Landform Analysis, Landform Description

Chapter Contents (Back)

Gökgöz, T.[Türkay], Baker, M.K.M.[Moustafa Khalil M.],
Large Scale Landform Mapping Using Lidar DEM,
IJGI(4), No. 3, 2015, pp. 1336.
DOI Link 1508

Guilbert, E.[Eric], Moulin, B.[Bernard],
Towards a Common Framework for the Identification of Landforms on Terrain Models,
IJGI(6), No. 1, 2017, pp. xx-yy.
DOI Link 1702

Kramm, T.[Tanja], Hoffmeister, D.[Dirk], Curdt, C.[Constanze], Maleki, S.[Sedigheh], Khormali, F.[Farhad], Kehl, M.[Martin],
Accuracy Assessment of Landform Classification Approaches on Different Spatial Scales for the Iranian Loess Plateau,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712

Mayoral, A.[Alfredo], Toumazet, J.P.[Jean-Pierre], Simon, F.X.[François-Xavier], Vautier, F.[Franck], Peiry, J.L.[Jean-Luc],
The Highest Gradient Model: A New Method for Analytical Assessment of the Efficiency of LiDAR-Derived Visualization Techniques for Landform Detection and Mapping,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Carbonell-Carrera, C.[Carlos], Hess-Medler, S.[Stephany],
3D Landform Modeling to Enhance Geospatial Thinking,
IJGI(8), No. 2, 2019, pp. xx-yy.
DOI Link 1903

Castillejo-González, I.L.[Isabel Luisa], Angueira, C.[Cristina], García-Ferrer, A.[Alfonso], Sánchez de la Orden, M.[Manuel],
Combining Object-Based Image Analysis with Topographic Data for Landform Mapping: A Case Study in the Semi-Arid Chaco Ecosystem, Argentina,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903

Gomes, R.[Rahul], Denton, A.[Anne], Franzen, D.[David],
Quantifying Efficiency of Sliding-Window Based Aggregation Technique by Using Predictive Modeling on Landform Attributes Derived from DEM and NDVI,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905

Du, L.[Lin], You, X.[Xiong], Li, K.[Ke], Meng, L.Q.[Li-Qiu], Cheng, G.[Gong], Xiong, L.Y.[Li-Yang], Wang, G.X.[Guang-Xia],
Multi-modal deep learning for landform recognition,
PandRS(158), 2019, pp. 63-75.
Elsevier DOI 1912
Landform recognition, Multi-modal geomorphological data fusion, Deep learning, Convolutional neural networks (CNN) BibRef

Yang, X.W.[Xian-Wu], Tang, G.[Guoan], Meng, X.[Xin], Xiong, L.Y.[Li-Yang],
Classification of Karst Fenglin and Fengcong Landform Units Based on Spatial Relations of Terrain Feature Points from DEMs,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909

Mihu-Pintilie, A.[Alin], Nicu, I.C.[Ionut Cristi],
GIS-based Landform Classification of Eneolithic Archaeological Sites in the Plateau-plain Transition Zone (NE Romania): Habitation Practices vs. Flood Hazard Perception,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905

Li, L.L.[Lei-Lei], Yang, J.T.[Jin-Tao], Wu, J.[Jin],
A Method of Watershed Delineation for Flat Terrain Using Sentinel-2A Imagery and DEM: A Case Study of the Taihu Basin,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link 1912

Kwak, J.[Jeonghoon], Sung, Y.[Yunsick],
Automatic 3D Landmark Extraction System Based on an Encoder-Decoder Using Fusion of Vision and LiDAR,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004

Aati, S.[Saif], Avouac, J.P.[Jean-Philippe],
Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010

Eisank, C., Dragut, L.D., Götz, J., Blaschke, T.,
Developing a Semantic Model of Glacial Landforms for Objectbased Terrain Classification: The Example of Glacial Cirques,
PDF File. 1007

Camargo, F.F., Almeida, C.M., Costa, G.A.O.P., Feitosa, R.Q., Oliveira, D.A.B., Ferreira, R.S., Heipke, C.,
Cognitive Approaches and Optical Multispectral Data for Semiautomated Classification of Landforms in a Rugged Mountainous Area,
PDF File. 1007

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Bathymetric Mapping, Analysis, Underwater Terrain .

Last update:Nov 23, 2020 at 10:27:11