Detection of change in Moroccan rangelands with multitemporal spot imagery

被引:4
|
作者
Bennouna, T
Nejmeddine, A
Lefevre-Fonollosa, MJ
Lacombe, JP
Kaemmerer, M
Revel, JC
机构
[1] Fac Sci Semlalia, Lab Toxicol Environm, Marrakech, Morocco
[2] Cnes Toulouse, Toulouse, France
[3] ENSAT, INP, Equipe Biodivers Agroecosyst, Toulouse, France
[4] ENSAT, INP, Equipe Agron Environm Ecotoxicol, Toulouse, France
关键词
aridity; degradation; mapping; remote sensing; vegetation;
D O I
10.1080/15324980490451311
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The purpose of this work was to establish a multitemporal methodology for monitoring and detecting changes of arid rangeland by remote sensing. Three steps compose this method. In the first step, visual interpretation of Spot images allows description of the distribution of vegetative biomass in the study area. A "color intensity" criterion indicates changes of each landscape unit. In the second step, radiometric analysis revealed the dynamic of each formation by the comparison of the coefficient of correlation between the Near Infrared (NIR) and Red (R) channels. The rate of vegetation development was correlated with climatic and socioeconomic data to determine its principal causes. In the final step, the changes occurring in each formation in relation to time were mapped according to a simple vegetation index (ratio NIR/R) and the coefficient of variation (standard deviation/mean) for each class. This latter coefficient indicated the change dynamics of each class. It corroborated the results obtained with the correlation coefficient and was directly linked to the relative heterogeneity of each class. The proposed temporal monitoring approach is based on simple criteria that are easy to apply and that demonstrate the differential change of each landscape unit. The degraded areas where change is regressive or those little frequented by animals where change is progressive can, thus, be rapidly identified. This is essential information which, in the hands of the decision-makers, will be able to ensure a rational and sustained management of these rangelands.
引用
收藏
页码:229 / 240
页数:12
相关论文
共 50 条
  • [41] Multitemporal change detection by spectral and multivariate texture information
    Li, Peijun
    Cheng, Tao
    Moser, Gabriele
    Serpico, Sebastiano B.
    Ma, Defeng
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 1922 - +
  • [42] Hierarchical Unsupervised Change Detection in Multitemporal Hyperspectral Images
    Liu, Sicong
    Bruzzone, Lorenzo
    Bovolo, Francesca
    Du, Peijun
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (01): : 244 - 260
  • [43] A MULTITEMPORAL CHANGE DETECTION SOLUTION TO OIL SPILL MONITORING
    Liu, Sicong
    Chi, Mingmin
    Zou, Yangxiu
    Samat, Alim
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 7718 - 7721
  • [44] Multitemporal Symmetric Fusion Network for Hyperspectral Change Detection
    Lu, Xukun
    Duan, Puhong
    Deng, Bin
    Kang, Xudong
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
  • [45] MULTITEMPORAL IMAGE CHANGE DETECTION WITH COMPRESSED SPARSE REPRESENTATION
    Fang, Leyuan
    Li, Shutao
    Hu, Jianwen
    2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2011,
  • [46] GPU Framework for Change Detection in Multitemporal Hyperspectral Images
    Javier López-Fandiño
    Dora B. Heras
    Francisco Argüello
    Mauro Dalla Mura
    International Journal of Parallel Programming, 2019, 47 : 272 - 292
  • [47] A method for detection and analysis of change between multitemporal images
    Hanaizumi, H
    Chino, S
    Fujimura, S
    IEICE TRANSACTIONS ON COMMUNICATIONS, 1995, E78B (12) : 1611 - 1616
  • [48] GPU Framework for Change Detection in Multitemporal Hyperspectral Images
    Lopez-Fandino, Javier
    Heras, Dora B.
    Argueello, Francisco
    Dalla Mura, Mauro
    INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, 2019, 47 (02) : 272 - 292
  • [49] Change detection in underwater imagery
    Seemakurthy, Karthik
    Rajagopalan, A. N.
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2016, 33 (03) : 301 - 313
  • [50] CHANGE DETECTION IN SAR IMAGERY
    WHITE, RG
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 1991, 12 (02) : 339 - 360