Automated measurement of sand dune migration using multi-temporal lidar data and GIS

被引:21
|
作者
Dong, Pinliang [1 ]
机构
[1] Univ N Texas, Dept Geog, Denton, TX 76203 USA
基金
美国国家科学基金会;
关键词
WHITE SANDS; NEW-MEXICO; TENGGER DESERT; FIELD PATTERN; OBLIQUE DUNES; LINEAR DUNES; DYNAMICS; GEOMORPHOLOGY; DEFORMATION; INFORMATION;
D O I
10.1080/01431161.2015.1093192
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Remote sensing has been used for coastal and desert sand dune studies over the past four decades, yet few methods have been developed for automated detection and measurement of dune migration directions and migration rates in large dune fields. Using high-resolution, high-accuracy, and multi-temporal light detection and ranging (lidar) data acquired in the White Sands Dune Field in New Mexico (USA) on 24 January 2009 and 6 June 2010, an automated method named Pairs of Source and Target Points (PSTP) was developed in a geographical information system (GIS) environment for automated detection and measurement of dune migration directions and migration rates. As markers for dune movement, dune slip faces were automatically extracted from lidar-derived digital elevation models (DEM), based on the range of the angle of repose, and converted into source lines and target lines through vectorization. Random target points were then generated on target lines and used to search for source points on source lines to form PSTP, thereby obtaining source direction, migration distance, and migration rate for each target point. Continuous raster data sets for dune migration rates were also created through spatial interpolation and point statistics to show dune field scale spatial patterns of dune migration rates. A total of 5936 PSTP were identified, producing dune migration directions and migration rates at 5936 locations in the study area of 9kmx2.4km. Histogram analysis revealed that a majority of the 3025 target points with source direction in the range 225 degrees-285 degrees (direction of prevailing winds) have a migration rate of 4-7myear(-1) and an average migration rate of 5.56myear(-1). The applicability of the PSTP method in special cases, and its potential as a generic method for change detection and measurement, are also discussed. The study obtained important results both in methodology development and in the study area.
引用
收藏
页码:5426 / 5447
页数:22
相关论文
共 50 条
  • [41] UAS Quality Control and Crop Three-Dimensional Characterization Framework Using Multi-Temporal LiDAR Data
    Fareed, Nadeem
    Das, Anup Kumar
    Flores, Joao Paulo
    Mathew, Jitin Jose
    Mukaila, Taofeek
    Numata, Izaya
    Janjua, Ubaid Ur Rehman
    REMOTE SENSING, 2024, 16 (04)
  • [42] Carbon Dynamics in a Human-Modified Tropical Forest: A Case Study Using Multi-Temporal LiDAR Data
    de Moura, Yhasmin Mendes
    Balzter, Heiko
    Galvao, Lenio S.
    Dalagnol, Ricardo
    Espirito-Santo, Fernando
    Santos, Erone G.
    Garcia, Mariano
    Bispo, Polyanna da Conceicao
    Oliveira, Raimundo C.
    Shimabukuro, Yosio E.
    REMOTE SENSING, 2020, 12 (03)
  • [43] Detection of heartwood rot in Norway spruce trees with lidar and multi-temporal satellite data
    Dalponte, Michele
    Solano-Correa, Yady Tatiana
    Orka, Hans Ole
    Gobakken, Terje
    Naesset, Erik
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 109
  • [44] Geomorphic impact and assessment of flexible barriers using multi-temporal LiDAR data: The Portaine mountain catchment (Pyrenees)
    Victoriano, Ane
    Brasington, James
    Guinau, Marta
    Furdada, Gloria
    Cabre, Marilo
    Moysset, Myriam
    ENGINEERING GEOLOGY, 2018, 237 : 168 - 180
  • [45] Comparative Analysis of Multi-Platform, Multi-Resolution, Multi-Temporal LiDAR Data for Forest Inventory
    Lin, Yi-Chun
    Shao, Jinyuan
    Shin, Sang-Yeop
    Saka, Zainab
    Joseph, Mina
    Manish, Raja
    Fei, Songlin
    Habib, Ayman
    REMOTE SENSING, 2022, 14 (03)
  • [46] Monitoring of forest change by using multi-temporal satellite data
    Musaoglu, N
    Örmeci, C
    REMOTE SENSING IN THE 21ST CENTURY: ECONOMIC AND ENVIRONMENTAL APPLICATIONS, 2000, : 41 - +
  • [47] Use of Multi-Temporal Remote Sensing Data and GIS for Wetland Change Monitoring and Degradation
    Ghobadi, Y.
    Pradhan, B.
    Kabiri, K.
    Pirasteh, S.
    Shafri, H. Z. M.
    Sayyad, G. A.
    2012 IEEE COLLOQUIUM ON HUMANITIES, SCIENCE & ENGINEERING RESEARCH (CHUSER 2012), 2012,
  • [48] Monitoring flood using multi-temporal ENVISAT ASAR data
    Lv, XL
    Liu, RG
    Liu, JY
    Song, XF
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 3627 - 3629
  • [49] ESTIMATION OF CROP EXTENT USING MULTI-TEMPORAL PALSAR DATA
    Milisavljevic, Nada
    Holecz, Francesco
    Bloch, Isabelle
    Closson, Damien
    Collivignarelli, Francesco
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 5943 - 5946
  • [50] Discrimination of glacier facies using multi-temporal SAR data
    Partington, KC
    JOURNAL OF GLACIOLOGY, 1998, 44 (146) : 42 - 53