HadjimitsisDGPapadavidGAgapiouA, et al. (2010) Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices. Natural Hazards and Earth System Sciences10(1): 89–95.
2.
HueteA (1988) A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment25(3): 295–309.
3.
MengQ (2023) Remote Sensing of Urban Green Space. Singapore: Springer Nature Singapore. DOI: 10.1007/978-981-99-0703-8.
4.
QiJChehbouniAHueteAR, et al. (1994) A modified soil adjusted vegetation index. Remote Sensing of Environment48(2): 119–126.
5.
SomvanshiSSKumariM (2020) Comparative analysis of different vegetation indices with respect to atmospheric particulate pollution using sentinel data. Applied Computing and Geosciences6: 100032.
6.
SongCWoodcockCESetoKC, et al. (2001) Classification and change detection using landsat TM data. Remote Sensing of Environment75(2): 230–244.
7.
TanKCLimHSMatJafriMZ, et al. (2011) A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in landsat imagery. Environmental Monitoring and Assessment184(6): 3813–3829.
8.
XieYZhaoXLiL, et al. (2010) Calculating NDVI for Landsat7-ETM data after atmospheric correction using 6S model: a case study in Zhangye city, China. In: 2010 18th international conference on geoinformatics, Beijing, China, 18–20 June 2010. DOI: 10.1109/geoinformatics.2010.5567553.