Remote Sensing Characteristics and Identification Methods of Cretaceous Palaeo-desert Outcrop: Taking the Red Bed Basin in Southeast Hunan as an Example
-
摘要: 白垩系古沙漠风成砂岩是近年来湖南省新发现的一种沉积类型，该岩石不仅是特色的旅游资源，而且是全球关注的储能、储碳的重要目标储集层，因此对湖南省古沙漠的空间分布规律深入研究意义重大。本文引入遥感技术手段建立古沙漠露头遥感特征的识别及提取方法：以谷歌地球引擎（Google Earth Engine，GEE）为主要处理平台，以Sentinel-2A（哨兵二号）多光谱影像为主要数据源，从光谱、遥感指数和地形地貌三个方面分析古沙漠露头的遥感特征，采用随机森林算法进行古沙漠露头的遥感识别。区别于传统的陡直型丹霞地貌，古沙漠遥感影像色调均匀、连片分布，植被和山体阴影皆不发育，具有“顶圆，坡缓”的地貌特征。同时，深入分析古沙漠地貌的岩性特征，结合地质条件辅助约束，实现古沙漠露头的精准识别。通过上述方法，本文解译出湖南白垩系丹霞地貌区的多处古沙漠露头，并从识别结果中选择面积较大的衡阳盆地东缘（渡口地区）和茶永盆地东南缘（郴州市飞天山-高椅岭地区）地区的古沙漠风成砂岩进行了实地验证，效果理想。本文为研究古沙漠空间分布规律提供了高效的途径，是遥感技术在古沙漠地质领域的重要应用，旨在为国内地学界同行提供技术参考和借鉴。Abstract: The Cretaceous palaeo-desert aeolian sandstone is a new type of sedimentary discovered in Hunan Province in recent years. This rock is not only a characteristic tourism resource, but also an important target reservoir for energy and carbon storage of global concern, so it is of great significance to conduct an in-depth study on the spatial distribution pattern of palaeo-deserts in Hunan Province. In this paper, remote sensing technology is introduced to establish the recognition and extraction method of remote sensing features of palaeo-desert outcrops: With Google Earth Engine (GEE) as the main processing platform and Sentinel-2A multi-spectral image as the main data source, by analyzing the remote sensing characteristics of palaeo-desert outcrops from three aspects: spectral, remote sensing index and topography and geomorphology features, and the Random Forest Algorithm was used to identify the palaeo-desert outcrops by remote sensing. Different from the traditional steep and straight Danxia landforms, the remote sensing images of the palaeo-desert are uniform in colour tone, continuously distributed, with undeveloped vegetation and mountain shadows, and with the geomorphological characteristics of‘rounded tops and gentle slopes’. At the same time, deeply analyzing the stratigraphic lithology characteristics of the palaeo-desert, the outcrop of the palaeo-desert is characterized accurately by increasing geological constraints. With the methods above, a number of palaeo-desert outcrops in Danxia landform area of various red bed basins in Hunan Province have been interpreted, and two large areas of palaeo-desert aeolian sandstones in the eastern margin of Hengyang Basin (Dukou area) and the southeastern margin of Chayong Basin (Feitianshan-Gaoyiling area of Chenzhou City) have been verified. This study provides an efficient way to study the spatial distribution law of palaeo-desert, which is an important application of remote sensing technology in the field of geology, aiming to provide technical and geoscience references.
-
Key words:
- palaeo-desert /
- remote sensing feature /
- Sentinel-2A /
- Google Earth Engine /
- Random Forest Algorithm /
- Hunan province
-
-
[1] 陈清华,庞飞,史鹏.2008.江苏白垩系古沙漠沉积特征及油气地质意义[J].石油天然气学报(江汉石油学院学报),30(5):161-164+383.
[2] 陈荣林.1987.江苏及邻区上白垩统赤山组中古沙漠沉积[J].江苏地质,(2)：20-23.
[3] 陈文光.2012.湖南丹霞地貌分布发育特点[A].//中国地质学会旅游地学与地质公园研究分会第27 届年会暨张掖丹霞国家地质公园建设与旅游发展研讨会论文集[C].张掖:中国地质学会旅游地学与地质公园研究分会：198-201.
[4] 丁丽雪,卢友月,付建明,秦拯纬,张遵遵,马丽艳,陈希清.2020.醉美丹霞——崀山[J].华南地质与矿产,36(2):204-211.
[5] 范莹琳,杜松,赵岳,邱景智,杜晓川,张玉峰,丁宴,宋思彤,车巧慧.2023.基于随机森林算法的煤矸石山信息提取[J/OL]. 自然资源遥感. https://link.cnki.net/urlid/10.1759.p.20231201.1103.002
[6] 高仁强,陈亮雄,杨静学,秦雁.2020.一种高分影像随机森林变化检测方法[J].测绘科学,45(11):130-138.
[7] 郝斌飞,韩旭军,马明国,刘一韬,李世卫.2018. Google Earth Engine 在地球科学与环境科学中的应用研究进展[J].遥感技术与应用,33(4):600-611.
[8] 何旭刚,买买提?沙吾提,盛艳芳,李荣鹏.2023.基于GEE平台渭库绿洲棉花水分生产率遥感估算[J].干旱区地理,46(10): 1632-1642.
[9] 湖南省地质调查院.2017.中国区域地质志·湖南志[M].北京：地质出版社.
[10] 胡菲菲.2017.湖南省丹霞地貌特征分析及旅游开发潜力研究[D].湖南师范大学硕士学位论文.
[11] 胡晓杰,陈灼康,莫罗坚,严朝东,王卫,罗晓莹.2023.基于遥感影像的丹霞山国家级自然保护区森林景观格局分析[J].生态科学,42(2):155-163.
[12] 黄宝华,郭福生,姜勇彪,刘林清,彭花明.2010.广丰盆地丹霞地貌遥感影像特征[J].山地学报,4(28):500-504.
[13] 黄华,陈柯伶.2011.江陵凹陷白垩系红花套组沙漠沉积特征[J].特种油气藏,18(3):43-46+137.
[14] 黄乐清,黄建中,罗来,王先辉,刘耀荣,梁恩云,马慧英.2019.湖南衡阳盆地东缘白垩系风成沉积的发现及其古环境意义[J].沉积学报,37(4):735-748.
[15] 黄乐清,吴驰华,周丽芸,金妮,彭世良,胡能勇,杨长明,陈杰.2023.湖南郴州丹霞地貌景观特征、成因及演化探讨[J].现代地质,37(6):1680-1694.
[16] 黄建文,李增元,陈尔学,赵磊,莫冰萍.2021.高分六号宽幅多光谱数据人工林类型分类[J].遥感学报,25(2):539-548.
[17] 康诺尧,傅强,向贤哲,刘晋晖,章桂芳,张珂,刘蔚秋,杨强,师超凡.2024.基于短波红外的丹霞山岩壁裸露特征[J].中山大学学报(自然科学版)(中英文), 63(2),26-34.
[18] 李丽,童立强,李小慧.2010.基于植被覆盖度的石漠化遥感信息提取方法研究[J].国土资源遥感,(2):59-62.
[19] 李鹏举,邱骏挺,陈一君,李红英.2016.遥感技术在地质公园与地质遗迹调查评价中的应用-以川南地区为例[J].资源开发与市场,32(5):513-539.
[20] 刘林清,郭福生,曾晓华.2007.丹霞地貌景观调查的遥感技术应用研究[J].东华理工学院学报,30(3):247-251.
[21] 刘坚,李树林,陈涛.2018.基于优化随机森林模型的滑坡易发性评价[J]. 武汉大学学报·信息科学版,43(7):1085-1091.
[22] 罗曦,杨志军,张珂,王汉雨,都衡恒,何旺.2021.广东丹霞山红色成因的矿物学研究[J].矿物学报,41(6):704-712.
[23] 潘霞.2021.基于Google Earth Engine 云平台下地物覆被类型的遥感影像智能分类方法研究[D].内蒙古农业大学博士学位论文.
[24] 彭华.2000. 中国丹霞地貌研究进展[J]. 地理科学,20(3):203-211.
[25] 彭华,潘志新,闫罗彬,Scott Simonson.2013.国内外红层与丹霞地貌研究述评[J].地理学报,68(9):1170-1181.
[26] 汤海磊.2020.楚雄盆地东北部白垩纪风成沉积特征与古气候研究[D].成都理工大学硕士学位论文.
[27] 田社权.2023.遥感综合地质解译方法在中尼铁路勘察中的应用研究[J].现代地质,37(4): 1054-1064.
[28] 王润生,熊盛青,聂洪峰,梁树能,齐泽荣,杨金中,闫柏琨,赵福岳,范景辉,童立强,林键,甘甫平,陈微,杨苏明,张瑞江,葛大庆,张晓坤,张振华,王品清,郭小方,李丽.2011.遥感地质勘查技术与应用研究[J]. 地质学报,85(11):1699-1743.
[29] 汪震,姜勇彪.2019.江西宜黄盆地丹霞地貌特征分析[J].山地学报,37(6):839-847.
[30] 吴润秋,胡旭东,梅红波,贺金勇,杨建英.2021.基于随机森林的滑坡空间易发性评价以三峡库区湖北段为例[J].地球科学,46(1):321-330.
[31] 吴学洪,徐亚东,许笑玮,张黎渊,何妍.2023. 湘东南茶永盆地白垩纪-古近纪沉积古地理演化[J].华南地质, 39(2):214-234.
[32] 谢渊,王剑,江新胜,李明辉,谢正温,罗建宁,侯光才,刘方,王永和,张茂省,朱桦,王德潜,孙永明,曹建科.2005.鄂尔多斯盆地白垩系沙漠相沉积特征及其水文地质意义[J].沉积学报,23(1):73-83.
[33] 徐涵秋.2005.基于谱间特征和归一化指数分析的城市建筑用地信息提取[J].地理研究,24(2):311-321.
[34] 张长俊,张天刚.1986.广东仁化县丹霞山红层内风成砂岩的特征[J].矿物岩石,6(3):51-54+193.
[35] 张仙,李伟,陈理,杨昭颖,窦宝成,李瑜.2023.露天开采矿区要素遥感提取研究进展及展望[J].自然资源遥感,35(2): 25-33.
[36] 郑雄伟,彭孛,尚坤.2021.基于国产卫星的遥感地质解译能力评估[J].自然资源遥感,33(3):1-10.
[37] 朱锐,张昌民,张尚锋,施和生,杜家元,余烨.2010.潮汐层偶的砂泥纹层厚度变化规律及其地质意义[J].海洋地质与第四纪地质,30(6):9-14.
[38] 朱筱敏,陈贺贺,谈明轩,李顺利,秦祎,杨棵.2023.从太平洋到喜马拉雅的沉积学新航程——21 届国际沉积学大会研究热点分析[J].沉积学报,41(1):126-149.
[39] Dong S W, Li J H, Gao R, Cawood P A, Thybo H, Johnston S T, Jiao L Q, Zhang Y Q, Wang J M.2023. Intraplate lithospheric extension revealed by seismic reflection profiling of South China[J]. Earth and Planetary Science Letters, 609: 118100.
[40] Jiao H J, Wu C H , Juan P R, Sun X M, Yi H S. 2020. Late Cretaceous plateau deserts in the South China Block, and Quaternary analogues; sedimentology, dune reconstruction and wind-water interactions[J]. Marine and Petroleum Geology, 120:104504.
[41] Suo Y H, Li S Z, Chong J, Zhang Y, Zhou J, Li X Y, Wang P C, Liu Z, Wang X Y, Ian Somerville. 2019. Eastward tectonic migration and transition of the Jurassic-Cretaceous Andean-type continental margin along Southeast China[J]. Earth-Science Reviews, 196:102884.
[42] Xu X B, Liang C H, Xu Y D.2021.Kinematic analysis of fault-slip data in the Nanling Tectonic Belt and Cretaceous to Paleogene tectonic evolution of the Central South China Block[J]. Journal of Asian Earth Sciences, 221: 104951.
[43] Wu C H, Rodríguez-López J P, Liu C L, Sun X M, Wang J Y, Xia G Q, Michael W.2018. Late Cretaceus climbing erg systems in the western Xinjiang Basin: Palaeoatmosphere dynamics and East Asia margin tectonic forcing on desert expansion and preservation[J]. Marine and Petroleum Geology, 93:539-552.
[44] Zhou X M, Li W X. 2000. Origin of Late Mesozoic igneous rocks in Southeastern China: implications for lithosphere subduction and underplating of mafic magmas[J]. Tectonophysics, 326(3-4):269-287.
-
计量
- 文章访问数: 40
- PDF下载数: 9
- 施引文献: 0
下载: