Landsat-8 (OLI) classification method based on tasseled cap transformation features

Ali, S. M.; Salman, Salema S.

doi:10.1109/aic-mitcsa.2016.7759914

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The samples for constructing and testing classifier were obtained from Gaofen satellite images, Google Earth high resolution imagery (2013 and 2017), and a field survey (2021). Nine spectral indices, including soil-adjusted atmospherically-resistant vegetation index (SARVI) [69], normalized difference water index (NDWI) [70], normalized difference buildup soil index (NDBSI) [71], brightness-greenness-wetness from Tasseled Cap Transform (TCT) [72], and hue-saturation-value from HSV transformation [53] were used as classifier feature variables. Table 2 shows the parameters of the RF classifier and corresponding validation metrics for three investigation years (2013, 2017, and 2021).…”

Section: Land Use Change Analysismentioning

confidence: 99%

Suitability Assessment Method of Red Tourism Development Using Geospatial and Social Humanity Data: A Case Study of Ruijin City, East China

Qin

Cao

et al. 2023

Sustainability

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It is important to analyze the trend in land use changes and assess the suitability of resource development for protecting natural resources, developing ecological industries, and land use planning issues. Ruijin City is located in South Jiangxi and has abundant resources for red tourism development. By analyzing the landscape changes in land use and the spatial distribution characteristics of local red culture resources, a supervised machine learning-based prediction model was constructed to quantitatively assess the suitability of red tourism development in a geographic information system (GIS) and the R language environment using geographical, economical, and human-related datasets. The results revealed that: (i) the increasing of human activities and economic vitality provide a beneficial social environment for the development of tourism resources; (ii) highly concentrated red resources, or those with special significance, are conducive to developing red tourism resources; (iii) preferentially, central–eastern Ruijin was followed by the extension areas to peripheral towns, which are potentially suitable areas for the development of red scenic spots. Generally, the findings of this study were consistent with the conventional cognitions and lessons on tourism development, and the constructed evaluation system is expected to be promoted to similar research.

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