Remote sensing as the foundation for high-resolution United States landscape projections - The Land Change Monitoring, assessment, and projection (LCMAP) initiative

被引:16
|
作者
Sohl, Terry [1 ]
Dornbierer, Jordan [2 ]
Wika, Steve [2 ]
Robison, Charles [2 ]
机构
[1] US Geol Survey, Earth Resources Observat & Sci EROS Ctr, 47914 252nd St, Sioux Falls, SD 57198 USA
[2] US Geol Survey, SGT Inc, EROS Ctr, 47914 252nd St, Sioux Falls, SD 57198 USA
关键词
Scenario; Projection; Model; Land use; Great plains; COVER CHANGE; FOREST DISTURBANCE; MISSISSIPPI RIVER; NATIONAL-SCALE; FUTURE; DATABASE; MODELS; URBAN; CROP; CLASSIFICATION;
D O I
10.1016/j.envsoft.2019.104495
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatial and thematic) landscape projections at a national scale, using a unique parcel-based modeling framework. The methodology was tested by modeling 11 land use scenarios and 3 climate realizations for the U.S. Great Plains. Results demonstrate 1) an ability to balance competing land-use demands from quite variable, complex scenarios, 2) urban growth that matches theoretical future patterns, 3) the value of remote sensing data sources for model parameterization and for deriving landscape parcels, and 4) a pragmatic approach that facilitates the development of high thematic- and spatial-resolution projections at a national scale.
引用
下载
收藏
页数:17
相关论文
共 50 条
  • [1] Training Data Selection for Annual Land Cover Classification for the Land Change Monitoring, Assessment, and Projection (LCMAP) Initiative
    Zhou, Qiang
    Tollerud, Heather
    Barber, Christopher
    Smith, Kelcy
    Zelenak, Daniel
    REMOTE SENSING, 2020, 12 (04)
  • [2] Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach
    Brown, Jesslyn F.
    Tollerud, Heather J.
    Barber, Christopher P.
    Zhou, Qiang
    Dwyer, John L.
    Vogelmann, James E.
    Loveland, Thomas R.
    Woodcock, Curtis E.
    Stehman, Stephen V.
    Zhu, Zhe
    Pengra, Bruce W.
    Smith, Kelcy
    Horton, Josephine A.
    Xian, George
    Auch, Roger F.
    Sohl, Terry L.
    Sayler, Kristi L.
    Gallant, Alisa L.
    Zelenak, Daniel
    Reker, Ryan R.
    Rover, Jennifer
    REMOTE SENSING OF ENVIRONMENT, 2020, 238
  • [3] Bridge monitoring and assessment by high-resolution satellite remote sensing technologies
    Gagliardi, Valerio
    Ciampoli, Luca Bianchini
    D'Amico, Fabrizio
    Alani, Amir M.
    Tosti, Fabio
    Battagliere, Maria Libera
    Benedetto, Andrea
    SPIE FUTURE SENSING TECHNOLOGIES (2020), 2020, 11525
  • [4] High-resolution remote sensing mapping of global land water
    Liao AnPing
    Chen LiJun
    Chen Jun
    He ChaoYing
    Cao Xin
    Chen Jin
    Peng Shu
    Sun FangDi
    Gong Peng
    SCIENCE CHINA-EARTH SCIENCES, 2014, 57 (10) : 2305 - 2316
  • [5] High-resolution remote sensing mapping of global land water
    AnPing Liao
    LiJun Chen
    Jun Chen
    ChaoYing He
    Xin Cao
    Jin Chen
    Shu Peng
    FangDi Sun
    Peng Gong
    Science China Earth Sciences, 2014, 57 : 2305 - 2316
  • [6] High-resolution remote sensing mapping of global land water
    LIAO AnPing
    CHEN LiJun
    CHEN Jun
    HE ChaoYing
    CAO Xin
    CHEN Jin
    PENG Shu
    SUN FangDi
    GONG Peng
    Science China Earth Sciences, 2014, 57 (10) : 2305 - 2316
  • [7] A Spatiotemporal Change Detection Method for Monitoring Pine Wilt Disease in a Complex Landscape Using High-Resolution Remote Sensing Imagery
    Zhang, Biyao
    Ye, Huichun
    Lu, Wei
    Huang, Wenjiang
    Wu, Bo
    Hao, Zhuoqing
    Sun, Hong
    REMOTE SENSING, 2021, 13 (11)
  • [8] Updating land cover map based on change detection of high-resolution remote sensing images
    Guo, Rui
    Xiao, Pengfeng
    Zhang, Xueliang
    Liu, Hao
    JOURNAL OF APPLIED REMOTE SENSING, 2021, 15 (04)
  • [9] Assessment and Quantification of the Accuracy of Low- and High-Resolution Remote Sensing Data for Shoreline Monitoring
    Apostolopoulos, Dionysios N.
    Nikolakopoulos, Konstantinos G.
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 9 (06)
  • [10] AUTOMATED CHANGE DETECTION FROM HIGH-RESOLUTION REMOTE SENSING IMAGES
    Ehlers, Manfred
    Klonus, Sascha
    Tomowski, Daniel
    Michel, Ulrich
    Reinartz, Peter
    GEOSPATIAL DATA AND GEOVISUALIZATION: ENVIRONMENT, SECURITY, AND SOCIETY, 2010, 38