Slope　spectrum　is　an　effective　methodology　of　digital　terrain　analysis　in　geomorphology.　However,　some　limitations　are　still　encountered　in　the　construction　of　the　slope　spectrum.　E.g.,　the　uncertainties　caused　by　slope　classification　and　resolution　of　digital　elevation　model　(DEM)　may　restrict　the　development　of　slope　spectrum　and　cause　a　certain　spatial　information　loss.　In　this　paper,　a　new　spectrum　method,　defined　as　continuous　slope　cumulative　frequency　(CSCF)　spectrum,　is　proposed.　Compared　with　the　slope　spectrum,　the　CSCF　spectrum　does　not　require　slope　classification　and　combines　the　spatial　information　of　all　grids.　Hence,　it　possesses　richer　terrain　feature　information　and　minimal　spatial　information　loss.　Meanwhile,　it　is　more　convenient　to　be　used　in　different　study　areas　without　requiring　heavy　work　of　slope　spectrum　in　determining　the　suitable　slope　classification.　We　also　found　that　the　CSCF　spectrum　can　be　generally　extracted　from　DEM　with　different　resolutions,　whereas　the　slope　spectrum　cannot.　Experiment　results　show　that　the　CSCF　spectrum　is　an　efficient　geomorphology　quantitative　analysis　method　that　can　quantitatively　depict　the　spatial　distribution　and　evolution　process　of　the　typical　loess　landforms　from　different　angles.　Besides,　the　CSCF　spectrum　can　accurately　deduce　the　stable　slope　spectrum,　whereas　the　slope　spectrum　cannot　deduce　the　CSCF　spectrum,　which　further　suggests　that　the　previous　studies　in　slope　spectrum　can　be　conducted　on　the　basis　of　the　CSCF　spectrum.　Furthermore,　the　CSCF　spectrum　shows　well　application　potentials　in　landform　classification　with　comparative　performance　to　previous　methods.　Overall,　the　CSCF　spectrum　is　an　effective　method　in　geomorphology　quantitative　analysis.　Considering　that　the　CSCF　spectrum　solves　two　key　deficiencies　in　the　present　model　of　slope　spectrum　(slope　classification　and　DEM　resolution)　and　extends　the　application　scope　and　concept　of　spectrum　method,　it　is　promising　to　be　the　research　paradigm　of　the　spectrum　method　in　digital　terrain　analysis.　©　2022