<|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:"Impacts of large-scale refugee resettlement on LCLUC: Bidi Bidi refugee settlement, Uganda case study."
Abstract:"Uganda is the third-largest refugee-hosting country partly due to its open-door policy-deemed one of the most progressive. When new refugees arrive, refugee settlements are established rapidly, and irreversible changes to the landscape are inevitable. We utilize satellite data to map land cover (LC), land use, and burned area (BA) to assess their relationship in the context of large-scale refugee resettlement in Bidi Bidi-Uganda's largest refugee settlement. We show inevitable dramatic changes in LC, e.g. built-up residential zones increased from 1.8% to 30%, while cropland increased from less than 0.7%-25.6% during our study period (2015-2019). In contrast, BA that affected more than 80% of the area was drastically reduced during the establishment phase (August-December 2017). Substantial reduction in BA was observed predominantly within the residential zones, but outside of the zones, BA was hardly affected by the arrival of refugees. Our study shows that these changes in LC and BA are mainly missing in the readily accessible satellite-derived data products, which impede assessment, planning, and implementation of humanitarian response programs. We discuss the importance of mapping at the appropriate spatial and temporal scales and the importance of context, sector, and geographic domain knowledge expertise in developing critical information products for informing programs to support vulnerable populations.."
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 = [];
Q2 = [];
Q3 = [];
Q4 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [4];
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Q5 = [];
Q6 = [1].
Impacts of large-scale refugee resettlement on LCLUC: Bidi Bidi refugee settlement, Uganda case study
Uganda is the third-largest refugee-hosting country partly due to its open-door policy-deemed one of the most progressive. When new refugees arrive, refugee settlements are established rapidly, and irreversible changes to the landscape are inevitable. We utilize satellite data to map land cover (LC), land use, and burned area (BA) to assess their relationship in the context of large-scale refugee resettlement in Bidi Bidi-Uganda's largest refugee settlement. We show inevitable dramatic changes in LC, e.g. built-up residential zones increased from 1.8% to 30%, while cropland increased from less than 0.7%-25.6% during our study period (2015-2019). In contrast, BA that affected more than 80% of the area was drastically reduced during the establishment phase (August-December 2017). Substantial reduction in BA was observed predominantly within the residential zones, but outside of the zones, BA was hardly affected by the arrival of refugees. Our study shows that these changes in LC and BA are mainly missing in the readily accessible satellite-derived data products, which impede assessment, planning, and implementation of humanitarian response programs. We discuss the importance of mapping at the appropriate spatial and temporal scales and the importance of context, sector, and geographic domain knowledge expertise in developing critical information products for informing programs to support vulnerable populations.