LULC - Special topic

Land Use and Land Cover I

6107.1 - Local generalization method for updating land-use maps across multi-scales: A Case of China

Thursday, July 6
8:30 AM - 8:50 AM
Location: Maryland B

Aims to model and monitor the states of land use, map agencies of china carried out the second national land survey in which a huge amount of spatial data with multiple scales have been collected and constructed. With the rapid development of urbanization, update and consistency maintenance of these multi-scale land-use maps become an important task. Traditionally, land-use data at each scale should be updated independently by using reference data such as field surveying data, aerial photos. It is a labor-intensive procedure and may result in poor consistency between different representations. In order to improve the efficiency and produce better results, we need to develop new updating strategies and methods.
In this study, we develop a local generalization updating method for land-use maps. Once the largest scale maps are updated using the monitoring reference data, the smaller scale maps will be updated by deriving in-formation from the updated larger scale maps. Different with the globe generalization method in map production, local generalization update method includes two major steps. In the first step, the updated larger scale maps and to-be-updated smaller scale maps are compared to detect changes. The identification of both temporal changes in real world and representation changes caused by scale transfer is a key question in this process. Facing this challenge, we examine various changes between newer, larger scale map and older, smaller scale map from different perspectives (e.g., occurring reason, behavior form, and out effect). Then, change detection and filtering operations supported by set operations (i.e., intersect, union) and map generalization knowledge are designed to identify temporal changes. In the second step, the identified temporal changed features are integrated into the older, smaller scale map by local generalization. Different local generalization transforms, such as aggregation, amalgamation, skeletonization, boundary simplification, are applied to the changed features which are deriving from the larger scale map. The selection of local generalization operations and their process order are controlled by the types of change, the context of local area and constraints such as topology maintenance.
We developed a software to realize the local generalization update method, which has been used for the updating tasks of 2850 counties, 334 prefectures, 34 provinces in china. The source data was constructed in 2009, and the reference data includes change data from 2010 to 2014. Our method is an incremental update targeted to deal with the change regions and influenced regions. Compared with the batch generalization method, it can reduce computations in regions with few changes occurred. Moreover, our method can make a whole decision for the change and influenced regions, which can better maintain the characteristics than sequential updating of individual change information.

Xiongfeng Yan

School of Resource and Environmental Science, Wuhan University

Xiongfeng Yan received the BS and MS degree in cartography from Wuhan University, China, and is pursuing his PhD in Wuhan University. His main research interests include data update and cartography generalization. Has published 3 papers in refereed conferences and journals.

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Tinghua Ai

Wuhan University

Tinghua Ai received the PhD in 2000 in the topic of generalization from Wuhan University, China. He is a full professor and head of department of cartography and geography information engineering at school of resource and environment sciences, Wuhan University. His main research interests include map generalization, visualization and spatial cognition. He has published more than 100 papers in refereed conferences and journals.

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Min Yang

Wuhan University

Min Yang received the PhD in 2013 from Wuhan University, China. He is a lecturer at school of resource and environment sciences, Wuhan University. His main research interests include data update, visualization. He has published 10+ papers in refereed conferences and journals.

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Rui Xin

Wuhan University

Rui xin is pursuing his PhD in Wuhan University. His main research interests include visualization.

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Ammatzia Peled

Prof.
University of Haifa

Dr. Ammatzia Peled is a professor for GIS&RS at the University of Haifa, Israel. Ammatzia Served as the Chair of the ICA Commission on Incremental Updating and Versioning of spatial Databases. He served also as ISPRS Treasurer and Second Vice President and as ISPRS president of Commission VIII. In 2010, Prof. Peled was awarded the Eduard Tsiolkovsky Memorial GOLD Medal by the Russian Academy for Cosmonautics for “Outstanding contribution to Cosmonautics”. In 2013 he was awarded as a Professor Honoris Causa by the Siberia State Academy for Geodesy & Cartography and last July he was awarded as ISPRS Fellow.

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