Applications of remote sensing and geographic information systems in geomorphological studies: Safaga - El Quseir area, Red Sea coast, Egypt as an example

In den letzten drei Jahrzehnten sind Fernerkundung und GIS in den Geowissenschaften zunehmend wichtiger geworden, um die konventionellen Methoden von Datensammlung und zur Herstellung von Landkarten zu verbessern. Die vorliegende Arbeit befasst sich mit der Anwendung von Fernerkundung und geographischen Informationssystemen (GIS) für geomorphologische Untersuchungen. Durch die Kombination beider Techniken ist es vor allem möglich geworden, geomorphologische Formen im Überblick und dennoch detailliert zu erfassen. Als Grundlagen werden in dieser Arbeit topographische und geologische Karten, Satellitenbilder und Klimadaten benutzt. Die Arbeit besteht aus 6 Kapiteln. Das erste Kapitel gibt einen allgemeinen Überblick über den Untersuchungsraum. Dieser umfasst folgende morphologische Einheiten, klimatischen Verhältnisse, insbesondere die Ariditätsindizes der Küsten- und Gebirgslandschaft sowie das Siedlungsmuster beschrieben. Kapitel 2 befasst sich mit der regionalen Geologie und Stratigraphie des Untersuchungsraumes. Es wird versucht, die Hauptformationen mit Hilfe von ETM-Satellitenbildern zu identifizieren. Angewandt werden hierzu folgende Methoden: Colour Band Composite, Image Rationing und die sog. überwachte Klassifikation. Kapitel 3 enthält eine Beschreibung der strukturell bedingten Oberflächenformen, um die Wechselwirkung zwischen Tektonik und geomorphologischen Prozessen aufzuklären. Es geht es um die vielfältigen Methoden, zum Beispiel das sog. Image Processing, um die im Gebirgskörper vorhandenen Lineamente einwandfrei zu deuten. Spezielle Filtermethoden werden angewandt, um die wichtigsten Lineamente zu kartieren. Kapitel 4 stellt den Versuch dar, mit Hilfe von aufbereiteten SRTM-Satellitenbildern eine automatisierte Erfassung des Gewässernetzes. Es wird ausführlich diskutiert, inwieweit bei diesen Arbeitsschritten die Qualität kleinmaßstäbiger SRTM-Satellitenbilder mit großmaßstäbigen topographischen Karten vergleichbar ist. Weiterhin werden hydrologische Parameter über eine qualitative und quantitative Analyse des Abflussregimes einzelner Wadis erfasst. Der Ursprung von Entwässerungssystemen wird auf der Basis geomorphologischer und geologischer Befunde interpretiert. Kapitel 5 befasst sich mit der Abschätzung der Gefahr episodischer Wadifluten. Die Wahrscheinlichkeit ihres jährlichen Auftretens bzw. des Auftretens starker Fluten im Abstand mehrerer Jahre wird in einer historischen Betrachtung bis 1921 zurückverfolgt. Die Bedeutung von Regentiefs, die sich über dem Roten Meer entwickeln, und die für eine Abflussbildung in Frage kommen, wird mit Hilfe der IDW-Methode (Inverse Distance Weighted) untersucht. Betrachtet werden außerdem weitere, regenbringende Wetterlagen mit Hilfe von Meteosat Infrarotbildern. Genauer betrachtet wird die Periode 1990-1997, in der kräftige, Wadifluten auslösende Regenfälle auftraten. Flutereignisse und Fluthöhe werden anhand von hydrographischen Daten (Pegelmessungen) ermittelt. Auch die Landnutzung und Siedlungsstruktur im Einzugsgebiet eines Wadis wird berücksichtigt. In Kapitel 6 geht es um die unterschiedlichen Küstenformen auf der Westseite des Roten Meeres zum Beispiel die Erosionsformen, Aufbauformen, untergetauchte Formen. Im abschließenden Teil geht es um die Stratigraphie und zeitliche Zuordnung von submarinen Terrassen auf Korallenriffen sowie den Vergleich mit anderen solcher Terrassen an der ägyptischen Rotmeerküste westlich und östlich der Sinai-Halbinsel.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Counting Koalas from space: Integrating remote sensing, GIS and traditional ecological survey techniques

Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference

Spatio-Temporal Changes in the Wetland Ecosystem of Cochin City using Remote Sensing and GIS

Urban developments have exerted immense pressure on wetlands. Urban areas are normally centers of commercial activity and continue to attract migrants in large numbers in search of employment from different areas. As a result, habitations keep coming up in the natural areas / flood plains. This is happening in various Indian cities and towns and large habitations are coming up in low-lying areas, often encroaching even over drainage channels. In some cases, houses are constructed even on top of nallahs and drains. In the case of Kochi the situation is even worse as the base of the urban development itself stands on a completely reclaimed island. Also the topography and geology demanded more reclamation of land when the city developed as an agglomerative cluster. Cochin is a coastal settlement interspersed with a large backwater system and fringed on the eastern side by laterite-capped low hills from which a number of streams drain into the backwater system. The ridge line of the eastern low hills provides a welldefined watershed delimiting Cochin basin which help to confine the environmental parameters within a physical limit. This leads to an obvious conclusion that if physiography alone is considered, the western flatland is ideal for urban development. However it will result in serious environmental deterioration, as it comprises mainly of wetland and for availability of land there has to be large scale filling up of these wetlands which includes shallow mangrove-fringed water sheets, paddy fields, Pokkali fields, estuary etc.Chapter 1 School 4 of Environmental Studies The urban boundaries of Cochin are expanding fast with a consequent over-stretching of the existing fabric of basic amenities and services. Urbanisation leads to the transformation of agricultural land into built-up areas with the concomitant problems regarding water supply, drainage, garbage and sewage disposal etc. Many of the environmental problems of Cochin are hydrologic in origin; like water-logging / floods, sedimentation and pollution in the water bodies as well as shoreline erosion

Ecological studies of the Parambikulam Tiger Reserve in the Western Ghats of India, using Remote Sensing and GIS

mbikulam Tiger Reserve of Western Ghats using Geospatial technology. The major objectives of the study are Land use land cover mapping (LULC) and Phytodiversity analysis. Satellite data was used to map the land use / land cover using supervised classification techniques in Erdas imagine. The change for a period of 32 years was assessed using the multi-temporal satellite datasets from Landsat MSS (1973), Landsat TM (1990), and IRS P6 LISS III (2005). A geospatial approach was used for the land cover analysis. Digital elevation models, Satellite imageries and SOI topo sheets were the data sets used in the analysis. Vegetation sampling plots distributed over the different forest types were enumerated and studied for Phytodiversity analysis.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Climate and infectious disease: Use of remote sensing for detection of Vibrio cholerae by indirect measurement

It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992–1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.

Integration of remote sensing and GIS for modelling flash floods in Wadi Hudain catchment, Egypt

This paper presents a new approach to modelling flash floods in dryland catchments by integrating remote sensing and digital elevation model (DEM) data in a geographical information system (GIS). The spectral reflectance of channels affected by recent flash floods exhibit a marked increase, due to the deposition of fine sediments in these channels as the flood recedes. This allows the parts of a catchment that have been affected by a recent flood event to be discriminated from unaffected parts, using a time series of Landsat images. Using images of the Wadi Hudain catchment in southern Egypt, the hillslope areas contributing flow were inferred for different flood events. The SRTM3 DEM was used to derive flow direction, flow length, active channel cross-sectional areas and slope. The Manning Equation was used to estimate the channel flow velocities, and hence the time-area zones of the catchment. A channel reach that was active during a 1985 runoff event, that does not receive any tributary flow, was used to estimate a transmission loss rate of 7·5 mm h−1, given the maximum peak discharge estimate. Runoff patterns resulting from different flood events are quite variable; however the southern part of the catchment appears to have experienced more floods during the period of study (1984–2000), perhaps because the bedrock hillslopes in this area are more effective at runoff production than other parts of the catchment which are underlain by unconsolidated Quaternary sands and gravels. Due to high transmission loss, runoff generated within the upper reaches is rarely delivered to the alluvial fan and Shalateen city situated at the catchment outlet. The synthetic GIS-based time area zones, on their own, cannot be relied on to model the hydrographs reliably; physical parameters, such as rainfall intensity, distribution, and transmission loss, must also be considered.

Applications of GIS and remote sensing techniques for studying the housing patterns in Cairo Governorate

The main objective of this study is to reveal the housing patterns in Cairo as one of the most rapidly urbanizing city in the developing world. The study outlines the evolution of the housing problem and its influencing factors in Egypt generally and in Cairo specifically. The study takes into account the political transition from the national state economy to the open door policy, the neo-liberal period and finally to the housing situation after the January 2011 Revolution. The resulting housing patterns in Cairo Governorate were identified as (1) squatter settlements, (2) semi-informal settlements, (3) deteriorated inner pockets, and (4) formal settlements. rnThe study concluded that the housing patterns in Cairo are reflecting a multifaceted problem resulting in: (1) the imbalance between the high demand for affordable housing units for low-income families and the oversupply of upper-income housing, (2) the vast expansion of informal areas both on agricultural and desert lands, (3) the deterioration of the old parts of Cairo without upgrading or appropriate replacement of the housing structure, and (4) the high vacancy rate of newly constructed apartmentsrnThe evolution and development of the current housing problem were attributed to a number of factors. These factors are demographic factors represented in the rapid growth of the population associated with urbanization under the dictates of poverty, and the progressive increase of the prices of both buildable land and building materials. The study underlined that the current pattern of population density in Cairo Governorate is a direct result of the current housing problems. Around the depopulation core of the city, a ring of relatively stable areas in terms of population density has developed. Population densification, at the expense of the depopulation core, is characterizing the peripheries of the city. The population density in relation to the built-up area was examined using Landsat-7 ETM+ image (176/039). The image was acquired on 24 August 2006 and considered as an ideal source for land cover classification in Cairo since it is compatible with the population census 2006.rnConsidering that the socio-economic setting is a driving force of change of housing demand and that it is an outcome of the accumulated housing problems, the socio-economic deprivations of the inhabitants of Cairo Governorate are analyzed. Small administrative units in Cairo are categorized into four classes based on the Socio-Economic Opportunity Index (SEOI). This index is developed by using multiple domains focusing on the economic, educational and health situation of the residential population. The results show four levels of deprivation which are consistent with the existing housing patterns. Informal areas on state owned land are included in the first category, namely, the “severely deprived” level. Ex-formal areas or deteriorated inner pockets are characterized as “deprived” urban quarters. Semi-informal areas on agricultural land concentrate in the third category of “medium deprived” settlements. Formal or planned areas are included mostly in the fourth category of the “less deprived” parts of Cairo Governorate. rnFor a better understanding of the differences and similarities among the various housing patterns, four areas based on the smallest administrative units of shiakhat were selected for a detailed study. These areas are: (1) El-Ma’desa is representing a severely deprived squatter settlement, (2) Ain el-Sira is an example for an ex-formal deprived area, (3) El-Marg el-Qibliya was selected as a typical semi-informal and medium deprived settlement, and (4) El-Nozha is representing a formal and less deprived area.rnThe analysis at shiakhat level reveals how the socio-economic characteristics and the unregulated urban growth are greatly reflected in the morphological characteristics of the housing patterns in terms of street network and types of residential buildings as well as types of housing tenure. It is also reflected in the functional characteristics in terms of land use mix and its degree of compatibility. It is concluded that the provision and accessibility to public services represents a performance measure of the dysfunctional structure dominating squatter and semi-informal settlements on one hand and ample public services and accessibility in formal areas on the other hand.rn

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.