Přemysl Štych

COMPARATIVE ANALYSIS OF THE IMPACT OF SLOPE INCLINATION AND ALTITUDE ON LONG-TERM LAND USE CHANGES IN CZECHIA

The aim of this article is to compare the effects of altitude and slope inclination on the spatial distribution of selected categories of land use. This study is based on Czechia’s LUCC database 1845–1948–1990–2000. The database contains nearly 9,000 basic territorial units (BTUs) and 8 LUCC categories that can be compared in all of the time periods mentioned. For the purpose of calculating the average altitude and slope inclination of all BTU s, a digital terrain model (DTM) of Czechia was created using interpolation methods. The average altitude and slope inclination of each BTU constituted the primary input variables for the correlation analysis. The strength of the relationship between these factors and the relevant categories was examined. Evidence concerning the increasing significance of inclination in the spatial distribution of arable land and grasslands after 1948 may be the most important finding. While in 1845, the first year in the database, altitude basically determined the location of arable land; after the World War II , there was a turn in this trend. Mainly in connection with the development of agro-industrial forms (the introduction of modern heavy machinery, the automation of modern cultivation methods, etc.), inclination became more important in determining the abandonment of arable land.

Land Use Changes in Czechia 1845–2010

The history of land use changes on the Czech territory since the very beginning is outlined; each subchapter deals with one important historical period. The emergence of organized agriculture (Neolithic revolution) is seen as the first period when humans began to influence nature on a certain scale. For thousands of years, however, land use changes were largely limited to inhabited lowlands. The transition from wilderness towards largely agricultural landscape accelerated only during the German plantation (eleventh–fourteenth centuries) when many forests were cleared in the frontier. As a whole, however, changes were rather modest until the eighteenth century. Really important economic and social changes that fundamentally influenced land use patterns have been taking place since the eve of Industrial Revolution. In that time, agricultural society was being gradually transformed into the industrial one at the beginning of the 20th century. The second half of the nineteenth century brought general modernization; agricultural land and arable land expanded to maximum. Since the turn of nineteenth and twentieth centuries, however, reverse trends are recorded: decrease of agricultural land (due to more intensive farming) and gradual expansion of forests. Land use patterns during the twentieth century were much influenced by turbulent political events like Czechoslovak independence (1918), World War II (1939–1945), Communist coup d’etat (1948), and restoration of democratic conditions (1989). The Communist legacy included outdated technology and production-oriented agriculture that could not compete on the international markets. The post-Communist period brought restitution of confiscated property (including land) and return to market-oriented conditions. In the most recent period, the accession of Czechia to European Union (2004) has also had profound effects on land use changes.

Selecting appropriate variables for detecting grassland to cropland changes using high resolution satellite data

Grassland is one of the most represented, while at the same time, ecologically endangered, land cover categories in the European Union. In view of the global climate change, detecting its change is growing in importance from both an environmental and a socio-economic point of view. A well-recognised tool for Land Use and Land Cover (LULC) Change Detection (CD), including grassland changes, is Remote Sensing (RS). An important aspect affecting the accuracy of change detection is finding the optimal indicators of LULC changes (i.e., variables). Inappropriately selected variables can produce inaccurate results burdened with a number of uncertainties. The aim of our study is to find the most suitable variables for the detection of grassland to cropland change, based on a pair of high resolution images acquired by the Landsat 8 satellite and from the vector database Land Parcel Identification System (LPIS). In total, 59 variables were used to create models using Generalised Linear Models (GLM), the quality of which was verified through multi-temporal object-based change detection. Satisfactory accuracy for the detection of grassland to cropland change was achieved using all of the statistically identified models. However, a three-variable model can be recommended for practical use, namely by combining the Normalised Difference Vegetation Index (NDVI), Wetness and Fifth components of Tasselled Cap. Increasing number of variables did not significantly improve the accuracy of detection, but rather complicated the interpretation of the results and was less accurate than detection based on the original Landsat 8 images. The results obtained using these three variables are applicable in landscape management, agriculture, subsidy policy, or in updating existing LULC databases. Further research implementing these variables in combination with spatial data obtained by other RS techniques is needed.

Influence of Natural Conditions on Land Use

This chapter deals with the influence of natural conditions on land use patterns. It also examines the human impacts on land use. Basic overview of natural conditions in Czechia is outlined with special regard to geology, climate and soils. Geological conditions are seen as the key factors that form landscapes and influence the diversity of soils. Climate, of course, also has profound influence on regional farming patterns; very warm (VW) and warm climatic regions are best suitable for agriculture. The biggest part of the Czech territory is covered by moderately heavy soils. Soil types are crucial for the spatial distribution of forests, arable lands, and permanent grasslands. Climatic zones and soil types are shown in maps. Regional patterns of Czech agriculture are discussed and the so-called less-favoured areas (LFA; important for allocation of EU subsidies) are explained. The history of human impacts on land use patterns over the past two centuries (covered by this research) has three phases. First, important changes in agriculture were taking place (changing balance between extensive and intensive farming). Second, forests began to shrink as more agricultural land was needed; with the advance of intensive farming, however, this process was reversed (“forest transition”). Third, new technologies and pressures exerted by the modern society brought a significant rise of built-up land and “other” areas. The ways how recent trends influenced the natural environment are explained. Changing political climate, especially the collapse of Communism and reintroduction of market conditions, has had profound effects on land use. The same applies to mining that caused large-scale devastation in some areas. Conservation programmes that accelerated after 1990 are seen as a “return to nature”.

Influence of Socio-Economic Conditions on Land Use

The main focus of this chapter is put on driving forces of land use changes. Authors distinguish among political, economic, social, technological, and cultural driving forces; the importance of different types much depends on how developed the society is. The greatest attention is devoted to social driving forces as these were behind the land use changes over the last 200 years especially in Europe and North America. Different phases of the “Complex Revolution of the Modern Age” are outlined and the spatial diffusion of new technologies are shown. In the nineteenth century Czechia, technological advance in agriculture and farming innovations were crucial and allowed to cultivate land in a more intensive way. Political driving forces of land use changes were especially important in the second half of the twentieth century. After Communists had seized the power in Czechoslovakia (1948), cooperatives and state-owned estates prevailed, private farming was suppressed. Later on, following the collapse of Communism in 1989, rural areas were significantly influenced by economic and social transformation. Socio-economic conditions in Czechia are outlined in brief, with special emphasis on geographical location and transport infrastructure. The concepts of centrality and peripherality are seen as crucial; core areas, neutral, and peripheral (marginal) regions are defined. The steady urban growth meant that most of the decision-making processes moved from rural areas to cities and towns—process that keeps continuing. The effects of transport infrastructure are studied too. The advance of railways seems to have a big influence on land use patterns in the fertile regions especially in the nineteenth century; later on, highways and modern roads became more important.

Land Use Changes in Selected Model Areas

Land use changes between mid-nineteenth century and present in four selected model areas are outlined. The analyses are based on research by individual plots and bring detailed results that cannot be obtained using conventional statistical methods. The model areas were chosen so that they would represent different landscape types in different parts of Czechia. The first one, Abertamy-Hřebecna, is a remote village located in the border mountains. The place has poor natural conditions and has been much influenced by the expulsion of German speaking population after World War II. In other words, human activities decreased significantly over the past 160 years; shift towards permanent grassland and forests was typical. Second, Kutliře is found in the fertile Elbe Plain in Central Bohemia and typifies the long tradition of farming. Unlike many other regions, farming remains crucial also nowadays, with emphasis on grain and other crops that require favourable soils and climate. Third, Cestlice is located near Prague adjacent to the main freeway, also in a quite fertile area. Due to the proximity of the capital city, however, the place has been recently much affected by suburbanization. In land use terms the result was a significant expansion of built-up and remaining areas. The last model area, Břekova Lhota, represents the so-called “inner periphery”, placed outside the major economic zones and part of the Less Favoured Areas (LFA). The traditional reliance on subsistence agriculture has been replaced over the past 150 years by a mix of agriculture and leisure activities (second homes). Changing patterns of land use are shown in tables for each of the model areas that include eight basic land use classes. Importance of aerial images as an evidence of land use/cover change is documented using an example of the mountainous cadastre Horni Rokytnice nad Jizerou.

Data Sources and Research Methods

Historical and current data sources and research methods in land use studies are described in this chapter. Regarding historical data sources, the Land Registry is mentioned as a primary source. Its long tradition spans almost 1000 years; from the second half of the eighteenth century Land Registry includes maps also. The so-called Stable Cadastre (data collected in the first half of the eighteenth century) presents an especially important source of historical land use data. Military Land Survey was a series of detailed land surveying covering the whole Austria-Hungary in three phases (eighteenth and nineteenth centuries). Maps produced by Military Land Survey had high quality and were often used during the following decades. Commencing mid-twentieth century, aerial photography brought new qualities and new possibilities into land use studies. Multispectral satellite images have been in use since 1970s. Creation and structure of the “LUCC Czechia Database: Database of long-term land use changes in Czechia 1845–2010” are described in detail. This database forms the main information source used by the research team. It includes cadastral data from 1845, 1896, 1948, 1990, 2000, and 2010. As the structure of land use data collected was slightly different in each of the above-mentioned years, compatibility of data must be secured in order to allow historical comparisons. Methods of land use change analyses are outlined, including various indices (development index, saturation index, index of change, ecological coefficients, etc.), typologies, and other quantitative methods. In selected model areas, detailed land use changes were studied. To do so, GIS technology was applied. Results include quantitative data as well as detailed spatial information.

Land Use Research

Basic terms, including “land use” and “land cover” are defined. Land use patterns are seen as a result of long-term interaction between humans and natural environment. Practical applications of land use research are discussed, namely with regard to land management and policy and land use planning. Later, the history of land use in the world is outlined. Four scientists that contributed most to land use research in the past are mentioned. First, Johann Heinrich von Thunen, who formulated the intensity theory and theory of crop zones. Second, Karl Marx, author of the term “differential ground rent”. Third, British geographer L. D. Stamp who is considered founder of modern land use research. Last, but not least, the Polish geographer J. Kostrowicki who focused on typology and classification of agricultural systems in the second half of the twentieth century. Current approaches in land use research in the world are also discussed. Special attention is given to the DPSIR model that works with “drivers” and “pressures”, “impacts” and “responses”. The multi-level explanatory scheme, formulated by Scottish geographer A. Mather, is seen as the most complex concept used in land use research so far. Mather worked with proximate, intermediate, and underlying factors and he is also the author of the “forest transition” concept. In Czechia, the first research projects focused on land use were carried out in the early 1960s. At the moment there are two main research directions: analyses of small areas, and complex land use studies carried out by the so-called “Prague school”. The latter studies often span a long period of time, starting in late eighteenth century. Old maps are utilized for comparisons; recently also remote sensing data have become available.

THE USE OF VEGETATION INDICES IN THE EVALUATION OF VEGETATION PHENOLOGY BASED ON MERIS DATA: THE CZECH REPUBLIC CASE STUDY

This article focuses on utilization of vegetation indices for vegetation phenology analysis based on multitemporal MERIS data. The model data set contained imagery acquired during the vegetation season of the year 2009 and it covered most of the area of the Czech Republic. Databases LPIS and GlobCover were used for spatial delimitation of the observed vegetation types. Firstly, a methodology of processing multitemporal MERIS data for atmospheric and geometric corrections is presented. The main part deals with the evaluation of spectral characteristic of the forest species and agricultural crops by means of vegetation indices. Results showed that the MTCI index is well related to the changes of chlorophyll concentration and it is a suitable measure for chlorophyll estimation from MERIS data. Indices fCover and LAI are very sensitive to the quantity of vegetation cover (biomass). Perspectives of the research regarding the planned missions of the satellites Sentinel 2 and Sentinel 3 are given in conclusion.

Multi-temporal analysis of vegetation reflectance using MERIS data in the Czech Republic

Abstract Accurate high temporal resolution data is a very important source of information for understanding processes in the landscape. High temporal and spectral resolution data enable the monitoring of dynamic landscape processes. For this reason, since 2008 a receiving station for Metosat, NOAA and Envisat data has been installed at the Department of Applied Geoinformatics and Cartography, Faculty of Science, Charles University in Prague. The aim of this study is to analyse the spectral characteristics of vegetation using MERIS data in the Czech Republic. Spectral characteristics of vegetation were examined both by analysing changes in reflectivity as well as by utilising vegetation indices. Vegetation in forests and agricultural land was evaluated. The results present the spectral characteristics of selected associations of vegetation based on MERIS data and a discussion of the methods of multitemporal classification of land cover.