Hasil untuk "Maps"

Berthold K. P. Horn

J. Tam

J. Mandhane, G. Gregory, K. Aziz

M. Andrade, P. Chacón, J. Merelo et al.

H. Zebker, R. Goldstein

W. Gangbo, R. McCann

R. Mãné

M. Causse, Theresa, M. et al.

H. Small

S. Thrun, Wolfram Burgard, D. Fox

D. Lehmann, H. Ozaki, I. Pal

John D. Marco LaDeana Robert H. Asif John Mandeep Krist McPherson Marra Hillier Waterston Chinwalla Wallis, John D. Marco LaDeana Robert H. Asif John Mandeep Krist McPherson Marra Hillier Waterston Chinwalla Wallis, J. McPherson et al.

T. Hudson, Lincoln Stein, Sebastian S. Gerety et al.

S. Thrun, Yufeng Liu, D. Koller et al.

R. Touzi, A. Lopes, J. Bruniquel et al.

J. Pickles

Zhaoping Li

C. V. van Westen, N. Rengers, R. Soeters

Jakub Talaga, Pawel Netzel, Dominika Cywicka

Forest tree species diversity plays a critical role in maintaining ecosystem resilience and function. However, large-scale assessments remain challenging due to the limitations of field-based and supervised remote sensing methods, which require costly training data and species-level labeling. In this study, we propose an unsupervised approach to estimating tree species diversity based solely on satellite imagery (Sentinel-2 or Landsat-8) acquired during the 2019 growing season. The method integrates vegetation indices (GNDVI, EVI, NDMI), self-organizing maps, and spectral clustering to derive the evenness index without the need for species classification. Validation against field data from over 10 000 hexagonal grid cells (10 square kilometers each) across Poland shows strong agreement, with Pearson&#x2019;s <italic>r</italic> &#x003D; 0.87 (Sentinel-2, <inline-formula><tex-math notation="LaTeX">$R^{2}$</tex-math></inline-formula> &#x003D; 0.75) and <italic>r</italic> &#x003D; 0.81 (Landsat-8, <inline-formula><tex-math notation="LaTeX">$R^{2}$</tex-math></inline-formula> &#x003D; 0.66). Because the approach does not require ground-based training data, it can be directly integrated into operational forest monitoring frameworks, including national forest inventory programs. This scalable, label-free method enables the repeatable monitoring of tree species diversity at national and continental scales.

K.A. Marwa , H.A. Ali , S.A. Farah et al.

In order to develop coatings to optimize the functioning of the solar panels, this study examines how laser energy affects the morphology, size, and optical properties of gallium oxide (Ga2O3) nanoparticles prepared through the use of pulsed laser deposition. The precursor powder is pressed into small particles, which are referred to as Ga2O3 pellets, and the thin films are deposited on the glass substrates prepared with extreme care onto the glass surface using Nd : YAG laser pulses. The nanoparticles preferred crystallographic orientation and phase composition is determined by using X-ray diffraction analysis. Ultraviolet visible spectroscopy is then applied to determine their transmittance, absorbance and optical band-gap. Fringes of optical interference are measured to arrive at the thicknesses of the films and a double-beam spectrophotometer gives the correct values of the optical constants. The topography is analyzed using atomic force microscopy and more specific height maps are created to assess the dispersion and homogeneity of grains - between which is vital in the obtaining of a homogenous light absorption and low scale of reflectance. It is observed in the experimental findings that a strong preferential orientation exists along the (111) plane, and that there are monoclinic crystal structures which develop in the films. The intensity of diffraction peaks is enhanced by increasing the energy of deposition. At the same time, a growth in the thickness of the film increases internal forces and simultaneously decreases the size of crystallites. High transmittance and low absorption in the ultraviolet region are indicated by optical measurements, and the band-gap is becoming narrower with thickness, with direct-band-gap semiconductor behaviour. In general, the research provides an explanation of the morphology, structure, and optical characteristics of the Ga2O3 nanoparticles, which are essential materials to understand how to create the best possible coating on solar panels in order to improve their energy-converting efficiency and service life.