Haikuan Feng
Ecology · 2014–2021
A researcher in the Science corpus: 13 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Ecology — 159 citations into it
- Plant Science — 109 citations into it
- Environmental Engineering — 94 citations into it
Whom Haikuan Feng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Haikuan Feng's perspective
Ordered by how strongly the researchers Haikuan Feng trusts endorse each paper. Same corpus, a different order for every researcher.
- Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
- Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
- Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. (Journal of Experimental Botany)
- Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle (IEEE Transactions on Geoscience and Remote Sensing)
- Comparison of different vegetation indices for the remote assessment of green leaf area index of crops
- Diagnosis tool for plant and crop N status in vegetative stage Theory and practices for crop N management
- Retrieval of canopy biophysical variables from bidirectional reflectance Using prior information to solve the ill-posed inverse problem
- Unmanned aerial systems for photogrammetry and remote sensing: A review
- Retrieval of foliar information about plant pigment systems from high resolution spectroscopy
- Neural network estimation of LAI, fAPAR, fCover and LAI×Cab, from top of canopy MERIS reflectance data : Principles and validation
Their papers
- A comprehensive yield evaluation indicator based on an improved fuzzy comprehensive evaluation method and hyperspectral data (2021) — 53 citations
- Estimation of maize yield by assimilating biomass and canopy cover derived from hyperspectral data into the AquaCrop model (2020) — 92 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
- 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
- Parameter sensitivity analysis of the AquaCrop model based on extended fourier amplitude sensitivity under different agro-meteorological conditions and application (2018) — 57 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
- Winter wheat biomass estimation based on spectral indices, band depth analysis and partial least squares regression using hyperspectral measurements (2014) — 182 citations