In this paper, we address the challenge of land use and land cover classification using remote sensing satellite images. For this challenging task, we use the openly and freely accessible Sentinel-2 satellite images provided within the scope of the Earth observation program Copernicus. The key contributions are as follows. We present a novel dataset based on satellite images covering 13 differe...

Land cover maps are fundamental materials for resource management and change detection. Remote sensing technology is crucial for fast mapping with low cost. However, besides the inherent classification errors in the land cover products, numerous illogical transitions exist between the neighboring time points. In this study, we introduce a series of logical codes for all the land cover types acc...

Taking northern Xinjiang, China, as an example, this study first compares the standard MODIS Terra and Aqua snow cover classifications, and then compares the accuracy of the standard MODIS daily and 8-day snow cover products with the new daily and multi-day snow cover combination of MODIS Terra and Aqua observations using in situ measurements. Under clear sky in both products, the agreement of ...

Our research focuses on assessing the usability of the International Geosphere Biosphere Programme (IGBP) classification scheme provided in the MODIS MCD12Q1-1 dataset for assessing the land cover of the city-state, Singapore. We conducted a user study with responses from 33 users by providing them with Google Earth images from different parts of Singapore, asking survey-takers to classify thes...

The main aim of this study was to assess and mapping land cover (LC) / use (LU), using Remote Sensing (RS) Geographical Information System (GIS) techniques in Elnor natural forest reserve, Blue Nile state, Sudan. also attempted update some information the area such as LC contour map by different methods data transformation analysis Normalized Different Vegetation Index (NDVI), interpolation sup...

Recently, there is an increasing demand for information on actual land use/land cover (LU/LC) from planning, administration and scientific institutions. Remote sensing combined with GIS tools can give quick reply providing timely information products in different geometric and thematic scales. Anyway the effort to make the land use map by visual interpretation is still very high and cannot keep...

two different methods of bayesian segmentation algorithm were used with different band combinations. sequential maximum a posteriori (smap) is a bayesian image segmentation algorithm which unlike the traditional maximum likelihood (ml) classification attempts to improve accuracy by taking contextual information into account, rather than classifying pixels separately. landsat 7 etm+ data with pa...

This study introduces a method for object-based land cover classification based solely on the analysis of LiDAR-derived information—i.e., without the use of conventional optical imagery such as aerial photography or multispectral imagery. The method focuses on the relative information content from height, intensity, and shape of features found in the scene. Eight object-based metrics were used ...

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...

Whereas C-band SAR data mainly provides information on the upper layer of land covers, properties of the lower surfaces can be captured using L-band SAR because of its higher capability of penetration. Moreover, optical imagery illuminates different characteristics of ground surfaces compared to radar images since they are obtained at different frequencies of the electro-magnetic spectrum. Henc...