Due to the inappropriate planning and explosive population growth in urban areas, especially in developing countries, sustainable and disaster-safe urbanization has become the most important challenge for governments. Urbanization presents benefits in different ways but has led simultaneously to changes in land use/land cover (LULC), impacting soil quality, runoff, surface temperature, water quality, and promoting climate change. The environmental implications of LULC changes cannot be understood well enough to take precautions without the knowledge of LULC change. This reality is the driving force behind my research, which focuses on impacts of urbanization on flood and soil erosion hazards in Istanbul, Turkey. Istanbul is the biggest city in Turkey with its almost 15.000.000 population. In 1999 the Marmara earthquake destroyed the city especially the newly developed zones. Every year Istanbul suffers also from flood damages. Istanbul has been experiencing uncontrolled migration, chiefly from rural areas, since the economic reform policies took place in the second half of the 20th century. These policies forced the city to expand towards the agricultural land and to the coastal areas. Istanbul has been faced with illegal housing and uncontrolled development since then. This development has produced significant decreases inproductive agricultural lands and created more impervious areas. Infrastructure development has not matched the rate of the population increase and uncontrolled urbanization, making the city vulnerable increasingly to natural disasters. This dissertation aims to understand the impacts of urbanization on flood and erosion hazards in Istanbul by examining changes in the city using remote sensing (RS) and geographical information systems (GIS) methods. LULC was examined first: Two change detection methods were applied to choose the best performer for Istanbul. The post-classification comparison (PCC) method produced better results than the principal component analysis (PCA). PCC utilized 1984, 1997, 2001, 2007 and 2010 Landsat images of the study area. These Landsat images were corrected atmospherically and radiometrically using COST Model (Markham and Barker, 1986). After the corrections geometric rectification was performed with the help of 1987 topographic map, 1995 orthophotos, 2005 GPS data. Location and nature of the change were derived for the time periods. Results show that since 1984, agricultural land have been replaced increasingly by urbanization. Flooding and related soil erosion are both natural events. Yet these events can be hazardous; they can harm/destroy lives and property. In recent years these events have become disasters for Istanbul. We investigated the role of urban growth in such disasters. To understand the urbanization and flood relation better, flood events for each time period were examined using LULC change, runoff information and watershed analysis. Soil erosion events occur slowly and in Istanbul they do not happen frequently (yearly) as with flooding. But some of the locations of erosion that occurred in the past are now urbanized areas. It is thus important to understand how the built environment affects soil erosion. We applied the Revised Universal Soil Loss Equation (RUSLE) method for each year in the time series. Prior erosion locations digitized from General Directorate of Mineral Research and Exploration were compared to predicted locations. The resultant maps indicates that European side of Istanbul is more prone to erosion than Anatolian side.

As land-cover conversion continues to expand into ever more remote areas in the humid tropics, montane rainforests are increasingly threatened. In the south Ecuadorian Andes, they are not only subject to man-made disturbances but also to naturally occurring landslides. I was interested in the impact of this ecosystem dynamics on a key parameter of the hydrologic cycle, the soil saturated hydraulic conductivity (synonym: permeability; Ks from here on), because it is a sensitive indicator for soil disturbances. My general objective was to quantify the effects of the regional natural and human disturbances on the saturated hydraulic conductivity and to describe the resulting spatial-temporal patterns. The main hypotheses were: 1) disturbances cause an apparent displacement of the less permeable soil layer towards the surface, either due to a loss of the permeable surface soil after land-sliding, or as a consequence of the surface soil compaction under cattle pastures; 2) ‘recovery’ from disturbance, either because of landslide re-vegetation or because of secondary succession after pasture abandonment, involves an apparent displacement of the less permeable layer back towards the original depth an 3) disturbances cause a simplification of the Ks spatial structure, i.e. the spatially dependent random variation diminishes; the subsequent recovery entails the re-establishment of the original structure. In my first study, I developed a synthesis of recent geostatistical research regarding its applicability to soil hydraulic data, including exploratory data analysis and variogram estimation techniques; I subsequently evaluated the results in terms of spatial prediction uncertainty. Concerning the exploratory data analysis, my main results were: 1) Gaussian uni- and bivariate distributions of the log-transformed data; 2) the existence of significant local trends; 3) no need for robust estimation; 4) no anisotropic variation. I found partly considerable differences in covariance parameters resulting from different variogram estimation techniques, which, in the framework of spatial prediction, were mainly reflected in the spatial connectivity of the Ks-field. Ignoring the trend component and an arbitrary use of robust estimators, however, would have the most severe consequences in this respect. Regarding variogram modeling, I encouraged restricted maximum likelihood estimation because of its accuracy and independence on the selected lags needed for experimental variograms. The second study dealt with the Ks spatial-temporal pattern in the sequences of natural and man-made disturbances characteristic for the montane rainforest study area. To investigate the disturbance effects both on global means and the spatial structure of Ks, a combined design-and model-based sampling approach was used for field-measurements at soil depths of 12.5, 20, and 50 cm (n=30-150/depth) under landslides of different ages (2 and 8 years), under actively grazed pasture, fallows following pasture abandonment (2 to 25 years of age), and under natural forest. Concerning global means, our main findings were 1) global means of the soil permeability generally decrease with increasing soil depth; 2) no significant Ks differences can be observed among landslides and compared to the natural forest; 3) a distinct permeability decrease of two orders of magnitude occurs after forest conversion to pasture at shallow soil depths, and 4) the slow regeneration process after pasture abandonment requires at least one decade. Regarding the Ks spatial structure, we found that 1) disturbances affect the Ks spatial structure in the topsoil, and 2) the largest differences in spatial patterns are associated with the subsoil permeability. In summary, the regional landslide activity seems to affect soil hydrology to a marginal extend only, which is in contrast to the pronounced drop of Ks after forest conversion. We used this spatial-temporal information combined with local rain intensities to assess the partitioning of rainfall into vertical and lateral flowpaths under undisturbed, disturbed, and regenerating land-cover types in the third study. It turned out that 1) the montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, which can switch to lateral directions below 20 cm depth for a small number of rain events, which may, however, transport a high portion of the annual runoff; 2) similar hydrological flowpaths occur under the landslides except for a somewhat higher probability of impermeable layer formation in the topsoil of a young landslide, and 3) pronounced differences in runoff components can be observed for the human disturbance sequence involving the development of near-surface impeding layers for 24, 44, and 8 % of rain events for pasture, a two-year-old fallow, and a ten-year-old fallow, respectively. / Der tropische Bergregenwald in den Südecuadorianischen Anden unterliegt sowohl anthropogenen Eingriffen, d.h. der Umwandlung von Naturwald in Rinderweiden, als auch natürlichen Störungen in der Form von Hangrutschen. Ziel meiner Arbeit war es, die Auswirkungen dieser regionalen Störungsdynamik auf einen Schlüsselparameter des hydrologischen Kreislaufs, die gesättigte hydraulische Wasserleitfähigkeit (Ks), zu untersuchen und die resultierenden raum-zeitlichen Muster zu beschreiben. In der ersten Studie habe ich eine Synthese aktueller geostatistischer Forschung hinsichtlich ihrer Eignung für die Analyse bodenhydrologischer Daten entwickelt. Diese beinhaltet explorative Datenanalyse und verschiedene Techniken zur Schätzung der Kovarianzparameter; die Ergebnisse habe ich in Bezug auf die Ungenauigkeit räumlicher Vorhersagen bewertet. Es hat sich dabei herausgestellt, dass die Schätztechniken teilweise beachtliche Unterschiede in den Parametern hervorrufen, welche sich hauptsächlich in der räumlichen Konnektivität widergespiegeln. Die wichtigste Rolle im Zusammenhang mit der räumlichen Vorhersage kommt jedoch den vorgeordneten explorativen Analyseschritten zu. In der zweiten Studie habe ich mich mit der Beschreibung des raum-zeitlichen Muster der Wasserleitfähigkeit in den anthropogenen und natürlichen Störungsgradienten beschäftigt. Wichtigste Ergebnisse waren, dass es keine signifikanten Unterschiede der Wasserleitfähigkeit zwischen den verschieden alten Hangrutschen und dem Naturwald gibt. Daraus lässt sich schließen, dass die natürlichen Störungen im Untersuchungsgebiet lediglich marginale Auswirkungen auf die Bodenhydrology haben. Das steht in starkem Kontrast zum anthropogenen Störungskreislauf: die Wasserleitfähigkeit im Weideboden hat gegenüber dem Naturwald um zwei Größenordnungen abgenommen; eine „Erholung“ nach Nutzungsaufgabe scheint mindestens ein Jahrzehnt in Anspruch zu nehmen. Die räumlichen Abhängigkeit von Ks in den Oberböden von Wald und einer alten Brache ist stärker als in jenen der gestörten Flächen, was auf eine störungsbedingte Beeinträchtigung der räumlichen Struktur in geringer Bodentiefe schließen lässt. In der dritten Studie habe ich diese raum-zeitlichen Informationen mit dem örtlichen Niederschlagsregime in Verbindung gebracht, um Rückschlüsse auf die Auswirkungen der störungsbedingten Änderungen von Ks auf hydrologische Fließwege zu ziehen. Es hat sich gezeigt, dass im tropischen Bergregenwald und unter Hangrutschen ubiquitäre Tiefenversickerung dominiert, es allerdings zu einer Verschiebung in laterale Fließrichtungen für die seltenen intensiven Regenereignisse kommen kann. Anthropogene Störungen gehen mit einer um bis zu 50 Prozent erhöheren Wahrscheinlichkeit des Auftretens oberflächennaher Stauschichten einher, was die Bedeutung lateraler Fließwege erhöht. Dies trifft in vergleichbarer Größenordnung auch auf ein Vergleichsökosystem im Tieflandregenwald zu.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25247号 / 工博第5206号 / 新制||工||1994(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 佐山 敬洋, 教授 田中 賢治, 教授 市川 温 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.

<p>Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.</p><p> </p>

There has been rapid change in the landcover/landuse in the Mekong delta, Viet Nam. The landcover/landuse has changed very fast due to intense population pressure, agriculture/aquaculture farming and timber collection in the coastal areas of the delta. The changing landuse pattern in the coastal areas of the delta is threatened to be flooded by sea level rise; sea level is expected to rise 33 cm until 2050; 45 cm until 2070 and 1 m until 2100. The coastline along the eastern Mekong delta has never been static, but the loss of mangrove forests along the coast has intensified coastline change. The objective of the present study is to map the changes in landcover/landuse along the eastern coast of the Mekong delta; and to detect the changes in position of the eastern coastline over the time period from 1989 to 2002.To detect changes in landuse, two satellite images of the same season, acquired by the TM sensor of Landsat 5 and the ETM+ sensor of Landsat 7 were used. The TM image was acquired on January 16, 1989 and ETM+ image was acquired on February 13, 2002. The landcover/landuse classes selected for the study are water, forest, open vegetation, soil and shrimp farms. Image differencing and post classification comparison are used to detect the changes between two time periods. Image to image correction technique is used to align satellite images. Maximum likelihood supervised classification technique is used to classify images. The result of the classification consists of five classes for 1989 and 2002, respectively. Overall accuracies of 87.5% and 86.8%, with kappa values of 0.85 and 0.84 are obtained for landuse 1989 and landuse 2002, respectively. The overall accuracy for the change map is 82% with kappa value 0.80. Post classification comparison is carried out in this study based on the supervised classification results. According to the results obtained from the post classification comparison, a significant decrease of 48% in forest and a significant increase of 74% in open vegetation and 21% in shrimp farms area observed over the entire study area. The coastline obtained by the combination of histogram thresholding and band ratio showed an overall advancement towards the South China Sea. The results showed that new land patches emerged along the eastern coast. The amount of new land patches appeared along the coast of the Mekong delta is approximately 2% of the entire study area.