Guijun Yang

Ecology · 2014–2020

A researcher in the Science corpus: 14 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Ecology — 170 citations into it
• Plant Science — 121 citations into it
• Environmental Engineering — 104 citations into it

Whom Guijun Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Juliane Bendig
2. Chaomei Chen
3. Anatoly A. Gitelson
4. Darren Turner
5. Ismael Colomina
6. Andreas Bolten
7. Jose A. Jiménez-Berni
8. Arko Lucieer
9. Helge Aasen
10. Andrea S. Laliberte

Who trusts Guijun Yang overall

1. K. Mochida
2. Rajendra P. Sishodia

Papers from Guijun Yang's perspective

Ordered by how strongly the researchers Guijun Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle (IEEE Transactions on Geoscience and Remote Sensing)
2. Unmanned aerial systems for photogrammetry and remote sensing: A review
3. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
4. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
5. Diagnosis tool for plant and crop N status in vegetative stage Theory and practices for crop N management
6. Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. (Journal of Experimental Botany)
7. Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring (Remote Sensing)
8. Development of a UAV-LiDAR System with Application to Forest Inventory (Remote Sensing)
9. An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds (Remote Sensing)
10. Early prediction of soybean yield from canopy reflectance measurements

Their papers

• A hierarchical interannual wheat yield and grain protein prediction model using spectral vegetative indices and meteorological data (2020) — 59 citations
• Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data (2019) — 374 citations
• Development of Fusarium head blight classification index using hyperspectral microscopy images of winter wheat spikelets (2019) — 65 citations
• Estimating total leaf nitrogen concentration in winter wheat by canopy hyperspectral data and nitrogen vertical distribution (2019) — 46 citations
• Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices (2019) — 368 citations
• A review of data assimilation of remote sensing and crop models (2018) — 478 citations
• Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images (2018) — 112 citations
• Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm (2017) — 140 citations
• Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives (2017) — 650 citations
• Estimation of Winter Wheat Above-Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models (2017) — 332 citations
• Estimating winter wheat (Triticum aestivum) LAI and leaf chlorophyll content from canopy reflectance data by integrating agronomic prior knowledge with the PROSAIL model (2015) — 56 citations
• Estimating wheat yield and quality by coupling the DSSAT-CERES model and proximal remote sensing (2015) — 52 citations
• Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat (2014) — 127 citations
• Winter wheat biomass estimation based on spectral indices, band depth analysis and partial least squares regression using hyperspectral measurements (2014) — 182 citations