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Analysis of multitemporal aerial images for fenyőfő Forest change detection
89-100Views:310This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.
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A remote sensing and GIS-based analysis on the impact of dam construction towards the land use land cover pattern of Bakreswar Watershed, India
25-42Views:172The present study evaluates the impact of the dam construction on land use and land cover (LULC) pattern of the Bakreswar Watershed in the Birbhum District, West Bengal, India during 1990-2020. Landsat 5 TM and Landsat 8 OLI data were used to analyze the LULC pattern during the pre- and post-dam construction periods. Supervised image classification using the maximum likelihood algorithm was done to generate LULC and change detection maps in ArcGIS. LULC dynamic attitude and transfer matrix were prepared based on the LULC maps of four years. The results show that the dam construction significantly influenced the LULC pattern of the region. The highest rate of increase is seen in waterbody (86.37%) during 1990–2000 due to dam construction. Cultivated land also increased by 12.31% during this period. After the dam construction, the conversion rate from fallow land to cultivated land is higher in the downstream area rather than the upstream area. The area under barren land decreased by 53.28% in 1990–2000 and by 41.23% during 2009–2020 due to its conversion to built-up area. The built-up area rapidly increased during the past 20 years, by 34.57% and 45% during 1990–2000 and 2009-2020, respectively. Major change is seen along the Panagarh–Morgram Highway which connects two urban centers, Suri and Dubrajpur. Settlement concentration is also high around the Bakreswar Thermal Power Plant (BkTPP) and BkTPP Township. This study provides a useful approach to understanding the impacts of dam construction on cultivated area change and how transportation facility influences urban agglomeration.
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Coastal landuse land cover change and transformations in-between Cuddalore and Nagore, south east coast of India using remote sensing and GIS
11-24Views:146This study was conducted to assess the Land use and land cover (LULC) changes in a dynamic coastal zone; this is also an essential factor of studying the relationships between the human activity and coastal environment. The study region has been suffered from various natural hazards such as cyclone impacts, coastal erosion and rarely tsunamis. LULC changes was studied and reported for the period of 4 decades from 1980 to 2020. The overall accuracy assessment and Kappa coefficient values shows the substantial results of LULC maps. In the study area LULC changes has been classified in the six classes. The result shows reduction in plantations, coastal wetland and fallow land. Whereas improvement found in barren land, built-up land and water body of the study area from 1980 to 2020. Immediate attention is required to the increase the mangrove forest to be as a natural protection from the calamities in coastal wetlands. The information resulting from this study can be used in forthcoming management plans for urbanization and towards the sustainable development of the region. This study can be adapted to the world’s any coastal region to establish a strategic plan of action to protect the coastal communities and the environment.
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Land use change detection along the Pravara River basin in Maharashtra, using remote sensing and GIS techniques
71-86Views:205In the past few decades there has been an increasing pressure of population all over the world, especially in India, resulting in the utilization of every available patch of available land from woodlands to badlands. The study area represents a basin which is economically growing fast by converting the fallow lands, badlands and woodlands to agricultural land for the past few decades. IRS (Indian Remote sensing Satellites) 1 C – LISS III and IRS 1 C PAN and IRS P6 – LISS III and IRS 1 D PAN Images were merged to generate imageries with resolution matching to the landscape processes operating in the area. The images of the year 1997, 2000, 2004 and 2007 were analyzed to detect the changes in the landuse and landcover in the past ten years. The analysis reveals that there has been 20% increase in the agricultural area over the past ten years. Built up area also has increased from 1.35% to 6.36% of the area and dense vegetation also has marginally increased. The remarkable increase in the agricultural area occurs owing to the reclaim of the natural ravines and fallow lands. Presently the area looks promising, but it is necessary to understand the sedimentological and geomorphological characteristics of the area before massive invasion on any such landscapes because the benefit may be short lived.
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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:359The 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.