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PENDUGAAN POTENSI HUTAN SAGU DENGAN MENGGUNAKAN TEKNIK PENGINDERAAN JAUH Ishak Sumantri Haryono
Jurnal Penelitian Hasil Hutan Vol 5, No 1 (1988): Jurnal Penelitian Hasil Hutan
Publisher : Pusat Penelitian dan Pengembangan Hasil Hutan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20886/jphh.1988.5.1.23-30

Abstract

The aim of this study is to apply remote sensing techniques to estimate sago potential.   The estimation  method  of sago potential  is a linear regression equation. Estimate  parameter from  aerial photo  scale of  1: 20000 is the crown  density  as dependent  variable  while sago soft  core (empulur)   volume as the in dependent  variable.                                                                                            .                                         The linear regression equation  of the sago potential  is Ŷ =  3.6731 X  +  147.43 with 0. 7313 coefficient  corelation.  Based  on the study  the linear regression equation  above appear to have reliable estimate  and proved  to be useful for  planning  of sago forest  management.
PENDUGAAN POTENSI HUTAN SAGU DENGAN MENGGUNAKAN TEKNIK PENGINDERAAN JAUH Ishak Sumantri Haryono
Jurnal Penelitian Hasil Hutan Vol 5, No 1 (1988): Jurnal Penelitian Hasil Hutan
Publisher : Pusat Penelitian dan Pengembangan Hasil Hutan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5857.529 KB) | DOI: 10.20886/jphh.1988.5.1.23-30

Abstract

The aim of this study is to apply remote sensing techniques to estimate sago potential.   The estimation  method  of sago potential  is a linear regression equation. Estimate  parameter from  aerial photo  scale of  1: 20000 is the crown  density  as dependent  variable  while sago soft  core (empulur)   volume as the in dependent  variable.                                                                                            .                                         The linear regression equation  of the sago potential  is Ŷ =  3.6731 X  +  147.43 with 0. 7313 coefficient  corelation.  Based  on the study  the linear regression equation  above appear to have reliable estimate  and proved  to be useful for  planning  of sago forest  management.