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...

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...

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...

Medium-scale land cover maps are traditionally created on the basis of a single cloud-free satellite scene, leaving information present in other scenes unused. Using 1309 field observations and 20 cloudand error-affected Landsat scenes covering Zanzibar Island, this study demonstrates that the use of multiple scenes can both allow complete coverage of the study area in the absence of cloud-free...

The importance of accurately describing the nature of land cover resources is increasing. With the aim to analyze the consistency of remotely sensed images from different sensors for land cover classification, three medium spatial resolution optical image sources in Xuzhou city were classified in the study, including CBERS, ETM, and ASTER. Land cover classification was conducted by Maximum Like...

land cover information is one of the most important prerequisite in urban management system. in this way remote sensing, as the most economic technology, is mainly used to produce land cover maps. considering the complicated and dense urban areas in third world countries, object based approaches are suggested as an effective image processing technique. the purpose of this paper are the introduc...

Analysis of hyperspectral data for defining the land-cover classes through classification techniques, in particular for small patches and scattered land-covers, is not a trivial task. Factors such as high spatial variability of landcover signatures, the “boundary effect” between neighboring land-covers, and the curse of dimensionality make this task more challenging [1]. As the integrity of a l...

[1] This paper presents an ARTMAP neural network approach for burn detection in Moderate Resolution Imaging Spectroradiometer (MODIS) data using two methods: discrete and continuous classifications. The study area covers the states of Idaho and Montana in the United States, where extensive fire events took place during the months of July and August in the year 2000. The proposed approach differ...

Detection of urban objects in very high resolution (VHR) satellite imagery is challenging due to the similarities in the spectral and textural characteristics of urban land cover classes. Therefore, additional information such as elevation data is required for a proper classification. In this study, instead of LiDAR data, elevation information generated from satellite stereo images is used to a...