Usability of VGI for validation of land cover maps
نویسندگان
چکیده
منابع مشابه
Usability of VGI for validation of land cover maps
Volunteered Geographic Information (VGI) represents a growing source of potentially valuable data for many applications, including land cover map validation. It is still an emerging field and many different approaches can be used to take value from VGI, but also many pros and cons are related to its use. Therefore, since it is timely to get an overview of the subject, the aim of this article is...
متن کاملLand cover validation game
Land cover data constitutes highly useful information to monitor the extension and status of land resources, hence it has been realized how important it is to have accurate land cover data. Here, an interactive WebGIS is built in order to validate GlobeLand30 global land cover data. The Game with a Purpose (GWAP) human-based computation technique is adopted. The system is based on crowdsourcing...
متن کاملValidation of Satellite Snow Cover Maps
Satellite-derived snow maps from NASA’s Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20o (~5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1, 2001, through March 21, 2002, and...
متن کاملOptimization Methods for Area Aggregation in Land Cover Maps
The aggregation of areas is an important subproblem of the map generalization task. Especially, it is relevant for the generalization of topographic maps which contain areas of different land cover, such as settlement, water, or different kinds of vegetation. An existing approach is to apply algorithms that iteratively merge adjacent areas, taking only local measures into consideration. In cont...
متن کاملSelf-Learning Based Land-Cover Classification Using Sequential Class Patterns from Past Land-Cover Maps
To improve the accuracy of classification with a small amount of training data, this paper presents a self-learning approach that defines class labels from sequential patterns using a series of past land-cover maps. By stacking past land-cover maps, unique sequence rule information from sequential change patterns of land-covers is first generated, and a rule-based class label image is then prep...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Geographical Information Science
سال: 2015
ISSN: 1365-8816,1362-3087
DOI: 10.1080/13658816.2015.1018266