Leaf and canopy nitrogen (N) status relates strongly to leaf and canopy chlorophyll (Chl) content. Remote sensing is a tool that has the potential to assess N content at leaf, plant, field, regional and global scales. In this study, remote sensing techniques were applied to estimate N and Chl contents of irrigated maize (Zea mays L.) fertilized at five N rates. Leaf N and Chl contents were dete...

Developments in hyperspectral remote sensing techniques during the last decade have enabled the use of narrowband indices to evaluate the role of forest ecosystem variables in estimating carbon (C) fluxes. In this study, narrowband bio-indicators derived from EO1 Hyperion data were investigated to determine whether they could capture the temporal variation and estimate the spatial variability o...

Accurate, precise, and timely estimation of crop yield is key to a grower’s ability proactively manage growth predict harvest logistics. Such predictions typically are based on multi-parametric models in-situ sampling. Here we investigate the extension greenhouse study, low-altitude unmanned aerial systems (UAS). Our principal objective was snap bean (Phaseolus vulgaris) using imaging spectrosc...

Even though research has shown that the spectral parameters of yellow-edge, red-edge and NIR (near-infrared) shoulder wavelength regions are able to estimate green cover leaf area index (LAI), a large amount dead materials in grasslands challenges accuracy their estimation using hyperspectral remote sensing. However, exact impact vegetation on these remains unclear. Therefore, we evaluated infl...

In this study, rice land designated for agricultural suitability indices belonging to the enterprise Yeşil Küre Farm Land with different time series Sentinel-2A satellite images calculated utilizing spectral vegetation index, which are Normalized Difference Vegetation Index and Red Edge Optimized Soil Adjusted values by statistical comparison of relationship between monitoring estimation potent...

Forest ecosystems are among the largest terrestrial carbon reservoirs on our planet earth thus playing a vital role in global carbon cycle. Presently, remote sensing techniques provide proper estimates of forest biomass and quantify carbon stocks. The present study has explored Landsat-8 sensor product and evaluated its application in biomass mapping and estimation. The specific objectives were...

This study demonstrates the applicability of visible-near infrared and thermal imaging for detection of Huanglongbing (HLB) disease in citrus trees. Visible-near infrared (440-900 nm) and thermal infrared spectral reflectance data were collected from individual healthy and HLB-infected trees. Data analysis revealed that the average reflectance values of the healthy trees in the visible region w...

Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgoru...

This study presents a method for quantitatively estimating leaf area index (LAI) in winter wheat by exploring bi-directional reflectance distribution function (BRDF) data. In BRDF data, near-infrared reflectance (NIR) which is sensitive to crown component, canopy cover and crown shape, is affected by illuminated crown component, while red reflectance is sensitive to canopy gaps and controlled b...