2011 YÜksek lisans tez özetleri

Anahtar kelimeler: Coğrafi bilgi sitemleri, mekansal tahmin, meşcere haritaları, özgür ve açık kaynak kodlu yazılım.

Producing Of Stand Draft Maps With Spatial Prediction Methods

In order to associate forest stand maps of forest development plans, utilization of forest stand draft maps is essential. Since set up of a forest stand map depends upon the knowledge, skills and experience, mostly non-objective maps are generated. Mapping forest stand and inventory according to scientific and objective parameters measured is significantly important for present and future condition of the forest stand.

For this reason, two types of working area were selected representing single and multiple species within a plan unit. First is Şelale Forest District Directorate under Manavgat Forest District Directorate associated to Antalya Regional Directorate of Forestry, and second ones are Alaçam, Kızlan and Yakakent Forest District Directorates which are linked to Amasya Regional Directorate of Forestry and Bafra Regional Directorate of Forestry. In this study, growing stock (volume) per hectar data in 463 topographic inventory spots in Şelale plan unit and 1.317 spots in Alaçam, Kızlan and Yakakent plan units were used.

Using SAGA-GIS free geographical information system software B-Spline, Multilevel B-Spline, Cubic Spline, Thin Plate Spline, Inverse Distance Weighting, Natural Neighbour, Ordinary Kiriging, Universal Kriging spatial prediction techniques, working areas’tree volume data spatial interpolation maps were generated on the basis of species and diameter class. Root mean square error and percent root mean square error values of generated maps were calculated and accuracy of them were compared against species and diameter class for each technique. Most accurate techniques were founf to be MBSP, TPSP and IDW with 1,31, 1,79 and 2,29 average percent root mean square error correspondingly. Worst results were obtained from CSP, UK and BSP methods with 94,06, 83,68 and 75,08 respectively. OK and NN methods with 11,44 and 16,86 had fair performances during the work held. There was not a significant difference identified between the two plan units for correctness.

Subsequently spatial prediction maps were used to generate forest stand draft maps, for sampling purposes maps generated from Bafra plan unit were processed within themselves. Therefore, each diameter class volume map were converted to volume maps of total species by raster calculation function. After, ratio of diameter classes within the mixture were mapped. Similarly, total stand volume maps and ratio of species maps were produced and converted to vector data. After then, generating stand outline maps by objective criteria, the ELECTRE TRI method was used.

This work aims to show that forest stand outline maps can be both used in generating a forest stand map as a helping layer, and functional ecosystem-based planning seperately.