90%) pada Area 1 dan ( This research deal with "Automatic Canopy Calculation Model Through Identification on Digital Aerialphoto : Case Study for Oilpalm Plantation in Pontianak West Kalimantan". The aim of this research was to identify and to calculate tree canopy automatical and to compare the result with manual calculation. It uses the quantification methode which based on: tone, texture, shape, area and illimunation effect. Canopy and image background was separated by morphology operation. Small format aerial photograph was acquired with Nikon DIX Camera integrated with Global Positioning System, so every sheet of areialphoto have a fit geographic coordinate for geographic references proccess and mozaic generation. EnzoMozaik software was used for mozaic proccess. This research have two steps, first is image model making and the second is the implementation of image model on the whole of aerialphoto coverages. Modelling proccess is used for compose solve model in every condition of image like tone, shape, texture, pattern and illumination. It was continued with automatic canopy calculation on the aerial photograph. The main factor of this result from modelling proccess is tone, texture and illumination. Area and shape was an easy factor to solve. The implementation process applied the approach which was obtained from modelling proccess. Every calculated block adapted with model condition, according to shape, tone, texture, pattern and illumination. It was continue with correct condition of image model. Area 1 have dominant old oilpalm (±13 years) and have higger accurate calculation (96.85%) than area 3 (76.51%). Area 3 is dominant with young canopy, about 5 years old. Unsuccessfully calculation in area 3 is caused by the coarse background texture and high illumination, but in a block with medium texture and medium illumination or less accuracy dramatically increase to 99% as area 3 block 27 fault in identification process only 0.24% and also good in auto-canopy delineation. Area 1 have a high accurate result of calculation than area 3, cause it have no effect from the image background except in parsial, even in area 1 the good delineation can not be donewell, it have complicated canopy shape, due to its oldness. The main differents in this count are, area 1 have good accuration (>90%) and area 3 was less than "> 90%) pada Area 1 dan ( This research deal with "Automatic Canopy Calculation Model Through Identification on Digital Aerialphoto : Case Study for Oilpalm Plantation in Pontianak West Kalimantan". The aim of this research was to identify and to calculate tree canopy automatical and to compare the result with manual calculation. It uses the quantification methode which based on: tone, texture, shape, area and illimunation effect. Canopy and image background was separated by morphology operation. Small format aerial photograph was acquired with Nikon DIX Camera integrated with Global Positioning System, so every sheet of areialphoto have a fit geographic coordinate for geographic references proccess and mozaic generation. EnzoMozaik software was used for mozaic proccess. This research have two steps, first is image model making and the second is the implementation of image model on the whole of aerialphoto coverages. Modelling proccess is used for compose solve model in every condition of image like tone, shape, texture, pattern and illumination. It was continued with automatic canopy calculation on the aerial photograph. The main factor of this result from modelling proccess is tone, texture and illumination. Area and shape was an easy factor to solve. The implementation process applied the approach which was obtained from modelling proccess. Every calculated block adapted with model condition, according to shape, tone, texture, pattern and illumination. It was continue with correct condition of image model. Area 1 have dominant old oilpalm (±13 years) and have higger accurate calculation (96.85%) than area 3 (76.51%). Area 3 is dominant with young canopy, about 5 years old. Unsuccessfully calculation in area 3 is caused by the coarse background texture and high illumination, but in a block with medium texture and medium illumination or less accuracy dramatically increase to 99% as area 3 block 27 fault in identification process only 0.24% and also good in auto-canopy delineation. Area 1 have a high accurate result of calculation than area 3, cause it have no effect from the image background except in parsial, even in area 1 the good delineation can not be donewell, it have complicated canopy shape, due to its oldness. The main differents in this count are, area 1 have good accuration (>90%) and area 3 was less than ">
Model penghitungan kanopi melalui identifikasi obyek secara otomatis pada Foto Udara format digital : Kasus kanopi pohon kelapa sawit di perkebunan sawit KSP inti Pontianak Kalimantan Barat
Rahmi Agtasari, Dr. Hartono, DEA., DESS.; Drs. Retnadi Heru Jatmiko, M.Sc.
2005 | Skripsi | S1 KARTOGRAFI DAN PENGINDERAAN JAUHPenelitian ini berjudul "Model Penghitungan Kanopi Melalui Identifikasi Obyek Secara Otomatis Pada Foto Udara Format Digital Kasus Kanopi Pohon Kelapa Sawit di Perkebunan Sawit KSP Inti Pontianak Kalimantan Barat". Tujuan penelitian ini adalah identifikasi dan penghitungan kanopi pohon secara otomatis dan membandingkan hasil penghitungan kanopi pohon secara manual dan secara otomatis. Penelitian dilakukan dengan melakukan kuantifikasi dari aspek: rona, tekstur, bentuk, area, dan efek iluminasi. Kanopi dan latar dipisahkan melalui proses morfologi citra. Citra penginderaan jauh yang digunakan adalah foto udara format kecil yang diakuisisi menggunakan Kamera Nikon D1X yang terintegrasi dengan Global Positioning System sehingga tiap lembar foto memiliki koordinat geografis yang berguna pada proses pereferensian geografis dan mozaik citra. Mozaik citra dilakukan dengan menggunakan poerangkat lunak EnzoMozaic. Penelitian dilakukan melalui dua tahap utama, yaitu: penyusunan model citra dan tahap implementasi. Tahap pemodelan ditujukan untuk menyusun suatu model penyelesaian dalam berbagai kondisi: bentuk, rona, tekstur, pola dan iluminasi, selanjutnya hasil dari pemodelan diimplementasikan untuk penghitungan citra foto udara. Hasil pada tahap pemodelan diperoleh tiga faktor utama yang mempengaruhi terhadap kesuksesan penghitungan kanopi, yaitu: rona, tekstur dan iluminasi sedangkan faktor: area dan bentuk merupakan faktor yang lebih mudah diselesaikan. Tahap implementasi adalah tahap menerapkan pendekatan yang telah diperoleh pada tahap pemodelan. Setiap blok yang akan dihitung disesuaikan dengan kondisi model, terhadap faktor: bentuk, rona, tekstur, pola dan iluminasi; selanjutnya dilakukan proses penghitungan menggunakan model citra yang kondisinya paling sesuai dengan citra yang akan dihitung. Penghitungan pada Area 1 yang lebih didominasi oleh tegakan sawit dengan umur sekitar 13 tahun atau dalam kategori sawit tua, secara akumulasi menghasilkan akurasi yang lebih tinggi (96,85%) dibanding Area 3 (76,51) yang didominasi oleh tegakan sawit dengan umur sekitar 5 tahun. Ketidaksuksesan penghitungan pada Area 3 diakibatkan faktor tekstur latar yang kasar dan faktor iluminasi yang tinggi tetapi pada blok dengan tekstur dan efek iluminasi yang sedang kesalahan hasil penghitungan otomatis tidak lebih dari 1% yaitu: 0,24% pada Area3 27 (Area 3 blok 27) dan dengan delineasi kanopi yang baik pula. Penghitungan pada Area I secara akumulatif lebih tinggi dikarenakan pada tegakan sawit yang tua faktor latar sudah hampir tidak berpengaruh kecuali secara parsial, sekalipun lebih tinggi pada Area 1 tidak dapat dilakukan delineasi kanopi secara baik karena bentuk kanopi sudah tidak mengumpul lagi (sudah tua). Perbedaan utama pada penghitungan yang memiliki akurasi yang tinggi (>90%) pada Area 1 dan (<80%) Area 3 dan pada Area 3 dapat dilakukan delineasi kanopi yang baik sedangkan Area 1 tidak sukses. Penelitian ini juga menghasilkan peningkatan kecepatan kerja dibanding penghitungan langsung dilapangan dengan 5,2 m²/detik, penghitungan manual dari citra 52 m²/detik (Wanasuria, 2003) menjadi 10000 m²/detik.
This research deal with "Automatic Canopy Calculation Model Through Identification on Digital Aerialphoto : Case Study for Oilpalm Plantation in Pontianak West Kalimantan". The aim of this research was to identify and to calculate tree canopy automatical and to compare the result with manual calculation. It uses the quantification methode which based on: tone, texture, shape, area and illimunation effect. Canopy and image background was separated by morphology operation. Small format aerial photograph was acquired with Nikon DIX Camera integrated with Global Positioning System, so every sheet of areialphoto have a fit geographic coordinate for geographic references proccess and mozaic generation. EnzoMozaik software was used for mozaic proccess. This research have two steps, first is image model making and the second is the implementation of image model on the whole of aerialphoto coverages. Modelling proccess is used for compose solve model in every condition of image like tone, shape, texture, pattern and illumination. It was continued with automatic canopy calculation on the aerial photograph. The main factor of this result from modelling proccess is tone, texture and illumination. Area and shape was an easy factor to solve. The implementation process applied the approach which was obtained from modelling proccess. Every calculated block adapted with model condition, according to shape, tone, texture, pattern and illumination. It was continue with correct condition of image model. Area 1 have dominant old oilpalm (±13 years) and have higger accurate calculation (96.85%) than area 3 (76.51%). Area 3 is dominant with young canopy, about 5 years old. Unsuccessfully calculation in area 3 is caused by the coarse background texture and high illumination, but in a block with medium texture and medium illumination or less accuracy dramatically increase to 99% as area 3 block 27 fault in identification process only 0.24% and also good in auto-canopy delineation. Area 1 have a high accurate result of calculation than area 3, cause it have no effect from the image background except in parsial, even in area 1 the good delineation can not be donewell, it have complicated canopy shape, due to its oldness. The main differents in this count are, area 1 have good accuration (>90%) and area 3 was less than <80%. Area 3 have good delineation, but it is not in area 1. This research has make an improvement for canopy counting with 1 second for 10000 m², compared with manual onscreen canopy count (52 m²/second) and 5.2 m²/second for terrestrial counting in Wanasuria; 2003 research. ?
Kata Kunci : Kanopi,Foto udara format kecil,Pontianak,Kalimantan Barat