Boudewijn van Leeuwen

Evaluation of precipitation-vegetation interaction on a climate-sensitive landscape using vegetation indices

Many places in the world show spectacular landscape changes caused by increasingly rapid alterations of natural phenomena observed in the last 3 to 4 decades. More and more studies reveal the consequences of global climate change strengthened by anthropogenic effects. The cause of rapid changes in the landscape is often due to the alteration of the natural water-cycle. Using moderate resolution imaging spectoradiometer vegetation indices, this study analyzed the relationship between biomass and precipitation, being one of the most important climate elements, over a Hungarian landscape that has been highly affected by the process of groundwater-table sinking in the last decades. Research proved that the reasons for this decrease are mainly the precipitation shortage due to climate change and to a much smaller extent, anthropogenic effects. In the forests of the study area, the annual distribution of precipitation proved to be an important factor, and the biomass produced by forests is influenced by the precipitation over a shorter interval—compared to less sensitive landscapes. Under increasing aridification, further degradation of vegetation can be expected as has already been observed during drier periods in the case of tree species with high water demand.

Satellite Based Analysis of Surface Urban Heat Island Intensity

Abstract The most obvious characteristics of urban climate are higher air and surface temperatures compared to rural areas and large spatial variation of meteorological parameters within the city. This research examines the long term and seasonal development of urban surface temperature using satellite data during a period of 30 years and within a year. The medium resolution Landsat data were (pre)processed using open source tools. Besides the analysis of the long term and seasonal changes in land surface temperature within a city, also its relationship with changes in the vegetation cover was investigated. Different urban districts and local climate zones showed varying strength of correlation. The temperature difference between urban surfaces and surroundings is defined as surface urban heat island (SUHI). Its development shows remarkable seasonal and spatial anomalies. The satellite images can be applied to visualize and analyze the SUHI, although they were not collected at midday and early afternoon, when the phenomenon is normally at its maximum. The applied methodology is based on free data and software and requires minimal user interaction. Using the results new urban developments (new built up and green areas) can be planned, that help mitigate the negative effects of urban climate.

Effect of Climate Change on the Hydrological Character of River Maros, Hungary-Romania

Abstract It is highly probable that the precipitation and temperature changes induced by global warming projected for the 21st century will affect the regime of Carpathian Basin rivers, e.g. that of River Maros. As the river is an exceptionally important natural resource both in Hungary and Romania it is necessary to outline future processes and tendencies concerning its high and low water hydrology in order to carry out sustainable cross-border river management. The analyses were based on regional climate models (ALADIN and REMO) using the SRES A1B scenario. The modelled data had a daily temporal resolution and a 25 km spatial resolution, therefore beside catchment scale annual changes it was also possible to assess seasonal and spatial patterns for the modelled intervals (2021- 2050 and 2071-2010). Those periods of the year are studied in more detail which have a significant role in the regime of the river. The study emphasizes a decrease in winter snow reserves and an earlier start of the melting period, which suggest decreasing spring flood levels, but also a temporally more extensive flood season. Changes in early summer precipitation are ambiguous, and therefore no or only slight changes in runoff can be expected for this period. Nevertheless, it seems highly probable that during the summer and especially the early autumn period a steadily intensifying water shortage can be expected. The regime of the river is also greatly affected by human structures (dams and reservoirs) which make future, more detailed modelling a challenge.

Classification Methods for Inland Excess Water Modeling

Abstract Inland excess water floodings are a common problem in the Carpathian Basin. Nearly every year large areas are covered by water due to lack of natural runoff of superfluous water. To study the development of this phenomenon it is necessary to determine where these inundations are occurring. This research evaluates different methods to classify inland excess water occurrences on a study area covering south-east Hungary and northern Serbia. The region is susceptible to this type of flooding due to its geographical circumstances. Three separate methods are used to determine their applicability to the problem. The methods use the same input data set but differ in approach and complexity. The input data set consists of a mosaic of RapidEye medium resolution satellite images. The results of the classifications show that all three methods can be applied to the problem and provide high quality satellite based inland excess water maps over a large area.

Land Cover Change Investigation in the Southern Syrian Coastal Basins During the Past 30-Years Using Landsat Remote Sensing Data

Abstract Land cover change and deforestation are important global ecosystem hazards. As for Syria, the current conflict and the subsequent absence of the forest preservation are main reasons for land cover change. This study aims to investigate the temporal and spatial aspects and trends of the land cover alterations in the southern Syrian coastal basins. In this study, land cover maps were made from surface reflectance images of Landsat-5(TM), Landsat-7(ETM+) and Landsat-8(OLI) during May (period of maximum vegetation cover) in 1987, 2002 and 2017. The images were classified into four different thematic classes using the maximum likelihood supervised classification method. The classification results were validated using 160 validation points in 2017, where overall accuracy was 83.75%. Spatial analysis was applied to investigate the land cover change during the period of 30 years for each basin and the whole study area. The results show 262.40 km2 reduction of forest and natural vegetation area during (1987-2017) period, and 72.5% of this reduction occurred during (2002-2017) period due to over-cutting of forest trees as a source of heating by local people, especially during the conflict period. This reduction was particularly high in the Alabrash and Hseen basins with 76.13 and 79.49 km2 respectively, and was accompanied by major increase of agriculture lands area which is attributed to dam construction in these basins which allowed people to cultivate rural lands for subsistence or to enhance their economic situation. The results of this study must draw the relevant authorities’ attention to preserve the remaining forest area.

Towards a continuous inland excess water flood monitoring system based on remote sensing data

Abstract Inland excess water (IEW) is a type of flood where large flat inland areas are covered with water during a period of several weeks to months. The monitoring of these floods is needed to understand the extent and direction of development of the inundations and to mitigate their damage to the agricultural sector and build up infrastructure. Since IEW affects large areas, remote sensing data and methods are promising technologies to map these floods. This study presents the first results of a system that can monitor inland excess water over a large area with sufficient detail at a high interval and in a timely matter. The methodology is developed in such a way that only freely available satellite imagery is required and a map with known water bodies is needed to train the method to identify inundations. Minimal human interference is needed to generate the IEW maps. We will present a method describing three parallel workflows, each generating separate maps. The maps are combined to one weekly IEW map. At this moment, the method is capable of generating IEW maps for a region of over 8000 km2, but it will be extended to cover the whole Great Hungarian Plain, and in the future, it can be extended to any area where a training water map can be created.

Investigating sensitivity in a Central European landscape

In many parts of the world, global climate change strengthened by human activities has resulted in severe landscape changes. With rapidly changing environmental conditions and climate elements, many studies have focused on the causes and consequences of climate change. For at least 30 years, remote sensing has been used for the continuous monitoring of the Earth’s surface, providing opportunities for long-term evaluation of vegetation changes. In our previous research, we focused on indicators that show and qualify processes such as vegetation, groundwater, and soil on the Great Hungarian Plain. We identified the connections