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The expansion of agricultural land at the cost of pastoral land is the common cause of land degradation 12 in the arid areas of developing countries, especially in Morocco. This study aims to assess and monitor 13 the transformation of pastoral land to agricultural land in the arid environment of the Feija Basin 14 (Southeast of Morocco) and to find the key drivers and the issues resulting from this transformation. 15 Spectral mixture analysis was applied to multi-temporal (1975-2017) and multi-sensor (i.e. Multi-16 spectral Scanner, Thematic Mapper, and Operational Land Imager) Landsat satellite images, from 17 which land use classifications were derived. The remote sensing data in combination with ground 18 reference data (household level), groundwater and climate statistics were used to validate and explain 19 the derived land use change maps. The results of the spatiotemporal changes in agricultural lands show 20 two pattens of changes, a middle expansion from 1975-2007, and a rapid expansion from 2008 to 2017. 21 In addition, the overall accuracy demonstrated a high accuracy of 94.4%. In 1975 and 1984, the 22 agricultural lands in Feija covered 0.17 km² and 1.32 km², respectively, compared with 20.10 km² in 23 2017. Since the adoption of the Green Morocco Plan in 2008, the number of watermelon farms and wells 24 has increased rapidly in the study area, which induced a piezometric level drawdown. The results show 25 that spectral mixture analysis yields high accuracies for agricultural lands extraction in arid dry lands 26 and accounts for mixed pixels issues. Results of this study can be used by local administrators to prepare 27 an effective environmental management plan of these fragile drylands. The proposed method can be 28 replicated in other regions to analyse land transformation in similar arid conditions.
The expansion of agricultural land at the cost of pastoral land is the common cause of land degradation 12 in the arid areas of developing countries, especially in Morocco. This study aims to assess and monitor 13 the transformation of pastoral land to agricultural land in the arid environment of the Feija Basin 14 (Southeast of Morocco) and to find the key drivers and the issues resulting from this transformation. 15 Spectral mixture analysis was applied to multi-temporal (1975-2017) and multi-sensor (i.e. Multi-16 spectral Scanner, Thematic Mapper, and Operational Land Imager) Landsat satellite images, from 17 which land use classifications were derived. The remote sensing data in combination with ground 18 reference data (household level), groundwater and climate statistics were used to validate and explain 19 the derived land use change maps. The results of the spatiotemporal changes in agricultural lands show 20 two pattens of changes, a middle expansion from 1975-2007, and a rapid expansion from 2008 to 2017. 21 In addition, the overall accuracy demonstrated a high accuracy of 94.4%. In 1975 and 1984, the 22 agricultural lands in Feija covered 0.17 km² and 1.32 km², respectively, compared with 20.10 km² in 23 2017. Since the adoption of the Green Morocco Plan in 2008, the number of watermelon farms and wells 24 has increased rapidly in the study area, which induced a piezometric level drawdown. The results show 25 that spectral mixture analysis yields high accuracies for agricultural lands extraction in arid dry lands 26 and accounts for mixed pixels issues. Results of this study can be used by local administrators to prepare 27 an effective environmental management plan of these fragile drylands. The proposed method can be 28 replicated in other regions to analyse land transformation in similar arid conditions.
The mining area in the Muli region, Qinghai Province, China, is an important source of water and an ecological security barrier in the Qilian Mountains region and has a very important ecological status. A series of ecological problems such as vegetation degradation and loss of biodiversity caused by mining have attracted widespread attention. In this paper, we used Landsat secondary data from 2000 to 2021 from the Muli region to obtain the spatial and temporal distribution characteristics of the vegetation in the Muli region by inversion of the fractional vegetation cover, above-ground biomass and the land surface phenology to comprehensively analyze the ecological changes in the vegetation in the Muli region. The results showed the following: (1) the above-ground biomass and cover of grassland in the Muli region showed a decreasing trend between 2000 and 2021, with a particularly pronounced decrease in grassland cover between 2009 and 2016; (2) the start of the vegetation growth cycle, i.e., the beginning of the vegetation growing season (SOG) became more advanced, the end of the vegetation growing season (EOG) was delayed, and the length of the growing cycle (LOG) became longer for most of the vegetation in the Muli region; (3) the results of this comprehensive analysis showed that the grassland in the Muli region showed dynamic changes with complex characteristics from 2000 to 2021, and anthropogenic disturbances had some influence on ecological indicators such as fractional vegetation cover and biomass. The extension of the vegetation growing season might be related to climate change. Based on the results of this paper, it is recommended to utilize biomass and fractional vegetation cover as indicators to assess the grass growth status of mining sites. This study analyzed the spatial and temporal characteristics of grasslands in the Muli area with several indicators, which will help relevant departments continue to improve and optimize ecological restoration measures. In addition, this study provides a reference for achieving comprehensive restoration of the ecological environment and ecological functions in mining areas.
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