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Integrating Airborne Hyperspectral, Topographic, and Soil Data for Estimating Pasture Quality Using Recursive Feature Elimination with Random Forest Regression
Overall, this study showed the potential of airborne hyperspectral data for producing accurate pasture quality maps, which will help farm managers to optimize decisions to improve environmental and economic benefits. Expand
Mapping of macro and micro nutrients of mixed pastures using airborne AisaFENIX hyperspectral imagery
Abstract On-farm assessment of mixed pasture nutrient concentrations is important for animal production and pasture management. Hyperspectral imaging is recognized as a potential tool to quantify theExpand
The use of visible and near‐infrared spectroscopy for the analysis of soil water repellency
Summary This study investigated the potential of visible/near-infrared reflectance spectroscopy (Vis-NIRS) to predict soil water repellency (SWR). The top 40 mm of soils (n = 288) across 48 sitesExpand
Integrating airborne hyperspectral imagery and LiDAR for volcano mapping and monitoring through image classification
It is shown that data fusion of remotely sensed data can be automated to map volcanoes and significantly benefit the understanding of volcanic processes and their hazards. Expand
Assessing the performance of multiple spectral–spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network
From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation. Expand
Proximal sensing techniques to monitor pasture quality and quantity on dairy farms : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Soil
Regular and timely measurements of pasture quality and quantity allow dairy farmers to make effective decisions ensuring an adequate supply of nutrients to animals, efficient utilization of pasture,Expand
Geological Mapping of Hydrothermal Alteration on Volcanoes from Multi-Sensor Platforms
The capacity of available multispectral satellites, high-resolution airborne hyperspectral and LiDAR imagery to provide an improved geological mapping and classification capability for volcanic terrains is explored. Expand
Detecting subtle environmental change: a multi-temporal airborne imaging spectroscopy approach
Airborne and satellite hyperspectral remote sensing is a key technology to observe finite change in ecosystems and environments. The role of such sensors will improve our ability to monitor andExpand
Determining Uncertainty Prediction Map of Copper Concentration in Pasture from Hyperspectral Data Using Qunatile Regression Forest
The results from this study suggest that QRF could provide more accurate and uncertain maps of pasture chemical properties, using a new approach called Quantile Regression Forest (QRF). Expand
Mapping Antimony Concentration over Geothermal Areas Using Hyperspectral and Thermal Remote Sensing
Variable distance isotropic buffers were utilized to extract data from a combination of different spectral images covering Waiotapu Geothermal Field in New Zealand, byrelating them with the antimony concentration of sampled kanuka plants in the Field, through a PLSR (Partial Least Squares Regression). Expand