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Articles | Volume XLII-4/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W12, 1–10, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W12-1-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W12, 1–10, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W12-1-2019

  21 Feb 2019

21 Feb 2019

MAPPING OF LAND-COVER CHANGE ANALYSIS IN MA’RIB AT YEMEN USING REMOTE SENSING AND GIS TECHNIQUES

S. Al-Akad1, Y. Akensous1, M. Hakdaoui1, F. Al-Nahmi2, S. Mahyoub2, K. Khanbari3, and H. Swadi4 S. Al-Akad et al.
  • 1Laboratory of Applied Geology, Geomatics and Environment, Faculty of Sciences ben M'sik, Hassan II University, Casablanca, Morocco
  • 2Laboratory Geosciences, Department of Geology, Faculty of Sciences, Hassan II University Casablanca, Morocco
  • 3Yemen Remote Sensing and GIS Centre, Sana’a University, Yemen
  • 4Department of Geography and GIS, University of Thi-Gar, Nasiriyah, Iraq

Keywords: Ma’rib Yemen, Land-use and land-cover (LULC), Remote sensing, Change detection, LULC map, Non-supervised classification, Recode

Abstract. Studies on the change in occupation and land-use are of great importance in order to understand landscape dynamics in the process of agricultural land degradation, urbanization, desertification, deforestation and all change in the landscape global of a region. The most effective procedure to measure the degree of land-cover and land-use changes is the multi-date study. For this purpose, the aim of this work is to analyze the current evolution of land-use and land-cover (LULC) using remote sensing techniques, in order to better understand this evolution. For this purpose, a diachronic approach is applied to satellite images acquired in 1987 to 2018 of Ma’rib city Yemen. The LULC maps we obtained were produced from different image analysis procedures (non-supervised classification and recode technique) to map the land-use and land-cover. The objective of this study is to apply reproducibly and generalizable a predefined nomenclature to different scenes of satellite images. The first step consists in interpreting the radiometric classes obtained by non-supervised classification so as to form the classes of the thematic nomenclature. An improvement of the classification is then obtained by using the recode technique which makes it possible to correctly reassign the previously badly classified pixels of the satellite images classification. Land-cover maps obtained from remote sensing were used to quantify the rate of change (Tc) and (Tg) of area occupied by each class. The results will indicate the most changeable period and the percentage of overall change in the study area (Ma’rib Yemen), and helped to identify and characterize the spatial and temporal evolution of land use in the district over a period of thirty-one years (1987 to 2018). They reveal that annual average rates of decline for the water body is −83.5% and −9.96% for the sandy land. However, it was observed an increase in built-up area 365.52% and farm land 324.52% classes.