Please wait a minute...
国土资源遥感  2019, Vol. 31 Issue (1): 1-7    DOI: 10.6046/gtzyyg.2019.01.01
  综述 本期目录 | 过刊浏览 | 高级检索 |
高分遥感在自然资源调查中的应用综述
陈玲1,贾佳2,王海庆1
1.中国自然资源航空物探遥感中心,北京 100083
2.河南测绘职业学院,郑州 451464
An overview of applying high resolution remote sensing to natural resources survey
Ling CHEN1,Jia JIA2,Haiqing WANG1
1.China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
2.Henan College of Surveying and Mapping, Zhengzhou 451464, China
全文: PDF(733 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

随着高分卫星的陆续发射,高分遥感数据在自然资源调查中的应用价值越显突出。在介绍高分(高空间分辨率、高时间分辨率、高光谱分辨率以及高辐射分辨率)遥感数据的基础上,综述了高分遥感数据在土地利用调查、矿产资源开发与环境监测、基础地质及资源能源调查、生态环境调查、地质灾害监测与应急调查等领域的应用,并分析了高分遥感数据的应用发展趋势,指出未来多源多尺度高分遥感数据协同应用将在自然资源调查中发挥越来越重要的作用。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
陈玲
贾佳
王海庆
关键词 高分遥感数据自然资源调查应用发展趋势    
Abstract

With the launch of high-resolution satellites, their applications in geological survey become more prominent. Based on the introduction of various kinds of high resolution data which include high spatial resolution satellite remote sensing, high temporal resolution satellite remote sensing, high spectral resolution satellite remote sensing and high radiation resolution satellite remote sensing, this paper gives a review of the application of optical high resolution images to geological survey, mainly in the aspects of dynamic monitoring of land use, basic geological and resources survey, mineral resources development and ecological monitoring, ecological environment investigation, geological disaster and emergency investigation. It is found that high resolution remote sensing images have great potential in natural resources survey,and collaborative application of multi-source multi-scale high resolution remote sensing data will play an increasingly important role in natural resources survey in the future.

Key wordshigh resolution remote sensing data    natural resources survey    application    development tendency
收稿日期: 2017-11-24      出版日期: 2019-03-15
ZTFLH:  TP79  
基金资助:中国地质调查局地质调查项目“天山—北山重要成矿区带遥感调查”资助(DD20160068)
作者简介: 陈 玲(1982-),女,博士,高级工程师,主要从事遥感地质、矿产等理论和应用研究。Email: chenling010@126.com。
引用本文:   
陈玲,贾佳,王海庆. 高分遥感在自然资源调查中的应用综述[J]. 国土资源遥感, 2019, 31(1): 1-7.
Ling CHEN,Jia JIA,Haiqing WANG. An overview of applying high resolution remote sensing to natural resources survey. Remote Sensing for Land & Resources, 2019, 31(1): 1-7.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.01.01      或      http://www.gtzyyg.com/CN/Y2019/V31/I1/1
传感器类型 波段号 光谱范围/nm 空间分辨率/m 重访周期/d 位深/bit 快速响应能力
GF-2 全色 450900 1 5 10 一般
1 450520 4
2 520590 4
3 630690 4
4 770890 4
GF-4 1 可见光 50 分钟级别 10 可接受紧急任务,应急响应高效
2 中波红外 400
WorldView-2 全色 450800 0.5 1.1 11 具备快速响应机制
1 400450 1.8
2 450510 1.8
3 510580 1.8
4 585625 1.8
5 630690 1.8
6 705745 1.8
7 770895 1.8
8 8601 040 1.8
WorldView-3 全色 450800 0.31 13 11 具备快速响应机制
1 400450 1.24
2 450510 1.24
3 510580 1.24
4 585625 1.24
5 630690 1.24
6 705745 1.24
7 770895 1.24
8 8601 040 1.24
9 1 1951 225 3.7
10 1 5501 590 3.7
11 1 6401 680 3.7
12 1 7101 750 3.7
13 2 1452 185 3.7
14 2 1852 225 3.7
15 2 2352 285 3.7
16 2 2952 365 3.7
传感器类型 波段号 光谱范围/nm 空间分辨率/m 重访周期/d 位深/bit 快速响应能力
GeoEye-1 全色 450800 0.5 23 11 具备快速响应机制
1 450510 2
2 510580 2
3 655690 2
4 780920 2
SPOT6/7 全色 450745 1.5 45 11 接收计划每4 h上传一次,可接受紧急任务
1 455520 6
2 530590 6
3 625695 6
4 760890 6
QuickBird 全色 445900 0.61 16 11 一般
1 450520 2.44
2 520600 2.44
3 630690 2.44
4 760900 2.44
Tab.1  自然资源调查中常用高空间、高时间及高辐射分辨率遥感数据及参数
成像仪
类型
传感器
类型
国家/地区 光谱范围/
nm
波段数 空间分
辨率/m
机载 HyMap 澳大利亚 4002 500 128 根据飞行高度不同而不同
AVIRIS 美国 4002 500 224
CASI 加拿大 3801 050 288
SASI 加拿大 9502 450 100
TASI 加拿大 8 00011 500 32
PHI 中国 400850 244
星载 Hyperion 美国 3572 576 220 30
CHRIS 欧盟 4151 050 62/34/18 34/17
HJ-1A 中国 450950 115 100
天宫一号 中国 4002 500 128 20/30
高分五号 中国 4002 500 330 30
Tab.2  自然资源调查中常用高光谱分辨率遥感数据参数
[1] Filion R, Bernier M, Paniconi C , et al.Remote sensing for mapping soil moisture and drainage potential in semi-arid regions:Applications to the Campidano plain of Sardinia, Italy[J].Science of the Total Environment, 2016, 543, Part B: 862-876.
doi: 10.1016/j.scitotenv.2015.07.068 pmid: 26254021
[2] 王润生 . 遥感地质技术发展的战略思考[J]. 国土资源遥感. 2008,20(1):1-12.doi: 10.6046/gtzyyg.2008.01.01.
doi: 10.6046/gtzyyg.2008.01.01
Wang R S . On the development strategy of remote sensing technology in geology[J]. Remote Sensing for Land and Resources, 2008,20(1):1-12.doi: 10.6046/gtzyyg.2008.01.01.
doi: 10.6046/gtzyyg.2008.01.01
[3] 张达, 郑玉权 . 高光谱遥感的发展与应用[J]. 光学与光电技术, 2013,11(3):67-73.
Zhang D, Zheng Y Q . Hyperspectral remote sensing and its development and application review[J]. Optics and Precision Engineering, 2013,11(3):67-73.
[4] Li M M, Stein A, Bijker W , et al. Urban land use extraction from very high resolution remote sensing imagery using a Bayesian network[J]. International Society for Photogrammetry and Remote Sensing Journal of Photogrammetry and Remote Sensing, 2016,122:192-205.
doi: 10.1016/j.isprsjprs.2016.10.007
[5] Wu M Q, Huang W J, Niu Z , et al. Fine crop mapping by combining high spectral and high spatial resolution remote sensing data in complex heterogeneous areas[J]. Computers and Electronics in Agriculture, 2017,139(Supplement C):1-9.
doi: 10.1016/j.compag.2017.05.003
[6] Zhou Q B, Yu Q Y, Liu J , et al. Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring[J]. Journal of Integrative Agriculture, 2017,16(2):242-251.
doi: 10.1016/S2095-3119(16)61479-X
[7] Zhang X L, Xiao P F, Feng X Z , et al. Separate segmentation of multi-temporal high-resolution remote sensing images for object-based change detection in urban area[J]. Remote Sensing of Environment, 2017,201(Supplement C):243-255.
doi: 10.1016/j.rse.2017.09.022
[8] 孙在宏, 吴长彬 . 基于“一张图”的土地动态监测系统研究[J].测绘通报, 2012(6):22-24,100.
Sun Z H, Wu C B . Land dynamic monitoring system based on “One Land Map”[J].Bulletin of Survey and Mapping, 2012(6):22-24,100.
[9] Asner G P, Heidebrecht K B . Imaging spectroscopy for desertification studies:Comparing AVIRIS and EO-1 Hyperion in Argentina drylands[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003,41(6):1283-1296.
doi: 10.1109/TGRS.2003.812903
[10] Okin G S, Murray B, Schlesinger W H . Degradation of sandy arid shrubland environments:Observations, process modelling,and management implications[J]. Journal of Arid Environments, 2001,47(2):123-144.
doi: 10.1006/jare.2000.0711
[11] 王静, 何挺, 李玉环 . 基于高光谱遥感技术的土地质量信息挖掘研究[J]. 遥感学报, 2005,9(4):438-445.
doi: 10.3321/j.issn:1007-4619.2005.04.015
Wang J, He T, Li Y H . Studying on extraction for land quality information based on hyperspectral data[J]. Journal of Remote Sensing, 2005,9(4):438-445.
doi: 10.3321/j.issn:1007-4619.2005.04.015
[12] 杨金中, 聂洪峰, 荆青青 . 初论全国矿山地质环境现状与存在问题[J]. 国土资源遥感, 2017,29(2):1-7.doi: 10.6046/gtzyyg.2007.02.01.
doi: 10.6046/gtzyyg.2007.02.01
Yang J Z, Nie H F, Jing Q Q . Preliminary analysis of mine geo-environment status and existing problems in China[J]. Remote Sensing for Land and Resources, 2017,29(2):1-7.doi: 10.6046/gtzyyg.2007.02.01.
doi: 10.6046/gtzyyg.2007.02.01
[13] 吴亚楠, 代晶晶, 周萍 . 基于高空间分辨率遥感数据的稀土矿山监测研究[J]. 中国稀土学报, 2017,35(2):262-271.
doi: 10.11785/S1000-4343.20170214
Wu Y N, Dai J J, Zhou P . Research of rare earth minerals monitoring based on high resolution remote sensing[J]. Journal of the Chinese Society of Rare Earths, 2017,35(2):262-271.
doi: 10.11785/S1000-4343.20170214
[14] 王燕波, 罗伟, 李名勇 , 等. 基于高分辨率遥感影像的矿山开发监测研究[J]. 热带地理, 2011,31(4):377-382.
doi: 10.3969/j.issn.1001-5221.2011.04.008
Wang Y B, Luo W, Li M Y , et al. Mine development monitoring based on high-resolution remote sensing images[J]. Tropical Geography, 2011,31(4):377-382.
doi: 10.3969/j.issn.1001-5221.2011.04.008
[15] 陈圣波, 谢明辉, 路鹏 , 等. 基于Hyperion数据的矿区废弃土土壤恢复潜力[J]. 地球科学, 2015,40(8):1353-1358.
doi: 10.3799/dqkx.2015.117
Chen S B, Xie M H, Lu P , et al. Restoration potential of abandoned soil at Dexing mine of Jiangxi Province based on Hyperion data[J]. Earth Science, 2015,40(8):1353-1358.
doi: 10.3799/dqkx.2015.117
[16] 李万伦, 甘甫平 . 矿山环境高光谱遥感监测研究进展[J]. 国土资源遥感, 2016,28(2):1-7.doi: 10.6046/gtzyyg.2016.02.01.
doi: 10.6046/gtzyyg.2016.02.01
Li W L, Gan F P . Progress in hyperspectral research and monitoring in mine environment[J]. Remote Sensing for Land and Resources, 2016,28(2):1-7.doi: 10.6046/gtzyyg.2016.02.01.
doi: 10.6046/gtzyyg.2016.02.01
[17] Chen N H, Dong J J, Chen J Y , et al. Geometry and emplacement of the Late Cretaceous mafic dyke swarms on the islands in Zhejiang Province,Southeast China:Insights from high-resolution satellite images[J]. Journal of Asian Earth Sciences, 2014,79:302-311.
doi: 10.1016/j.jseaes.2013.10.001
[18] 王晓鹏, 杨志强, 康高峰 , 等. WorldView-2高分辨率卫星数据在西昆仑塔什库尔干地区遥感地质调查中的应用[J]. 地质找矿论丛, 2014,29(3):428-432.
doi: 10.6053/j.issn.1001-1412.2014.03.018
Wang X P, Yang Z Q, Kang G F , et al. Application of WorldView-2 data to remote sensing geological survey in Tashkurgan Area at west Kunlun[J]. Contributions to Geology and Mineral Resources Research, 2014,29(3):428-432.
doi: 10.6053/j.issn.1001-1412.2014.03.018
[19] 任广利, 杨军录, 杨敏 , 等. 高光谱遥感异常提取在甘肃北山金滩子—明金沟地区成矿预测中的应用[J]. 大地构造与成矿学, 2013,37(4):765-776.
Ren G L, Yang J L, Yang M , et al. Application of hyperspectral remote sensing anomaly information on metallogenic prediction in the Jintanzi—Mingjingou area of Beishan,Gansu[J]. Geotectonica et Metaalogenia, 2013,37(4):765-776.
[20] 王润生, 熊盛青, 聂洪峰 , 等. 遥感地质勘查技术与应用研究[J]. 地质学报, 2011,85(11):1699-1743.
Wang R S, Xiong S Q, Nie H F , et al. Remote sensing technology and its application in geological exploration[J]. Acta Geological Sinica, 2011,85(11):1699-1743.
[21] 周子勇 . 高光谱遥感油气勘探进展[J]. 遥感技术与应用, 2014,29(2):352-361.
doi: 10.11873/j.issn.1004-0323.2014.2.0352
Zhou Z Y . Progress in hyperspectral remote sensing for petroleum prospecting[J]. Remote Sensing Technology and Application, 2014,29(2):352-361.
doi: 10.11873/j.issn.1004-0323.2014.2.0352
[22] 胡畔, 田庆久, 闫柏琨 . 柴达木盆地烃蚀变矿物高光谱遥感识别研究[J]. 国土资源遥感, 2009,21(2):54-61.doi: 10.6046/gtzyyg.2009.02.12.
doi: 10.6046/gtzyyg.2009.02.12
Hu P, Tian Q J, Yan B K . The application of hyperspectral remote sensing to the identification of hydrocarbon alteration minerals in Qaidam basin[J]. Remote Sensing for Land and Resources, 2009,21(2):54-61.doi: 10.6046/gtzyyg.2009.02.12.
doi: 10.6046/gtzyyg.2009.02.12
[23] Xu D Q, Ni G Q, Jiang L L , et al. Exploring for natural gas using reflectance spectra of surface soils[J]. Advances in Space Research, 2008,41(11):1800-1817.
doi: 10.1016/j.asr.2007.05.073
[24] Willis K S . Remote sensing change detection for ecological monitoring in United States protected areas[J]. Biological Conservation, 2015,182:233-242.
doi: 10.1016/j.biocon.2014.12.006
[25] 腾明君, 曾立雄, 肖文发 , 等. 长江三峡库区生态环境变化遥感研究进展[J]. 应用生态学报, 2014,25(12):3683-3693.
Teng M J, Zeng L X, Xiao W F , et al. Research progress on remote sensing of ecological and environmental changes in the Three Gorges[J]. Chinese Journal of Applied Ecology, 2014,25(12):3683-3693.
[26] 韩阳, 秦伟超, 王野乔 . 吉林省西部典型盐渍化土壤偏振反射高光谱特征与模型研究[J]. 光谱学与光谱分析, 2014,34(6):1640-1644.
Han Y, Qin W C, Wang Y Q . Study on the polarized reflectance hyperspectral characteristics and models of typical saline soil in the west of Jilin Province,China[J]. Spectroscopy and Spectral Analysis, 2014,34(6):1640-1644.
[27] Chu T A, Guo X L, Takeda K . Remote sensing approach to detect post-fire vegetation regrowth in Siberian boreal larch forest[J]. Ecological Indicators, 2016,62:32-46.
doi: 10.1016/j.ecolind.2015.11.026
[28] Garni R, Tran A, Guis H , et al. Remote sensing,land cover changes, and vector-borne diseases:Use of high spatial resolution satellite imagery to map the risk of occurrence of cutaneous leishmaniasis in Ghardaia,Algeria[J]. Infection,Genetics and Evolution, 2014,28:725-734.
doi: 10.1016/j.meegid.2014.09.036 pmid: 25305006
[29] Jiang S, Wen B P, Zhao C , et al. Kinematics of a giant slow-moving landslide in Northwest China:Constraints from high resolution remote sensing imagery and GPS monitoring[J]. Journal of Asian Earth Sciences, 2016,123:34-46.
doi: 10.1016/j.jseaes.2016.03.019
[30] 苏凤环, 刘洪江, 韩用顺 . 汶川地震山地灾害遥感快速提取及其分布特点分析[J]. 遥感学报, 2008,12(6):956-963.
doi: 10.3321/j.issn:1007-4619.2008.06.019
Su F H, Liu H J, Han Y S . The extraction of mountain hazard induced by Wenchuan earthquake and analysis of its distributing characteristic[J]. Journal of Remote Sensing, 2008,12(6):956-963.
doi: 10.3321/j.issn:1007-4619.2008.06.019
[31] 朱静, 唐川 . 遥感技术在我国滑坡研究中的应用综述[J]. 遥感技术与应用, 2012,27(3):458-464.
Zhu J, Tang C . An overview of remote sensing applications for landslides research in China[J]. Remote Sensing Technology and Application, 2012,27(3):458-464.
[1] 孙长奎,刘善磊,王圣尧,陈超,沈泉飞,石善球,王玮. 浅谈无人机遥感技术在智慧城市建设中的应用[J]. 国土资源遥感, 2018, 30(4): 8-12.
[2] 王瑞军,闫柏琨,李名松,董双发,孙永彬,汪冰. 甘肃红山地区重要控矿地质单元GF-1数据遥感解译与应用[J]. 国土资源遥感, 2018, 30(2): 162-170.
[3] 郑鸿瑞,徐志刚,甘乐,陈玲,杨金中,杜培军. 合成孔径雷达遥感地质应用综述[J]. 国土资源遥感, 2018, 30(2): 12-20.
[4] 王瑞军, 董双发, 孙永彬, 李婧玥. 基于高分一号卫星数据新疆索拉克地区控矿地质单元遥感解译与应用[J]. 国土资源遥感, 2017, 29(s1): 137-143.
[5] 郑雄伟, 杨金中, 陈玲, 陈华, 孙永军, 付长亮, 童立强, 钟昶, 魏英娟. 国土资源卫星地质矿产应用成效[J]. 国土资源遥感, 2017, 29(s1): 1-7.
[6] 吴永亮, 陈建平, 姚书朋, 徐彬. 无人机低空遥感技术应用[J]. 国土资源遥感, 2017, 29(4): 120-125.
[7] 丁相元, 高志海, 孙斌, 吴俊君, 薛传平, 王燕. 基于高分一号时间序列数据的沙化土地分类[J]. 国土资源遥感, 2017, 29(3): 196-202.
[8] 代晶晶, 王登红, 吴亚楠. 基于高分遥感数据的稀有矿山监测——以江西宜春414稀有矿山为例[J]. 国土资源遥感, 2017, 29(3): 104-110.
[9] 张振华, 甘甫平, 王军. 面向应用需求的星载多光谱相机指标设置探讨[J]. 国土资源遥感, 2015, 27(2): 1-7.
[10] 梁树能, 甘甫平, 魏红艳, 肖晨超, 张振华, 魏丹丹. 哈密遥感地质资源评价综合应用野外试验场建设进展[J]. 国土资源遥感, 2015, 27(2): 8-14.
[11] 安志宏, 聂洪峰, 王昊, 荆青青. ZY-1 02C星数据在矿山遥感监测中的应用研究与分析[J]. 国土资源遥感, 2015, 27(2): 174-182.
[12] 孙亚飞, 江利明, 柳林, 孙永玲, 汪汉胜. TanDEM-X双站SAR干涉测量及研究进展[J]. 国土资源遥感, 2015, 27(1): 16-22.
[13] 陈玲, 梁树能, 周艳, 甘甫平, 魏红艳. 国产高分卫星数据在高海拔地区地质调查中的应用潜力分析[J]. 国土资源遥感, 2015, 27(1): 140-145.
[14] 魏永明, 魏显虎, 陈玉. 岷江流域映秀—茂县段地震次生地质灾害分布规律及发展趋势分析[J]. 国土资源遥感, 2014, 26(4): 179-186.
[15] 汤童, 范一大, 杨思全, 王磊, 王平. 重大自然灾害应急监测与评估应用示范系统的设计与实现[J]. 国土资源遥感, 2014, 26(3): 175-181.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《国土资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 Email:gtzyyg@agrs.cn; gtzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发