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Time series analysis of major land resources using Landsat images in a part of district Jhansi, Uttar Pradesh, India
41-57Views:22Space born technology, with its repetitive nature, uses electromagnetic energy to capture digital data from the Earth's surface by remote sensing systems. The purpose of this research is to track changes in land resources with six time series (2003-09, 2003-15, 2003-21, 2009-15, 2009-21 and 2015-21) over a period of 18 years. Multi-date Landsat images of 2003, 2009, 2015 and 2021 have been used to monitor the changing pattern. Level – I classification scheme composed by NRSC/ ISRO and supervised Maximum Likelihood Classification (MLC) techniques were used to identify and classify land use/ land cover features located in Jhansi Tehsil. The findings show that there have been significant changes in land resources over the years. The area under agriculture land, built-up and waterbodies were increased by 48.83%, 53.53% and 106.73% while forest/ tree outside forest and wastelands were reduced by 59.74% and 38.68% respectively It is concluded that, the expansion of key land resources indicates the growth in population and socio-economic activities whereas the loss in some land resources might be due to human induced progressive activities.
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Accuracy assessment of different soil databases concerning WRB reference soil groups
1-12Views:208As a result of international cooperation, the conditions of data access and data usage have been significantly improved during the last two decades. Also, the establishment of web-based geoinformatic infrastructure allowed researchers to share their results with the scientific community more efficiently on the international level. The aim of this study is to investigate the accuracy of databases with different spatial resolutions, using the reference profiles of LUCAS topsoil database. In our study, we investigated the accuracy of World Reference Base for Soil Resources (WRB) Reference Soil Groups (RSG) groups stored in freely accessible soil databases (European Soil Database (ESDB), International Soil Reference and Information Centre (ISRIC)) in Hungary. The study concluded that the continental scale database tends to be more accurate. We used the Kappa Index of Agreement (KIA) statistical index to evaluate accuracy. The European and the international databases showed a value of 0.9643 and 0.3968, respectively. Considering the results, we can conclude that the spatial resolution has a relevant impact on the accuracy of databases, however, the study should be extended to the national level and the indices should be assessed together.
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Interferences between the ecological network and urbanized areas in Poland
65-77Views:37This paper presents spatial relations between Polish urban areas and valuable habitats and links between them composing the country’s ecological network. The quantitative analysis for 891 towns and cities was conducted using GIS techniques based on cartographic vector data and statistical data. Valuable habitats and links between them, such as national parks, landscape parks, CORINE biotopes sites, wildlife corridors linking NATURA 2000 sites and ECONET areas, can be found in 72% of Polish towns and cities. The proportion of artificial surfaces in those areas is different depending on the size of a town or city and its location. Urban areas with the highest index of presence of valuable habitats and links between them are concentrated in the south of Poland, where settlement network is most dense. However, in the case of those areas the proportion of artificial surfaces interfering with the ecological network is lower than Poland’s average, being 16%. The pressure of anthropogenic land cover extending onto the country’s ecological network is most conspicuous in urban areas with a population of at least several dozen thousand residents where the average developed area is 20.8% of their total area. The danger for the continuity of the nature system is best seen in the north western Poland, where artificial surfaces interference in towns and cities is largest. The analysis performed identified 82 towns and cities, in which the preservation of the continuity of the ecological network should be a priority in spatial management because of a higher than average index of the presence of valuable habitats and links between them and large proportion of artificial surfaces in those areas.
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Sentinel-2 satellite-based analysis of bark beetle damage in Sopron Mountains, Hungary
33-40Views:31Sopron mountains were affected by bark beetle (Ips typographus) damage between 2017 and 2020, which was surveyed on high-resolution ESA Sentinel-2 satellite images for the period 2017 and 2020 using Mosaic Hub, Anaconda, and Jupyter Notebook web-based computing environments. Biotic forest damage was detected based on vegetation (NDVI) and moisture (MSI, NDWI) indices derived from satellite images. The spatial and temporal change of damage was observed in the image series, resulting in information about the level of degradation and regeneration. In pursuance of GIS processing, 84 forest compartments were compared, which showed in most of the cases (97%) negative interannual change in the index mean values (MSI = - 0.14, NDWI = - 0.2, NDVI= - 0.19) when years compared to each other. The remote sensing-based survey was marked out and validated based on the forest database of the Hungarian Division of Forest of National Land Centre and forest protection damage reports of the Hungarian National Forest Damage Registration System.
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Prediction of industrial land use using linear regression and mola techniques: A Case Study of Siltara Industrial belt
59-70Views:270The Siltara Industrial belt is an important industrial pocket of Chattisgarh state located in the northern part of the Raipur city, which is rapidly growing. In this process spatial, cultural, political and administrative factors are controlling its rate, direction and pattern. The Simple Linear Regression (SLR) and Multi-Objective Land Allocation (MOLA) techniques, which are embedded in SPSS and Idrisi Kilimanjaro software respectively, and have been used for the estimation of future scenario of the industrial growth. In this model, a suitable platform has been prepared in which future industrialization has been estimated by integrating physical, social, cultural factors and land acquisition policy. In this article, results have revealed that industrialization has occurred very fast during last one decade. The industrial land was 6.15 km2 in 2001 and 18.725 km2 in 2011 and estimated as 31.30 km2 in 2021 and 43.87 km2 in 2031 using SLR. The rapid industrial growth is very critical issues for agrarian society and fresh environment. This model very accurately estimating (overall accuracy=95.39%, Kno=97.24%, agreement=98.63 %) the future growth of industrial land. This work will be useful to the planners and policy makers of private and government sectors to regulate the sustainable planning practices and smart decision-making.
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Connection between the potential wind energy and the windy days
6-24Views:36Preliminary wind climate information are required for the selection of the sites of energetic wind measurements. Optimal locations of wind energy projects, where the amount of utilizable wind energy can be forecasted with a good approach, can be determined using GIS and statistical methods. Anyhow, it is necessary to elaborate methods what make posible to gain data for the wind potential of a given location on the base of measured data. Monthly number of windy days can be such predictor if its basic statistical parameters and its connection to the monthly mean wind power can be determined. This latter one can be substituted by the area under the curve of the function fitted to the hourly averages of the cubes of the wind speeds. A regression modell is fitted to the monthly number of windy days and areas under the curve, on the base of time series of 7 Hungarian weather stations and the error of the modell is determined. On this base, the modell is extrapolated to a 35 years long period. The area under the curve proportional to the monthly mean wind power calculated on the base of the monthly number of windy days show a significant decreasing trend in 4 Hungarian weather stations.