1,720,993 research outputs found
Quantifying land use/cover change and landscape fragmentation in Danang City, Vietnam: 1979-2009
No full textStudying temporal changes of land use and land cover (LULC) from satellite images has been conducted in Vietnam several years. However, few studies have been done to consider seriously the relationship between LULC changes and the fragmentation of landscape. Hence, analysing the changes of LULC and landscape pattern helps revealing the interactions between anthropogenic factors and the environment, through which planning actions could be effectively supported. The present study aimed to examine these changes in the surroundings of Danang City, Vietnam from 1979 to 2009 based on Landsat Multi-Spectral Scanner (MSS), Landsat Enhanced Thematic Mapper Plus (ETM+) and ASTER satellite images. The Multivariate Alteration Detection (MAD) approach was employed for processing and postclassification change detection, from which key landscape indices were applied by using FRAGSTATS. The results showed that during the whole study period, there was a notable decrease of forestland, shrub, agriculture and barren while urban areas expanded dramatically. Further spatial analysis by using landscape metrics underlined the evidence of changes in landscape characteristics with an increase in total number of patches and patch density while the mean patch area decreased during the span of 30 years. Consequently, the landscape structure of Danang city became more fragmented and heterogeneou
Quantifying land use/cover change and landscape fragmentation in Danang City, Vietnam: 1979-2009
No full textStudying temporal changes of land use and land cover (LULC) from satellite images has been conducted in Vietnam several years. However, few studies have been done to consider seriously the relationship between LULC changes and the fragmentation of landscape. Hence, analysing the changes of LULC and landscape pattern helps revealing the interactions between anthropogenic factors and the environment, through which planning actions could be effectively supported. The present study aimed to examine these changes in the surroundings of Danang City, Vietnam from 1979 to 2009 based on Landsat Multi-Spectral Scanner (MSS), Landsat Enhanced Thematic Mapper Plus (ETM+) and ASTER satellite images. The Multivariate Alteration Detection (MAD) approach was employed for processing and postclassification change detection, from which key landscape indices were applied by using FRAGSTATS. The results showed that during the whole study period, there was a notable decrease of forestland, shrub, agriculture and barren while urban areas expanded dramatically. Further spatial analysis by using landscape metrics underlined the evidence of changes in landscape characteristics with an increase in total number of patches and patch density while the mean patch area decreased during the span of 30 years. Consequently, the landscape structure of Danang city became more fragmented and heterogeneou
Digital multi-image photogrammetry combined with oblique aerial photography enables glacier monitoring survey flights below clouds in Alaska
No full textUsually "bad weather" for aerial surveys in mountain terrain means something like normal weather. Only exceptionally good weather conditions can be used successful for vertical aerial photography. In the coastal mountains of Alaska this kind of weather is rare enough to seriously hamper survey activities. Recognizing this problem, a method for survey flights that can deal with far less than ideal weather conditions was developed and is now being tested in a joint venture with the USGS Glaciology section in Fairbanks, Alaska. Our current study is focused on evaluating a new, self contained approach to study high mountain geomorphology using a close range remote sensing method with a low flying light aircraft as a basis for digital oblique aerial photogrammetry. With a special type of camera and digital multiimage photogrammetry system its now possible to extract DEM (Digital Elevation Models) from oblique aerial photography, acquired out of the open window of almost any light aircraft. With this method the aircraft is not bound to a straight flight path and can move freely around and over the target area. This allows it to fly very close to a specific target and get a very high accuracy, depending on target size and distance to it. Even more important, any weather good enough for normal photography and "mountain flying" can be used to get data There are few restrictions on the weather unlike in the case of the usual vertical aerial photography, which requires clear skies, no clouds, and is hampered by strong thermal activity in the air. Especially in a oceanic high mountain weather environment this is a significant advantage, since weather delays are significantly reduced. Depending on target area location, it here is normal to fly low under the clouds within the mountain valleys and approach the photo destination. With this method one flys around the target and takes the measurement pictures from all sides of it, under the clouds. If weather conditions allow, vertic..
Biomass yield development of early, medium and late Maize varieties under a future climate in Lower Saxony, Germany
No full textLower Saxony, with a total land area of about 46 500 km2, constitutes one of the most important agricultural areas in Germany and thus within Europe. Roughly one third of its agricultural area is used for maize cultivation and as of today only few information exist on how a future changing climate will affect its local growing conditions. Thus the newly developed carbon-based crop model BioSTAR and a high-resolution regional climate data-set (Wettreg) were used to evaluate the change in biomass yields of an early, medium and late maize variety. The climate input data is based on the SRES A1B scenario, with a potential fertilization effect or better still, an increased water use efficiency due to rising CO2 levels, taken into account. The biomass yield for all varieties was calculated for each year from 2001 until 2099 on a total of 91 014 sites. The results suggest clearly differentiated development paths of all varieties. All three show a significant positive trend until the end of the century. However the medium variety shows a statistical significant decline of 5% during the first 30 years and only a slight recovery towards +5% around the century's end. The late variety has the clearest and strongest positive trend, with partially more than 30% increase of biomass yields around the end of the century or +25% mean increase in the last three decades. The early variety can be seen as in-between, with no negative but also not an as strong positive development path. All varieties have their strongest increase in yields after the mid of the 21st century. Statistical evaluation of these results suggests that the shift from a summer rain to a winter rain climate in Germany will be the main limiting factor for all varieties. In addition summer temperatures will become less optimal for all maize crops. Only if the plants can supply themselves sufficiently with water outside of the increasingly dry summer months, when also temperatures are much more favorable, an increase in biomass yields is feasible. As the data suggests the increasing atmospheric CO2 concentrations will play a critical role in reducing the crops water uptake, thus enabling yield increases in the first place.Open-Access-Publikationsfonds 201
Klimawandel: eine andauernde Kontroverse und Herausforderung für Natur- und Sozialwissenschaft
No full textDie Auseinandersetzung über das Phänomen Klimawandel wird uns auch in Zukunft weiterhin kontrovers begleiten. Diese Auseinandersetzung ist aber auch gleichzeitig Inhalt und Sinn wissenschaftlichen Arbeitens und Basis zukünftiger Politikberatung
Estimation of global bioenergy potentials and their contribution to the world's future energy demand - A short review
No full textThe global energy question is currently dominated by three concerns that strongly affect decisions on energy development priorities, i.e. the security of the energy supply, the security of the food supply and climate change. A very challenging question in this context is the estimation of global bioenergy potentials and their possible contribution to the world’s future energy demand. The sustainability potential of global biomass for energy is widely recognised and thus a primary concern of the book. The annual global primary production (GPP) of biomass is equivalent to the 4,500 EJ (EJ = 1 Exajoule = 1018 J = 1,000 Petajoule; 14.0 EJ = Germany’s primary energy consumption in 2008, while 508 EJ = the primary energy consumption of mankind in 2009) of solar energy captured each year. Around 5 % of that energy (225 EJ) could deliver 50 % of the world’s total energy use today. This approximation is in accordance with other estimates that show a sustainable annual bioenergy production of around 270 EJ. The 50 EJ that biomass contributed to the global energy supply in 2006 (the approximate energy demand was 490 EJ) was mainly used in the form of traditional non-commercial biomass fuels and contributed only 10 % to global energy use. This chapter provides a synthesis of analyses of the longer term potential of biomass resource availability on a global scale. Various studies have assessed global biomass potentials and have arrived at widely varying results. These studies highlight the reasons for these uncertainties and explain the factors that can affect biomass availability. Estimates, for instance, are sensitive to assumptions about crop yields and the amount of land that could be made available for the production of biomass for energy usage. The sustainable use of biomass as an energy source requires comprehensive management of specific landscapes and their natural resources, which are subject to restrictions (e.g., nature protection, contaminated land, priority for food production, etc.). Knowledge of the regional landscape’s potential to provide biomass and hence bioenergy, is urgently needed and best provided by bottom-up approaches, because unsustainable biomass production would diminish the climate-related environmental advantage of bioenergy. Therefore, based on a review of currently available studies on the subject, this chapter discusses the role of sustainable biomass in the future global energy supply
The Identification of Irrigated Crop Types Using Support Vector Machine, Random Forest and Maximum Likelihood Classification Methods with Sentinel-2 Data in 2018: Tashkent Province, Uzbekistan
No full textAccurately mapping land use and land cover including agricultural use and the state of crops at various stages is important to address specific agro-ecological challenges, to implement sustainable agricultural practices, and monitor crops periodically. This study aims to provide a timely and accurate main irrigated crop types mapping at 10m resolution for Tashkent province based on multi-temporal Sentinel-2 data acquired for the growing season in 2018. This paper shows the potential use of multitemporal Sentinel-2 satellite data to derive an up-to-date irrigated crop types classification map of the study area. As single-date satellite imagery does not allow proper cropland classification, multitemporal and high-resolution Sentinel-2 data was used to capture small cropland fields and specific crop types for the vegetation period (April to October 2018). NDVI monthly profiles of crop types as well as additional 10 m resolution bands 2 and 3 were used as input data to perform and assess three classification algorithms: Support Vector Machine (SVM), Random Forest (RF), and Maximum Likelihood Classification (MLC). Accuracy assessment results showed that SVM showed the highest Overall Accuracy (OA) and Kappa Accuracy (KA). KA of classified images for SVM were 0.90 and 0.89 for the RF algorithm. Both performed well with close values. But MLC showed a lower result of KA 0.60. The paper also compares the area of derived irrigated cropland area with data from the State Committee for Statistics of Uzbekistan for selected crop types. Values for the crops "cotton" and "wheat" derived by SVM and RF methods show a high correlation with the provided statistical data. Based on the results, the SVM classification method is recommended for further mapping and monitoring of irrigated crop types in the region when Sentinel-2 data is used
Malariaübertragung in Westafrika: Die Rolle natürlicher und anthropogener Determinanten
No full textMalaria zählt bis heute zu den weltweit bedeutendsten Infektionskrankheiten. Die Weltgesundheitsorganisation (WHO) geht im "World Malaria Re-port 2005" davon aus, dass derzeit mehr als drei Milliarden Menschen in Malariarisikogebieten leben, von denen sich jährlich zwischen 350 und 500 Millionen mit der Krankheit infizieren. Dabei zeigt sich allerdings ein deutlicher regionaler Schwerpunkt: Etwa 60 % aller klinischen Malariafälle und über 80 % der malariabedingten Sterbefälle ereignen sich in Afrika südlich der Sahara. Malaria fordert dort jährlich über eine Million Todesopfer
CELLULAR AUTOMATA (CA) CONTIGUITY FILTERS IMPACTS ON CA MARKOV MODELING OF LAND USE LAND COVER CHANGE PREDICTIONS RESULTS
No full textAbstract. In this study, attempts has been made to find out cellular automata (CA) contiguity filters impacts on Land use land cover change predictions results. Cellular Automata (CA) Markov chain model used to monitor and predict the future land use land cover pattern scenario in a part of Brahmaputra River Basin, India, using land use land cover map derived from multi-temporal satellite images. Land use land cover maps derived from satellite images of Landsat MSS image of 1987 and Landsat TM image of 1997 were used to predict future land use land cover of 2007 using Cellular Automata Markov model. The validity of the Cellular Automata Markov process for projecting future land use and cover changes calculates using various Kappa Indices of Agreement (Kstandard) predicted (results) maps with the reference map (land use land cover map derived from IRS-P6 LISS III image of 2007). The validation shows Kstandard is 0.7928. 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict LULC in 2007 using 1987 and 1997 LULC maps. Regression analysis have been carried out for both predicted quantity as well as prediction location to established the cellular automata (CA) contiguity filters impacts on predictions results. Correlation established that predicted LULC of 2007 and LULC derived from LISS III Image of 2007 are strongly correlated and they are slightly different to each-other but the quantitative prediction results are same for when 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict land use land cover. When we look at the quantity of predicted land use land cover of 2007 area statistics are derived by using 3x3, 5x5 and 7x7 CA contiguity filters, the predicted area statistics are the same. Other hands, the spatial difference between predicted LULC of 2007 and LULC derived from LISS III images of 2007 is evaluated and they are found to be slightly different. Correlation coefficient (r) between predicted LULC classes and LULC derived from LISS III image of 2007 using 3x3, 5x5, 7x7 are 0.7906, 0.7929, 0.7927, respectively. Therefore, the correlation coefficient (r) for 5x5 contiguity filters is highest among 3x3, 5x5, and 7x7 filters and established/produced most geographically / spatially distributed effective results, although the differences between them are very small
Malariaübertragung in Westafrika: Die Rolle natürlicher und anthropogener Determinanten
No full textMalaria zählt bis heute zu den weltweit bedeutendsten Infektionskrankheiten. Die Weltgesundheitsorganisation (WHO) geht im "World Malaria Re-port 2005" davon aus, dass derzeit mehr als drei Milliarden Menschen in Malariarisikogebieten leben, von denen sich jährlich zwischen 350 und 500 Millionen mit der Krankheit infizieren. Dabei zeigt sich allerdings ein deutlicher regionaler Schwerpunkt: Etwa 60 % aller klinischen Malariafälle und über 80 % der malariabedingten Sterbefälle ereignen sich in Afrika südlich der Sahara. Malaria fordert dort jährlich über eine Million Todesopfer
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