2023
DOI: 10.1016/j.jag.2023.103523
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Spatial optimization of cotton cultivation in Xinjiang: A climate change perspective

Yaqiu Zhu,
Liang Sun,
Qiyou Luo
et al.
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Cited by 8 publications
(4 citation statements)
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“…However, cotton is a crop with high water consumption, and the effect of planting density on the canopy photosynthetic rate can be studied to improve the cotton yield in Xinjiang [39]. In addition, land-use conflicts can be identified and suggestions made to optimize the spatial layout of cotton planting [40]. However, in the arid region of northwest China, maize is the main contributor to the blue and green water footprints (accounting for 21.15% and 20.31% of the total blue and green water footprints, respectively), which is closely related to the agricultural planting structure in the arid region of northwest China [37].…”
Section: Discussionmentioning
confidence: 99%
“…However, cotton is a crop with high water consumption, and the effect of planting density on the canopy photosynthetic rate can be studied to improve the cotton yield in Xinjiang [39]. In addition, land-use conflicts can be identified and suggestions made to optimize the spatial layout of cotton planting [40]. However, in the arid region of northwest China, maize is the main contributor to the blue and green water footprints (accounting for 21.15% and 20.31% of the total blue and green water footprints, respectively), which is closely related to the agricultural planting structure in the arid region of northwest China [37].…”
Section: Discussionmentioning
confidence: 99%
“…The NSEBTM is deep inland and far from the sea with a closed terrain, which makes it difficult for marine moisture to reach the region. It is controlled by continental air masses throughout the year, with scarce precipitation and an arid climate [45], which pose significant challenges to vegetation growth in the region. The main LUCC types in the NSEBTM are unused land, grassland, and farmland.…”
Section: Implications Of Human Actions On Changes In Luccmentioning
confidence: 99%
“…6). This data is sourced from the Xinjiang Statistical Yearbook [45]. Due to the cotton boll formation period being concentrated from July to August each year, we selected the daily average temperature data (T) from July 1st to August 31st in the past decade.…”
Section: Meteorological Data Sourcesmentioning
confidence: 99%