Stein Rune Karlsen,Arve Elvebakk,Hans Tømmervik et al.
Stein Rune Karlsen et al.
The global temperature is increasing, and this is affecting the vegetation phenology in many parts of the world. The most prominent changes occur at northern latitudes such as our study area, which is Svalbard, located between 76°30'N and ...
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery [0.03%]
基于Sentinel-2影像的阿根廷冬小麦灌溉性状季节映射的混合反演工作流
Gabriel Caballero,Alejandro Pezzola,Cristina Winschel et al.
Gabriel Caballero et al.
Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant dev...
Introducing ARTMO's Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape [0.03%]
介绍ARTMO的机器学习分类算法工具箱：在伊朗半草原景观中进行植物类型检测的应用
Masoumeh Aghababaei,Ataollah Ebrahimi,Ali Asghar Naghipour et al.
Masoumeh Aghababaei et al.
Accurate plant-type (PT) detection forms an important basis for sustainable land management maintaining biodiversity and ecosystem services. In this sense, Sentinel-2 satellite images of the Copernicus program offer spatial, spectral, tempo...
Crop Nitrogen Retrieval Methods for Simulated Sentinel-2 Data Using In-Field Spectrometer Data [0.03%]
基于实地光谱仪数据的Sentinel-2模拟数据作物氮素吸收方法
Gregor Perich,Helge Aasen,Jochem Verrelst et al.
Gregor Perich et al.
Nitrogen (N) is one of the key nutrients supplied in agricultural production worldwide. Over-fertilization can have negative influences on the field and the regional level (e.g., agro-ecosystems). Remote sensing of the plant N of field crop...
Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow [0.03%]
基于变分异方差高斯过程的农作物多性状天顶角反演算法及流程研究
José Estévez,Katja Berger,Jorge Vicent et al.
José Estévez et al.
In support of cropland monitoring, operational Copernicus Sentinel-2 (S2) data became available globally and can be explored for the retrieval of important crop traits. Based on a hybrid workflow, retrieval models for six essential biochemi...
Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor [0.03%]
基于Sentinel-3 OLCI传感器的多尺度分析下的中分辨率叶面积含叶绿素及冠层叶绿素含量的反演与验证
Charlotte De Grave,Luca Pipia,Bastian Siegmann et al.
Charlotte De Grave et al.
ESA's Eighth Earth Explorer mission "FLuorescence EXplorer" (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential ...
Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy [0.03%]
基于PROSAIL的 maize冠层多光谱无人机图像数据反演作物参数研究
Erekle Chakhvashvili,Bastian Siegmann,Onno Muller et al.
Erekle Chakhvashvili et al.
Mapping crop variables at different growth stages is crucial to inform farmers and plant breeders about the crop status. For mapping purposes, inversion of canopy radiative transfer models (RTMs) is a viable alternative to parametric and no...
Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine [0.03%]
基于高斯过程回归的Google Earth Engine平台叶面积指数制图与云隙填充技术研究
Luca Pipia,Eatidal Amin,Santiago Belda et al.
Luca Pipia et al.
For the last decade, Gaussian process regression (GPR) proved to be a competitive machine learning regression algorithm for Earth observation applications, with attractive unique properties such as band relevance ranking and uncertainty est...
Approximating Empirical Surface Reflectance Data through Emulation: Opportunities for Synthetic Scene Generation [0.03%]
基于仿真的实测场景表面反射数据建模及在合成孔径成像中的应用研究
Jochem Verrelst,Juan Pablo Rivera Caicedo,Jorge Vicent et al.
Jochem Verrelst et al.
Collection of spectroradiometric measurements with associated biophysical variables is an essential part of the development and validation of optical remote sensing vegetation products. However, their quality can only be assessed in the sub...
Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms [0.03%]
异质半草原上的植物生态单元分类：四种分类算法的性能评估
Masoumeh Aghababaei,Ataollah Ebrahimi,Ali Asghar Naghipour et al.
Masoumeh Aghababaei et al.
Plant Ecological Unit's (PEUs) are the abstraction of vegetation communities that occur on a site which similarly respond to management actions and natural disturbances. Identification and monitoring of PEUs in a heterogeneous landscape is ...