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EN
In this paper the authors describe the steps of building of a new automated complex land evaluation system based on the D-e-Meter land quality index. Complex evaluation means an organic systematization of ecological and economical factors. Necessary of development of a new land evaluation system based on the undeveloped land market in Hungary, which causes difference between the level of actual land price and economic value of agricultural land. The land evaluation has - among others - an important task: that is to convey the value towards the land market actors, which can be the starting point in negotiation about market price and in decision-making about the land use. The estimated land value indicates the total values of land estates on the basis of their rent-production ability. These values can differ from land-estate prices formed on land market, nevertheless they are decidedly adequate to replace the Hungarian current land evaluation system, so called Gold- -crown System and to solve whole series of objectives connected with land evaluation. The new land evaluation system is useful for estimating the realistic land value, but also helps to manage the land use on sustainable way.
PL
W artykule opisano etapy budowania nowego zautomatyzowanego systemu kompleksowej ocen) gruntów na podstawie wskaźnika jakości gruntów De-Meter. Kompleksowa ocena oznacza organiczni usystematyzowanie czynników ekologicznych i ekonomicznych, wpływających na cenę ziemi. Metodyki powstała na potrzeby rozwoju nowego systemu oceny rynku gruntów na Węgrzech, związanego z różnicam rzeczywistych cen działek a wartością ekonomiczną gruntów rolnych.
EN
Land cover change in any ecosystem vary in space and time. The study analyzed spatialtemporal land cover change to predict forest degradation pressure points in Eastern Mau Forest Reserve. The study objectives were to determine types and amount of spatial-temporal land cover change; land cover change drivers and; forest resources use sustainability. The study used mixed sample survey design involving purposive sampling of spatial data and cluster sampling of forest resource use data. Primary data included ground control points, field validation data and forest resource use data. Secondary data included Landsat imagery, forest and administration boundaries and settlements data. Analysis was done for 1986-2014 period using Remote Sensing and Geographical Information System. The analysis techniques used included object based image segmentation and classification, accuracy assessment and land cover change detection. Land cover types in Eastern Mau Forest consisted of indigenous forest, shrubland, grassland, plantation forest, cultivated fields, bare ground and built-up area. The analysis results depicted that cultivated fields coverage increased from 1% to 47%. Indigenous and plantation forests decreased from 43% to 36% and 34% to 7% respectively. Grassland and shrubland decreased from 16% to 8% and 6% to 2% respectively. Bare ground and built up area had a change of less than 1% each. Causes of pressure that lead to forest degradation included crop cultivation, settlement construction, livestock grazing, charcoal burning, firewood collection, logging, bee keeping and medicinal herbs extraction. Land cover change was more on the eastern side than on the western side. Indigenous and plantation forests were likely to disappear if cropland and built up area expansions were to remain unchecked. The study recommendations were: resettlement activities be eliminated in the Eastern Mau Forest; excision of forest land for crop cultivation should be discouraged; and scientific research should be carried out on sustainable plantation forest activities.
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