Arid

浏览/检索结果: 共10条,第1-10条 帮助

已选(0)清除 条数/页:   排序方式:
The use of LiDAR in reconstructing the pre-World War II landscapes of abandoned mountain villages in southern Poland 期刊论文
发表期刊: ARCHAEOLOGICAL PROSPECTION. 出版年: 2022
作者:  Affek, Andrzej N.;  Wolski, Jacek;  Latocha, Agnieszka;  Zachwatowicz, Maria;  Wieczorek, Malgorzata
收藏  |  浏览/下载:31/0  |  提交时间:2021/11/19
airborne laser scanning  cadastral maps  deserted villages  landscape archaeology  the Carpathians  the Sudetes  
Prediction of spatial land use changes based on LCM in a GIS environment for Desert Wetlands - A case study:Meighan Wetland,Iran 期刊论文
发表期刊: International Soil and Water Conservation Research. 出版年: 2019, 卷号: 7, 期号: 1, 页码: 64-70
作者:  Ansari Amir;  Golabi Mohammad H
收藏  |  浏览/下载:3/0  |  提交时间:2021/01/08
LCM  Prediction  Meighan wetland  Land use changes  Artificial Neural Network  
Prediction of spatial land use changes based on LCM in a GIS environment for Desert Wetlands - A case study: Meighan Wetland, Iran 期刊论文
发表期刊: INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH. 出版年: 2019, 卷号: 7, 期号: 1, 页码: 64-70
作者:  Ansari, Amir;  Golabi, Mohammad H.
收藏  |  浏览/下载:3/0  |  提交时间:2021/11/30
LCM  Prediction  Meighan wetland  Land use changes  Artificial Neural Network  
Monitoring and predicting land use/cover changes in the Aksu-Tarim River Basin, Xinjiang-China (1990-2030) 期刊论文
发表期刊: ENVIRONMENTAL MONITORING AND ASSESSMENT. 出版年: 2019, 卷号: 191, 期号: 8
作者:  El-Tantawi, Attia M.;  Bao, Anming;  Chang, Cun;  Liu, Ying
收藏  |  浏览/下载:21/0  |  提交时间:2019/11/29
Land use  cover change  Artificial neural network (ANN)  Reconnaissance Drought Index  Aksu  Tarim River Basin  Xinjiang  
Reconstruction of the Water Cultivation Paleoenvironment Dating Back to the Han and Tang Dynasties Surrounding the Yangguan Frontier Pass Using X- and L-Band SAR Data 期刊论文
发表期刊: REMOTE SENSING. 出版年: 2018, 卷号: 10, 期号: 10
作者:  Zhu, Xiaokun;  Chen, Fulong;  Guo, Huadong
收藏  |  浏览/下载:5/0  |  提交时间:2019/11/29
spaceborne SAR  Nanhu oasis  Yangguan frontier pass  water cultivation paleoenvironment  Han and Tang dynasties  
Urban Travel Time Estimation from Sparse GPS Data : An Efficient and Scalable Approach 学位论文
学位授予机构: KTH, Transportplanering, ekonomi och teknik, Stockholm. 出版年: 2015
作者:  Rahmani;Mahmood
收藏  |  浏览/下载:12/0  |  提交时间:2019/11/29
Map-matching  Path inference  Sparse GPS probes  Floating car data  Arterial  Urban area  Digital road network  Iterative travel time estimation  Fixed point problem  Stockholm  Taxi  
GIS-based estimation of flood hazard impacts on road network in Makkah city, Saudi Arabia 期刊论文
发表期刊: ENVIRONMENTAL EARTH SCIENCES. 出版年: 2012, 卷号: 67, 期号: 8, 页码: 2205-2215
作者:  Dawod, Gomaa M.;  Mirza, Meraj N.;  Al-Ghamdi, Khalid A.
收藏  |  浏览/下载:2/0  |  提交时间:2019/11/29
Flood assessment  Rainfall-runoff model  Road network  GIS  Saudi Arabia  
Path Inference of Sparse GPS Probes for Urban Networks : Methods and Applications 学位论文
学位授予机构: KTH, Trafik och logistik, Stockholm. 出版年: 2012
作者:  Rahmani;Mahmood
收藏  |  浏览/下载:7/0  |  提交时间:2019/11/29
Map-matching  Path inference  Sparse GPS probes  FCD  Urban area  Digital road network  Stockholm  Taxi  IMobility Lab  MapViz  Travel time  
Urban growth dynamics (1956-1998) in Mediterranean coastal regions: The case of Alicante, Spain 会议论文
会议名称: NATO Mediterranean Dialogue Workshop on Desertification in the Mediterranean Region - A Security Issue. 会议地点: Valencia, SPAIN. 会议日期: DEC 02-05, 2003
作者:  Aguilar, JAP;  Ano, C;  Valera, A;  Sanchez, J
收藏  |  浏览/下载:3/0  |  提交时间:2019/12/07
Mediterranean environments  urban dynamics  desertification  land degradation  soil sealing  aerial photograph  Geographical Information Systems  
Characterizing the flash flood hazards potential along the Red Sea coast of Egypt 会议论文
会议名称: International Symposium on Extraordinary Floods. 会议地点: REYKJAVIK, ICELAND. 会议日期: JUL, 2000
作者:  Ghoneim, EM;  Arnell, NW;  Foody, GM
收藏  |  浏览/下载:4/0  |  提交时间:2019/12/07
geographical information system (GIS)  digital elevation model (DEM)  morphometric parameters  flash floods  dry wadis  Red Sea coast  eastern Egyptian desert  road network  risk categories