The　construction　of　the　pest　detection　algorithm　is　a　process　of　coupling　the　＇ground-space＇　features,　which　is　an　important　guarantee　to　realize　its　remote　sensing　monitoring.　Taking　Sanming　City,　Jiangle　County,　Sha　County　and　Yanping　District　in　Nanping　City　in　Fujian　Province　as　the　experimental　areas,　it　gathered　182　samples　of　Dendrolimus　punctatus　Walker　damage　and　randomly　divided　them　into　training　set　and　validation　set,　and　5　repeated　tests　and　1　test　of　index　screening　were　performed.　According　the　host　representations　damaged　by　Dendrolimus　punctatus　Walker,　7　ground　and　remote　sensing　characteristic　indices　including　pine　forest　leaf　area　index　(LAI),　standard　deviation　of　LAI　(SEL),　normalized　difference　vegetation　index　(NDVI),　wetness　from　tasseled　cap　transformation　(WET),　green　band　(B2),　red　band　(B3),　near　infrared　band　(B4)　were　obtained,　then　the　models　of　Fisher　discriminant　analysis　and　random　forest　for　pest　levels　were　constructed.　The　detection　precision,　Kappa　coefficient　and　ROC　curve　were　used　to　comprehensively　compare　the　detection　effects　of　these　two　algorithms,　as　well　as　the　paired　t-test.　The　results　showed　that　all　the　7　indices　have　the　pest　responsiveness,　while　SEL　and　NDVI　are　relatively　weak;　the　average　detection　precision　of　Fisher　discriminant　analysis　in　6　tests　was　73.26%,　Kappa　coefficient　was　0.631　9,　and　79.30%,　0.715　1　of　RF　respectively,　indicating　RF　is　significantly　better　than　the　former　one　(p　©　2018,　Peking　University　Press.　All　right　reserved.