我国地理学研究的数据识别及应用特征——基于地理类中文核心期刊文献分析视角

Research on Data Identification and Application Characteristics of Geographical in China——From the Perspective of Chinese Core Journal of Geography and Literature Analysis

数据是科学研究的基础,识别地理学研究领域数据来源及其特征对学科的理论研究和实际应用都具有重要的现实意义.以2000年以来5种地理学中文核心期刊所刊载的学术性论文为样本,采用文献内容分析、文献计量、 CiteSpace与编码相结合的方法对这些论文使用的数据进行识别、归类,并探索这些数据的获取方式以及在地理学中的应用特征.结果表明:高频使用数据主要有面板数据、遥感影像、调查数据、 TM数据、空间数据、遥感数据、 Landsat数据、 NDVI数据、人口普查数据和MODIS数据等;使用高频数据的文献聚集主题主要为土地利用、时空分异、青藏高原、长江经济带、旅游交通、位置定位、气温降水等;数据获取方式及渠道主要有WoS等数据库、政府部门官网、百度腾讯等企业、调研实测和卫星遥感;地理学研究数据的获取方式及载体形式呈现多样化现代化,数据内容与人类社会活动密切相关、时代性特征明显,且人文地理类数据类型更丰富.

Data is the most basic part of scientific research, thus identifying the data sources and data features of geography is of vital importance for both theoretical study and practical application. Having selected academic papers written in the 21 st century from five geography core journals as examples, this study has adopted the combination of content analysis, bibliometric, CiteSpace and encoding to identify and categorize the data in these papers, and then explored the acquiring approaches and application features in geography of these data. The result showed that the most frequently used data are panel data, remote-sensing images, survey data, TM data, spatial data, Landsat data, NDVI data, census data and MODIS data. The main topics of literature aggregation using high-frequency data were land use, temporal and spatial differentiation, Qinghai Tibet Plateau, Yangtze River economic belt, tourism and transportation, location positioning, temperature and precipitation, etc. Additionally, the main acquiring approaches were database such as Web of Science, official websites of government departments, Baidu, Tencent and other enterprises, field investigation and satellite remote sensing. Meanwhile, the data acquiring approach and carrier format were diverse and modern, data were closely related to human society activities and all data have obvious contemporary characteristics, and human geography data types were more abundant.