Mapping Inter-Annual Land Cover Variations Automatically Based on a Novel Sample Transfer Method

Automated Training Sample Extraction for Global Land Cover Mapping

Land cover is one of the essential climate variables of the ESA Climate Change Initiative (CCI). In this context, the Land Cover CCI (LC CCI) project aims at building global land cover maps suitable for climate modeling based on Earth observation by satellite sensors. The challenge is to generate a set of successive maps that are both accurate and consistent over time. To do so, operational met...

A Bayesian Based Method to Generate a Synergetic Land-Cover Map from Existing Land-Cover Products

Global land cover is an important parameter of the land surface and has been derived by various researchers based on remote sensing images. Each land cover product has its own disadvantages and limitations. Data fusion technology is becoming a notable method to fully integrate existing land cover information. In this paper, we developed a method to generate a synergetic global land cover map (s...

Land-cover and Land-use Mapping

Land Cover Classification based on the Universal Pattern Decomposition Method

* Corresponding author. E-mail: [email protected] Abstract – The universal pattern decomposition method (UPDM) has been successfully applied to simulated data for Landsat/ETM+, Terra/MODIS, ADEOS-II/GLI and others using ground-measured data. The UPDM is tailored to decrease dimensions of hyper multi-spectral data that have sensor-independent characteristics and thus exploit hyper multi-s...

Land-Use and Land-Cover Mapping Using a Gradable Classification Method

Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a g...