Assessing Landscape Sensitivity Based on Fragmentation Caused by the Artificial Barriers in Hungary

Artificial barriers significantly disturb the landscape unit. Roads split the contiguous landscape units, thus basically modi fying their ecological characters. The more artificial barriers are constructed in the landscape, the more fragmented it is. Theref ore, the contiguous landscape unit is divided into two or more patches, weakening resilience and stability of ecological systems. During decrease in patch size, the stability reduces until the patch size is at its minimum viable or effective population size. In current study analysing the degree of fragmentation caused by artificial barriers in meso-scale landscape units (meso-regions) we can get an overall picture about changes in their stability and sensitivity. The major aims of this study is to investigate the fragmentation of landscape units caused by three types of artificial barriers (roads, railways and settlements) in micro-regions, and to measure the degree of fragmentation and its spatial-temporal (1990, 2011 and future scenario to 2027) changes using mathemat ical/ statistical analysis and landscape metrics (Number of Patches, Division, Landscape Splitting Index and Effective Mesh Size). By calculating landscape fragmentation metrics, the micro-regions are identified, which must be protected with high priority in the future. In the planning processes, type and position of artificial barriers could be more properly determined by calculation of these landscape metrics

Estimation of the Changes in the Rainfall Erosivity in Hungary

According to the forecasts of numerous regional models (eg. REMO, ALADIN, PREGIS), the number of predicted rainfall events decreases, but they are not accompanied by considerably less precipitation. It represents an increase in rainfall intensity. It is logical to ask (if the limitations of the models make it possible) to what extent rainfall intensity is likely to change and where these changes are likely to occur in the long run. Rain intensity is considered to be one of the key causes of soil erosion. If we know which areas are affected by more intense rain erosion, we can identify the areas that are likely to be affected by stronger soil erosion, and we can also choose effective measures to reduce erosion. This information is necessary to achieve the neutral erosion effect as targeted by the EU. We collected the precipitation data of four stations every 30 minute between 2000 and 2013, and we calculated the estimated level of intensity characterizing the Carpathian Basin. Based on these data, we calculated the correlation of the measured data of intensity with the values of the MFI index (the correlation was 0.75). According to a combination of regional climate models, precipitation data could be estimated until 2100, and by calculating the statistical relationship between the previous correlation and this data sequence, we could estimate the spatial and temporal changes of rainfall intensity

Tájak természetességének értékelése tájmetriai módszerekkel Magyarország példáján

A kutatás célja a tájmetriai mutatók alkalmazása a hemeróbia változásának vizsgálatában

A táj antropogén átalakítottságának térképezése Magyarország példáján

A vizsgálatok elemi egységei minden egyes, a hemeróbiát befolyásoló tényező elemzése során a 2006-os évben készült CORINE felszínfedettség térkép azonos felszínborítással jellemezhető foltjai voltak. Ezekre a területi egységekre vonatkozóan összegeztük majd átlagoltuk a hemeróbiát meghatározó tényezőket

Estimation of the changes in the rainfall erosivity in Hungary

According to the forecasts of numerous regional models (eg. REMO, ALADIN, PREGIS), the number of predicted rainfall events decreases, but they are not accompanied by considerably less precipitation. It represents an increase in rainfall intensity. It is logical to ask (if the limitations of the models make it possible) to what extent rainfall intensity is likely to change and where these changes are likely to occur in the long run. Rain intensity is considered to be one of the key causes of soil erosion. If we know which areas are affected by more intense rain erosion, we can identify the areas that are likely to be affected by stronger soil erosion, and we can also choose effective measures to reduce erosion. This information is necessary to achieve the neutral erosion effect as targeted by the EU. We collected the precipitation data of four stations every 30 minute between 2000 and 2013, and we calculated the estimated level of intensity characterizing the Carpathian Basin. Based on these data, we calculated the correlation of the measured data of intensity with the values of the MFI index (the correlation was 0.75). According to a combination of regional climate models, precipitation data could be estimated until 2100, and by calculating the statistical relationship between the previous correlation and this data sequence, we could estimate the spatial and temporal changes of rainfall intensity

New results on landscape boundaries

The correct delineation of geographical and landscape ecological units, being the fundamental territorial domains of both physical and human geography, is very important from the aspect of several other related disciplines as well. It is hard to tell how distinct landscape units, or landscape ecological units can be, from a statistical point of view. The present study investigates how welldefined (definable) geographical units (landscapes, landscape types) are in a statistical and mathematical sense. Since landscape forming factors do not exhibit distinct boundaries either, during the analysis it is better to consider them as ecotones. Integration of factors, and the unclear interpretation of present landscape boundaries do further complicate the sound mathematical evaluation of the studied geographical units. In order to resolve these problem GIS techniques were applied

A hemeróbiaszint változásának vizsgálata tájmetriai módszerekkel Magyarország példáján

A tanulmány a tájmetriai mutatók változási tendenciái alapján mutatja be Magyarország hemeróbiaszintjének változását

Magyarországi kistájak hemeróbiaszintjének értékelése tájmetriai mutatók és a Természeti Tőke Index közötti kapcsolat elemzésével

A vizsgálat során a tájmetriai mutatók közül a LPI (Largest Pach Index), NP (Number of Paches), a MPS (Main Pach Size), az AWMPFD (Area Weighted Mean Patch Fractal Dimension), PRD (Perimeter Area Ratio Distribution), és a MSI (Mean Shape Index) tájindexek természetesség értékeléséhez történő használhatóságát elemeztük. Ezen tájmetriai mutatószámokat kiszámítottuk a 2000-es év felszínborítását tükröző 1:50000, és 1:100 000 méretarányú CORINE adatbázis (EEA, 2000) alapján az ArcGIS szoftver V- LATE kiegészítő panel segítségével. A MÉTA adatbázis terepi felmérései alapján számított Természeti Tőke Index kistáj szintű értékei közül csak azokat a kistájakat vontuk be a vizsgálatba, melyekben a feldolgozott terepi adatok aránya elérte a 30% -ot, így összesen 212 db kistáj adatait hasonlítottuk össze a kistájra kiszámolt tájmetriai paraméterekkel. A kapott elempárokat Statgraphics szoftverrel normalizáltuk, majd kivettük az elemzett adatok köréből azokat az adatpárokat amelyek a normál eloszlást torzították. Eredményeink alapján sikerült meghatároznunk a tájak hemeróbiaszintjének jellemzésére leginkább alkalmas tájmetriai mutatókat