?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=ANALISIS+PERUBAHAN+TUTUPAN+REPONG+DAMAR+DI+PESISIR%0D%0ABARAT+LAMPUNG+MENGGUNAKAN+DATA+PENGINDERAAN+JAUH%0D%0ADAN+SISTEM+INFORMASI+GEOGRAFIS&rft.creator=CECILINIA+TIKA+LAURA%2C+1414151019&rft.subject=Kehutanan&rft.description=Repong+Damar+merupakan+suatu+bentuk+perkebunan+yang+memiliki+struktur+mirip%0D%0Adengan+hutan+alam.+Keuntungan+yang+diberikan+Repong+Damar+kepada%0D%0Amasyarakat+sekitar+tidak+hanya+terkait+ekonomi+saja%2C+namun+juga+keuntungan%0D%0Aekologis.+Sebagai+kekayaan+alam+yang+dimiliki+Provinsi+Lampung+maka+Repong%0D%0ADamar+patut+untuk+dijaga+kelestariannya.+Penelitian+ini+bertujuan+untuk%0D%0Amenganalisis+metode+yang+tepat+dan+akurat+dalam+mendeteksi+sebaran+Repong%0D%0ADamar+menggunakan+citra+satelit%2C+mengetahui+sejarah+luasan+lahan+Repong+Damar%0D%0Adan+juga+untuk+mengetahui+apakah+dari+data+tersebut+FRL+Repong+Damar+dapat%0D%0Adibangun+dalam+hubungannya+dengan+potensi+penerapan+REDD%2B+di+lahan%0D%0Aagroforestri.+Repong+Damar+dideteksi+menggunakan+tiga+metode+deteksi+yaitu%0D%0AObject+Oriented+Classification+(OOC)%2C+Maximum+Likelihood+Classification%0D%0A(MLC)+dan+Vegetation+Indices+Classification.+Hasil+menunjukkan+bahwa+metode%0D%0Adeteksi+yang+paling+tepat+dan+akurat+dalam+mendeteksi+sebaran+Repong+Damar%0D%0Aadalah+metode+berbasis+objek+(OOC)+dengan+nilai+akurasi+sebesar+92%2C27%25.Dengan+menggunakan+metode+ini+diketahui+bahwa+sejak+tahun+1990+sampai+2018%0D%0ARepong+Damar+mengalami+aforestasi+dan+deforestasi.+Penilaian+FRL+dilakukan%0D%0Adengan+menghitung+karbon+yang+tersimpan+(termasuk+teremisi+dan+terserap)%0D%0Aberdasarkan+rerata+tutupan+Repong+Damar+tahun+1990+-+2015%2C+yaitu+sebesar%0D%0A33.187.752+tC%2Ftahun+(104.364+ha%2Fth).+Kinerja+REDD+%2B+dari+Repong+Damar+pada%0D%0Atahun+2018+terlihat+dari+area+jangkauannya%2C+yaitu+99.693+hektar.+Berdasarkan+data%0D%0Atersebut%2C+maka+kinerja+emisi+gas+rumah+kaca+(GRK)+Repong+Damar+menghasilkan%0D%0Anilai+negatif+(-1.485.378+tC)%2C+sehingga+dapat+disimpulkan+bahwa+Repong+Damar%0D%0Atelah+mengemisikan+karbon+sebesar+1.485.378+tC+pada+tahun+2018.%0D%0AKata+Kunci%3A+Citra+satelit%2C+metode+deteksi+Repong+Damar%2C+penginderaan+jauh%2C%0D%0AREDD%2B%2C+SIG%0D%0A%0D%0A%0D%0ARepong+Damar+is+a+form+of+gardening+that+have+a+structure+similar+to+that+of%0D%0Anatural+forests.+The+role+of+Repong+Damar+to+the+community+is+not+merely+related%0D%0Ato+the+economic+value%2C+but+also+its+ecological+advantages.+As+one+of+rich+natural%0D%0Aresources+located+in+the+Lampung+Province%2C+Repong+Damar+is+worth+to+be%0D%0Apreserved.+This+research+aims+to+analyze+the+most+appropriate+and+accurate%0D%0Amethod+for+detecting+the+distribution+of+Repong+Damar+using+satellite+images+and%0D%0Ato+understand+the+history+of+time-series+cover+change+of+Repong+Damar+as+well+as%0D%0Ato+find+out+whether+the+data+of+FRL+Repong+Damar+can+be+built+in+relation+to+the%0D%0AREDD%2B+potential+implementation+in+agroforestry.+Three+methods+of+detection%0D%0Awere+used+i.e.+Object+Oriented+Classification+(OOC)%2C+Maximum+Likelihood%0D%0AClassification+(MLC)+and+Vegetation+Indices+Classification.+The+most+accurate%0D%0Amethod+for+detecting+Repong+Damar+was+the+object+based+method+(OOC)+with%0D%0A92.27%25+accuracy+was+derived.+By+using+this+method+the+time-series+change+in%0D%0ARepong+Damar+coverage+from+1990+until+2018+was+found.+The+results+show+that+the+area+of+Repong+Damar+experienced+afforestation+and+deforestation.+FRL%0D%0Aassessment+was+conducted+by+calculating+carbon+stock+(including+emission+and%0D%0Asink)+based+on+average+value+of+time-series+coverage+area+of+Repong+Damar+from%0D%0A1990+-+2015%2C+i.e.+33%2C187%2C752+tC%2Fyr+(104%2C364+ha%2Fyr).+REDD%2B+performance+of%0D%0ARepong+Damar+in+2018+was+seen+from+its+coverage+area%2C+i.e.+99%2C693+hectares.%0D%0AHence%2C+based+on+that+data%2C+the+emission+performance+of+Repong+Damar+in+2018%0D%0Awas+-1%2C485%2C378+(negative)%2C+or+in+conclusion+Repong+Damar+has+emitted+1%2C485%2C378%0D%0Atons+of+carbon+in+2018.%0D%0AKeywords%3A+GIS%2C+REDD%2B%2C+remote+sensing%2C+Repong+Damar+detection+method%2C%0D%0Asatellite+images.&rft.publisher=FAKULTAS+PERTANIAN&rft.date=2019-02-18&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F55408%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F55408%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F55408%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++CECILINIA+TIKA+LAURA%2C+1414151019++(2019)+ANALISIS+PERUBAHAN+TUTUPAN+REPONG+DAMAR+DI+PESISIR+BARAT+LAMPUNG+MENGGUNAKAN+DATA+PENGINDERAAN+JAUH+DAN+SISTEM+INFORMASI+GEOGRAFIS.++FAKULTAS+PERTANIAN%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F55408%2F