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References from UAV-based multispectral inversion models for soil moisture content across the whole growth cycle of mung bean using SHAP interpretation. Local targets link to admitted publications; unresolved targets remain external evidence.
Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale
10.1016/j.rse.2021.112301 · 2021 · External reference
Ground, proximal, and satellite remote sensing of soil moisture
10.1029/2018rg000618 · 2019 · External reference
UAV-based multispectral and thermal cameras to predict soil water content - a machine learning approach
10.1016/j.compag.2022.107262 · 2022 · External reference
Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density
10.1016/s0034-4257(00)00197-8 · 2001 · External reference
Assessment of the SMAP passive soil moisture product
10.1109/tgrs.2016.2561938 · 2016 · External reference
Evaluation of vegetation indices and a modified simple ratio for boreal applications
10.1080/07038992.1996.10855178 · 1996 · External reference
Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning
10.1016/j.agwat.2022.107530 · 2022 · External reference
UAV-based thermal imaging in the assessment of water status of soybean plants
10.1080/01431161.2019.1673914 · 2020 · External reference
Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves
10.1080/014311699211778 · 1999 · External reference
Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance
10.1016/s0034-4257(00)00113-9 · 2000 · External reference
Crop water stress detection based on UAV remote sensing systems
10.1016/j.agwat.2024.109059 · 2024 · External reference
The soil moisture active passive (SMAP) mission
2010 · External reference
Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review
10.1016/j.isprsjprs.2019.11.018 · 2020 · External reference
Water content
1986 · External reference
Estimating agricultural soil moisture content through UAV-based hyperspectral images in the arid region
10.3390/rs13081562 · 2021 · External reference
Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation
10.1078/0176-1617-01176 · 2004 · External reference
Detection of red edge position and chlorophyll content by reflectance measurements near 700 nm
10.1016/s0176-1617(96)80285-9 · 1996 · External reference
Novel algorithms for remote estimation of vegetation fraction
10.1016/s0034-4257(01)00289-9 · 2002 · External reference
Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves
10.1078/0176-1617-00887 · 2003 · External reference
Remote estimation of canopy chlorophyll content in crops - art. no. L08403
10.1029/2005gl022688 · 2005 · External reference
Prediction of soil water content and electrical conductivity using random forest methods with UAV multispectral and ground-coupled geophysical data
10.3390/rs14041023 · 2022 · External reference
Soil moisture content estimation in winter wheat planting area for multi-source sensing data using CNNR
10.1016/j.compag.2021.106670 · 2022 · External reference
Unresolved reference
2009 · External reference
Site-specific soil water characteristic curve prediction with extremely scarce data using data-driven hierarchical bayesian model
10.1016/j.trgeo.2025.101527 · 2025 · External reference
A soil-adjusted vegetation index (SAVI)
10.1016/0034-4257(88)90106-x · 1988 · External reference
Soybean water monitoring and water demand prediction in arid region based on UAV multispectral data
2025 · External reference
Development of a two-band enhanced vegetation index without a blue band
10.1016/j.rse.2008.06.006 · 2008 · External reference
Derivation of leaf-area index from quality of light on the forest floor
10.2307/1936256 · 1969 · External reference
Water relations in plants treated with growth promoting rhizosphere bacteria
10.1007/s11104-023-06270-6 · 2024 · External reference
Soil moisture prediction using remote sensing and machine learning algorithms: a review on progress, challenges, and opportunities
10.3390/rs17142397 · 2025 · External reference
Mapping the groundwater level and soil moisture of a montane peat bog using UAV monitoring and machine learning
10.3390/rs13050907 · 2021 · External reference
Machine learning applications in vadose zone hydrology: a review
10.1002/vzj2.20361 · 2024 · External reference
Fine resolution mapping of forest soil organic carbon based on feature selection and machine learning algorithm
2025 · External reference
Improving accuracy and interpretability of rice aboveground biomass estimation by integrating CatBoost and SHAP model
10.1002/fes3.70159 · 2025 · External reference
A unified approach to interpreting model predictions
2017 · External reference
From local explanations to global understanding with explainable AI for trees
10.1038/s42256-019-0138-9 · 2020 · External reference
Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach
10.1016/j.engstruct.2020.110927 · 2020 · External reference
The use of the normalized difference water index (NDWI) in the delineation of open water features
10.1080/01431169608948714 · 1996 · External reference
Evaluation of sentinel-1 & 2 time series for predicting wheat and rapeseed phenological stages
10.1016/j.isprsjprs.2020.03.009 · 2020 · External reference
Estimating soil moisture at the watershed scale with satellite-based radar and land surface models
10.5589/m04-043 · 2004 · External reference
Influence of soil nutrients on plant characteristics and soil hydrological responses
10.1680/jgele.17.00104 · 2018 · External reference
A low-cost approach for soil moisture prediction using multi-sensor data and machine learning algorithm
10.1016/j.scitotenv.2022.155066 · 2022 · External reference
Evapotranspiration estimation with small UAVs in precision agriculture
10.3390/s20226427 · 2020 · External reference
Advancing Soil Erosion Mapping in Active Agricultural Lands Using Machine Learning and SHAP Analysis
2025 · External reference
Crop type classification using fusion of Sentinel-1 and Sentinel-2 data: assessing the impact of feature selection, optical data availability, and parcel sizes on the accuracies
10.3390/rs12172779 · 2020 · External reference
Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach
2021 · External reference
Deep learning for monitoring agricultural drought in south asia using remote sensing data
10.3390/rs13091715 · 2021 · External reference
Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index
10.3390/s8063744 · 2008 · External reference
A modified soil adjusted vegetation index
10.1016/0034-4257(94)90134-1 · 1994 · External reference
Optimization of soil-adjusted vegetation indices
10.1016/0034-4257(95)00186-7 · 1996 · External reference
Incorporating environmental variables into a MODIS-based crop yield estimation method for United States corn and soybeans through the use of a random forest regression algorithm
10.1016/j.isprsjprs.2019.12.012 · 2020 · External reference
Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
10.1016/s0034-4257(02)00010-x · 2002 · External reference
Legume nitrogen fixation and drought
10.1038/378344a0 · 1995 · External reference
Applications of remote sensing in precision agriculture: a review
10.3390/rs12193136 · 2020 · External reference
Unresolved reference
1999 · External reference
Aerial color infrared photography for determining early in-season nitrogen requirements in corn
10.2134/agronj2005.0200 · 2006 · External reference
Interpretable deep learning framework for land use and land cover classification in remote sensing using SHAP
10.1109/lgrs.2023.3251652 · 2023 · External reference
Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV
10.1016/j.compag.2014.02.009 · 2014 · External reference
Red and photographic infrared linear combinations for monitoring vegetation
10.1016/0034-4257(79)90013-0 · 1979 · External reference
Bias in error estimation when using cross-validation for model selection
10.1186/1471-2105-7-91 · 2006 · External reference
Prediction of sugar beet yield and quality parameters using Stacked-LSTM model with pre-harvest UAV time series data and meteorological factors
2025 · External reference
Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt
10.1088/1748-9326/ab68ac · 2020 · External reference
Inversion of farmland soil moisture based on multi-band synthetic aperture radar data and optical data
10.3390/rs16132296 · 2024 · External reference
Cross-scale soil moisture content monitoring of winter wheat by integrating UAV and sentinel-1/2 data
10.1016/j.agwat.2025.109831 · 2025 · External reference
Remote sensing-based analysis of yield and water-fertilizer use efficiency in winter wheat management
10.1016/j.agwat.2025.109390 · 2025 · External reference
Multi-layer grid-scale soil moisture estimation using spatiotemporal deep learning methods with physical constraints
10.1016/j.jhydrol.2025.133086 · 2025 · External reference
Evaluating soil moisture content under maize coverage using UAV multimodal data by machine learning algorithms
10.1016/j.jhydrol.2023.129086 · 2023 · External reference
Soil properties: their prediction and feature extraction from the LUCAS spectral library using deep convolutional neural networks
10.1016/j.geoderma.2021.115366 · 2021 · External reference
Classification of soybean leaf wilting due to drought stress using UAV-based imagery
10.1016/j.compag.2020.105576 · 2020 · External reference
Developing a fused vegetation temperature condition index for drought monitoring at field scales using Sentinel-2 and MODIS imagery
10.1016/j.compag.2019.105144 · 2020 · External reference
