Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review

被引:2
|
作者
E. D. Chaves, Michel [1 ]
C. A. Picoli, Michelle [1 ]
D. Sanches, Ieda [1 ]
机构
[1] Natl Inst Space Res INPE, Gen Coordinat Earth Observat OBT, Remote Sensing Div DSR, Ave Astronautas, BR-1758 Sao Jose Dos Campos, Brazil
关键词
operational land imager; multiSpectral instrument; vegetation indices; text mining; DIFFERENCE WATER INDEX; IMAGE TIME-SERIES; TREE CROP CLASSIFICATION; VEGETATION INDEXES; RED-EDGE; SPATIAL-RESOLUTION; LEARNING CLASSIFICATION; COMBINING SENTINEL-1; SPECTRAL REFLECTANCE; CHLOROPHYLL CONTENT;
D O I
10.3390/rs12183062
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2 MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land cover (LULC) provide a new perspective in remote sensing data analysis. Jointly, these sources permit researchers to improve operational classification and change detection, guiding better reasoning about landscape and intrinsic processes, as deforestation and agricultural expansion. However, the results of their applications have not yet been synthesized in order to provide coherent guidance on the effect of their applications in different classification processes, as well as to identify promising approaches and issues which affect classification performance. In this systematic review, we present trends, potentialities, challenges, actual gaps, and future possibilities for the use of L8/OLI and S2/MSI for LULC mapping and change detection. In particular, we highlight the possibility of using medium-resolution (Landsat-like, 10-30 m) time series and multispectral optical data provided by the harmonization between these sensors and data cube architectures for analysis-ready data that are permeated by publicizations, open data policies, and open science principles. We also reinforce the potential for exploring more spectral bands combinations, especially by using the three Red-edge and the two Near Infrared and Shortwave Infrared bands of S2/MSI, to calculate vegetation indices more sensitive to phenological variations that were less frequently applied for a long time, but have turned on since the S2/MSI mission. Summarizing peer-reviewed papers can guide the scientific community to the use of L8/OLI and S2/MSI data, which enable detailed knowledge on LULC mapping and change detection in different landscapes, especially in agricultural and natural vegetation scenarios.
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页数:39
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