<|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:"Not all those who Wander are lost: exploring human mobility using a smartphone application."
Abstract:"Since the 1970s, activity diaries have been the principal source of data used by geographers and urban planners to capture human mobility patterns; however, memory recall requirements and participant burden are limiting features of this approach. While handheld GPS devices were initially used to simply validate activity diaries, the ubiquity of smartphones makes GPS-based technology a viable alternative for collecting human mobility data. This research visualises human mobility patterns using spatiotemporally GPS-rich traces collected from 24 participants during a pilot study of a new smartphone applicationWander. The results illustrate the utility of such data for capturing individuals' multi-nodal activity spaces to better understand people-place interactions in the context of increasingly fluid and mobile lifestyles. Finally, we draw on our experiences of implementing this pilot study to discuss the benefits and limitations of this technology for its broader application in domains such as transportation planning, tourism management, and in the management of crime and disorder.."
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 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [];
Q3 = [2];
Q4 = [0];
Q5 = [];
Q6 = [1].
Not all those who Wander are lost: exploring human mobility using a smartphone application
Since the 1970s, activity diaries have been the principal source of data used by geographers and urban planners to capture human mobility patterns; however, memory recall requirements and participant burden are limiting features of this approach. While handheld GPS devices were initially used to simply validate activity diaries, the ubiquity of smartphones makes GPS-based technology a viable alternative for collecting human mobility data. This research visualises human mobility patterns using spatiotemporally GPS-rich traces collected from 24 participants during a pilot study of a new smartphone applicationWander. The results illustrate the utility of such data for capturing individuals' multi-nodal activity spaces to better understand people-place interactions in the context of increasingly fluid and mobile lifestyles. Finally, we draw on our experiences of implementing this pilot study to discuss the benefits and limitations of this technology for its broader application in domains such as transportation planning, tourism management, and in the management of crime and disorder.