst; Bhagyashree Verma; Pablo Reyes-Muñoz
err分享
err收藏
A cloud-computing framework for downscaled global 300 m SIF retrieval from Sentinel-3 and TROPOSIF基于云计算框架的Sentinel-3和TROPOSIF数据降尺度全球300米SIF反演
errInternational Journal of Applied Earth Observation and Geoinformation
IF8.6
err2026-05-07
err0
errOAAI
errYuxin Zhang; Pablo Reyes-Muñoz; Jochem Verrelst
err分享
err收藏
Cloud-Native Earth Observation for Quantitative Vegetation Science: Architectures, Workflows, and Scientific Implications云原生地球观测在定量植被科学中的应用：架构、工作流及科学意义
errRemote Sensing
IF4.1
err2026-04-13
err0
errOAAI
errJochem Verrelst; Emma De Clerck; Bhagyashree Verma; Kavach Mishra; Gabriel Caballero
err分享
err收藏
RTM Surrogate Modeling in Optical Remote Sensing: A Review of Emulation for Vegetation and Atmosphere ApplicationsRTM代理建模在光学遥感中的应用：植被和大气应用中仿真的综述
errRemote Sensing
IF4.1
err2026-03-03
err0
errOAAI
errJochem Verrelst; Miguel Morata; José Luis García-Soria; Yilin Sun; Jianbo Qi; Juan Pablo Rivera-Caicedo
err分享
err收藏
Epistemic and aleatoric uncertainty in optical vegetation trait retrieval: Concepts, Methods, and Outlook认知不确定性和随机不确定性在光学植被性状反演中的概念、方法与展望
errISPRS Journal of Photogrammetry and Remote Sensing
IF12.2
err2026-02-14
err0
PREAI
errJochem Verrelst; José Luis García-Soria; Pablo Reyes-Muñoz; Emma De Clerck; Miguel Morata; Juan Pablo Rivera-Caicedo
err分享
err收藏
Machine Learning for Satellite Solar-Induced Fluorescence: Retrieval, Reconstruction, Downscaling, and Applications卫星太阳诱导荧光的机器学习方法：反演、重构、降尺度和应用
errRemote Sensing
IF4.1
err2026-02-10
err0
errOAAI
errJochem Verrelst; Yuxin Zhang; Miguel Morata; Emma De Clerck; Leizhen Liu
err分享
err收藏
Assessment of PlanetScope Spectral Data for Estimation of Peanut Leaf Area Index Using Machine Learning and Statistical Methods
errSensors
IF3.5
err2026-02-05
err0
errOAAI
errMichael Ekwe; Hansanee Fernando; Godstime James; Oluseun Adeluyi; Jochem Verrelst; Angela Kross
err分享
err收藏
A User-Friendly Google Earth Engine Web Application for Vegetation Trait Mapping and Time Series Analysis From Sentinel-2 and Sentinel-3 Imagery一个用户友好的Google Earth Engine网络应用程序，用于植被性状制图和时间序列分析，数据来源于Sentinel-2和Sentinel-3影像
errIEEE Geoscience and Remote Sensing Letters
IF4.4
err2026-01-26
err0
errOAAI
errEmma De Clerck; Jochem Verrelst
err分享
err收藏
Enhancing Plant Ecological Unit Mapping Accuracy with Auxiliary Data from Landsat-8 in a Heterogeneous Rangeland利用Landsat-8辅助数据提高异质性牧场植物生态单元制图精度
errRemote Sensing 2025, Vol. 17, Page 4025
IF4.1
err2025-12-13
err0
errOAAI
errMasoumeh Aghababaei; Ataollah Ebrahimi; Ali Asghar Naghipour; Esmaeil Asadi; Jochem Verrelst
err分享
err收藏
High-spatial-resolution gross primary production estimation from Sentinel-2 reflectance using hybrid Gaussian processes modeling基于混合高斯过程建模的Sentinel-2反射率高空间分辨率总初级生产力估算
errISPRS Journal of Photogrammetry and Remote Sensing
IF12.2
err2025-12-10
err0
errOAAI
errEmma De Clerck; Pablo Reyes-Muñoz; Egor Prikaziuk; Dávid D.Kovács; Jochem Verrelst
err分享
err收藏
Bridging Gaps in Aquatic Remote Sensing Reflectance Validation: Pixel Boundary Effect and Its Induced Errors桥接水生遥感反射率验证中的差距：像素边界效应及其诱导误差
errSensors 2025, Vol. 25, Page 7333
IF3.5
err2025-12-03
err0
errOAAI
errShuling Xiao; Chunguang Lyu; Chi Zhang; Jochem Verrelst; Ling Wang; Yunfei Shi; Yanmei Lyu; Haochuan Shi
err分享
err收藏
Spatiotemporal Analysis of Water Quality Conditions in High-Andean Lakes Based on Satellite Indicators Using Sentinel 2 and Landsat 8/9 Images基于Sentinel 2和Landsat 8/9影像的卫星指标在高海拔安第斯湖泊水质条件时空分析中的应用
errWater 2025, Vol. 17, Page 3145
IF3
err2025-11-02
err0
errOAAI
errValeria Fernanda Flores Cantos; Patricio X. Lozano Rodríguez; Johanna Elizabeth Ayala Izurieta; Carlos Arturo Jara Santillán; Antonio Ruiz-Verdú; Jochem Verrelst; Peter L. M. Goethals; Jesús Delegido
err分享
err收藏
PyEOGPR: A Python package for vegetation trait mapping with Gaussian Process Regression on Earth observation cloud platformsPyEOGPR：一个基于地球观测云平台的、使用高斯过程回归进行植被性状制图的Python软件包
errEcological Informatics
IF7.3
err2025-10-29
err0
errOAAI
errDávid D. Kovács; Emma De Clerck; Jochem Verrelst
err分享
err收藏
Scaling-up plant chlorophyll retrieval from proximal to UAV-borne hyperspectral data using a Gaussian process hybrid model利用高斯过程混合模型，将植物叶绿素反演从近地面数据扩展至无人机载高光谱数据
errInternational Journal of Remote Sensing
IF2.6
err2025-08-17
err0
PREAI
errRabi N. Sahoo; R. G. Rejith; Tarun Kondraju; Rajeev Ranjan; Amrita Bhandari; Shalini Gakhar; Mohd Asim; Jochem Verrelst; Ramanjit Kaur; Teekam Singh; Anchal Dass
err分享
err收藏

研究方向

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