<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Revealing the relationship of human convergence-divergence patterns and land use: A case study on Shenzhen City, China."
Abstract:"Understanding the relationship between human mobility and land use has been a longstanding topic in multiple disciplines, including transport geography and urban planning. Recently, urban collective mobility patterns have become a hot research direction and has been explored at an unprecedented space-time scale due to the emerging big human tracking datasets (e.g., mobile phone data). However, only a few studies have comprehensively quantified the effects of land use on human mobility patterns while considering the influence of the scale of spatial analysis units. This study attempts to reinforce this knowledge by investigating urban human convergence-divergence patterns and their relationship with land use distribution characteristics at three popular types of spatial analysis units of human mobility studies (voronoi polygons, grid cells, and traffic analysis zones) using mobile phone data. A case study on Shenzhen, China is implemented, and results indicate that eight distinct convergence-divergence patterns could be extracted to describe urban collective mobility patterns despite the use of different types of spatial analysis unit. Moreover, the scale of spatial analysis units exerts a few effects on the quantification of the influence of land use distribution on human convergence-divergence patterns, but some common characteristics could be summarized from these discrepant results. The findings can help policy makers understand urban human mobility and can serve as a guide for urban management and planning.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
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Q4 = [0];
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Revealing the relationship of human convergence-divergence patterns and land use: A case study on Shenzhen City, China
Understanding the relationship between human mobility and land use has been a longstanding topic in multiple disciplines, including transport geography and urban planning. Recently, urban collective mobility patterns have become a hot research direction and has been explored at an unprecedented space-time scale due to the emerging big human tracking datasets (e.g., mobile phone data). However, only a few studies have comprehensively quantified the effects of land use on human mobility patterns while considering the influence of the scale of spatial analysis units. This study attempts to reinforce this knowledge by investigating urban human convergence-divergence patterns and their relationship with land use distribution characteristics at three popular types of spatial analysis units of human mobility studies (voronoi polygons, grid cells, and traffic analysis zones) using mobile phone data. A case study on Shenzhen, China is implemented, and results indicate that eight distinct convergence-divergence patterns could be extracted to describe urban collective mobility patterns despite the use of different types of spatial analysis unit. Moreover, the scale of spatial analysis units exerts a few effects on the quantification of the influence of land use distribution on human convergence-divergence patterns, but some common characteristics could be summarized from these discrepant results. The findings can help policy makers understand urban human mobility and can serve as a guide for urban management and planning.