Zobrazeno 1 - 10
of 14
pro vyhledávání: '"B. Bigdel"'
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W18, Pp 1085-1090 (2019)
In this paper, Radial Basis Function (RBF) Neural Network and Logistic Regression (LR) models were proposed for hazard prediction of landslides in a part of the Semirom area (Iran) to compare their accuracy and performance. For this purpose, a spatia
Externí odkaz:
https://doaj.org/article/3b89b54490af483cb20502351fd2222b
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W18, Pp 455-460 (2019)
In this study, a GIS based approach has been proposed for the flood risk zonation based on a multi-criteria spatial group fuzzy AHP decision making analysis and its integration with fuzzy overlay analysis. For this purpose, 10 layers affecting flood
Externí odkaz:
https://doaj.org/article/73b82eaccb92417080d53719ec75f7df
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W18, Pp 429-434 (2019)
Updating digital maps is a challenging task that has been considered for many years and the requirement of up-to-date urban maps is universal. One of the main procedures used in updating digital maps and spatial databases is building extraction which
Externí odkaz:
https://doaj.org/article/6a77db39cf4a409b8f98934aa2e1179c
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W18, Pp 435-440 (2019)
Vegetation mapping is one of the most critical challenges of remote sensing society in forestry applications. Sentinel-1 dataset has the potential of vegetation mapping, but because of its limited number of polarizations, full polarized vegetation in
Externí odkaz:
https://doaj.org/article/e4259fa4b5ed4d948226bf2300232a27
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W18, Pp 153-158 (2019)
This paper proposed a methodology for finding changes in agricultural land of Tehran during past years and simulating these changes for future years. The proposed method utilized the spatial GIS-based techniques and Landsat satellite imagery to predi
Externí odkaz:
https://doaj.org/article/11ed3bca56ce445d9d6b4d84d7651e58
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W4, Pp 305-309 (2017)
Based on world health organization (WHO) report, driving incidents are counted as one of the eight initial reasons for death in the world. The purpose of this paper is to develop a method for regression on effective parameters of highway crashes. In
Externí odkaz:
https://doaj.org/article/a11e047ea2604c70b2c2245fe911018f
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W4, Pp 477-481 (2017)
According to the industrialization of cities and the apparent increase in pollutants and greenhouse gases, the importance of forests as the natural lungs of the earth is felt more than ever to clean these pollutants. Annually, a large part of the for
Externí odkaz:
https://doaj.org/article/d38b272df775446eb2211466286a9bc0
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W4, Pp 117-122 (2017)
Due to urbanization and changes in the urban thermal environment and because the land surface temperature (LST) in urban areas are a few degrees higher than in surrounding non-urbanized areas, identifying spatial factors affecting on LST in urban are
Externí odkaz:
https://doaj.org/article/e20c555b2660483ba1ee3d5e09d89913
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-1-W5, Pp 1-4 (2015)
The existence of various natural objects such as grass, trees, and rivers along with artificial manmade features such as buildings and roads, make it difficult to classify ground objects. Consequently using single data or simple classification approa
Externí odkaz:
https://doaj.org/article/34b43b37b03b43bb82b92022fdf7ecae
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-7/W3, Pp 575-580 (2015)
An image classification method based on Support Vector Machine (SVM) is proposed on hyperspectral and 3K DSM data. To obtain training data we applied an automatic method relating to four classes namely; building, grass, tree, and ground pixels. First
Externí odkaz:
https://doaj.org/article/fbafbd587fa945c7babada6193e2c6e4