Imaging from low altitudes is nowadays commonly used in remote sensing and photogrammetry. More and more often, in addition to acquiring images in the visible range, images in other spectral ranges, e.g., near infrared (NIR), are also recorded. During low-altitude photogrammetric studies, small-format images of large coverage along and across the flight route are acquired that provide information about the imaged objects. The novelty presented in this research is the use of the modified method of the dark-object subtraction technique correction with a modified Walthall’s model for correction of images obtained from a low altitude. The basic versions of these models have often been used to radiometric correction of satellite imagery and classic aerial images. However, with the increasing popularity of imaging from low altitude (in particular in the NIR range), it has also become necessary to perform radiometric correction for this type of images. The radiometric correction of images acquired from low altitudes is important from the point of view of eliminating disturbances which might reduce the capabilities of image interpretation. The radiometric correction of images acquired from low altitudes should take into account the influence of the atmosphere but also the geometry of illumination, which is described by the bidirectional reflectance distribution function (BRDF). This paper presents a method of radiometric correction for unmanned aerial vehicle (UAV) NIR images. The study presents a method of low-altitude image acquisition and a fusion of the method of the dark-object subtraction technique correction with a modified Walthall’s model. The proposed solution performs the radiometric correction of images acquired in the NIR range with the root mean square error (RMSE) value not exceeding 10% with respect to the original images. The obtained results confirm that the proposed method will provide effective compensation of radiometric disturbances in UAV images.

The paper presents an enhanced analysis of the Lax-Wendroff difference scheme-up to the eighth-order with respect to time and space derivatives-of the modified-partial differential equation (MDE) of the constant-wind-speed advection equation. The modified equation has been so far derived mainly as a fourth-order equation. The Π-form of the first differential approximation (differential approximation or equivalent equation) derived by expressing the time derivatives in terms of the space derivatives is used for presenting the MDE. The obtained coefficients at higher order derivatives are analyzed for indications of the character of the dissipative and dispersive errors. The authors included a part of the stencil applied for determining the modified differential equation up to the eighth-order of the analyzed modified differential equation for the second-order Lax-Wendroff scheme. Neither the derived coefficients at the space derivatives of order p ∈ (7 -8) in the modified differential equation for the Lax-Wendroff difference scheme nor the results of analyses on the basis of these coefficients of the group velocity, phase shift errors, or dispersive and dissipative features of the scheme have been published. The MDEs for 2 two-step variants of the Lax-Wendroff type difference schemes and the MacCormack This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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AbstractThis paper is a continuation of [38]. The analysis of the modified partial differential equation (MDE) of the constant-wind-speed linear advection equation explicit difference scheme up to the eighth-order derivatives is presented. In this paper the authors focus on the dissipative features of the Beam–Warming scheme. The modified partial differential equation is presented in the so-called Π-form of the first differential approximation. The most important part of this form includes the coefficients μ (p) at the space derivatives. Analysis of these coefficients provides indications of the nature of the dissipative errors. A fragment of the stencil for determining the modified differential equation for the Beam–Warming scheme is included. The derived and presented coefficients μ (p) as well as the analysis of the dissipative features of this scheme on the basis of these coefficients have not been published so far.

Satellite remote sensing technology development induced new capabilities of investigating various atmospheric phenomena and processes. Among the most dangerous and causing the greatest losses are phenomena related with strong convection, e.g. Cumulonimbus development with thunderstorms, hail, downpour, strong turbulence and icing zones, downbursts, squalls or wind shear. Although phenomena related with convection are sometimes limited in space and change rapidly, they develop harsh weather conditions and often endanger life by instantaneous floods, fires of premises and infrastructure caused by lightning, damages to forests and crops due to hurricane winds or hail. Convective clouds and phenomena sometimes cover areas too small to be observed at meteorological stations and reported in standard weather charts due to large distances between the stations. Satellite data provide valuable information for detection of such phenomena. Images acquired by the SEVIRI radiometer from a geostationary orbit and by the MODIS spectroradiometer from a polar orbiting satellite are the main source of data for this research. VIIRS data are also used in the experiment. The sensor, installed on the Suomi NPP, is a new generation of imaging instruments for satellites replacing the NOAA series. The comprehensive analysis concerned interpretation of single channel satellite images and multispectral ones composed of differential images and color compositions of appropriately selected sets of spectral channels. The analyses were also complemented with information derived from dispersion diagrams which enables to assess the internal structure of the clouds, phase of water and cloud particles size, and hence to assess the prevailing processes in the cloud for identifying its development. The developing techniques of combining satellite images compositions with emission, absorption and scattering characteristics of various grounds, aerosols and clouds for identifying objects provide a new quality for hazardous convection monitoring. The methods described in the paper may be successfully used in hazardous weather phenomena warning systems.