TY - JOUR
T1 - Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change
AU - Lamqadem, Atman Ait
AU - Afrasinei, Gabriela Mihaela
AU - Saber, Hafid
N1 - Publisher Copyright:
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE).
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Oasis agroecosystems monitoring plays a significant role in the economic development, sustainable management, and policy-making of arid and Saharan regions. The aims of this study are to analyze the spatiotemporal changes of oasis vegetation and discuss possible driving forces of changes. This analysis employed field and ancillary data, geographic information system, Landsat imagery, and remote-sensing techniques. Minimum noise fraction is used for endmembers extraction, and spectral mixture analysis is applied to each image to extract vegetation fraction, which is used as an indicator of change. Change detection is performed in six oases in south-eastern Morocco over eight separate periods from 1984 to 2017 using Landsat data. The pattern of the spatiotemporal changes in vegetation cover is analyzed using time- and space-oriented change detection algorithms. Results indicate that the Mezguita, Tinzouline, and Ternata oases had an evenly distributed and constant expansion during the last three decades (of 41.35%), whereas the oases of Fezouata and Ktaoua presented low expansion and randomly distributed change (29%). However, the vegetation cover of MHamid oasis decreased by 23% over the studied period. The results show that spectral mixture analysis yields high accuracies for oasis vegetation extraction in arid areas and accounts for mixed pixel issues. The results are discussed considering also climate and socioeconomic factors, showing that the driving forces of these dynamics are primarily anthropogenic.
AB - Oasis agroecosystems monitoring plays a significant role in the economic development, sustainable management, and policy-making of arid and Saharan regions. The aims of this study are to analyze the spatiotemporal changes of oasis vegetation and discuss possible driving forces of changes. This analysis employed field and ancillary data, geographic information system, Landsat imagery, and remote-sensing techniques. Minimum noise fraction is used for endmembers extraction, and spectral mixture analysis is applied to each image to extract vegetation fraction, which is used as an indicator of change. Change detection is performed in six oases in south-eastern Morocco over eight separate periods from 1984 to 2017 using Landsat data. The pattern of the spatiotemporal changes in vegetation cover is analyzed using time- and space-oriented change detection algorithms. Results indicate that the Mezguita, Tinzouline, and Ternata oases had an evenly distributed and constant expansion during the last three decades (of 41.35%), whereas the oases of Fezouata and Ktaoua presented low expansion and randomly distributed change (29%). However, the vegetation cover of MHamid oasis decreased by 23% over the studied period. The results show that spectral mixture analysis yields high accuracies for oasis vegetation extraction in arid areas and accounts for mixed pixel issues. The results are discussed considering also climate and socioeconomic factors, showing that the driving forces of these dynamics are primarily anthropogenic.
KW - Change detection
KW - Land degradation
KW - Landsat imagery
KW - Oasis agroecosystems
KW - Spectral mixture analysis
KW - Vegetation cover
UR - http://www.scopus.com/inward/record.url?scp=85062731445&partnerID=8YFLogxK
U2 - 10.1117/1.JRS.13.014517
DO - 10.1117/1.JRS.13.014517
M3 - Article
AN - SCOPUS:85062731445
SN - 1931-3195
VL - 13
JO - Journal of Applied Remote Sensing
JF - Journal of Applied Remote Sensing
IS - 1
M1 - 014517
ER -