Comparison of various pan-sharpening methods using Quickbird-2 and Landsat-8 imagery

Pan-sharpening is the process of transferring the spatial resolution of panchromatic (PAN) image to a multispectral (MS) image for producing a single image with high spatial detail and rich spectral information. In this study, PAN and MS imagery of Quickbird-2 and Landsat-8 are fused separately, using ten different pan-sharpening methods such as principal component analysis (PCA), modified-intensity hue saturation (M-IHS), multiplicative, brovey transform (BT), wavelet-principal component analysis (W-PCA), hyperspectral color space (HCS), high-pass filter (HPF), Gram-Schmidt (GS), Fuze Go, and non-subsampled contourlet transform (NSCT). The effectiveness of these techniques is assessed and compared by qualitative analysis and 14 quantitative analysis methods including bias, correlation coefficient (CC), difference in variance (DIV), relative dimensionless global error in synthesis (ERGAS), universal image quality index (Q), relative average spectral error (RASE), root mean square error (RMSE), structural similarity index method (SSIM), signal-to-noise ratio (SNR), peak SNR (PSNR), spatial correlation coefficient (SCC), image entropy (E), and gradient and quality with no reference image (QNR). The results of both analysis types show that the Fuze Go and NSCT produced the best fused image with high spatial detail and rich spectral information followed by the HPF and GS.     

Spatiotemporal estimation of hourly 2-km ground-level ozone over China based on Himawari-8 using a self-adaptive geospatially local model

Ground-level ozone(O₃)is a primary air pollutant,which can greatly harm human health and ecosystems.At present,data fusion frameworks only provided ground-level O₃ concentrations at coarse spatial(e.g.,10 km)or temporal(e.g.,daily)resolutions.As photochemical pollution continues increasing over China in the last few years,a high-spatial–temporal-resolution product is required to enhance the comprehension of ground-level O₃ formation mechanisms.To address this issue,our study creatively explores a brand-new framework for estimating hourly 2-km ground-level O₃ concentrations across China(except Xinjiang and Tibet)using the brightness temperature at multiple thermal infrared bands.Considering the spatial heterogeneity of ground-level O₃,a novel Self-adaptive Geospatially Local scheme based on Categorical boosting(SGLboost)is developed to train the estimation models.Validation results show that SGLboost performs well in the study area,with the R2 s/RMSEs of 0.85/19.041 lg/m³ and 0.72/25.112 lg/m³ for the space-based cross-validation(CV)(2017–2019)and historical space-based CV(2019),respectively.Meanwhile,SGLboost achieves distinctly better metrics than those of some widely used machine learning methods,such as e Xtreme Gradient boosting and Random Forest.Compared to recent related works over China,the performance of SGLboost is also more desired.Regarding the spatial distribution,the estimated results present continuous spatial patterns without a significantly partitioned boundary effect.In addition,accurate hourly and seasonal variations of ground-level O₃ concentrations can be observed in the estimated results over the study area.It is believed that the hourly 2-km results estimated by SGLboost will help further understand the formation mechanisms of ground-level O₃ in China.     

Characterization of alluvial bajada facies distribution using TM imagery

Automatic mapping techniques using multiband satellite image information have been used to study sediment grain‐size variations on an alluvial bajada. A previous study of sparsely vegetated alluvial surfaces in central‐western Argentina showed that the reflectivity recorded in seven‐band Landsat TM images is controlled by sediment composition, age and grain size. At diameters >4 mm, clast composition influences image information, while at grain sizes smaller than sand, clay mineralogy begins to influence spectral characteristics. The progressive increase in desert varnish and the loss of fine grain‐size fractions as a result of deflation cause the age influence. The bajada sedimentary environment is well suited for testing the influence of grain‐size variability on image recovery, as most drainage basins are small and sourced by a single geological unit, which produces compositionally homogeneous alluvial surfaces. Additionally, most drainage lines are active within intervals of 10–50 years, reducing the effect of surface ageing. Larger than average drainage basins produce oversized drainage lines that disrupt the bajada, generate individual alluvial fans and have slightly different compositions. Two typical bajadas were selected to map grain‐size characteristics using automatic classification techniques. The obtained classes were checked in the field, and grain‐size and compositional counts were completed. Although both bajadas are very different in composition, most grain‐size curves showed similar shapes, suggesting that deposition took place by the same process (hyperconcentrated flash floods). The values of the median and mean were consistent across the same class between both bajadas. Thus, unsupervised classification techniques are useful for mapping sediment grain size, although minor field control is needed. Image classes represent areas of similar grain size, which are elongated parallel to the mountain front in an active alluvial bajada, indicating a homogeneous distribution of sedimentary processes along strike. Changes in the width of image classes indicate different downstream fining rates closely related to the topographic gap and the slope change rate. In contrast to bajadas, alluvial fans have semi‐circular belts and a pie‐piece‐shaped area in which most active streams are located. Thus, unlike fans, bajadas lack autocyclic mechanisms for producing heterogeneous sedimentary sequences. The sedimentary log of an ancient bajada was measured in order to show the influence of allocyclic factors in the absence of autocyclicity.     

Retrieval of stratospheric O3 and NO2 vertical profiles using zenith scattered light observations

Daily zenith scattered light intensity observations were carried out in the morning twilight hours using home-made UV-visible spectrometer over the tropical station Pune (18‡31′, 73‡51′) for the years 2000–2003. These observations are obtained in the spectral range 462–498 nm for the solar zenith angles (SZAs) varying from 87‡ to 91.5‡. An algorithm has been developed to retrieve vertical profiles of ozone (O₃) and nitrogen dioxide (NO₂) from ground-based measurements using the Chahine iteration method. This retrieval method has been checked using measured and recalculated slant column densities (SCDs) and they are found to be well matching. O₃ and NO₂ vertical profiles have been retrieved using a set of their air mass factors (AMFs) and SCDs measured over a range of 87–91.5‡ SZA during the morning. The vertical profiles obtained by this method are compared with Umkehr profiles and ozonesondes and they are found to be in good agreement. The bulk of the column density is found near layer 20–25 km. Daily total column densities (TCDs) of O₃ and NO₂ along with their stratospheric and tropospheric counterparts are derived using their vertical profiles for the period 2000–2003. The total column, stratospheric column and tropospheric column amounts of both trace gases are found to be maximum in summer and minimum in the winter season. Increasing trend is found in column density of NO₂ in stratospheric, tropospheric and surface layers, but no trend is observed in O₃ columns for above layers during the period 2000–2003     

Measuring daytime CO2 fluxes from the inter-tidal mangrove soils of Indian Sundarbans

The aim of this research was to measure the rate of carbon dioxide (CO₂) exchange between the soil and atmosphere in the inter-tidal forest floor of the Indian Sundarbans mangrove ecosystem and to study its response with soil temperature and soil water content. Soil CO₂ effluxes were monitored every month at two stations (between April, 2011 and March, 2012); one situated at the land–ocean boundary of the Bay of Bengal (outer part of the mangrove forest) and the other lying 55 km inshore from the coast line (inner part of the mangrove forest). The static closed chamber technique was implemented at three inter-tidal positions (landward, seaward and bare mudflats) in each station. Fluxes were measured in the daytime every half an hour by circulating chamber headspace air through a sampling manifold assembly and a closed-path non-dispersive infrared gas analyser. The fluxes ranged between 0.15 and 2.34 μmol m^?2 s^?1 during the annual course of sampling. Effluxes of higher magnitude were measured during summer; however, it abruptly decreased during the monsoon. CO₂ flux from the forest floor was strongly related to soil temperature, with the highest correlation found with temperature at 2 cm depth. No such significant relationship between soil water content and CO₂ efflux could be properly ascertained; however, excessively high soil water content was found to be the only reason which hampered the rate of effluxes during the monsoon. On the whole, landward (LW) sites of the mangrove forest emitted more than the seaward (SW) sites. Q ₁₀ values (obtained from simple exponential model) which denote the multiplicative factor by which the efflux rate increases for a 10 °C rise in temperature ranged between 2.07 and 4.05.     

Investigating the application of pixel-level and product-level image fusion approaches for monitoring surface water changes

The aim of this paper was to investigate the suitability of the pixel-level and product-level image fusion approaches to detect surface water changes. In doing so, firstly, the principal component analysis technique was applied to Landsat TM 2010 multispectral image to generate the PC components. Several pixel-level image fusion techniques were then performed to merge the Landsat ETM+ 2000 panchromatic with the PC1PC2PC3 band combination of Landsat TM 2010 imagery to highlight the surface water changes between the two images. The suitability of the resulting fused images for surface water change detection was evaluated quantitatively and visually. Finally, the support vector machine (SVM) technique was applied to the qualified fused images to map the highlighted changes. Furthermore, a product level fusion (PLF) approach based on various satellite-derived indices was employed to detect the surface water changes between ETM+ 2000 and TM 2010 images. The accuracy of the resulting change maps was assessed based on a reference change map produced using visual interpretation. The results demonstrated the effectiveness of the proposed approaches for surface water change detection, especially using the Gram Schmidt-SVM, PLF-NDWI, and PLF-NDVI methods which improved the accuracy of change detection over 99.70 %.     

The effect of the geomagnetic activity to the hourly variations of ionospheric foF2 values at low latitudes

In this study, the relationship between the hourly changes of the ionospheric critic frequency values of F2 layers in low latitudes and geomagnetic activity is examined by using statistical methods. The ionospheric critical frequency data has been taken from the Manila (121.1° E, 14.7° N) ionosonde station. In order to investigate the effect of sun activity on ionospheric critical frequency, the data of 1981 when the sun was active and of 1985 when the sun was less active has been used. According to the Granger causality test results, on 5 % significance level, a causality relationship from disturbance storm time (Dst) index values to ionospheric critical frequency values direction has been observed. However, a causality relationship from ionospheric critical frequency values to Dst values has not been observed. From the results of cause-and-effect analysis, it is evaluated that the effect of a shockwave occurring in geomagnetic activity on ionospheric critical frequency continues along 72 h, that is, geomagnetic activity has a long-term effect on ionospheric critical frequency. The response of ionospheric critical frequency to geomagnetic activity substantially depends on seasons. This response is more observed especially in equinox period when the sun is active and in winter months. The increase in geomagnetic activity causes ionospheric critical frequency to decrease in night hours and increase in day hours. The same relationship has not been observed exactly, though observed very little in winter months, for 1985 when the sun was less active.     

Retrieval of cloud classification parameters using two-dimensional fast Fourier transform

A method is presented for the retrieval of classification parameters of clouds observed by satellite-borne imaging systems. It is based on a two-dimensional fast Fourier transform of cloud images and an analysis of their power spectra. The parameters retrieved provide quantitative information on mean brightness, size, shape and directional properties of clouds. The efficacy of the subdivision of the original cloud image into smaller regions and the determination of individual parameters is demonstrated by applying this procedure to some NOAA and INSAT cloud images.     

Interpretation of landslide distribution triggered by the 2005 Northern Pakistan earthquake using SPOT 5 imagery

The 2005 northern Pakistan earthquake (magnitude 7.6) of 8 October 2005 occurred in the northwestern part of the Himalayas. We interpreted landslides triggered by the earthquake using black-and-white 2.5-m-resolution System Pour l’Observation de la Terre 5 (SPOT 5) stereo images. As a result, the counts of 2,424 landslides were identified in the study area of 55 by 51 km. About 79% or 1,925 of the landslides were small (less than 0.5 ha in area), whereas 207 of the landslides (about 9%) were large (1 ha and more in area). Judging from our field survey, most of the small landslides are shallow rock falls and slides. However, the resolution and whitish image in the photos prevented interpreting the movement type and geomorphologic features of the landslide sites in detail. It is known that this earthquake took place along preexisting active reverse faults. The landslide distribution was mapped and superimposed on the crustal deformation detected by the environmental satellite/synthetic aperture radar (SAR) data, active faults map, geological map, and shuttle radar topography mission data. The landslide distribution showed the following characteristics: (1) Most of the landslides occurred on the hanging-wall side of the Balakot–Garhi fault; (2) greater than one third of the landslides occurred within 1 km from the active fault; (3) the greatest number of landslides (1,147 counts), landslide density (3.2 counts/km²), and landslide area ratio (2.3 ha/km²) was found within Miocene sandstone and siltstone, Precambrian schist and quartzite, and Eocene and Paleocene limestone and shale, respectively; (4) there was a slight trend that large landslides occurred on vertically convex slopes rather than on concave slopes; furthermore, large landslides occurred on steeper (30° and more) slopes than on gentler slopes; (5) many large landslides occurred on slopes facing S and SW directions, which is consistent with SAR-detected horizontal dominant direction of crustal deformation on the hanging wall.     

Quantitative analysis of the effect of human migration on the landslides after the 2010 Haiti earthquake using Landsat imagery

Natural Hazards - The 2010 Haiti earthquake displaced millions of people and induced numerous landslides. Migrants triggered staggering deforestation since new settlers need wooden resources. This...