Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks

Landslides ◽  
2020 ◽  
Vol 17 (6) ◽  
pp. 1337-1352 ◽  
Author(s):  
Shunping Ji ◽  
Dawen Yu ◽  
Chaoyong Shen ◽  
Weile Li ◽  
Qiang Xu
Keyword(s):  
Neural Networks ◽  
Digital Elevation Model ◽  
Convolutional Neural Networks ◽  
Satellite Imagery ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals RSPCN: Super-Resolution of Digital Elevation Model Based on Recursive Sub-Pixel Convolutional Neural Networks

2021 ◽  
Vol 10 (8) ◽  
pp. 501
Author(s):  
Ruichen Zhang ◽  
Shaofeng Bian ◽  
Houpu Li
Keyword(s):  
Neural Networks ◽  
Digital Elevation Model ◽  
Convolutional Neural Networks ◽  
Adaptive Learning ◽  
Nearest Neighbor ◽  
Super Resolution ◽  
Recursion Theory ◽  
Research Issues ◽  
Digital Elevation ◽  
Elevation Model

The digital elevation model (DEM) is known as one kind of the most significant fundamental geographical data models. The theory, method and application of DEM are hot research issues in geography, especially in geomorphology, hydrology, soil and other related fields. In this paper, we improve the efficient sub-pixel convolutional neural networks (ESPCN) and propose recursive sub-pixel convolutional neural networks (RSPCN) to generate higher-resolution DEMs (HRDEMs) from low-resolution DEMs (LRDEMs). Firstly, the structure of RSPCN is described in detail based on recursion theory. This paper explores the effects of different training datasets, with the self-adaptive learning rate Adam algorithm optimizing the model. Furthermore, the adding-“zero” boundary method is introduced into the RSPCN algorithm as a data preprocessing method, which improves the RSPCN method’s accuracy and convergence. Extensive experiments are conducted to train the method till optimality. Finally, comparisons are made with other traditional interpolation methods, such as bicubic, nearest-neighbor and bilinear methods. The results show that our method has obvious improvements in both accuracy and robustness and further illustrate the feasibility of deep learning methods in the DEM data processing area.

scholarly journals APPLICATION OF DSM IN OBSTACLE CLEARANCE SURVEYING OF AERODROME

2016 ◽  
Vol XLI-B2 ◽  
pp. 227-233 ◽  
Author(s):  
X. Qiao ◽  
S. H. Lv ◽  
L. L. Li ◽  
X. J. Zhou ◽  
H. Y. Wang ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Primary Objective ◽  
Considerable Improvement ◽  
Surface Model ◽  
Digital Surface Model ◽  
Horizontal Position ◽  
Obstacle Clearance ◽  
Digital Elevation ◽  
Elevation Model

Compared to the wide use of digital elevation model (DEM), digital surface model (DSM) receives less attention because that it is composed by not only terrain surface, but also vegetations and man-made objects which are usually regarded as useless information. Nevertheless, these objects are useful for the identification of obstacles around an aerodrome. The primary objective of the study was to determine the applicability of DSM in obstacle clearance surveying of aerodrome. According to the requirements of obstacle clearance surveying at QT airport, aerial and satellite imagery were used to generate DSM, by means of photogrammetry, which was spatially analyzed with the hypothetical 3D obstacle limitation surfaces (OLS) to identify the potential obstacles. Field surveying was then carried out to retrieve the accurate horizontal position and height of the obstacles. The results proved that the application of DSM could make considerable improvement in the efficiency of obstacle clearance surveying of aerodrome.

Landform classification from a digital elevation model and satellite imagery

Geomorphology ◽  
2008 ◽  
Vol 100 (3-4) ◽  
pp. 453-464 ◽  
Author(s):  
Hossein Saadat ◽  
Robert Bonnell ◽  
Forood Sharifi ◽  
Guy Mehuys ◽  
Mohammad Namdar ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Landform Classification ◽  
Digital Elevation ◽  
Elevation Model

The Maras Triple Junction (southern Turkey) based on digital elevation model and satellite imagery interpretation

1994 ◽  
Vol 99 (B10) ◽  
pp. 20225-20242 ◽  
Author(s):  
Jean Chorowicz ◽  
Pascal Luxey ◽  
Nikos Lyberis ◽  
José Carvalho ◽  
Jean-François Parrot ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Triple Junction ◽  
Digital Elevation ◽  
Southern Turkey ◽  
Elevation Model

scholarly journals A new look at the Butic Canal, Egypt

2021 ◽  
Vol 70 (1) ◽  
pp. 29-38
Author(s):  
Robert Schiestl
Keyword(s):  
Remote Sensing ◽  
Roman Empire ◽  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Nile Delta ◽  
Remote Sensing Data ◽  
Historical Sources ◽  
Sensing Data ◽  
Digital Elevation ◽  
Elevation Model

Abstract. The Butic Canal – a Roman period transversal route across the northern Nile Delta – was the longest artificial watercourse in the Nile Delta, yet it remains very poorly understood. To date, the canal has not yet been verified by archeological excavations. The route of the eastern section of the canal has been indirectly identified based on a linear elevated feature most likely representing earth from the excavation of the canal. This study combines the analysis of historical sources and remote sensing data, such as satellite imagery and the TanDEM-X digital elevation model, in order to discuss its date of construction, route, and functions. Based on the data of the digital elevation model, new constructional features are visible in the eastern delta providing the first detailed route of a Roman-era artificial watercourse in Egypt. It is suggested that the canal's construction is placed in the context of imperial investments in the infrastructure of the eastern part of the Roman empire.

scholarly journals The draa Cerro Medanoso (Atacama, Chile) and its importance in the study of desert

2016 ◽  
pp. 25
Author(s):  
José F. Araya Vergara ◽  
Ricardo Vilaró
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Morphological Analysis ◽  
Aerial Photos ◽  
Desert Pavement ◽  
Aster Gdem ◽  
Digital Elevation ◽  
The World ◽  
Long Time ◽  
Elevation Model

This work presents a morphological analysis of the Cerro Medanoso draa (Atacama Marginal Desert) and the type of contact with the desert pavements of neighboring glacis and piedmont. This study is based on an analysis of aerial photos, and a digital elevation model. Aster GDEM was used as a basis for the survey. Fieldwork observations covered two principal zones: the nucleus and the envelope. Following fieldwork, analysis of satellite imagery was conducted. It was possible to identify the following phases of formation: construction of a stellate nucleus, merging of the eastern envelope, merging of the southern envelope and merging of a complex western envelope. The southeastern facing envelope is much bigger than the northwestern facing one. Consequently, the construction of the complex draa is asymmetric. The correlation of this megadune with similar star and compound draas to other deserts in the world indicates that the closest analogue exists in Namibia, but without merging signals between the envelope and the nucleus. Star draas observed in other deserts exhibit a lack of this envelope. With reference to the neighboring piedmont, the beginning of its deflation must be necessarily correlative to the initial construction of the nuclear twin star draa. The later deflation could be responsible for the pulses, which formed the envelope. Therefore, the neighboring desert pavement and the draa are correlative landforms, which represent a very long time formation, in an important part of the desert history, as evidenced by the cited and referenced research works.

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