收稿：2019-08-08，
纸质出版：2022-03-07
移动端阅览
近年来不合理的开发利用矿产资源一直是备受关注的问题，对违法开采矿产资源的时空分布特征研究显得尤为重要。为解决大范围矿产资源违法开采信息获取难、精度低，数据零散、缺乏长时序的问题，本文提出了基于多源卫星遥感数据与克立金数据分析相结合的矿山违法开采时空分布特征研究方法。首先以湖南省为研究区域，采用2010年—2017年多时相多平台卫星遥感影像数据，结合湖南省采矿权数据，采用人机交互解译方法，提取了2010年—2017年的矿山违法开采数据；然后利用克立金空间数据插值方法，分析了8 a的矿山违法开采数据；最后在此基础上重点研究了湖南省矿山违法开采的时空分布特征。结果显示：2010年—2017年湖南省共有矿山违法开采矿山2815处；空间上主要分布在湘南、湘西南、湘中和湘东地区，时间上呈波浪逐年上升趋势；违法开采集中区存在着由湘南向湘中、湘西、湘东、湘北及湘西北分阶段扩展，由“高度集中”向“多点开花”再向“广泛分布”的发展趋势；违法开采矿种主要以非金属矿为主，存在一定数量的能源和金属矿，非金属矿的违法开采呈显著上升趋势；违法开采类型主要为无证开采和越界开采，越界开采呈上升态势。本研究表明利用多源卫星遥感数据结合克立金数据分析方法，能客观、准确、长时序地提取大范围的矿山违法开采信息，能有效揭示矿山违法开采的时空分布特征，为深入研究矿山违法开采行为驱动力提供数据基础，为国家制定适应性政策提供科学依据。
In recent years
the unreasonable development and utilization of mineral resources have been a global concern
and studying the spatial and temporal distribution characteristics of illegal mining resources is of particular importance. To solve the difficulty in obtaining information on the illegal mining of large-scale mineral resources
low accuracy
scattered data
and lack of long time series
this paper proposes a method for extracting the spatiotemporal distribution characteristics of illegal mining in multi-source satellite remote sensing data. First
Hunan Province was used as the research area
and the multi-source satellite remote sensing image data of 2010—2017 were combined with the mining rights data of Hunan Province. The human-machine interactive interpretation method was used to extract the illegal mining data of 2010—2017. The Kriging spatial data interpolation method analyzes the mining illegal mining data for 8 years. Finally
on this basis
the spatial and temporal distribution characteristics of illegal mining in Hunan Province are mainly studied. Results show that from 2010 to 2017
Hunan Province had a total of 2815 illegal mines
which were mainly distributed in Southern Hunan
Southwestern Hunan
Central Hunan
and Eastern Hunan
showing a year-on-year rising trend in time. Xiangnan
Xiangxi
Xiangdong
Xiangbei
and Northwestern Hunan expand and change in stages and regions. The spatial distribution also tends to develop from “high concentration” to “multiple points and wide areas.” Illegal mining is mainly based on non-metallic mines. A certain number of energy and metal mines exists. The illegal mining of non-metal mines shows a significant upward trend; the types of illegal mining are mainly unlicensed and cross-border mining
and the behavior of cross-border mining is on the rise. This study shows that the use of multi-source satellite remote sensing data can objectively
accurately
and long-term extract large-scale mining illegal information and effectively reveal the spatial and temporal distribution characteristics of illegal mining. An in-depth study of the driving force of illegal mining behavior is provided. Scientific and theoretical bases are provided for the country to formulate adaptive policies.
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