A　novel　combination　model　of　topography-adjusted　vegetation　index　(TAVI)　was　developed　based　on　the　band-ratio　model　and　spectral　feature　of　land　covers　in　a　rugged　terrain　to　reduce　the　topographic　effect.　Firstly,　the　topographic　correction　strategies　in　rugged　terrain　were　introduced,　including　the　traditional　empirical　statistical　model　based　on　digital　elevation　model　(DEM),　terrain　radiative　transfer　model　combined　with　DEM　and　band-ratio　model.　With　the　support　of　terrain　radiative　transfer　model　basic　principle,　the　concept　model　of　TAVI　was　proposed　to　eliminate　the　topographic　effect.　Secondly,　the　operational　land　imager　(OLI)　7　bands　of　Landsat　8　on　December　13th,　2014,　in　a　sample　within　research　area　in　Fuzhou　city,　China　were　illustrated.　Meanwhile,　the　spectral　features　of　5　major　land　covers　in　the　sample　were　also　analyzed,　such　as　the　cement　road,　water,　vegetation　in　flat,　vegetation　in　shady　slope　and　vegetation　in　sunny　slope.　After　the　illustration　and　analysis,　the　OLI　red　and　near-infrared　wavebands　were　selected　to　develop　a　new　TAVI　combination　model.　Thirdly,　a　novel　shady　vegetation　index　(SVI)　was　developed　based　on　the　band-ratio　model　and　the　physical　feature　of　red　band.　The　ratio　vegetation　index　(RVI),　as　the　basic　band-ratio　model,　was　selected　to　form　the　novel　combination　model　of　TAVI　integrating　with　the　SVI.　Fourthly,　the　TAVI　of　research　area　was　computed　with　the　newly　proposed　combination　model　and　the　topographic　adjustment　coefficient　optimization　algorithm　that　is　depended　on　the　balance　between　the　maximal　TAVI　values　in　shady　and　sunny　slopes　in　rugged　terrains.　Then,　three　validation　methods　were　adopted　to　verify　the　correction　effect　of　new　TAVI　combination　model,　including　the　visual　examination,　statistics　analysis　and　vegetation　indices　difference　analysis.　The　statistics　analysis　were　the　comparisons　the　correlation　coefficient　and　the　inclination　between　the　cosine　of　solar　incidence　and　vegetation　indices,　including　the　TAVI　calculated　from　the　apparent　reflectance　directly,　RVI　and　normalized　different　vegetation　index　(NDVI)　computed　from　the　correction　models.　These　correction　models　include　the　atmospheric　correction　with　the　fast　line-of-sight　atmospheric　analysis　of　spectral　hypercubes　(FLAASH)　model　in　ENVI　software,　topographic　correction　with　C-model　based　on　the　DEM　and　the　correction　with　the　second　simulation　of　the　satellite　signal　in　the　solar　spectrum　(6S)　model　combined　with　DEM.　The　verification　results　showed　that　the　novel　combination　of　TAVI　achieved　similar　correction　effect　to　that　from　the　NDVI　after　the　correction　with　6S　model　combined　with　DEM,　which　achieved　the　best　corrected　result　in　these　correction　models.　The　correlation　coefficient　between　the　cosine　of　solar　incidence　and　TAVI　decreased　to　0.075,　while　the　inclination　of　the　linear　regression　equation　between　them　reduced　to　0.035.　These　numbers　showed　that　the　topographic　effect　was　successfully　eliminated　by　TAVI.　In　summary,　the　novel　combination　model　of　TAVI,　even　without　the　DEM　support,　could　achieve　satisfactory　result　in　elimination　of　topographic　effect　in　rugged　terrain,　which　amounts　to　nearly　the　same　effect　of　atmospheric+topographic　corrections.　Therefore,　the　novel　model　of　TAVI　can　be　utilized　to　monitor　vegetation　information　and　retrieve　bio-physical　parameters　in　rugged　terrains,　while　the　topographic　adjustment　coefficient　needs　to　be　improved　from　the　empirical　method　to　physical　or　semi-physical　model　in　the　next　step.　©　2017,　Editorial　Department　of　the　Transactions　of　the　Chinese　Society　of　Agricultural　Engineering.　All　right　reserved.