Extraction of Remote Sensing Alteration Information Based on Integrated Spectral Mixture Analysis and Fractal Analysis Article Swipe
Kai Qiao
,
Tao Luo
,
Shihao Ding
,
Licheng Quan
,
Juwon Kong
,
Yiwen Liu
,
Zhiwen Ren
,
Seokhyun Gong
,
Yong Huang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/min15101047
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/min15101047
As a key target area in China’s new round of strategic mineral exploration initiatives, Tibet possesses favorable metallogenic conditions shaped by its unique geological evolution and tectonic setting. In this paper, the Saga region of Tibet is the research object, and Level-2A Sentinel-2 imagery is utilized. By applying mixed pixel decomposition, interfering endmembers were identified, and spectral unmixing and reconstruction were performed, effectively avoiding the drawback of traditional methods that tend to remove mineral alteration signals and masking interference. Combined with band ratio analysis and principal component analysis (PCA), various types of remote sensing alteration anomalies in the region were extracted. Furthermore, the fractal box-counting method was employed to quantify the fractal dimensions of the different alteration anomalies, thereby delineating their spatial distribution and fractal structural characteristics. Based on these results, two prospective mineralization zones were identified. The results indicate the following: (1) In areas of Tibet with low vegetation cover, applying spectral mixture analysis (SMA) effectively removes substantial background interference, thereby enabling the extraction of subtle remote sensing alteration anomalies. (2) The fractal dimensions of various remote sensing alteration anomalies were calculated using the fractal box-counting method over a spatial scale range of 0.765 to 6.123 km. These values quantitatively characterize the spatial fractal properties of the anomalies, and the differences in fractal dimensions among alteration types reflect the spatiotemporal heterogeneity of the mineralization system. (3) The high-potential mineralization zones identified in the composite contour map of fractal dimensions of alteration anomalies show strong spatial agreement with known mineralization sites. Additionally, two new prospective mineralization zones were delineated in their periphery, providing theoretical support and exploration targets for future prospecting in the study area.
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- https://www.mdpi.com/2075-163X/15/10/1047/pdf?version=1759412003
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Raw OpenAlex JSON
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https://doi.org/10.3390/min15101047Digital Object Identifier
- Title
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Extraction of Remote Sensing Alteration Information Based on Integrated Spectral Mixture Analysis and Fractal AnalysisWork title
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enPrimary language
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2025Year of publication
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2025-10-02Full publication date if available
- Authors
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Kai Qiao, Tao Luo, Shihao Ding, Licheng Quan, Juwon Kong, Yiwen Liu, Zhiwen Ren, Seokhyun Gong, Yong HuangList of authors in order
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https://doi.org/10.3390/min15101047Publisher landing page
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https://www.mdpi.com/2075-163X/15/10/1047/pdf?version=1759412003Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2075-163X/15/10/1047/pdf?version=1759412003Direct OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.low | 148 |
| abstract_inverted_index.map | 236 |
| abstract_inverted_index.new | 7, 253 |
| abstract_inverted_index.the | 31, 37, 64, 97, 102, 110, 114, 140, 163, 184, 202, 207, 210, 219, 223, 233, 272 |
| abstract_inverted_index.two | 131, 252 |
| abstract_inverted_index.was | 106 |
| abstract_inverted_index.Saga | 32 |
| abstract_inverted_index.area | 4 |
| abstract_inverted_index.band | 81 |
| abstract_inverted_index.over | 188 |
| abstract_inverted_index.show | 243 |
| abstract_inverted_index.tend | 70 |
| abstract_inverted_index.that | 69 |
| abstract_inverted_index.this | 29 |
| abstract_inverted_index.were | 53, 60, 99, 135, 181, 257 |
| abstract_inverted_index.with | 80, 147, 247 |
| abstract_inverted_index.(SMA) | 155 |
| abstract_inverted_index.0.765 | 194 |
| abstract_inverted_index.6.123 | 196 |
| abstract_inverted_index.Based | 127 |
| abstract_inverted_index.These | 198 |
| abstract_inverted_index.Tibet | 14, 35, 146 |
| abstract_inverted_index.among | 215 |
| abstract_inverted_index.area. | 274 |
| abstract_inverted_index.areas | 144 |
| abstract_inverted_index.known | 248 |
| abstract_inverted_index.mixed | 48 |
| abstract_inverted_index.pixel | 49 |
| abstract_inverted_index.range | 192 |
| abstract_inverted_index.ratio | 82 |
| abstract_inverted_index.round | 8 |
| abstract_inverted_index.scale | 191 |
| abstract_inverted_index.study | 273 |
| abstract_inverted_index.their | 120, 260 |
| abstract_inverted_index.these | 129 |
| abstract_inverted_index.types | 90, 217 |
| abstract_inverted_index.using | 183 |
| abstract_inverted_index.zones | 134, 230, 256 |
| abstract_inverted_index.(PCA), | 88 |
| abstract_inverted_index.cover, | 150 |
| abstract_inverted_index.future | 269 |
| abstract_inverted_index.method | 105, 187 |
| abstract_inverted_index.paper, | 30 |
| abstract_inverted_index.region | 33, 98 |
| abstract_inverted_index.remote | 92, 167, 177 |
| abstract_inverted_index.remove | 72 |
| abstract_inverted_index.shaped | 19 |
| abstract_inverted_index.sites. | 250 |
| abstract_inverted_index.strong | 244 |
| abstract_inverted_index.subtle | 166 |
| abstract_inverted_index.target | 3 |
| abstract_inverted_index.unique | 22 |
| abstract_inverted_index.values | 199 |
| abstract_inverted_index.contour | 235 |
| abstract_inverted_index.fractal | 103, 111, 124, 173, 185, 204, 213, 238 |
| abstract_inverted_index.imagery | 43 |
| abstract_inverted_index.masking | 77 |
| abstract_inverted_index.methods | 68 |
| abstract_inverted_index.mineral | 11, 73 |
| abstract_inverted_index.mixture | 153 |
| abstract_inverted_index.object, | 39 |
| abstract_inverted_index.reflect | 218 |
| abstract_inverted_index.removes | 157 |
| abstract_inverted_index.results | 138 |
| abstract_inverted_index.sensing | 93, 168, 178 |
| abstract_inverted_index.signals | 75 |
| abstract_inverted_index.spatial | 121, 190, 203, 245 |
| abstract_inverted_index.support | 264 |
| abstract_inverted_index.system. | 225 |
| abstract_inverted_index.targets | 267 |
| abstract_inverted_index.thereby | 118, 161 |
| abstract_inverted_index.various | 89, 176 |
| abstract_inverted_index.Combined | 79 |
| abstract_inverted_index.Level-2A | 41 |
| abstract_inverted_index.analysis | 83, 87, 154 |
| abstract_inverted_index.applying | 47, 151 |
| abstract_inverted_index.avoiding | 63 |
| abstract_inverted_index.drawback | 65 |
| abstract_inverted_index.employed | 107 |
| abstract_inverted_index.enabling | 162 |
| abstract_inverted_index.indicate | 139 |
| abstract_inverted_index.quantify | 109 |
| abstract_inverted_index.research | 38 |
| abstract_inverted_index.results, | 130 |
| abstract_inverted_index.setting. | 27 |
| abstract_inverted_index.spectral | 56, 152 |
| abstract_inverted_index.tectonic | 26 |
| abstract_inverted_index.unmixing | 57 |
| abstract_inverted_index.China’s | 6 |
| abstract_inverted_index.agreement | 246 |
| abstract_inverted_index.anomalies | 95, 180, 242 |
| abstract_inverted_index.component | 86 |
| abstract_inverted_index.composite | 234 |
| abstract_inverted_index.different | 115 |
| abstract_inverted_index.evolution | 24 |
| abstract_inverted_index.favorable | 16 |
| abstract_inverted_index.possesses | 15 |
| abstract_inverted_index.principal | 85 |
| abstract_inverted_index.providing | 262 |
| abstract_inverted_index.strategic | 10 |
| abstract_inverted_index.utilized. | 45 |
| abstract_inverted_index.Sentinel-2 | 42 |
| abstract_inverted_index.alteration | 74, 94, 116, 169, 179, 216, 241 |
| abstract_inverted_index.anomalies, | 117, 208 |
| abstract_inverted_index.anomalies. | 170 |
| abstract_inverted_index.background | 159 |
| abstract_inverted_index.calculated | 182 |
| abstract_inverted_index.conditions | 18 |
| abstract_inverted_index.delineated | 258 |
| abstract_inverted_index.dimensions | 112, 174, 214, 239 |
| abstract_inverted_index.endmembers | 52 |
| abstract_inverted_index.extracted. | 100 |
| abstract_inverted_index.extraction | 164 |
| abstract_inverted_index.following: | 141 |
| abstract_inverted_index.geological | 23 |
| abstract_inverted_index.identified | 231 |
| abstract_inverted_index.performed, | 61 |
| abstract_inverted_index.periphery, | 261 |
| abstract_inverted_index.properties | 205 |
| abstract_inverted_index.structural | 125 |
| abstract_inverted_index.vegetation | 149 |
| abstract_inverted_index.delineating | 119 |
| abstract_inverted_index.differences | 211 |
| abstract_inverted_index.effectively | 62, 156 |
| abstract_inverted_index.exploration | 12, 266 |
| abstract_inverted_index.identified, | 54 |
| abstract_inverted_index.identified. | 136 |
| abstract_inverted_index.interfering | 51 |
| abstract_inverted_index.prospecting | 270 |
| abstract_inverted_index.prospective | 132, 254 |
| abstract_inverted_index.substantial | 158 |
| abstract_inverted_index.theoretical | 263 |
| abstract_inverted_index.traditional | 67 |
| abstract_inverted_index.Furthermore, | 101 |
| abstract_inverted_index.box-counting | 104, 186 |
| abstract_inverted_index.characterize | 201 |
| abstract_inverted_index.distribution | 122 |
| abstract_inverted_index.initiatives, | 13 |
| abstract_inverted_index.metallogenic | 17 |
| abstract_inverted_index.Additionally, | 251 |
| abstract_inverted_index.heterogeneity | 221 |
| abstract_inverted_index.interference, | 160 |
| abstract_inverted_index.interference. | 78 |
| abstract_inverted_index.decomposition, | 50 |
| abstract_inverted_index.high-potential | 228 |
| abstract_inverted_index.mineralization | 133, 224, 229, 249, 255 |
| abstract_inverted_index.quantitatively | 200 |
| abstract_inverted_index.reconstruction | 59 |
| abstract_inverted_index.spatiotemporal | 220 |
| abstract_inverted_index.characteristics. | 126 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile.value | 0.6256217 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |