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When large areas of forest are modelled, spatial detail can create excessively large databases and adversely affect the processing time. Spatial generalization can be an efficient means of aggregating polygons into blocks in strategic forest planning models. In this study, a sensitivity analysis on spatial generalization was conducted to examine the trade-off between accuracy and spatial resolution to meet the objectives of strategic planning. Five scenarios were designed by generalizing forest cover polygons into the uniform hexagon block sizes of 5, 10, 20, 50 and 100 ha. To quantitatively assess accuracy, deviations caused by spatial generalization were calculated by criteria for hexagon scenarios relative to the base case. Criteria include model inputs (area of natural disturbance type and ungulate winter range) and outputs (harvest volume, growing stock and seral stage distribution). In general, deviations in all criteria increased with the block size. Spatial resolution was also evaluated by the database size and simulation runtime. A negative relationship was observed between spatial resolution and the block size. The trade-off analysis between accuracy and spatial resolution indicated that using the smallest block size of 5 ha creates more detail than necessary. Although scenarios with the block sizes of 50 and 100 ha reduced spatial resolution significantly, the maximum deviations relative to the base case were as high as 14% and 17% in growing stock, 12% and 12% in seral stage distribution, and 6% and 21% in ungulate winter range, respectively. For this study, the preferred block size is in the range of 10-20 ha, however, in general, the preferred block size will vary depending on the importance of each criterion used in the trade-off analysis.

The process of performing cartographic generalization in an automatic way applied on geographic information is of highly interest in the field of cartography, both in academia and industry. Many research e↵orts have been done to implement di↵erent automatic generalization approaches. Being able to answer the research question on automatic generalization, another interesting question opens up: ”Is it possible to retrieve and visualize geographic information in any arbitrary scale?” This is the question in the field of vario-scale geoinformation. Potential research works should answer this question with solutions which provide valid and efficient representation of geoinformation in any on-demand scale. More brilliant solutions will also provide smooth transitions between these on-demand arbitrary scales. Space-Scale-Cube (Meijers and Van Oosterom 2011) is a reactive tree (Van Oosterom 1991) data structure which shows positive potential for achieving smooth automatic vario-scale generalization of area features. The topic of this research work is investigation of adaptation of this approach on an interesting class of geographic information: road networks datasets. Firstly theoretical background will be introduced and discussed and afterwards, implementing the adaptation would be described. This research work includes development of a hierarchical data structure based on road network datasets and the potential use of this data structure in vario-scale geoinformation retrieval and visualization.

When large areas of forest are modelled, spatial detail can create excessively large databases and adversely affect the processing time. Spatial generalization can be an efficient means of aggregating polygons into blocks in strategic forest planning models. In this study, a sensitivity analysis on spatial generalization was conducted to examine the trade-off between accuracy and spatial resolution to meet the objectives of strategic planning. Five scenarios were designed by generalizing forest cover polygons into the uniform hexagon block sizes of 5, 10, 20, 50 and 100 ha. To quantitatively assess accuracy, deviations caused by spatial generalization were calculated by criteria for hexagon scenarios relative to the base case. Criteria include model inputs (area of natural disturbance type and ungulate winter range) and outputs (harvest volume, growing stock and seral stage distribution). In general, deviations in all criteria increased with the block size. Spatial resolution was also evaluated by the database size and simulation runtime. A negative relationship was observed between spatial resolution and the block size. The trade-off analysis between accuracy and spatial resolution indicated that using the smallest block size of 5 ha creates more detail than necessary. Although scenarios with the block sizes of 50 and 100 ha reduced spatial resolution significantly, the maximum deviations relative to the base case were as high as 14% and 17% in growing stock, 12% and 12% in seral stage distribution, and 6% and 21% in ungulate winter range, respectively. For this study, the preferred block size is in the range of 10-20 ha, however, in general, the preferred block size will vary depending on the importance of each criterion used in the trade-off analysis.

Thesis (M.A.)--University of Nevada, Reno, 2006. / "May, 2006." Includes bibliographical references (leaves 50-55). Online version available on the World Wide Web.

Thesis (Ed. D.)--Illinois State University, 1980. / Title from title page screen, viewed March 10, 2005. Dissertation Committee: Max R. Rennels (chair), Barry Moore, Richard A. Salome, Leon Manelis, Macon Williams. Includes bibliographical references (leaves 23-24) and abstract. Also available in print.

Σκοπός της εργασίας αυτής είναι να μελετήσουμε την έννοια της γενίκευσης στη Μαθηματική Παιδεία. Αρχικά διερευνούμε την ετυμολογία και την ιστορικότητα του όρου και αναδεικνύουμε της σχέση μεταξύ γενίκευσης επαγωγής και αφαίρεσης. Αφού μελετήσουμε τη λέξη και την έννοια του φυσικού αριθμού, δύο γενετικά καθοριστικές για την ανθρώπινη νόηση γενικεύσεις, προσπαθούμε να αναδείξουμε, με βάση την υπάρχουσα βιβλιογραφία, το ρόλο της γενίκευσης στην απόκτηση γνώσης, αλλά και να εξετάσουμε την ικανότητα του ανθρώπου για γενίκευση. Έχοντας εντοπίσει το ρόλο της γενίκευσης στην ανάπτυξη επιστημονικών εννοιών και θεωριών, περνάμε στη περιοχή των Μαθηματικών και εξετάζουμε τις έννοιες του Ορισμού, του Θεωρήματος και της Ευθείας Απόδειξης, αναφορικά με την έννοια της γενίκευσης. Μέσα από τα ερευνητικά δεδομένα αναδεικνύονται τα προβλήματα που αντιμετωπίζουν οι μαθητές στην προσπάθεια τους να παράγουν κατάλληλες γενικεύσεις. Εστιάζουμε την προσοχή μας στις δυσκολίες των μαθητών αναφορικά με την κατανόηση της έννοιας της μεταβλητής αλλά και της Τέλειας Επαγωγής και παραθέτουμε διδακτικά αξιοποιήσιμα παραδείγματα. / --

The current study evaluated the efficacy of a set of procedures described in the PEAK Relational Training System’s Generalization Module in teaching three skills to two 3-year old boys with autism. The three skills taught were tacting sensory feelings, tact collateral responses, and tacting then asking for reinforcing items for each participant. These skills were not only trained but also generalization probes were conducted throughout the study. The results suggested that the procedures were effective in not only direct training participants to label sensory feelings, emotions, and reinforcing items, but also promoted the untrained emergence of novel skills through generalization.