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Land cover analysis based on descriptive statistics of Sentinel-2 time series data
1-9Views:586In our paper we examined the opportunities of a classification based on descriptive statistics of NDVI throughout a year’s time series dataset. We used NDVI layers derived from cloud-free Sentinel-2 images in 2018. The NDVI layers were processed by object-based image analysis and classified into 5 classes, in accordance with Corine Land Cover (CLC) nomenclature. The result of classification had a 76.2% overall accuracy. We described the reasons for the disagreement in case of the most remarkable errors.
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Evaluation of the possibilities for stream restoration: preassessment of the Váli-stream (Hungary)
26-44Views:423The purpose of this study is to evaluate the potential of restoration of a stream section. The starting point of the multiple-step assessment process was a historical analysis, which resulted in the definition of different sections within the study area, providing a base for the further restoration goals. The assessment of the current conditions was elaborated particularly to determine those factors, which could limit restoration. These assessments cover the land use pattern, furthermore the analysis of vegetation and habitat patches. As a result of the historical analysis, it has been found that the stream side habitat patches have decreased significantly despite the constant space available. This change was not caused by the increased area of the settlement, but rather by the higher dominancy of arable forms of land use. The greatest share of wet and mesic meadows and agricultural habitats in the study areas, covering 57.5% of the total area, indicates significant anthropogenic effects. Consequently it can be stated that the reference conditions are not the only determining factors of the restoration possibilities. Restoration style and intensity have been defined on basis of all assessed factors.
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Landscape shape index, as a potencial indicator of urban development in Hungary
78-88Views:626The study of settlement shape, morphology and structure is a classic topic of urban geography. Since the 1960s multiple shape indices have been developed. Urban patterns were then compared with geometric forms or, alternatively their temporal changes were tracked and analysed. In the current study we adapted the landscape shape index (LSI) to analyse the historical shape development of eight Hungarian cities. The LSI is capable to demonstrate the functional and mutual relationship between the developed area and their immediate physical and natural environment. Over the past 230 years the land area of the studied cities has increased manifold for several reasons: on average, an areal increase of 10.4 to 24.5 was observed for the eight settlements, while their perimeter increased by 8.8 to 30.3 times. Simultaneously with their size growth, the studied cities are characterized by an increasingly fragmented and dissected ground plans. Consequently, due to the longer border between the developed areas and the adjacent natural zones, urban areas have become increasingly sensitive to environmental effects over the past century, while mutual ecological and environmental interactions has also considerably increased between the adjoining zones. In general, cities of hilly and low-mountain areas had the highest LSIs, whereas cities located on relatively flat grounds had comparatively low LSIs. We also investigated the rank correlation of the historical change of LSI of the studied settlements. Cities of high positive correlations (> 0.9) were classified into two major categories. Miskolc, Pécs, Szeged and Kecskemét belonged to the group of higher LSIs, whereas Székesfehérvár and Nyíregyháza fell into the class of medium LSIs and the third category included Debrecen and Győr, cities of low (< 0.9) LSIs. Based on the temporal trends of the LSIs, our results provide applicable information for decision makers in order to monitor, manage and track their investments, city management policies and infrastructural development strategies.
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Correction of Atmospheric Haze of IRS-1C LISS-III Multispectral Satellite Imagery: An Empirical and Semi-Empirical Based Approach
63-74Views:538The atmospheric effect greatly affects the quality of satellite data and mostly found in the polluted urban area in the great extent. In this paper, the atmospheric correction has been carried out on IRS-1C LISS-III multispectral satellite image for efficient results for the Raipur city, India. The atmospheric conditions during satellite data acquisition was very clear hence very clear relative scattering model of improved dark object subtraction method for the correction of atmospheric effects in the data has been carried out to produce the realistic results. The haze values (HV) for green band (band 2), red band (band 3), NIR band (band 4) and SWIR (band 5) are 79, 53, 54 and 124, respectively; were used for the corrections of haze effects using simple dark object subtraction method (SDOS). But the final predicted haze value (FPHV) for these bands are 79, 49.85, 21.31 and 0.13 that were used for the corrections of haze effects applying improved dark object subtraction method (IDOS). We found that IDOS method produces very realistic results when compared with SDOS method for urban land use mapping and change detection analysis. Consequently, ATCOR2 model provides better results when compared with SDOS and IDOS in the study.
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Above ground forest biomass distribution in the landscape of Jorhat, Assam, India
16-31Views:46This study aims to analyze the spatial and temporal variations in above-ground biomass (AGB) within the Jorhat region from 2001 to 2023. It also highlights the impacts of urbanization, physiographic characteristics, and soil types on AGB variation. In order to accurately assess landscape-level variation of biomass, a combination of field surveys, remote sensing techniques, and modelling approaches are employed in this study. Biomass estimation is difficult over large area using traditional method. The synoptic nature of satellite-based data improves the monitoring of inaccessible areas. Results show approximately 16.6% decrease in AGB, with urban and peripheral areas experiencing the most notable declines due to reduced forest cover. Physiographic analysis reveals low AGB values in marshes (13 t/ha), swamps (14 t/ha), and char lands (25 t/ha). The growth of trees is suppressed seasonal flooding in this physiography. Additionally, AGB follows an increasing trend from North to South, in alignment with the region’s elevation profile. Soils also exhibit variations in AGB, with alluvial soils supporting higher biomass compared to other soil types. Key ecological linkages and spatial patterns are highlighted in this study, laying the groundwork for more proactive and comprehensive environmental management. Finally, in a time of fast environmental change, these insights can assist stakeholders and policymakers
in creating more evidence-based, flexible solutions to protect ecosystems.