This poster presents image processing by ILWIS GIS. It demonstrates changes in land cover types in tundra landscapes (Yamal) since 1988 to 2011. The research method is supervised classification (Minimal Distance) of the Landsat TM scenes. The new approach of the current work is application of ILWIS GIS and RS tools for Arctic, Bovanenkovo region. The poster demonstrates techniques of the remote sensing data processing by ILWIS GIS.
Myanmar is one of the most forested countries in mainland South-east Asia. These forests support a large number of important species and endemics and have great value for global efforts in biodiversity conservation.
Soil Classification Using Image Processing and Modified SVM Classifierijtsrd
Recently the use of soil classification has gained more and more importance and recent direction in research works indicates that image classification of images for soil information is the preferred choice. Various methods for image classification have been developed based on different theories or models. In this study, three of these methods Maximum Likelihood classification MLC , Sub pixel classification SP and Support Vector machine SVM are used to classify a soil image into seven soil classes and the results compared. MLC and SVM are hard classification methods but SP is a soft classification. Hardening of soft classifications for accuracy determination leads to loss of information and the accuracy may not necessary represent the strength of class membership. Therefore, in the comparison of the methods, the top 20 compositions per soil class of the SP were used instead. Results from the classification, indicated that output from SP was generally poor although it performs well with soils such as forest that are homogeneous in character. Of the two hard classifiers, SVM gave a better output than MLC. Priyanka Dewangan | Vaibhav Dedhe "Soil Classification Using Image Processing and Modified SVM Classifier" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18489.pdf
Assessing mangrove deforestation using pixel-based image: a machine learning ...journalBEEI
Mangrove is one of the most productive global forest ecosystems and unique in linking terrestrial and marine environment. This study aims to clarify and understand artificial intelligence (AI) adoption in remote sensing mangrove forests. The performance of machine learning algorithms such as random forest (RF), support vector machine (SVM), decision tree (DT), and object-based nearest neighbors (NN) algorithms were used in this study to automatically classify mangrove forests using orthophotography and applying an object-based approach to examine three features (tree cover loss, above-ground carbon dioxide (CO2) emissions, and above-ground biomass loss). SVM with a radial basis function was used to classify the remainder of the images, resulting in an overall accuracy of 96.83%. Precision and recall reached 93.33 and 96%, respectively. RF performed better than other algorithms where there is no orthophotography.
Paddy field classification with MODIS-terra multi-temporal image transformati...IJECEIAES
This paper presents the paddy field classification model using the approach based on periodic plant life cycle events and how these elevations in climate as well as habitat factors, such as elevation. The data used are MODIS-Terra two tiles of H28v09 and H29v09 of 2016, consist of 46 series of 8-daily data, with 500 meter resolution in Java region. The paddy field classification method based on the phenological model is done by Maximum Likelihood on the transformed annual multi-temporal image of the reflectance data, index data, and the combination of reflectance and index data. The results of the study showed that, with the reference of the Paddy Field Map from the Ministry of Agriculture (MoA), the overall accuracies of the paddy field classification results using the combination of reflectance and index data provide the highest (85.4%) among the reflectance data (83.5%) and index data (81.7%). The accuracy levels were varied; these depend on the slope and the types of paddy fields. Paddy fields on the slopes of 0-2% could be well identified by MODIS-Terra data, whereas it was difficult to identify the paddy fields on the slope >2%. Rain-fed lowland paddy field type has a lower user accuracy than irrigated paddy fields. This study also performed correlation (r2) between the analysis results and the statistical data based on district and provincial boundaries were >0.85 and >0.99 respectively. These correlations were much higher than the previous study results, which reached 0.49-0.65 (hilly-flat areas of county-level), and 0.80-0.88 (hilly-flat areas of provincial level) for China, and reached 0.44 for Indonesia.
Myanmar is one of the most forested countries in mainland South-east Asia. These forests support a large number of important species and endemics and have great value for global efforts in biodiversity conservation.
Soil Classification Using Image Processing and Modified SVM Classifierijtsrd
Recently the use of soil classification has gained more and more importance and recent direction in research works indicates that image classification of images for soil information is the preferred choice. Various methods for image classification have been developed based on different theories or models. In this study, three of these methods Maximum Likelihood classification MLC , Sub pixel classification SP and Support Vector machine SVM are used to classify a soil image into seven soil classes and the results compared. MLC and SVM are hard classification methods but SP is a soft classification. Hardening of soft classifications for accuracy determination leads to loss of information and the accuracy may not necessary represent the strength of class membership. Therefore, in the comparison of the methods, the top 20 compositions per soil class of the SP were used instead. Results from the classification, indicated that output from SP was generally poor although it performs well with soils such as forest that are homogeneous in character. Of the two hard classifiers, SVM gave a better output than MLC. Priyanka Dewangan | Vaibhav Dedhe "Soil Classification Using Image Processing and Modified SVM Classifier" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18489.pdf
Assessing mangrove deforestation using pixel-based image: a machine learning ...journalBEEI
Mangrove is one of the most productive global forest ecosystems and unique in linking terrestrial and marine environment. This study aims to clarify and understand artificial intelligence (AI) adoption in remote sensing mangrove forests. The performance of machine learning algorithms such as random forest (RF), support vector machine (SVM), decision tree (DT), and object-based nearest neighbors (NN) algorithms were used in this study to automatically classify mangrove forests using orthophotography and applying an object-based approach to examine three features (tree cover loss, above-ground carbon dioxide (CO2) emissions, and above-ground biomass loss). SVM with a radial basis function was used to classify the remainder of the images, resulting in an overall accuracy of 96.83%. Precision and recall reached 93.33 and 96%, respectively. RF performed better than other algorithms where there is no orthophotography.
Paddy field classification with MODIS-terra multi-temporal image transformati...IJECEIAES
This paper presents the paddy field classification model using the approach based on periodic plant life cycle events and how these elevations in climate as well as habitat factors, such as elevation. The data used are MODIS-Terra two tiles of H28v09 and H29v09 of 2016, consist of 46 series of 8-daily data, with 500 meter resolution in Java region. The paddy field classification method based on the phenological model is done by Maximum Likelihood on the transformed annual multi-temporal image of the reflectance data, index data, and the combination of reflectance and index data. The results of the study showed that, with the reference of the Paddy Field Map from the Ministry of Agriculture (MoA), the overall accuracies of the paddy field classification results using the combination of reflectance and index data provide the highest (85.4%) among the reflectance data (83.5%) and index data (81.7%). The accuracy levels were varied; these depend on the slope and the types of paddy fields. Paddy fields on the slopes of 0-2% could be well identified by MODIS-Terra data, whereas it was difficult to identify the paddy fields on the slope >2%. Rain-fed lowland paddy field type has a lower user accuracy than irrigated paddy fields. This study also performed correlation (r2) between the analysis results and the statistical data based on district and provincial boundaries were >0.85 and >0.99 respectively. These correlations were much higher than the previous study results, which reached 0.49-0.65 (hilly-flat areas of county-level), and 0.80-0.88 (hilly-flat areas of provincial level) for China, and reached 0.44 for Indonesia.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
Carbon Stocks Estimation in South East Sulawesi Tropical Forest, Indonesia, u...ijceronline
This paper was aimed to estimate carbon stocks in South East Sulawesi tropical forest, Indonesia, using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR). Two coherence Synthetic Aperture Radar (SAR) images of ALOS PALSAR full-polarimetric were used in this research. The research method is forming Random Volume over Ground (RVoG) model from interferometric phase coherence of two Full-Polarimetric ALOS PALSAR which temporal baseline is 46 days. Due to temporal decorrelation, coherence optimization was conducted to produce image with optimum coherences. The result showed that the RVoG forest height and carbon stocks which obtained from height inversion has a positive correlation with ground measurement.
Innovations in the Geoscience Research: Classification of the Landsat TM Imag...Universität Salzburg
Current research presents application of the ILWIS GIS for satellite image processing and classification aimed at land cover types mapping. Two images were classified and analysed. Changes in land cover types were detected for the time 1988 - 2011. The study area covers selected example regions of North Russia. Supervised classification of the raster imagery aims at recognizing of the class membership for each pixel during image analysis. The results demonstrate application of the ILWIS GIS approach of technical processing of the raster images and recognizing classes of the land cover types. The The Minimal Distance Classifier was used as an approach. due to its applicability, logical methodology and precision. The supervised classification of the multi-spectral imagery has been performed using 'Classify' operator in ILWIS GIS applied to Landsat TM 1988, 2001 and 2011. This work has a technical character of GIS applications for remote sensing (RS) data processing. It reports ILWIS GIS approach of the RS data processing Landsat TM satellite image using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described. Presented at the 8th International Conference 'Prospects for the Higher School Development', Grodno State Agrarian University (GGAU) Grodno, Belarus, May 28-29 2015.
Cost-Effective Raster Image Processing for Geoecological Analysis Using “ISOC...Universität Salzburg
Current presentation demonstrates environmental analysis of the landscapes in Estonia, Eastern Europe. Methods include the use of Arc GIS 10.0 and IDRISI GIS Andes 15.0 for image processing. Research aim is o detect land cover changes using method of image classification 'ISOCLUST'. The raster processing GIS approach and classification was applied towards Landsat TM two images. The ISOCLUST is an unsupervised classification method in IDRISI GIS performs the most of the image processing workflow in semi-automatically regime. The study also reports photos of the Estonian landscapes. Results include 16 land cover types typical for the study area classified and visualized on the images. In 2006 the urban area became larger than in 1992 (land cover class "3" on the histogram. This can be explained by various reasons. Changes in land cover types in selected Estonian landscapes are shown on the statistical histograms on 1992 and 2006.
Analysis of Changing Land Use Land Cover in Salinity Affected Coastal RegionIJERA Editor
Anthropogenic activities have induced many changes in land use over a period of three decades in a salinity
affected semi-arid region of coastal Saurashtra in Gujarat. To overcome water scarcity and quality issues, efforts
have been undertaken by state authorities to conserve and effectively use surface water resource to supplement
the irrigation and domestic water requirements. Surface water schemes implemented in the area have altered the
general land use conditions. In the present study, remotely sensed data coupled with ancillary data are used for
analysing the land use-land cover change. Supervised classification and post classification techniques are
employed to classify various land use-land cover classes and to detect changes, respectively. Landscape pattern
change has been studied by analysing the spatial pattern of land use land cover classes structure. The results
show that the region has experienced significant changes over a thirty year period. Growth in agricultural
activities, policies developed to conserve freshwater runoff, and increase in built-up area, are the main driving
forces behind these changes
American Research Journal of Humanities & Social Science (ARJHSS) is a double blind peer reviewed, open access journal published by (ARJHSS).
The main objective of ARJHSS is to provide an intellectual platform for the international scholars. ARJHSS aims to promote interdisciplinary studies in Humanities & Social Science and become the leading journal in Humanities & Social Science in the world.
Comparing of Land Change Modeler and Geomod Modeling for the Assessment of De...IJAEMSJORNAL
The forest destruction, climate change and global warming can reduce an indirect forest benefit because forest is the largest carbon sink and it plays a very important role in global carbon cycle. To support reducing emissions from deforestation and forest degradation (REDD+) program, there is a need to understand the characteristics of existing Land Use/Cover Change (LUCC) modules. The aims of this study are 1) to calculate the rate of deforestation at Poso Regency; and 2) to compare the performance of LCM and GM for simulating baseline deforestation of multiple transitions based on model structure and predictive accuracy. The data used in this study are : 1) Indonesia tophographic map scale 1; 50.000, produced by Geospatial Information Agency (BIG), 2) Landcover maps (1990, 2000, and 2011) which were collected from the Director General of Forestry Planning, Ministry of Environment and Forestry. Meanwhile independent variables (environmental variables) such as : distance from the edge of the forest, the distance from roads, the distance from streams, the distance from settlement, elevation and slope. Landcover changes analysis was assessed by using Idrisi Terrset software and Geomod software. Landcover maps from 1990 and 2000 were used to simulate land-cover of 2011. The resulting maps were compared with an observed land-cover map of 2011. The predictive accuracy of multiple transition modeling was calculated by using Relative Operating Characteristics (ROC). The results show that the deforestation on the period of 1990-2011 reached 19,944 ha (3.55 %) or the rate of deforestation 949 ha year1. Based on the model structure and predictive accuracy comparisons, the LCM was more suitable than the GM for the asssement of deforestation.
Land Use / Land Cover Classification of kanniykumari Coast, Tamilnadu, India....IJERA Editor
The land use/ land cover details of Kanniyakuamri coast which is Located in the southern part of Tamil Nadu (India) is studied. Satellite imagery is used to identify the Land use/ Land cover status of the study area. The software like ERDAS and Arc GIS are used to demarcate the land use / Land cover features of Kanniyakuamari coast. Remote sensing and GIS provided consistent and accurate base line information than many of the conventional surveys employed for such a task. The total area of Kanniyakumari coast is 715 sq.km. The land use / land cover classes of the study area has been categorized into thirteen such as Plantation, Sandy area, Water logged area, Scrub forest, Crop Land, Water bodies, Land with scrub, Reserve forest, Land without Scrub, Salt area, Beach Ridge, Settlement and Fallow land on the basis NRSA Classifications. Among these categories, land with scrub land is predominantly found all over the study area, It is occupied about 336.36 sq.km (44.61 percent), Crop Land 273.82 sq.km(38.29 percent), water bodies lands sharing about 20.44 sq.km (2.85 percent ), settlement occupied with 6.96 sq.km (0.97 percent), and Fallow land was occupied 13.98 sq.km ( 1.95 percent ).
Classification Sensing Image of Remote Using Landsat 8 through Unsupervised C...IJAEMSJORNAL
Bangkalan regency is classified as a new regency which is located East Java, Indonesia. This regency possesses several potential areas in agriculture, plantation, and fishery. This research employs image analysis process of remote sensing satellite Landsat 8 in Bangkalan regency. This research uses Landsat 8 satellite image processing method from image data collection stage to classification stage by using unsupervised classification technique. This method produces land appearance, such as agriculture, ponds, and settlements in Bangkalan regency. This research classification result can be used as a reference of vegetation coverage in Bangkalan regency. Based on the research result, rice field vegetation is very dominant compared to other areas in Bangkalan Regency. Rice field vegetation coverage is much more dominant than other coverage such as residential area. The main objective of this study is to obtain the scale of comparison or area percentage in Bangkalan.
Recent Study on National Deforestation Estimate CIFOR-ICRAF
This roundtable discussion, first delivered in Jakarta, shares research into Indonesia's national deforestation estimate, with the objective of sharing approaches and ultimately improve the reliability of the estimate.
Risks of Cryogenic Landslide Hazards and Their Impact on Ecosystems in Cold E...Universität Salzburg
Research focuses on monitoring landscapes downgrading in specific conditions of Arctic ecosystems with cold climate conditions (marshes, permafrost, high humidity and moisture). Specific case study: cryogenic landslides typical for cold environments with permafrost. Area: Yamal Peninsula. Aim: analysis of the environmental changes caused by cryogenic landslides in northern land- scapes affecting sensitive Arctic ecosystems. Thaw of the permafrost layer causes destruction of the ground soil layer and activates cryogenic landslide processes. After disaster, vegetation coverage needs a long time to recover, due to the sensitivity of the specific northern environment, and land cover types change. ILWIS GIS was used to process 2 satellite images Landsat TM taken at 1988 and 2011, to assess spatiotemporal changes in the land cover types. Research shown ILWIS GIS based spatial analysis for environmental mapping.
Application of remote sensing in forest ecosystemaliya nasir
Established remote sensing systems provide opportunities to develop and apply new measurements of ecosystem function across landscapes, regions and continents.
New efforts to predict the consequences of ecosystem function change, both natural and human- induced, on the regional and global distributions and abundances of species should be a high research priority
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
Carbon Stocks Estimation in South East Sulawesi Tropical Forest, Indonesia, u...ijceronline
This paper was aimed to estimate carbon stocks in South East Sulawesi tropical forest, Indonesia, using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR). Two coherence Synthetic Aperture Radar (SAR) images of ALOS PALSAR full-polarimetric were used in this research. The research method is forming Random Volume over Ground (RVoG) model from interferometric phase coherence of two Full-Polarimetric ALOS PALSAR which temporal baseline is 46 days. Due to temporal decorrelation, coherence optimization was conducted to produce image with optimum coherences. The result showed that the RVoG forest height and carbon stocks which obtained from height inversion has a positive correlation with ground measurement.
Innovations in the Geoscience Research: Classification of the Landsat TM Imag...Universität Salzburg
Current research presents application of the ILWIS GIS for satellite image processing and classification aimed at land cover types mapping. Two images were classified and analysed. Changes in land cover types were detected for the time 1988 - 2011. The study area covers selected example regions of North Russia. Supervised classification of the raster imagery aims at recognizing of the class membership for each pixel during image analysis. The results demonstrate application of the ILWIS GIS approach of technical processing of the raster images and recognizing classes of the land cover types. The The Minimal Distance Classifier was used as an approach. due to its applicability, logical methodology and precision. The supervised classification of the multi-spectral imagery has been performed using 'Classify' operator in ILWIS GIS applied to Landsat TM 1988, 2001 and 2011. This work has a technical character of GIS applications for remote sensing (RS) data processing. It reports ILWIS GIS approach of the RS data processing Landsat TM satellite image using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described. Presented at the 8th International Conference 'Prospects for the Higher School Development', Grodno State Agrarian University (GGAU) Grodno, Belarus, May 28-29 2015.
Cost-Effective Raster Image Processing for Geoecological Analysis Using “ISOC...Universität Salzburg
Current presentation demonstrates environmental analysis of the landscapes in Estonia, Eastern Europe. Methods include the use of Arc GIS 10.0 and IDRISI GIS Andes 15.0 for image processing. Research aim is o detect land cover changes using method of image classification 'ISOCLUST'. The raster processing GIS approach and classification was applied towards Landsat TM two images. The ISOCLUST is an unsupervised classification method in IDRISI GIS performs the most of the image processing workflow in semi-automatically regime. The study also reports photos of the Estonian landscapes. Results include 16 land cover types typical for the study area classified and visualized on the images. In 2006 the urban area became larger than in 1992 (land cover class "3" on the histogram. This can be explained by various reasons. Changes in land cover types in selected Estonian landscapes are shown on the statistical histograms on 1992 and 2006.
Analysis of Changing Land Use Land Cover in Salinity Affected Coastal RegionIJERA Editor
Anthropogenic activities have induced many changes in land use over a period of three decades in a salinity
affected semi-arid region of coastal Saurashtra in Gujarat. To overcome water scarcity and quality issues, efforts
have been undertaken by state authorities to conserve and effectively use surface water resource to supplement
the irrigation and domestic water requirements. Surface water schemes implemented in the area have altered the
general land use conditions. In the present study, remotely sensed data coupled with ancillary data are used for
analysing the land use-land cover change. Supervised classification and post classification techniques are
employed to classify various land use-land cover classes and to detect changes, respectively. Landscape pattern
change has been studied by analysing the spatial pattern of land use land cover classes structure. The results
show that the region has experienced significant changes over a thirty year period. Growth in agricultural
activities, policies developed to conserve freshwater runoff, and increase in built-up area, are the main driving
forces behind these changes
American Research Journal of Humanities & Social Science (ARJHSS) is a double blind peer reviewed, open access journal published by (ARJHSS).
The main objective of ARJHSS is to provide an intellectual platform for the international scholars. ARJHSS aims to promote interdisciplinary studies in Humanities & Social Science and become the leading journal in Humanities & Social Science in the world.
Comparing of Land Change Modeler and Geomod Modeling for the Assessment of De...IJAEMSJORNAL
The forest destruction, climate change and global warming can reduce an indirect forest benefit because forest is the largest carbon sink and it plays a very important role in global carbon cycle. To support reducing emissions from deforestation and forest degradation (REDD+) program, there is a need to understand the characteristics of existing Land Use/Cover Change (LUCC) modules. The aims of this study are 1) to calculate the rate of deforestation at Poso Regency; and 2) to compare the performance of LCM and GM for simulating baseline deforestation of multiple transitions based on model structure and predictive accuracy. The data used in this study are : 1) Indonesia tophographic map scale 1; 50.000, produced by Geospatial Information Agency (BIG), 2) Landcover maps (1990, 2000, and 2011) which were collected from the Director General of Forestry Planning, Ministry of Environment and Forestry. Meanwhile independent variables (environmental variables) such as : distance from the edge of the forest, the distance from roads, the distance from streams, the distance from settlement, elevation and slope. Landcover changes analysis was assessed by using Idrisi Terrset software and Geomod software. Landcover maps from 1990 and 2000 were used to simulate land-cover of 2011. The resulting maps were compared with an observed land-cover map of 2011. The predictive accuracy of multiple transition modeling was calculated by using Relative Operating Characteristics (ROC). The results show that the deforestation on the period of 1990-2011 reached 19,944 ha (3.55 %) or the rate of deforestation 949 ha year1. Based on the model structure and predictive accuracy comparisons, the LCM was more suitable than the GM for the asssement of deforestation.
Land Use / Land Cover Classification of kanniykumari Coast, Tamilnadu, India....IJERA Editor
The land use/ land cover details of Kanniyakuamri coast which is Located in the southern part of Tamil Nadu (India) is studied. Satellite imagery is used to identify the Land use/ Land cover status of the study area. The software like ERDAS and Arc GIS are used to demarcate the land use / Land cover features of Kanniyakuamari coast. Remote sensing and GIS provided consistent and accurate base line information than many of the conventional surveys employed for such a task. The total area of Kanniyakumari coast is 715 sq.km. The land use / land cover classes of the study area has been categorized into thirteen such as Plantation, Sandy area, Water logged area, Scrub forest, Crop Land, Water bodies, Land with scrub, Reserve forest, Land without Scrub, Salt area, Beach Ridge, Settlement and Fallow land on the basis NRSA Classifications. Among these categories, land with scrub land is predominantly found all over the study area, It is occupied about 336.36 sq.km (44.61 percent), Crop Land 273.82 sq.km(38.29 percent), water bodies lands sharing about 20.44 sq.km (2.85 percent ), settlement occupied with 6.96 sq.km (0.97 percent), and Fallow land was occupied 13.98 sq.km ( 1.95 percent ).
Classification Sensing Image of Remote Using Landsat 8 through Unsupervised C...IJAEMSJORNAL
Bangkalan regency is classified as a new regency which is located East Java, Indonesia. This regency possesses several potential areas in agriculture, plantation, and fishery. This research employs image analysis process of remote sensing satellite Landsat 8 in Bangkalan regency. This research uses Landsat 8 satellite image processing method from image data collection stage to classification stage by using unsupervised classification technique. This method produces land appearance, such as agriculture, ponds, and settlements in Bangkalan regency. This research classification result can be used as a reference of vegetation coverage in Bangkalan regency. Based on the research result, rice field vegetation is very dominant compared to other areas in Bangkalan Regency. Rice field vegetation coverage is much more dominant than other coverage such as residential area. The main objective of this study is to obtain the scale of comparison or area percentage in Bangkalan.
Recent Study on National Deforestation Estimate CIFOR-ICRAF
This roundtable discussion, first delivered in Jakarta, shares research into Indonesia's national deforestation estimate, with the objective of sharing approaches and ultimately improve the reliability of the estimate.
Risks of Cryogenic Landslide Hazards and Their Impact on Ecosystems in Cold E...Universität Salzburg
Research focuses on monitoring landscapes downgrading in specific conditions of Arctic ecosystems with cold climate conditions (marshes, permafrost, high humidity and moisture). Specific case study: cryogenic landslides typical for cold environments with permafrost. Area: Yamal Peninsula. Aim: analysis of the environmental changes caused by cryogenic landslides in northern land- scapes affecting sensitive Arctic ecosystems. Thaw of the permafrost layer causes destruction of the ground soil layer and activates cryogenic landslide processes. After disaster, vegetation coverage needs a long time to recover, due to the sensitivity of the specific northern environment, and land cover types change. ILWIS GIS was used to process 2 satellite images Landsat TM taken at 1988 and 2011, to assess spatiotemporal changes in the land cover types. Research shown ILWIS GIS based spatial analysis for environmental mapping.
Application of remote sensing in forest ecosystemaliya nasir
Established remote sensing systems provide opportunities to develop and apply new measurements of ecosystem function across landscapes, regions and continents.
New efforts to predict the consequences of ecosystem function change, both natural and human- induced, on the regional and global distributions and abundances of species should be a high research priority
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
ILWIS GIS for Monitoring Landscapes in Tundra Ecosystems: Yamal Peninsula, Ru...Universität Salzburg
P. Lemenkova, B. Forbes, and T. Kumpula. ILWIS GIS for Monitoring Landscapes in Tundra Ecosystems: Yamal Peninsula, Russia. Paper presented at the 3rd International Geosciences Student Conference ’Remote Sensing and Global Surveillance’. Oral presentation. Serbia, Belgrade. Association of Geophysicists and Environmentalists of Serbia (AGES), 2012. doi: 10. 13140/RG.2.2.18851.50729.
Modelling Landscape Changes and Detecting Land Cover Types by Means of the Re...Universität Salzburg
The emphasis of this research is to demonstrate application of Landsat satellite imagery as a major resource for environmental research using ILWIS GIS. Landsat images are highly useful and strongly recommended for educational purposes as they are provided free of charge and timely regular geospatial data with 30-m resolution covering any places of the Earth. The case study describes mapping land cover types in ecosystems. It details how exactly satellite images can be used for geospatial research step by step. In the current research I used orthorectified Landsat Thematic Mapper (TM), MSS and Enhanced Thematic Mapper (ETM+) data in Geographic Tagged Image-File Format (GeoTIFF) acquired over the area of Bovanenkovo region, Yamal. The images cover study area for different time periods. The choice of Landsat data application for land cover mapping is explained by its 30-m high spatial resolution, well-known advantages of application of the Landsat scenes in research and cartography, almost 40 year old history of the image record, successful distribution and open availability. Landsat scenes were selected for the pair analysis: Landsat TM scenes for 1988-08-07 and 2011-07-14 and Landsat ETM+, 2001. The research methodology is based spatial analysis tools of the open source GIS software: Quantum GIS and ILWIS GIS. The images were georeferenced, preprocessed and imported to ILWIS from .img into ILWIS .mpr raster map format (ASCII) using GDAL (Geospatial Data Abstraction Library) in main ILWIS. Minimal Distance method was sued to classify images. After converting, each image contained collection of 7 Landsat raster bands, as well as theirs metadata stored in Map List (.mpl) file, information about georeference (.grf) and coordinate system in .csy file. To visualize spectral information from the Landsat image, a color composite map has been created using combination of three raster images of the individual bands. Supervised classification of the raster imagery includes image analysis aimed at recognizing class membership for each pixel. The respective pixels are selected in Sample Set Editor, ILWIS GIS. The research method used in current research is supervised classification, which enabled to assign land cover classes by adjusting classification parameters and thresholds in DN values of spectral signature of pixels. The principle of Minimum Distance method, used for pixels classification is based on the calculating of shortest straight-line distance in Euclidian coordinate system from each pixel’s DN to the pattern pixels of land cover classes.
Bringing Geospatial Analysis to the Social Studies: an Assessment of the City...Universität Salzburg
Current poster presents an example of Landsat TM image processing using ENVI GIS. Research area: Taipei, Taiwan. Located on the north of the island, Taipei is Taiwan’s core urban, political and economic center; population >2.6 M continuing to expand affecting urban landscapes. Research aim: spatio- temporal analysis of urban dynamics in study area during 15 years (1990- 2005) Research objective: application of GIS methodology and remote sens- ing data to spatial analysis for a case study of Taipei. Data: Landsat TM images taken from the USGS. Software: ENVI GIS. Workflow includes following steps: 1) Preliminary processing 2) Creation color composites 3) Classification using K-means algorithm 4) Mapping using classification results 5) Accuracy assessment. The preliminary data processing includes image contrast stretching, which is useful as by default, ENVI displays images with a 2\% linear contrast stretch. For better contrast the histogram equalization contrast stretch was applied to the image in order to enhance the visual quality. The analysis of landscape changes was performed by geospatial analysis. 2 satellite images Landsat TM were processed and classified using ENVI GIS. Result of classification: areas occupied by different land cover types were calculated and analyzed. It has been detected that different parts of the city of Taipei were developing with different rate and intensity. 3 different residential types of the city were recognized and mapped. The results demonstrated following outcomes: 1) intensive urban development of the city of Taipei; 2) decline of green areas and natural spaces and, on the contrary, increase in anthropogenic urban spaces; 3) not parallel urban development in different districts of the city of Taipei during the 15-year period of 1990-2005.
To the question of the environmental education: how Landsat TM, ETM+ and MSS ...Universität Salzburg
The emphasis of this research is to demonstrate application of Landsat satellite imagery as a major resource for student and educational research. Landsat images are highly useful and strongly recommended for educational purposes as they are provided free of charge and timely regular geospatial data with 30-m resolution covering any places of the Earth. The case study describes mapping land cover types in ecosystems. It details how exactly satellite images can be used for geospatial research step by step. In the current research I used orthorectified Landsat Thematic Mapper (TM), MSS and Enhanced Thematic Mapper (ETM+) data in Geographic Tagged Image-File Format (GeoTIFF) acquired over the area of Bovanenkovo region, Yamal. The images cover study area for different time periods. The choice of Landsat data application for land cover mapping is explained by its 30-m high spatial resolution, well-known advantages of application of the Landsat scenes in research and cartography, almost 40 year old history of the image record, successful distribution and open availability. Landsat scenes were selected for the pair analysis: Landsat TM scenes for 1988-08-07 and 2011-07-14 and Landsat ETM+, 2001. The research methodology is based spatial analysis tools of the open source GIS software: Quantum GIS and ILWIS GIS. The images were georeferenced, preprocessed and imported to ILWIS from .img into ILWIS .mpr raster map format (ASCII) using GDAL (Geospatial Data Abstraction Library) in main ILWIS. Minimal Distance method was sued to classify images. After converting, each image contained collection of 7 Landsat raster bands, as well as theirs metadata stored in Map List (.mpl) file, information about georeference (.grf) and coordinate system in .csy file. To visualize spectral information from the Landsat image, a color composite map has been created using combination of three raster images of the individual bands. Supervised classification of the raster imagery includes image analysis aimed at recognizing class membership for each pixel. The respective pixels are selected in Sample Set Editor, ILWIS GIS. The research method used in current research is supervised classification, which enabled to assign land cover classes by adjusting classification parameters and thresholds in DN values of spectral signature of pixels. The principle of Minimum Distance method, used for pixels classification is based on the calculating of shortest straight-line distance in Euclidian coordinate system from each pixel’s DN to the pattern pixels of land cover classes.
Estimation of Spatial Variability of Land Surface Temperature using Landsat 8...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Greening of the Arctic: An IPY initiative
1-Rationale and overview of the GOA initiative.
2-North American Arctic Transect.
3-Yamal Russia Transect.
4-Circumpolar analysis of 28-year trends of sea-ice concentration, land-surface temperatures and greening patterns
The North America and Eurasia Arctic transects: Edie Barbour
Walker, D.A., Kuss, H.P., Kopecky, M., Frost, G.V., Kade, A., Vonlanthen, C., Raynolds, M.K., and Epstein, H., 2011, The North America and Eurasia Artctic transects: Using phytosociology and remote sensing to detect vegetation pattern and change: Proceedings Euiropean Vegetation Survey, 20th Workshop, Rome, 6-9 April 2011,
Similar to Mapping Land Cover Changes Using Landsat TM: a Case Study of Yamal Ecosystems, Arctic Russia (20)
Accurate and rapid big spatial data processing by scripting cartographic algo...Universität Salzburg
Accurate and rapid big spatial data processing by scripting cartographic algorithms: advanced seafloor mapping of the deep-sea trenches along the margins of the Pacific Ocean
Detection of Vegetation Coverage in Urban Agglomeration of Brussels by NDVI I...Universität Salzburg
Detection of vegetation coverage in urban agglomeration of Brussels by NDVI indicator using eCognition software and remote sensing measurements Lemenkova Polina Introduction The study area encompasses selected regions of the Brussels municipality, Belgium. In the past years the city of Brussels is experiencing intensification of the density of building structures. Unlike in some other European cities, where the most evident problem is urbanization and expansion of the city margins to the suburbia, the urban structure Brussels is the intensification of the buildings density in the city centre and the existing dwelling districts. Thus, the city structure tends to become more intense and dense, due to the process of filling the empty spaces in the urban patterns and high level housing. Another example of urban processes in Brussels is reorganisation of the industrial areas. At the same time, monitoring vegetation areas is essential for environmental sustainability of the capital city. The lack of the green spaces may cause ecological instability and increase atmospheric pollution. For studies of the specific problems of the Brussels city the remote sensing data (raster image) was used together with NDVI function, in order to detect areas covered by city parks. Acknowledgement: Current work has been supported by Bourse d'excellence, Service de Bourse d' ́ etude, Wallonie-Bruxelles International for research stay of Polina Lemenkova at l'Université libre de Bruxelles.
Investigation of the Lake Victoria Region (Africa: Tanzania, Kenya and Uganda)Universität Salzburg
This poster is a student assignment for a course 'GISA 02 GIS: Geographical Information Systems - Advanced Course 0701', a part of the MSc studies. It presents an ArcGIS based spatial analysis of the Victoria Lake region including environmental, biological, social and economic characteristics of the region. The methodology includes data organizing and management in ArcGIS 9.3. Operations and technique: ArcGIS Spatial Analyst. Project architecture: ArcCatalog. Spatial referencing and re-projection: ArcToolbox. Data include DEMs: elevations (USGS). 2 tiles of the USGS DEM, Land cover data (raster), Population data: UNEP, ArcGIS vector.shp files of administrative boundaries fof Uganda, Tanzania, Kenya. Data preprocessing include following data preparation. Initial vector data: UNEP .shp. Spatial reference properties: Africa Albers Equal Area Conic projection, standard parallels 20 and -23, central meridian 25 and Datum WGS-84, Projection GEOGRAPHIC, Spheroid CLARKE1866. Data conversion from ASCII text data format to raster using ArcToolbox / Conversion Tools / ASCII to Raster (Climate precipitation data). Data were projected, processed and several layer formatting and overlays were created. Mapping was created using ArcMap. Victoria Lake has unique environment, important role in the economy of countries supporting 25 M people through fish catchment reaching up to 90-270$ per capita per annum. Kenya, Tanzania and Uganda control 6%, 49% and 45% of the lake surface. Lake catchment provides livelihood of 1/3 of the population of 3 countries with agricultural economy supported by fishing and agriculture (tea and coffee plantations).
Interpretation of Landscape Values, Typology and Quality Using Methods of Spa...Universität Salzburg
The main result of this work consists in determined ecological significant areas of habitats that are under protection´s system of Natura 2000 Sites. The patches quantification of habitats is the partial result that influences process of determination of ecological significance. The interpretative process examines land cover patches by the set of landscape metrics for the area, size, density and shape (NP, PD, MPS, PSSD and MSI). The output values could express a spatial processes in the landscape, such as perforation, dissection, fragmentation, shrinkage or attrition. The final ecological significance of the study area-Sitno Natura 2000 site-is at degree 3, what means that the area is represented by moderately significant land cover patches-habitats. It indicates the same value as the one at the initial level. According to the value of the ecological significance, the study area has been diversified into three zones, where each one indicates specific level of conservation. The zones and the final degree of the ecological significance of habitats are retroactively compared to historical and cultural human development that started in this area as early as in 1st century BC. Theoretically, such a long period of intense human impacts on the local environment should completely destroy natural environment. Nevertheless, this area demonstrates rather good natural ecosystems conditions and well functioning ecological processes within the habitats. The human impact is now observed only in small range of size not more than 1,50% from total area of Sitno Natura 2000 Site. It can be explained, first, by low population density within the study area comparing to other EU areas, secondly, by accurate usage of the living area by the local population in general, and thirdly, by high resilience of the elements of landscapes towards any human impacts.
Economic assessment of landslide risk for the Waidhofen a.d. Ybbs region, Alp...Universität Salzburg
The research focuses on the monetary estimation of the possible losses caused by landslides. Estimation of the economic damages is performed using existing simplified methodologies. Calculations were based on real estate and market price of the elements at risk. While assessing potential damage of landslides confusion arises due to these factors. 1. First, the temporal probability of the landslides occurrence is highly difficult to assess: it can only be estimated based on the reliable and obtainable data. This includes historical data continuously reporting the occurrence of the landslides. 2. Secondly, difficulties arise by estimation of the indirect losses and partially damaged objects. The amount of the damages can be assessed based on elements vulnerability, which is very uncertain to estimate exactly. Thus, the vulnerability may differ depending on object location, individual characteristics and external factors. 3. The term “landslide” is not differentiated between debris flows and shallow or rotational landslides. This is an important source for uncertainty, as movement characteristics of these landslides are different. 4. Confusing over different method approaches in the risk assessment may generate various results: difference in magnitude and occurrence of landslides, risk perception and vulnerability assessment. The estimation of landslide risk should be based on complex investigations. The data about landslide probability should be gained from monitoring programmes. The elements at risk are defined based on spatial analysis and infrastructure inventory. The vulnerability estimation should include census data and social questionnaire. The real-life situations may vary depending on the exact price of the individual object.
Current poster presents a student assignment for the CHRIS/PROBA image processing by ENVI GIS. Study Area: Thorney Island, Chichester harbour (UK): unique wetland environment, a place for rare bird colonies. Quality of CHRIS images is affected by two types of noises: vertical noise (vertical stripes; can be corrected by comparing values of neighbouring pixels) and horizontal noise (easy to detect and correct using the horizontal profile of each file. Correction of noises can be made through DIELMO 3D Methodology. PROBA (Project for On-Board Autonomy) and CHRIS (Compact High Resolution Imaging Spectrometer) image was taken with characteristics: 18 bands, 07/10/2004, 17m ground resolution. To obtain a good-quality natural-coloured image of wetlands a need: nadir-taken colour CHRIS image with bands combination of corresponding spectral channels was selected and processed. Comparing images taken at +55° dgr (47A2_41) and nadir images (479F_41) right Images taken at the nadir are of good quality, while those at different angles have defects: Images taken at +36° dgr (47A0_41), left and nadir images (479F_41) right. Images taken at +36° and-36° (CHRIS 47A0_41 and CHRIS 47A1_41) both have inverted direction. Several bands were tried, processed and visualized. Spectral bands assessed and visually compared. This is a student poster as a part of MSc studies, University of Southampton.
Current poster presents a student assignment on Course: 'GEOG6038 Calibration and Validation of Earth Observation Data'. Study aim is image classification using ENVI GIS and remote sensing data aimed at national park area classification. Study area is Páramo National Park in Ecuador is known for its unique natural resources in high altitude grasslands. The ecosystems of Páramo consist mostly of rare species and are the key protected area for exceptionally high endemism. ENVI software enablesd to make an analysis of the area in 9 (nine) working steps and to produce a map based on 2 criteria: vegetation amount and altitude. Methodology includes following steps: 1) True-colour composite of the ETM+ image, bands 3,2,1; 2) Image contrast enhancement (Enhance-Gaussian); 3) SRTM-Data Upload to derive elevation model; 4) 3D surface visualization; 5) Calculating Greenness Index; 6) Creation Vegetation Layer ROI; 7) Creating Altitude Layer Zones by “Intersect Regions” for each pair of ROIs. Final altitude zones are: Lowland Vegetation (1-2500m), Subparamo Vegetation (2501-3500), Paramo Vegetation (3501-4100) and Superparamo Vegetation (4101 – 5000). These zones are shown on the map in different colors (yellow, beige, two greens) ; 8) Mapping and Design; 9) 3D-Mapping and DEM. The research was done as part of MSc studies at the University of Southampton, UK, autumn 2009.
Seagrass mapping and monitoring along the coast of Crete, GreeceUniversität Salzburg
Job interview for the Research Training Group (RTG) Baltic TRANSCOAST. topic ’B1: Impact of nutrient emissions from land on communities of macrophytes’. This research is presented at the job interview in the University of Rostock. Originally based on author's MSc thesis (2009-2011) summarizing research in marine observations using remote sensing and GIS methods. Study object is seagrass Posidonia oceanic (P. oceanica) along the coast of Crete, Greece. The most important facts about seagrass: endemic Mediterranean seagrass, P. oceanica is a main species in marine coastal environment of Greece. P. oceanica is the largest, the most widespread, homogeneous, dense “mattes” forming meadows between 5-40 m in Mediterranean Sea. Seagrass is a component of coastal ecosystems of high importance for the marine life, playing important functions in the marine environment. Seagrasses are subjects to external factors and therefore have environmental vulnerability. The study area is located in General research area: Island of Crete, Greece. Seagrass sampling will be performed at three stations at a depth of 6-7 m: Heraklio, Agia Pelagia, Xerokampos, Crete Island, Greece. The general research objectives of the MSc research includes GIS and environmental analysis: 1) Mapping the extent of the spatial distribution of seagrass P. oceanica along the northern coast of Crete; 2) Monitoring environmental changes in seagrass meadows in the selected fieldwork sites (Agia Pelagia, Xerokampos) over the 10-year period (2000-2010). There are various multi-sources data proposed for using in spatial analysis. data of the previous measurements received during the last year fieldwork, to analyze whether P.oceanica is spectrally distinct from other sea floor types, using differences in the spectral signatures on the graphs in a WASI, the Water Color Simulator software. Other data include satellite images from the open sources (Landsat TM), aerial images, Google Earth; underwater videographic measurements of 3 cameras Olympus ST 8000 made during the ship route (20 total in the selected areas of the research places) resulting in series of consequent images, covering area under the boat path; in-situ measurements of the seagrass in selected spots, using measurement frame and other devices for marine biological research for the validation of the results. Arc GIS vector layers of Crete island and surroundings (.shp files). Hypothesis testis is performed by ANOVA, SPSS. The results of WASI spectral analysis illustrating graphs of the spectral reflectance of different sea floor types (sand, P.oceanica, rocky, etc) at various depths (0.5-4 m), based on the results of 20. Precise, correct and up-to-date information about the seagrass distribution over the coasts is necessary for the sustainable conservation of marine environment.
Why Should We Stand for Geothermal Energy ? Example of the Negative Impacts o...Universität Salzburg
Geothermal energy is a clean, environmentally friendly, renewable resource that provides energy around the world. Heat flowing constantly from the interior of the Earth ensure to be an inexhaustible supply of energy. However, existing traditional sources of energy, such as oil and gas are still popular nowadays. Current paper gives an example of environmentally danger of these sources of energy. The given example of oil and gas operations within the shelf and the coast of the Barents Sea and Pechora Sea causes contamination of waters by phenol and its accumulation in the bottom sediments and life tissues of the marine habitants. At the same time, ecosystems of the south-eastern part of the Barents Sea and Pechora Sea are characterized by their high biodiversity and high level of primary production. The last one is the fundamental biological characteristics for the marine ecosystems meaning the formation of the organic substance in the water by the chlorophyll-contains organisms: phytoplankton. The primary production plays an exceptional role in the functionality of the marine ecosystem's components. Therefore, presentation gives some brief ideas on the importance of the 'green', eco-friendly sources of energy and a need for the constant development in the environmental protection of our planet. The presentation was given at the International Conference 'Geoenergy' in Grozny (Chechnya), Russia, 19 June 2015.
This presentation introduces research on using geoinformation technologies for education at universities. A case study is ArcGIS 9.1. Specifically, it presents a methodology of effective teaching of a group of students based on ArcGIS. Several ArcGIS modules are presented and their functionality reviewed and highlighted: ArcGIS Spatial Analyst, ArcScene, ModelBuilder, ArcMap, ArcCatalog. Technical questions of how to better explain students data processing, data converting and modelling using ArcGIS are discussed and better pedagogical solutions are proposed. The presentation also briefly reviews the advantages of using ArcGIS by different groups of students studying at various specializations: geomorphology, cadaster, hydrology, economic geography. In this way it is stressed that using a highly functional GIS software such as ArcGIS should be learned not only by cartographers but also to wider audience of students. Presented at Lomonosov Moscow State University, Faculty of Educational Studies as a graduation works for additional qualification 'University Teacher', Moscow, Russia, 2007. The presentation is given in Russian language with a TOC summary in English.
How could obligation chain be structured along cross-border gas supply for...Universität Salzburg
Research points: to measure components and linkages of legal obligations undertaken by the actors involving cross-border gas supply chain; to investigate possibility to establish a legal structure for promoting security of gas supply chain; to examine consequences of gas supply chain for government and companies; to analyze legal structures (international-domestic-contract law): entitlement vs. state responsibility as requirements for functioning/enforcing obligation chain.
The seminar presentation demonstrates research on land cover analysis in western Estonia. Study area is Pärnu region located on the western part of the country, along the coasts of Baltic Sea. The region is a valuable environmental part and a unique recreational area of Estonia. The presentation consists of two parts. The fist part presents technical workflow of the image processing by means of GIS and Lansat TM satellite imagery. Methodology is base don Arc GIS 10.0 and IDRISI GIS Andes 15.0 for image processing. The aim is to detect land cover changes using image classification by 'ISOCLUST'. Raster images processing and classification was applied for Landsat TM two images. The ISOCLUST is an unsupervised classification method in IDRISI GIS. It performs image processing workflow in semi-automatically regime. Results include 16 land cover types typical for the study area classified and visualized on the images. In 2006 the urban area became larger than in 1992 (land cover class "3" on the histogram. This can be explained by various reasons. Changes in land cover types in selected Estonian landscapes are shown on the statistical histograms on 1992 and 2006. The second part presents social analysis of the current development of tourism and recreation on Baltic Sea coasts with discussion of new directions and perspectives. Notable natural settings include mild marine climate condition and precious coniferous forests. Presentation briefly discusses historical development of the tourism in the country and gives directions on its modern development caused by active socio-economic changes since 1990s. The research is methodologically based on the author's fieldwork in the study area, literature review and analysis of the statistical graphs of the socio-economic data. The study presents photos of the Estonian landscapes.
Using K-means algorithm classifier for urban landscapes classification in Tai...Universität Salzburg
Current presentation summarizes spatial analysis studies of Taipei urban growth using ENVI GIS based image classification. The presentation consists in two parts. The first part describes the city, urban and social settings and gives a brie history of the development in 20th century. The second part is focused don the GIS based technical description of the algorithms of image analysis: classification of the multi-temporal Landsat TM series of the selected stud area of Taipei, Taiwan. Methodology aims at spatio-temporal analysis of urban dynamics in study area during 15 years (1990-2005). Research objective: application of geoinformatic tools, remote sensing data and application of methodology to spatial analysis for urban studies, a case study of Taipei. Current presentation consists in 2 parts: 1) Overview of the environmental research problem, urbanization and characteristics of Taipei. Consequences of urban sprawl for the global cities, such as Taipei; 2) Detailed technical description of the GIS part: remote sensing data capture, pre-processing, algorithm processing, image classification and spatial analysis. The spatial analysis performed by means of GIS ENVI enabled to use satellite images for social and urban studies. The spatio-temporal analysis was applied to Landsat TM images taken at 1990 and 2005. Built-in functions of the mathematical algorithms (K-means) enabled to process raster Landsat TM images and to derive information from them.
Rural Sustainability and Management of Natural Resources in Tian Shan Region,...Universität Salzburg
Current presentation introduces an analysis of the land use and current environmental situation of the Tian Shan region. Tian Shan (the ’Celestial Mountains’) is the largest high mountain systems (800,000 km2) in the World. geopolitically, Tian Shan is located in the heart of Central Asia. It crosses five densely populated countries: China, Kazakhstan, Kyrgyzstan, Uzbekistan and Tajikistan. Tian Shan regions has unique ecosystems, Shrenk mountain forests and endemic species. Tian Shan is composed by large, isolated mountains, surrounded by the Tarim desert basin of north-western China, Lake Issyk Kul and deserts of Uzbekistan and Kazakhstan. Tian Shan region is outstanding for the richness of natural resources, landscapes and ecosystems. Rare species: ca 70\% of species (both animal and plants) have specific south Asian distribution, typical for steppe and desert ecosystems. The ecosystems include numerous protected and rare species (over 4000 wild species), relicts and endemics, unique coniferous forests, rich biodiversity. The slopes of the Tian Shan mountains at altitudes 2000 to 3000m are mostly covered by precious coniferous forests of Schrenk’s Spruce (Picea schrenkiana), recorded in the International Union for Conservation of Nature (IUCN) Red List of Threatened Species. At the same time, the region has environmental problems such as overgrazing, deforestation, decreased species composition, soil depletion and erosion, desertification and land degradation. Current presentation demonstrates and discusses these problems.
Mapping Agricultural Lands by Means of GIS for Monitoring Use of Natural Reso...Universität Salzburg
The presentation demonstrates a technical case study of the image processing by ILWIS GIS. Study area is located in the southwestern, agricultural part of Hungary (Mecsek Hills foothill area). The landscapes of the Mecsek region represent a unique part of the Hungarian environment belonging to the Carpathian basin. However, changes in the land cover types were detected recently caused by various environmental reasons. Study aim was to compare changes in the land cover types and landscape dynamics. 3 Landsat TM images have a temporary gap of 14 years (1992-2006). The gap aimed to assess vegetation changes in the summer months (June). The study includes following methodological steps: 1) Data collection: 3 Landsat TM images; 2) Data import and conversion. 3) Data preprocessing: scenes of 1992, 1999 and 2006. 4) Making color composites from 3 Landsat TM spectral channels (multi-band layers). 5) Image segmentation and classification (clustering). 6) GIS mapping and spatial analysis. 7) Google Earth snapshot verification. 8) Results interpretation. Results analysis shown changes in the selected area detected by ILWIS GIS image classification.
Seagrass Mapping and Monitoring Along the Coasts of Crete, GreeceUniversität Salzburg
This research proposal introduces MSc thesis research. Study object is seagrass Posidonia oceanic (P. oceanica) along the coast of Crete, Greece. The most important facts about seagrass: endemic Mediterranean seagrass, P. oceanica is a main species in marine coastal environment of Greece. P. oceanica is the largest, the most widespread, homogeneous, dense “mattes” forming meadows between 5-40 m in Mediterranean Sea. Seagrass is a component of coastal ecosystems of high importance for the marine life, playing important functions in the marine environment. Seagrasses are subjects to external factors and therefore have environmental vulnerability. The study area is located in General research area: Island of Crete, Greece. Seagrass sampling will be performed at three stations at a depth of 6-7 m: Heraklio, Agia Pelagia, Xerokampos, Crete Island, Greece. The general research objectives of the MSc research includes GIS and environmental analysis: 1) Mapping the extent of the spatial distribution of seagrass P. oceanica along the northern coast of Crete; 2) Monitoring environmental changes in seagrass meadows in the selected fieldwork sites (Agia Pelagia, Xerokampos) over the 10-year period (2000-2010). There are various multi-sources data proposed for using in spatial analysis. data of the previous measurements received during the last year fieldwork, to analyze whether P.oceanica is spectrally distinct from other sea floor types, using the differences in the spectral signatures on the graphs in a WASI, the Water Color Simulator software. Other data include satellite images from the open sources (Landsat TM), aerial images, Google Earth; underwater videographic measurements of 3 cameras Olympus ST 8000 made during the ship route (ca 20 total in the selected areas of the research places) resulting in series of consequent images, completely covering the area under the boat path; in-situ measurements of the seagrass in selected spots, using measurement frame and other devices for marine biological research for the validation of the results. Arc GIS vector layers of Crete island and surroundings (.shp files). Hypothesis testis is formulated for the proposed research, questions defined, methods prepared and planned. The research work is expected to have following results : Over the northern coasts of Crete: thematic maps showing seafloor types and seagrass P.oceanica spatial distribution along the coasts of Crete. Within the fieldwork locations, Ligaria beach: monitoring the environmental changes, based on the classification of the satellite and aerial imagery and fieldwork video camera footage. Within the fieldwork locations : maps of the sea floor cover types, based on the fieldwork measurements and UVM. Results of the WASI spectral analysis illustrating graphs of the spectral reflectance of different sea floor types (sand, P.oceanica, rocky, etc) at various depths (0.5-4 m), based on the results of 20.Precise, correct and up-to-date information about th
Data Sharing, Distribution and Updating Using Social Coding Community Github ...Universität Salzburg
The presentation introduces using LaTeX and GitHub for data sharing, distribution and updating in graduate research. The questions of using, advantages and functionality of GitHub, a web-service for hosting (i.e. serving and maintenance) of IT-projects online, are discussed and screenshots of the projects are presented. The main advantages in using GitHub consists in the fact that Github allows control latest changes, discuss and discuss work with students, post comments into the text using syntax coloring add online comments. This enables to effectively collaborate for a group of students of to supervise a research thesis. Technical illustrations of the git config command of GitHub area presented. Command ’git init’ is an initiation of the project from scratch. Command ’git add files’ - selecting all files for the project. (texts, tables, graphs, maps, figures). Advantages of LaTeX for thesis writing consists in its a built-in flexible system of bibliographic cross-referencing in the list of references, which enables making automatic linking to the bib sources, as well as updating links. Examples of structuring text in a thesis by LaTeX and GitHub are presented. Mark up language was used to highlight text when writing codes with a high level of nesting, allowing to quickly navigate over the work. The presentation has a technical and methodological character and introduces using IT tools, GitHub and LaTeX in academic environments.
…
Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece. MSc Thesis...Universität Salzburg
Current presentation introduces a MSc thesis defense. The research focuses on the P. oceanica, an endemic species of the seagrass in Mediterranean Sea. Study area is Crete Island, Greece. The goal of this study is to analyse optical properties of the seagrass P. oceanica and other seafloor types (carbonate sand), and to apply remote sensing techniques for seagrass mapping in the selected locations of northern Crete. Analyzing spectral reflectance of the P. oceanica and other seafloor cover types by means of tools Radiative Transfer Model (RTM) using Water Color Simulator (WASI). Other technical tools included ArcGIS and Erdas Imagine GIS software, Gretle for plotting and statistical analysis, SPSS for ANOVA based Hypothesis testing. Data include spectral measurements of the seagrass optical properties by Trios-RAMSES (Hyperspectral radiometers for measuring optical properties of water), Google Earth aerial images, Landsat TM scenes. Fieldwork measurements were done using iPAQ data and GPS records, SCUBA equipment. Optical properties of the water columns were tested : spectral reflectance, radiance, irradiance. Characteristics reflect current chemical content and physical specifics of the water with and without sediments. Results of this research proved that P. oceanica is spectrally distinct from other seafloor types (carbonate sand) at varying environmental conditions, as well as from other seagrass species (Thalassia testudinum). The RTM software is a useful tool for analyzing spectral signatures of various seafloor types enabling simulations of data received from the broadband and narrowband remote sensors. Application of the RS data from the broadband sensors is highly advantageous for the seagrass mapping. Spectral discrimination of P. oceanica from other seafloor cover types is possible at diverse and changing environmental conditions (water column height). Maps, graphics and imagery are provided. Current presentation contains 72 slides. Defended at University of Twente, Faculty of Earth Observation and Geoinformation (ITC), Enschede, Overijssel Province, the Netherlands on March 8, 2011.
Seagrass mapping and monitoring along the coast of Crete, Greece. Mid-Term Pr...Universität Salzburg
Research problem focuses on studying dynamics of spatial distribution of the seagrass meadows with a case study of P. oceanica, using aerial and satellite imagery over the 10-years period. Characteristics of the spectral reflectance of seagrass enables its discrimination from other seafloor types. Raster images processing using RS methods is suitable for seagrass mapping. Current MSc research is based on various sources of data: fieldwork in-situ measurements, satellite imagery, aerial imagery and GIS layers (maps of Crete). Technically, research is based on using GIS and RS methods: ENVI and ArcGIS software.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Predicting property prices with machine learning algorithms.pdf
Mapping Land Cover Changes Using Landsat TM: a Case Study of Yamal Ecosystems, Arctic Russia
1. Mapping land cover changes using Landsat TM:
a case study of Yamal ecosystems, Arctic Russia
Lemenkova Polina1
, Forbes Bruce C.2
, and Kumpula Timo3
1
Dresden University of Technology (TU Dresden), Germany; 2
Arctic Center, University of Lapland (Rovaniemi, Finland); 3
University of Eastern Finland (Joensuu, Finland)
This poster is created in LATEX Contact B: Polina.Lemenkova@mailbox.tu-dresden.de
Summary
This paper details changes in land cover types in tundra landscapes (Yamal)
during since 1988. The research method is supervised classification (Minimal
Distance) of the Landsat TM scenes. The new approach of the current work
is application of ILWIS GIS and RS tools for Bovanenkovo region.
Research area: location & environmental settings
Figure: 1. Yamal Peninsula
The research area is geographically located on the
Bovanenkovo region, the north-western part of Yamal
Peninsula, West Siberia, Russia (Fig.1). The Yamal
Peninsula is a flat homogeneous lowland region with
low-lying plains of heights <90m. Such geographic
settings create specific local environmental conditions
in the region. Thus, Yamal is the worlds largest
high-latitude wetland system covering in total 900,000
km2
of peatlands, complex system of wetlands,
dense lake and river network. Typical for this
region are seasonal flooding, active erosion processing,
permafrost distribution and intensive local landslides.
Dominating vegetation types are typical tundra species
(heath, grasses, moss, and lichens), and woody plants (shrubs and willows).
Research data
Figure: 2. Landsat TM images: 1988 (left) and 2011 (right)
The research data
are orthorectified Landsat
TM scenes covering
north-west of Yamal. The
images have a time span
of 23 years: 1988-08-07
and 2011-07-14,
taken in growing
season when vegetation
coverage is clearly visible.
Methods
The research methods consist of image classification, spatial analysis and
thematic mapping, technically performed in ILIWIS GIS. Research steps:
1. Data pre-processing: a) import .img into ASCII raster format (GDAL).
After converting, each image contained collection of 7 Landsat raster bands
b) visual color and contrast enhancement c) geographic referencing of
Landsat scenes: UTM (Universal Transverse Mercator), Eastern Zone 42,
Northern Zone W, WGS 1984 datum (Georeference Corner Editor, ILWIS).
Figure: 3. Selecting AOI
(study area)
2. Research area
selection. The area of interest (AOI) was identified
and cropped on the raw images (Fig.3). This
area shows Bovanenkovo region in a large scale. The
AOI area best represents typical tundra landscapes.
3. Image classification method is supervised
classification (Minimal Distance), which is based on
the spatial analysis of spectral signatures of object
variables, i.e. vegetation types. The classes sampling
was performed using Sample Set tool in ILWIS GIS.
The training pixels for each land cover type were
selected as representative samples and stored as classification key. They have
contrasting colors, visually visible and distinguishable on the image. The
defined classes include shrub tundra, willows, tall willows, short shrub tundra, sparse
short shrub tundra, dry grass heath, sedge grass tundra, dry short shrub tundra, dry short
shrub sedge tundra, wet peatland, peatland (sphagnum). The pixels were associated
with land cover classes, using their DNs, similar to the key samples.
4. Thematic mapping: layout of main research results, represented as
maps of the land cover classes. The created domain Land classes includes
legend with representation colors visualizing each category.
Funding
The financial support of this research has been provided by the Fellowship of the Center for
International Mobility (CIMO) of Finland. Contract No. TM-10-7124 (Decision 9.11.2010).
Results
The research output includes following results:
1) two thematic maps of land cover types in Bovanenkovo area, Yamal (Fig.4)
2) calculation of the areas in ha of land cover types (Tab.1).
Figure: 4. Land Cover Classes in Bovanenkovo area, Yamal Peninsula: 1988 (left) and 2011 (right)
The assessment of the areas of all land cover classes shows following results. Willows
covers 2750,57 ha in 2011, which is more than in 1988, when it covered 1547,52 ha
(both ’tall willows’ & ’willows’ classes). Noticeable is increase in tundra vegetation:
’short shrub tundra’, ’sparse short shrub tundra’ and ’dry short shrub tundra’ have
more areas covered in 2011 comparing to 1988: almost 5442,00 ha vs 1823,00 ha.
Table: 1. Statistics on the land cover classes, Bovanenkovo region, Yamal Pennsula.
Land Cover Class 1988, # pixels 2011, # pixels 1988, ha 2011, ha
Shrub tundra 220447 168226 1146.3244 874.7752
Short shrub tundra 165079 270158 858.4108 1404.8216
Willows 193645 457004 1006.954 2376.4208
Tall willows 103954 71952 540.5608 374.1504
Sparse short shrub tundra 176511 759380 917.8572 3948.776
Dry grass heath 641420 231719 3335.384 1204.9388
Sedge grass tundra 27545 57052 143.234 296.6704
Dry short shrub tundra 8984 16993 46.7168 88.3636
Wet peatland 761231 531809 3958.4012 2765.4068
Peatland (sphagnum) 120328 93979 625.7056 488.6908
Dry short shrub-sedge tundra 173693 92242 903.2036 479.6584
Increase of wooden vegetation class goes along with shrunk of grass and heath areas:
’dry grass heath’ occupied area of 3335.39 ha in 1988, while currently it covers
1204.94 ha. Slight decrease can be noticed in the ’peatlands’ and ’wet peatlands’
classes: 3958.40 ha against 2765.41 ha in 2011 by ’wet peatlands’, and 625.71 ha in
1988 versus 488.69 ha by ’peatland (sphagnum)’ class.
Conclusion
The GIS-based mapping of the northern ecosystems is important tool for the
landscape monitoring and management. Processing of remote sensing data (e.g.
Landsat TM scenes) by means of GIS (e.g. ILWIS) improves technical aspects of the
landscape studies, since it enables assessment of spatio-temporal changes in
vegetation coverage. Spatial analysis of land cover types in northern landscapes can
help to detect local environmental changes in Arctic regions.
Current research details changes in the land cover types in Bovanenkovo region,
Yamal Peninsula, during the past 2 decades. These results are received as a result of
the spatial analysis of classified images. The GIS mapping is based on the results of
the image classification. The research results presented in the current work illustrate
spatial distribution of land cover types in the selected area.
Analysis of the results shows noticeable overall increase of woody vegetation (willows
and shrubs) and decrease of peatlands, grass and heath areas. This illustrates
environmental process of greening in Arctic, i.e. the unnatural increase of woody
plants. The gradual changes in plant species patterns and distribution affect
landscape structure in Yamal ecosystems. The triggering factors for these processes
could be complex environmental changes in Arctic, as well as local cryogenic
processes (e.g. successive change in vegetation recovering after cryogenic landslides).
References
1. Kremenetski, K.V., Velichko, A.A., Borisova, O.K., MacDonald, G.M., Smith, L.C., Frey, K.E. and Orlova, L.A. [2003]. Peatlands of the Western Siberian lowlands:
current knowledge on zonation, carbon content and Late Quaternary history. Quaternary Science Reviews, 22, 703723.
2. Leibman, M.O. and Kizyakov, A.I. [2007]. Kriogennyie opolzni Yamala Yugorskovo poluostrova (Cryogenic Landslides of the Yamal and Yugorsky Peninsula). Moscow,
Earth Cryosphere Institute, Siberian Branch, Russian Academy of Science (in Russian).
3. Ukraintseva N.G and Leibman M.O. [2007]. The effect of cryogenic landslides (active-layer detachments) on fertility of tundra soils on Yamal Peninsula, Russia, 1st
North American Landslide Conference. Eds.: V. Schaefer, R. Schuster and A. Turner (Vail, CO: Omnipress),1605-1615.
4. Walker, D.A., Leibman, M.O., Epstein, H.E., Forbes, B.C., Bhatt, U.S., Raynolds, M.K., Comiso, J.C., Gubarkov, A.A., Khomutov, A.V., Jia., G.J., Kaarlejrvi, E.,
Kaplan, J.O., Kumpula, T., Kuss, P., Matyshak, g., Moskalenko, N.G., Orekhov, P., Romanovsky, V.E., Ukraintseva, N.G. and Yi, Q. [2009]. Spatial and temporal
patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index.
Environmental Research Letters, 4 (16), 045004.