Current lanscape in the neighbourhood of open cast mines in northern Bohemia

- 1 - UNIVERSIDAD POLITÉCNICA DE VALENCIA ESCUELA POLITÉCNICA SUPERIOR DE GANDIA Licenciado en Ciencias Ambientales "Current Landscape in the neighbourhood of Open Cast Mines in Northern Bohemia" TRABAJO FINAL DE CARRERA Autor/es: Alejandro Hidalgo Escrihuela Director/es: Ivana Kasparova / Jesus Martí Gavilà GANDIA, 2011 - 2 - - 3 - List of contents 1. Abstract……………………………………………………………………………………..4 2. Introduction…………………………………………………………………………………5 3. Literature review……………………………………………………………………………6 3.1.1. Ratclidde………………………………………………………………...…….6 3.1.2 Classify land use by GIS and Khat coefficient:………………………...……...8 3.1.3. A landscape approach for quantifying land-use and land-cover change……...10 3.1.4. Classify and evaluate the land by interviews..………………………………...11 3.1.5. Biosafe……………………………………………………………..……..…...12 3.1.6. Identifying patterns of land-cover change..………………………….………..14 3.1.7. Geographical landscape change analysis based on cadaster maps and land registers…………………………………………………………………………….…16 3.1.8. Comparison my method with these other methods…..……………..……...…..18 3.1. Characteristics of the area…………………………………………………………...20 3.2. CORINE land cover…………………………………………………………………22 3.3. Open pit mining coal brown………………………………………………………....23 3.4. Impacts from open cast mining coal Brown………………………………………....23 4. Method…….……………………………………...………………………………………….26 4.1. Methodology...………………………………………………….…………………....26 4.2. Data check……………..……………………………………………………………..28 4.2.1. Nomenclature………………………………………………………………..29 4.2.2. Aerial photographies………………………………………………………...34 5. Results………………………………………………………………………………..………36 5.1. Comparison of land uses in the study area …………………………………..…...….36 5.2. Proportion stable land use and unstable land use…………………………........…….38 5.3. Comparison results about original map and vectorized map……………...……..…...39 6. Discussion: Correction method of these impacts.………………………………...…………..42 7. Conclusion…………………………………………………………………………………....45 8. Maps………………………………………………………………………………………….46 9. References…………………………………………………………………………………....47 Abstract - 4 - 1. Abstract: The classification of the landscape through different types of uses, it will be the basis of this classification of the work area. This study will explain in detail the method by which to classify the composition land units and the resulting land use composition. Using the GIS (geographic information system that integrates hardware, software and data for capturing, managing, analyzing and displaying all forms of geographically referenced information) with the orthophotos identify are identified the different types of land use of the work area. Land uses refer to the existing activity in this area at the time. GIS have proved to be very effective not only for determining the different types of landuse in an area, but also for the classification collecting valuable information for interpreting and it can determine trends in land use by comparing these maps from different years, very useful to see how it evolves and how it will do in the future, allowing to make decisions in advance. For land classification there are several methods, some also work using the GIS computer program but instead of classifying the land regarding its use, classified by their landscape value, others through the use of land of this area not only the actual but also in past years. In this project included different methods of classification, with a brief explanation of their methodology. Although some of these methods in addition to making the corresponding classification are also methods of analysis of changes in the work area over time. In this case working only with a layer of a specific year and I did not do this kind of study. Therefore, after the vectorization and correction of the original layer, I made an assessment of the data, grouped the values of land use in stable and unstable. Commenting on the corrected changes, the original data and the proportion of different land use types, I mean making an ecological assessment, including the impacts of open pit mining and possible corrective measures both during activity and abandonment. Introduction - 5 - 2. Introduction: This study of land classification is based on the use made of the land, land use is characterized by its physical characteristics, where in this area at north of the Czech Republic predominant land use is derived from the mining activity and most of the other existing uses are related to this activity classification of which is carried out through GIS. Noteworthy in this area the importance of open pit mining of coal, much of the land is allocated to this activity. In this study in addition to the classification zone, I also detail the most important impacts on the environment caused by this mining activity, both during construction and decommissioning phase. Due to this method of land classification, I can observe that the proportion considered as ecologically stable land are present in the area and as distributed each type of land use on the map. Many of the computer-modelling approaches used in science are based on quite complicated and expensive techniques such as hexagonal-packing models, general neutral models, percolation theory, cellular automata and others, which would not translate easily into landscape-planning practice. This method is based on a visual classification based on aerial images, where from these I make the appropriate classification of land use for their activity and estimate the impacts of each activity. Literature review - 6 - 3. Literature review: At this point I will make a brief summary of other methods used for land classification. In contrast to my approach in these methods to use layers or data from two different years that allow to compare and evaluate changes between years. This section also explain besides that data are based, methodology, ... and conclusion of each of the methods. 3.1.1.Ratclidde: The purpose was to develop an evaluation of the land use of the area, it was to give an importance value for conservation to each land use. Thus, measures are needed which reflect both the character of the landscape, and its importance locally and regionally. Ratclidde (1977) developed a set of assessment criteria for nature conservation. He suggested 10 criteria, some of which are species-based such as diversity and rarity, others are related to spatial arrangement (e.g. size, position) and others are essentially subjective measures of importance. Therefore, land uses which have a long history of intensive management are less natural and thus less valuable to nature conservation than those which have undergone minimal or very careful management. Rare or threatened habitats such as ancient semi-natural woodland and calcareous grassland are highly fragile, in that they have a limited existing distribution and a history of loss to development pressure, and are therefore valuable The second criterion used was patch size which has two aspects. Firstly, large patches of a very natural land use have a high landscape value and large patches hold habitat more number of species than smaller patches, whereas similarly sized patches of a heavily managed land use such as arable farming will have low landscape value. The third criterion reflects the importance of the land use and combines local and regional considerations. The area of land use is expressed as a proportion of the total for the county so that less valuable landscapes such as arable land and plantation woodland are, if regionally rare, highly valued. Literature review - 7 - This GIS-based method to assess the landscape value, land-use data were used in conjunction with spatial statistics with the aim of producing a simple decision-making tool for the evaluation of landscape importance. The classifications were based on descriptive accounts of topography, land use and visual elements in the landscape. In this method aerial photographs were interpreted for their land uses. The three major categories of grassland, woodland and other land were separated into subclasses. The land-use data were transcribed to hardcopy and then digitized as field/patch polygon boundaries and labels in ARC/INFO GIS. The data layers for each year were thoroughly checked for errors and processed to give polygon topology. Ratclidde performed a land classification based on three criteria; these were land use, field/patch size and land use importance. The first of these associated land use with perceived landscape value based on ecological value, so that deciduous woodland and calcareous grassland were given the highest scores and arable land, improved grassland used for grazing and coniferous plantation are scored lowest. The second criteria was the patch size of each land use. The patches were assigned different scores based on the range of sizes of each land use in the study area. Quintiles were calculated for each land use. Land-use importance was the third criteria used and was expressed as the amount of each land use as a proportion of the total for the county. The method consisted a summation of scores according to the assigned landscape values for each patch. LV TOTAL1 = LV LU + LV AREA Where, LVTOTAL1 is the total landscape value; LVLU is the landscape value due to land use type and LVAREA is the landscape value due to patch size. In Ratclidde’s study, each land use categories which are identified from aerial photographs we calculate the number of polygons, the total area and the percentage. Literature review - 8 - A landscape assessment scheme is presented based on land-use type and some simple landscape indices. Land-use data were interpreted from aerial photographs and are used with a GIS to calculate patch size and relative importance of the land use. The use of GIS for landscape assessment at fine resolution is essential since large quantities of data are generated. The technology is a valuable tool in the assessment process allowing rapid manipulation of spatial and attribute data for the development of landscape indices. Although start up costs were potentially very high it is argued that the long-term benefits such as access to information and efficiency of data manipulation outweigh the short-term costs (Lee et al., 1999). 3.1.2. Classify land use by GIS and Khat coefficient: Khat coefficient focuses on the quantitative and qualitative analysis of the spatio-temporal changes that have occurred in an area, and interpretation of the factors driving these changes. Photointerpretation of historical aerial photographs by Geographic Information System (GIS). Land cover mapping of recent history based on black / white aerial photographs were used. Orthorectification and mosaicing of the aerial photographs by applying photogrammetric methods with high accuracy ensured data quality and allow the further processing of the earth observational data. The images were radiometrically corrected prior to the mosaic process to adjust black and white tonal variation by using an empirical linear spectral normalization technique (Hall, Strebel, Nickeson, & Goetz, 1991). Also the land cover mapping was based on multispectral (2.4 m) and panchromatic (0.60 m) Quickbird images. The satellite data were orthorectified using a 20 m pixel size Digital Elevation Model (DEM) with a maximum Root Mean Square error (RMS) of 1 m using ERDAS Imagine 9.1 software. Additionally, the two image components were merged by applying the GrameSchmidt method of image fusion within the RSI ENVI 4.6 software (Laben & Brower, 2000). Literature review - 9 - LCLU (Land cover / land use) categories were identified based on visual stereoscopic photointerpretation of panchromatic aerial photographs. It was developed a common classification scheme. The definition of the thematic categories relied on the Level I scheme of Anderson’s LCLU classification system (Anderson, Hardy, Roach, & Witmer, 1976) and includes: agricultural land (cereals and other irrigated crops, Populus canadensis and Robinia pseudoacacia plantations); barren land (representing only alluvial areas); urban or built-up areas; forest land (mostly Populus alba, Fraxinus angustifolia subsp. oxycarpa, Quercus robur subsp. pedunculiflora and Ulmus procera); rangelands (riparian scrub, Arundo donax reedbeds); inlandwaters; wetlands and sea. Additionally, to measure the similarity between the different maps and assess the stability of changes, it was estimated the Khat Coefficient of Agreement for the whole area (global stability) and the Conditional Khat Coefficient of Agreement for each category as (Jensen, 2005): Where bK Coefficient of Agreement for the whole area, bKi Conditional Coefficient of Agreement for each category, Pii representing the proportion of the landscape where a category i shows persistence between the first and last date of the analysis, and Piþ, Pþi representing the proportion of the landscape in each category at the first and last date, respectively. The Coefficient of Agreement ranges between - 1 to 1, indicating the degree of similarity between the maps, and having been adjusted for chance agreement. Qualitative and quantitative information on spatio-temporal LCLU changes and landscape dynamics was obtained by analyzing multitemporal earth observational data. The different components of LCLU changes that were identified, allowed the better understanding of the transformation processes and the driving factors (Mallinis et al., 2011). Literature review - 16 - levels (i.e. the rural district). Thus, the aim of an area-wide landscape classification was achieved at the expense of spatial resolution. There are many possible ways to classify a landscape depending on the nature of input data and scales. The use of k-means cluster analysis has proven to be a simple and workable approach to classify patterns of recent and historic land cover for large areas at the district scale. The authors conclude that the combination of remote sensing data with agricultural statistics is suitable to identify patterns of current land cover and land-cover dynamics at the landscape scale (Reger et al., 2007) . 3.1.7. Geographical landscape change analysis based on cadaster maps and land registers It's a cultural landscape information system that assigns a value to the diachronic approach for direct applications within the planning process. In landscapes can be seen as topological variations of vegetation cover, and it is possible to determine these landscape units based on the various forms of anthropogenic use. Analyses were carried out by the use of GIS. The analysis of cultural landscape change was generally based on a variety of sources, including topographic and historical maps, aerial and satellite photographs, land registers with geodetic survey maps and land plot records, original surveys of relict species (where available), as well as various statistical and archival data. A state of the landscape, which represents the traditional land use system, should be the starting point for the diachronic analysis of landscapes. From the cadastral data and remote sensing data, it was determined each type of land use of the area. Likewise, the continuity of the sources was of great importance. The authors made time slices with cadastral maps, land registers and complementary data from agricultural administration. These data included particular information regarding the soil quality and the owner of the land parcel. It detailed the names and ages of farm owners as well as the type of agricultural activities and information on successors. Such socio-economic data were supplemented with spatial data that were derived from a digital terrain model (DTM), i.e. altitude, slope gradient and exposure. Literature review - 17 - The GIS served in this method predominantly to analyze the changes and to calculate the proportion of each land use type. The conceptual model for the GIS is, therefore, determined by land-register data. As a consequence, the cadastral landscape model consisted of types of land use, ownership status and other attributes (mainly for tax purposes). Thus, a database of land plot attributes can be compiled from data in older land plot records contained in the archives of the land register, and by entering the current data of the automated land tax register, which includes land cover, soil quality and property data. Nevertheless, in a diachronic comparison and in specifications of the land-register data, the terminology for the basic category “type of use” was adapted, because it may vary and sometimes change over time. The implementation of GIS through the use of a vector model (in the present case, simple and complex polygons for sub-plots by type of land use) is consistent to describe objects in the real world. Then, the vector database was created on the basis of current and historic cadastral maps by digitising the land plots. The different time slices of our study were handled in a layer GIS model. A layer was created for each time period, beginning with the latest, and presumably most accurate cadastral map (if already available, by use of digital data), and working backwards in time to the earlier temporal layers. The older maps only served to identify the changes, possible distortions and projection errors in the historical maps needed to be visually corrected. The conversion of data into a GIS offer more than simply a visual interpretation of thematic maps or statistical evaluation (plot use balance), because this geo-relational approach also permitted an assessment of development trends. It thus is possible to determine various changes in land use according to categories of change. The use of a land record-based GIS can help to find explanations for cultural landscape change on a large-scale (1:5000) basis. Standardized approaches to changes in land use, including cultural and environmental factors, are developed in order to understand which plots are involved, and why changes occur on these plots. The GIS-based simulation model assumes that the future parcel utilization is determined by the characteristics of the various attributes in the three categories of ownership structure, parcel structure and habitat quality. Literature review - 18 - The attribute queries result primarily from a combination of attributes. Here one must be aware that these operations can simulate a causal chain of events but no definite outcome can be predicted. Ultimately, the simulation determines for each individual parcel whether a continued or subsequent use is anticipated by the owner or whether, under certain circumstances, the plot will become part of the leasing market, lay fallow or be completely abandoned. The land-register based diachronic GIS proved to be advantageous especially for the quantification and description of landscape change at the local level. Land-register based diachronic GIS seems to offer many opportunities for landscape planning. For example, it can be employed to quantify the surface areas of habitat types, and to assess how, when and why the sizes of different habitats have changed (Bender et al., 2005). 3.1.8. Comparison of methods In all these methods mentioned above, a classification of land is made, each method using different techniques. My classification is based on the use of GIS, there are also methods that work using GIS, but some of these are based on other criteria. Highlight the classification of land by interviews method in which the land classification is performed based on interviews with citizens, political groups, associations, companies, ... in this method is given great importance to the cultural value of the soil because many respondents valued the land from the culturally point. The problem with this method is subjective, because each interviewee gives a value to each land use based on their self interest. Many methods rely on GIS for classification, for example the method that performs a land classification based on the number of species living, giving a value to each species according to their rarity and condition of hazard that is, for each habitat or ecotope. Ecotopes are classified into ranges according to their biological value There is a method that is similar to mine when classifying the land, and is to perform the classification of land from aerial photographs, but does not express the result in relation to land use, but from these photographs defines the areas and then given a value depending on the patch size, land use and importance of land use. Literature review - 19 - There is another method that works with a cadastral landscape model which is composed of types of land use, ownership and other attributes (mainly for tax purposes). This method also uses the GIS software to work with all the cadastral information and interpret this information in layers. This method is very useful for landscape planning. Literature review - 20 - 3.2. Characteristics of the area: The study area covers brown coal open cast area open. The area is located in the northern part of the Czech Republic (Fig. 3.1), it's closed to the town of Vrskmaň and very near to Most, at an altitude of 233 m. north center near geographic coordinates 13° 50´ E, 50° 50´ N. Besides this main activity there are many crop fields. The forestry typology belongs to the deciduous forest type, principally coniferous. Here I show an aerial photograph in which the study area is marked in red (Fig. 3.2) . Fig. 3.1: Location of study area in Czech Republic Source: Cenia_t_podklad Literature review - 21 - Fig. 3.2: Aerial photo of study area Literature review - 22 - 3.3. CORINE : Corine land cover Thematic mapping of the biophysical cover of the area's surface must be approached considering these aspects, land cover essentially that concerns the nature of features (forests, crops, water bodies, bare rock, etc.) and the land use that is concerned with the socio-economic function (agriculture, habitat, environmental protection) of basic surfaces. My study shows the land cover project's technical unit that the use of satellite data necessitate detailed consideration of the unit area to be mapped. Main characteristics of the each unit of land use, these land use correspond an area which is homogeneous (grass, water, forest, etc.) or to a combination of elementary areas (homogeneous as defined above). The unit must represent a significant area of land, it is clearly distinguishable from surrounding units. The unit area has two functions to be conceptual tool for land cover analysis; one tool for reading and organizing space borne remote-sensing data Furthermore, irrespective of how they have been processed, data acquired by space borne remote-sensing systems do not provide a representation of the actual land cover situation; nor can land cover be mapped in all its complexity/diversity. Given these circumstances, each unit of land use must meet two requirements which are it must provide the thematic data required by the users, in this case land use, and it must provide an acceptable representation of reality. Based on this logical framework, the selected nomenclature meet a certain number of requirements; all Community territory is classified; in other words there can be no heading for 'unclassified land' and the headings must correspond to the needs of future users of the geographic database, in this case the land use (Corine – land cover) Literature review - 23 - 3.4. Open mining pit coal brown Open pit mining is an industrial activity of high environmental, social and cultural, and industrial activity is also unsustainable by definition. This is a non renewable resource whose extraction is limited. Technical innovations that mining has experienced since the second half of this century have radically altered the activity so that it went underground veins of the use of high quality to the farm - in open pit mines - of lower quality ores, disseminated in large deposits. Open pit mining removes the top layer or overload of the land to make available the vast deposits of low-grade. To develop this process, it requires that the site covering large areas and are near the surface. As part of the process, huge craters dug, which can have more than 150 hectares and over 500 meters deep. Vaughan (1989) considers that "in environmental and social terms, no industrial activity is more devastating than open pit mining”. 3.5. Impacts from open cast mining: Mining activities in each one stages produce specific environmental impacts. Broadly, these stages would be: - Prospecting and exploration of mineral deposits, - Development and preparation of mines - Exploitation of mines - Treatment of minerals obtained in the respective plants in order to obtain marketable products. The main environmental impacts caused by open pit mining in its exploitation phase are: Deteriorating air quality: Mining has a large effect on air quality. Due to the need to blast through rock to reach a mineral, the air is contaminated with solid impurities, such as dust and toxic fuels or inert, capable of penetrating into the lungs, during various stages of the process. Coal mines releasing methane, which contributes to environmental problems, since it is a greenhouse gas. Methane is sometimes captured, but only when economically feasible. Literature review - 24 - Some cooling plants can release ozone-depleting substances, but the amount released is very small. Also impact on water: Mines use a lot of water, although some water can be reused. Sulfurcontaining minerals, when oxidized by contact with air, through mining are acid, sulfuric acid. This, when combined with trace elements, negative impact on groundwater. Another way in surface and ground water are affected by the tailings dams and waste rock piles, because are a source of acid drainage water. Chemical deposits of surplus explosives are generally toxic, and increase salinity of the water and pollution of mine. Groundwater can be contaminated directly through "in situ" mining, in which a solvent is filtered in rock untapped, leaching of minerals. In addition, there may be a decline in groundwater levels when these are sources of fresh water for mineral processing operations. Land: There are many environmental concerns about the effects mining has on the land. Mining involves moving large quantities of rock, and in surface mining, overburden land impacts are immense. Overburden is the material that lies over top of the desirable mineral deposits that must be removed before the mining process begins. Moreover the use of heavy machinery creates roads which leads to soil compaction and encourages soil erosion. Some mines make an effort to return the rock and land to its original appearance by returning the rock and overburden to the pit that they were taken out of. Toxins used in the extraction of minerals can permanently pollute the land, which make makes people not able to farm in certain places. Open-pit mining leaves behind large craters that can be seen from outer-space. Ecosystem Damage: Mines are highly damaging to the ecosystems surrounding them. Mining destroys animal habitats and ecosystems. Pits that mines create could have been home to some animals. Also, the activity that surrounds the mine, including people movement, explosions, road construction, transportation of the goods, the sounds made, etc. are harmful to the ecosystems and will change the way the animals have to live, because they will have to find a new way to cope with the mine and live around it. Impact on flora: involves the removal of vegetation in the area of mining operations and a partial destruction or modification of the flora in the surrounding area due to the alteration of the water table. It also causes pressure on existing forests in the area, which can be destroyed by the process of exploitation or the expectation that it occurs. Literature review - 25 - Impact on wildlife: the wildlife is disturbed and / or driven away by noise and pollution of air and water, raising the level of sediment in rivers. In addition, the erosion of barren waste piles can particularly affect aquatic life. Poisoning can also occur in water content residual reactants from the area of operation. Health and Safety: Mining can be very safe, but often it is extremely dangerous. The biggest health risks are from dust, which can cause breathing problems. Usually the problems are respiratory, mainly due to inhalation of dust and smoke, but there are also by contact. Common to all diseases of mining is their evolution that is long and protracted being considered as a chronic disease. As pneumoconiosis, fibrosis pulmonary and lung cancer. Energy Consumption: Mining requires vast amounts of energy. The ore and rock has to be transported great distances by large vehicles, which require a large amount of energy in the form of gasoline. Pneumatic equipment, which is used a lot in the mining industry, also takes energy. Smelting ores and metal requires lots of energy. Impact on populations: causes conflicts over use rights to land, giving uncontrolled rise to human settlements, causing a social problem. Can cause a decrease in the performance of farmers due to poisoning and changes in the course of the river. On the other hand, can also cause a negative economic impact by the displacement of existing local economic activities current and / or future. Impact landscape both during operation and after operation: left deep craters in the landscape. Its removal may lead to such high costs that may prevent the exploitation itself. It is a very significant impact because can be appreciated the crates and waste deposits from great distances, severely deteriorating the visual quality of landscape that leads to a decrease of the tourist attraction. Another factor is noise. Which produce the machinery used during the extraction process, explosions, vehicle traffic ... All these affect the population of the surrounding areas, disrupting normal life. And it affects not only humans but all living organisms from the surrounding areas. Method - 32 - In some cases, distinguishing between continuous urban fabric and discontinuous urban fabric can be difficult. The boundary can be set principally by determining the presence and quantity of vegetation. 9.2 Industrial companies and warehouse Artificially surfaced areas (with concrete, asphalt, or stabilised, e.g. beaten earth) devoid of vegetation, occupy most of the area in question, which also contains buildings and/or vegetated areas. Typically, the texture will be heterogeneous (mixture of large buildings, car parks, sheds, etc.) represent entire industrial or commercial complexes, including access roads, landscaped areas, car parks, etc. The category also includes major industrial livestock rearing facilities, waste water treatment plants, cement fish farming ponds. Industrial or commercial units located in continuous or discontinuous urban fabric are taken into account only if they are clearly distinguishable from residential areas 9.3 Mine, sandpit, gravelpit, concrete surfaces, solar powerplants Areas with open-pit extraction of industrial minerals (sandpits, quarries) or other minerals (opencast mines). Also includes spaces under construction development, soil or bedrock excavations, earthworks. Quarries are easily recognisable on satellite images (white patches) because they contrast with their surroundings. Disused open-cast mines, quarries, sandpits, slate quarries and gravel pits (not filled with water) are included in this category. However, ruins do not come under this heading. Sites being worked or only recently abandoned, with no trace of vegetation, come under this heading. Where vegetal colonisation is visible, sites are classified under the appropriate vegetal cover category. This heading includes buildings and associated industrial infrastructure (e.g. cement factories). 9.4 Roads It corresponds to asphalt roads in the area of study. Category is composed mainly of large road intersections with associated infrastructure and planted areas, and large marshalling yards. I use nomenclature used at the various scales must enable me to identify, analyse and monitor land use in the areas. Generally, coefficient of ecological stability of the landscape is formulated as the proportion of ecologically relatively stable and ecologically relatively unstable areas. Method - 33 - Table 4.1: Legend of land uses of study area Ecologic Landuse Unit U 1,1 Bare soil U 1,12 Harvested field U 1,13 Poppy field U 1,14 Poppy field U 1,2 Harvested U 1,3 Wheat field U 1,5 Oaks U 1,7 Corn field U 1,8 Colza field S 10,0,1 Forest reclamation height > 2m U 10,0,2 Forest reclamation height 1 - 2m U 10,0,3 Forest reclamation height 0,5 - 1m U 10,0,4 Forest reclamation height < 50cm U 10,0,5 Dumps U 2,1 Clover S 2,3 Mesophilous meadow S 3,1 Wetland with prevailing herbaceous layer: reeds, sedge S 4,0 Ruderal species, fallow (left field) - with trees up to 10% S 4,0+4,1 Plate trees + Ruderal especies, fallow S 4,1 Plates trees - grown ditches, limits, riparian vegetation, etc. S 4,2 Covered by grasses with scattered trees, abandoned fields U 4,3 Bare rock with some scattered vegetation U 4,4 Manure heap and junkyard U 4,5 Abandoned field without vegetation S 6,1 Deciduous forests S 6,3 Mixed forests (coniferous and deciduous) S 7 Fish ponds, pools, rivers U 9,1 Continuous urbanized area U 9,2 Industrial companies and warehouse U 9,3 Mine, sandpit, gravelpit, concrete surfaces, solar powerplants U 9,4 Roads Source: Self elaboration. Where U means unstable ecological land use and S means stable ecological land use. Method - 34 - 4.2.2. Aerial photographies: I used these aerial photos because land cover methodology requires the use of such photographs. Along with the standard topographic maps, aerial photographs play a major role in the land cover project. They were used to determine the exact boundaries of units which are not resolved clearly on the satellite image and to verify and validate the results of the land cover mapping. The photographs help to identify and delineate the various land cover categories by their spatial resolution, which is considerably greater than that of Earth observation satellite sensors (1 to 3m, as against 20 to 80m), and by the three-dimensional view they provide through systematic 60% overlap coverage of the successive photos. Although the aerial photographs themselves are not included with the initial ancillary documentation (since they are used only as needed) the list and flightline index maps of photographs which may be of use, are part of the ancillary data. Use of aerial photographs Through observation of aerial images, overlapping on my study layer makes it possible to identify the following categories of land cover: Natural vegetation - Forest: clearly visible by the height and shape of trees. The color on the satellite false-color image suggests that it is a coniferous forest. - Sclerophyllous vegetation: this can be identified from the density and height of the shrubs visible on the photo. - Reclamation forest: it is possible to identify individual trees and low vegetation. - Scattered habitation: easy to identify. Method - 35 - Artificial land - Complex cultivation patterns: the air photos clearly depict the complexity of the field pattern and the occurrence of grassland, orchards and crops. - Land principally occupied by agriculture, with areas of natural vegetation: while the image suggests a wooded area, the photographs show overlapping agriculture and forestry. - Urban and industrial areas are very easy to identify by their characteristic colors. - Highways and roads are linear features that connect urban areas, so they tend to be useful for determining certain areas, because they limit the different types of land cover categories. Results - 36 - 5. Results 5.1. Comparison of land uses in the study area: After performing the classification of the land use and considering the use of land from each area, I made the calculations respective areas of each polygon and have calculated the total area of each land use, I sum all the polygons with the same value. The results are shown in Table 5.1 Where each land use is present in my study area with total area of each, the share of each land use compared to the total area of the area and the number of polygons that exist for each type of land use. Table 5.1: Proportion of land uses of study area Land use text Landuse Area (m2) Proportion % N° polygons Bare soil 1,1 100691 0,24% 1 Harvested field 1,12 230602 0,55% 2 Poppy field 1,13 76776 0,18% 1 Poppy field 1,14 537420 1,27% 4 Harvested 1,2 8067176 19,11% 57 Wheat field 1,3 1121490 2,66% 10 Oaks 1,5 724299 1,72% 8 Corn field 1,7 294297 0,70% 3 Colza field 1,8 38078 0,09% 1 Forest reclamation height > 2m 10,0,1 1732481 4,10% 4 Forest reclamation height 1 - 2m 10,0,2 1188658 2,82% 9 Forest reclamation height 0,5 - 1m 10,0,3 177224 0,42% 2 Forest reclamation height < 50cm 10,0,4 1396592 3,31% 8 Dumps 10,0,5 594581 1,41% 4 Clover 2,1 9413 0,02% 1 Mesophilous meadow 2,3 204654 0,48% 5 Wetland with prevailing herbaceous layer: reeds, sedge 3,1 174467 0,41% 6 Ruderal species, fallow (left field) - with trees up to 10% 4,0 861456 2,04% 18 Ruderal especies, fallow 4,0+4,1 361823 0,86% 2 Grown ditches, limits, riparian vegetation, etc. 4,1 1440310 3,41% 28 Covered by grasses with scattered trees, abandoned fields 4,2 300336 0,71% 7 Bare rock with some scattered vegetation 4,3 320895 0,76% 6 Manure heap and junkyard 4,4 13035 0,03% 1 Abandoned field without vegetation 4,5 497355 1,18% 7 Deciduous forests 6,1 497388 1,18% 2 Mixed forests (coniferous and deciduous) 6,3 3141158 7,44% 18 Fish ponds, pools, rivers 7 166085 0,39% 6 Continuous urbanized area 9,1 1156083 2,74% 4 Industrial companies and warehouse 9,2 1184519 2,81% 20 Mine, sandpit, gravelpit, concrete surfaces, 9,3 15427210 36,54% 4 Roads 9,4 188065 0,45% 3 TOTAL 42224616 100% 252 Source: Self elaboration. Proportion of land use respect total area, area of each land use in square meters and number of polygons. Results - 37 - Also I classified land uses into two groups, stable areas like forests, waters, grasslands and unstable areas like arable lands, built-up and disturbed areas, industrial sites etc. . The predominant land use is 9.3 (Mine, sandpit, gravel pit, concrete surfaces) is because my classification is made in an area where mining is of great importance. This kind of land use is the 36.53% of the total area that is one third of the territory. This land use represents not only the open cast mining areas but also storage areas for waste from the extraction, sanders, gravel and concrete surfaces adjacent to mining areas. Clearly the nature and activities in this area will include the use of land in the unstable group. This land use is only made up of only four polygons, all polygons are large, there is especially a polygon (FID polygon nº 117) which constitutes a large part of the map and is located in the central area of the studied area, which area is 15.251.838 square meters. Unlike other uses, this land use 9.3 is represented by very large polygons because representing the 36.54% of the total area of the map in only 4 polygons and in others land uses can see that they are composed of many polygons but much smaller size, which means that land use is much more concentrated, because its activity required it and is not as dispersed as other land uses that are represented as spots patches the map. Another land use is harvested field, land use 1.2 that represents a very important area. This land use is very abundant in the Czech Republic, in fact it's the second most widespread land use in the area. In this land use we can find crop fields. All land uses 1. are crop and lands basically represent several types of crops. In particular land use 1.2 is the most abundant by far to the others with a 19.10% regarding the total area of the zone. Apart from the mining activity which is the main resource of the area, consider that a percentage of the population lives off also of the crops. Land use 6.1 and 6.3 represent forest areas, both together constituting 8.60% of total area, with a total of 20 polygons. These forest communities have been greatly reduced by residential areas that fragment the forest area, also implementation of crops which have reduced the forestry area, but have mostly fallen by the implementation of the open cast mines that occupy a very important area in this zone. When the mines are abandoned because they are no longer economically profitable or for another reason, a way to restore this area of environmental impact would be recovered through reforestation with native species in the area. Also I must emphasize forest of less 50 cm height area, with very low vegetation, which area is 3.31% of total area. They are easy to identify areas and are usually found in areas near mining operations. Results - 38 - Other land uses, should be noted, land use is 9.1 (2.73%) are residential area mainly composed of urban houses. In the map we can observe four main population centers, these centers are similar in size and are surrounded by grass lands. Another use of unstable land is 9.2, which are all areas of industrial activity, where we see warehouses, manufacturing facilities and more industrial facilities. All these facilities are connected by highways and roads between them and residential areas and sometimes crossing a forest area, causing fragmenting action. Land use 9.4 includes all paved roads in the study area; the area is small size because it is a linear land use. The overall trend of landscape changes shows a considerable decrease in the structural heterogeneity of the landscape, and especially in the agricultural landscape. 5.2. Proportion of stable landuse and unstable landuse: Proportion between these two groups (stable and unstable land use) will indicate us the intensity in which the soil has been altered from their natural land use, indicating the influence of man as it has been over this area. It's the proportion between ecologically stable and unstable lands from the environmental point (table 5.2). Table 5.2 Proportion between stable and unstable land use Area (m 2 ) Proportion % N° polygons Stable landuse 8880159 21,03% 96 Unstable landuse 33344457 78,97% 156 TOTAL 42224616 100% 252 Source: Self elaboration. Ecologically stable and unstable proportion of area respect total area. The development of the ecological stability changes in the landscape of the study area is expressed by means of the temporal development of the ecological stability coefficients (KES). Phenomenon of ecological stability of the cultural landscape is based on the proportion of different land use categories in the area under investigation. Generally, coefficient of ecological stability of the landscape is formulated as the proportion of ecologically relatively stable Results - 39 - (positive) areas like forests, waters, grasslands and ecologically relatively unstable areas (like arable lands, built-up and disturbed areas, industrial sites etc.). The simplest coefficient of ecological stability after MÍCHAL (1992) is counted as: Kes = S/L To establish the proportion between these two groups using the KES index, which is very simple. It is simply a division between stable and unstable land use, in this case the result is 0.266, a very low mainly due to the large area o The ecological stability of the study area is exceptionally low, which indicates a not balanced and ecologically highly unstable landscape, also indicates a disturbed ecologically unstable landscape. 5.3. Comparison results about original map and vectorized map: Once I've made all the changes in the final map, the result was that in almost all land uses there was a reduction in the number of polygons present each use on the map, because I had homogenized the map previously, since in the original map there were abundant polygons with very small areas, what I did it was remove and expand the area of the polygon that is adjacent to the eliminated polygon and which value is appropriate for this area. In this way, the 1467 polygons on the original layer were reduced to 252, so 1215 polygons are removed. Because these 1215 polygons, 1206 polygons didn't have land use value assigned on the original map, primarily because whose area were negligible (Table 5.3). Results - 40 - Table 5.3 Comparison number of polygons between original map and corrected map Initial N° polygons Final N° polygons Difference N° polygons Landuse no value 1206 0 -1206 1,1 1 1 0 1,12 4 2 -2 1,13 1 1 0 1,14 5 4 -1 1,2 65 57 -8 1,3 9 10 1 1,5 5 8 3 1,7 2 3 1 1,8 1 1 0 10,0,1 5 4 -1 10,0,2 8 9 1 10,0,3 3 2 -1 10,0,4 8 8 0 10,0,5 6 4 -2 2,1 1 1 0 2,3 5 5 0 3,1 7 6 -1 4,0 17 18 1 4,0+4,1 2 2 0 4,1 27 28 1 4,2 7 7 0 4,3 7 6 -1 4,4 1 1 0 4,5 8 7 -1 6,1 2 2 0 6,3 21 18 -3 7 4 6 2 9,1 9 4 -5 9,2 16 20 4 9,3 3 4 1 9,4 1 3 2 TOTAL 1467 252 -1215 Source: Self elaboration. It’s the difference between the number total of polygons in the original map and vectorized map. The value of land use 1.2 also suffer a considerable reduction both in the number of polygons in the map and in total area, that means that the polygons of this land use value were eliminated or changed to other different value, which is to be considered for his reduction in the size. The land use value 9.3 suffer a reduction in area of about 2.60% but its presence on the map is so large, this occupied in the original map almost 40% (39.19%) that its decrease is not visually identifiable on the map. Results - 41 - There are certain land uses that increase the area on the map but very little significance, the only case in which there is an important increase in the land use 6.3 (mixed forests) where even though as number of polygons decreases, undergoes an increase of 6.17%, a sharp rise. All these calculations and results about the difference in the area and proportions are expressed in the table (5.4) Table 5.4 Comparison number of polygons between original map and corrected map Initial Final Difference Landuse Area (m 2 ) Area (m 2 ) Area (m 2 ) no value 182550 0 -182550 1,1 97963 100691 2728 1,12 430707 230602 -200106 1,13 74751 76776 2025 1,14 531273 537420 6147 1,2 8211878 8067176 -144702 1,3 1014693 1121490 106797 1,5 351133 724299 373166 1,7 281492 294297 12805 1,8 38085 38078 -7 10,0,1 1723686 1732481 8795 10,0,2 896049 1188658 292609 10,0,3 234041 177224 -56817 10,0,4 1408656 1396592 -12065 10,0,5 608435 594581 -13854 2,1 9379 9413 34 2,3 202417 204654 2237 3,1 170626 174467 3841 4,0 795786 861456 65670 4,0+4,1 357313 361823 4510 4,1 1306524 1440310 133786 4,2 382194 300336 -81859 4,3 316682 320895 4213 4,4 12991 13035 45 4,5 484463 497355 12892 6,1 488126 497388 9262 6,3 488126 3141158 2653032 7 157880 166085 8206 9,1 985410 1156083 170673 9,2 1071200 1184519 113319 9,3 15113242 15427210 313967 9,4 137903 188065 50162 TOTAL 38565653 42224616 3658963 Source: Self elaboration. It’s the difference between the area on the original map and vectorized map. Modified data of land uses of Northern Bohemian Ü Legend Types landuse 1.1 1.12 1.13 1.14 1.2 1.3 1.5 1.7 1.8 10.0.1 10.0.2 10.0.3 10.0.4 10.0.5 2.1 2.3 3.1 4.0 4.0+4.1 4.1 4.2 4.3 4.4 4.5 6.1 6.3 7 7. 9.1 9.2 9.3 9.4 Plan n° 2 Scale: 1/50.000 Current landscape in the neighbourhood of open cast mines in Northern Bohemia Date: May - 2011 Developer: Ceska Zemedelska Univerzita 0 0,75 1,5 2,25 30,375 Km Author of study: Alejandro Hidalgo Escrihuela Land use ecologically stable and unstable Ü Legend Types ecological Stable land use Unstable land use Plan n° 3 Scale: 1/50.000 Current landscape in the neighbourhood of open cast mines in Northern Bohemia Date: May - 2011 Developer: Ceska Zemedelska Univerzita 0 0,75 1,5 2,25 30,375 Km Author of study: Alejandro Hidalgo Escrihuela Location of the area 0 1 500 3 000 4 500 6 000750 Meters Location of the area 0 1 500 3 000 4 500 6 000750 Meters Location of the area 0 1 500 3 000 4 500 6 000750 Meters References - 47 - 9. 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