Studi klasifikasi tututpan lahan menggunakan data scansar alos palsar dan citra landsat TM

Profilyanti, Belly (2015) Studi klasifikasi tututpan lahan menggunakan data scansar alos palsar dan citra landsat TM. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Metode penginderaan jauh dibedakan menjadi 2, yaitu sistem aktif dan sistem pasif. Sistem pasif menggunakan bantuan energi matahari untuk memantulkan gelombang dari permukaan bumi sehingga dapat diterima oleh sensor. Sistem ini memiliki kekurangan yaitu adanya “blank area”, yang ditimbulkan apabila permukaan bumi tertutup awan. Sedangkan sistem aktif menggunakan gelombang yang dipancarkan oleh sensor, dan pantulan baliknya diterima kembali oleh sensor yang sama. Salah satunya adalah SAR (Synthetic Aperture Radar), sistem ini menggunakan gelombang mikro yang memiliki kemampuan menembus awan sehingga data yang didapat lebih maksimal. Radar memiliki kemampuan untuk melakukan perekaman pada segala cuaca, baik siang maupun malam hari. Data citra ALOS Palsar berisikan kenampakan tingkatan karakteristik backscatter dari obyek di permukaan bumi. Kualitas citra radar bergantung pada volume backscatter yang diterima kembali oleh antena. Nilai backscatter inilah yang akan digunakan sebagai dasar penentuan klasifikasi. Data scanSAR Alos Palsar dilakukan filtering menggunakan gamma method untuk mengurangi speckle noise. Selanjutnya diklasifikasi menggunakan metode K-Means dan ISOData. Pembagian kelas klasifikasi dari citra radar ini antara lain vegetasi, badan air, dan lahan terbangun. Hasil klasifikasi menunjukkan bahwa data scanSAR Alos Palsar dengan klasifikasi K-Means menghasilkan 3 kelas tutupan lahan yaitu badan air (127,7938 km2), vegetasi (707,4445 km2), dan lahan terbangun (488,7484 km2). Sedangkan pada klasifikasi ISOData menghasilkan 6 kelas tutupan lahan yaitu tubuh air (danau, sungai, tambak) memiliki luas 25,6006 km2, sawah basah/rawa (39,1675 km2), vegetasi (673,1982 km2), hutan (77,2798 km2), lahan terbangun (262,63 km2), tanah terbuka (246,1106 km2). Sebagai pembanding digunakan citra Landsat dengan akurasi sebesar 78,8216% pada klasifikasi Maximum Likelihood, dihasilkan 4 kelas tutupan yaitu badan air (28,7663 km2), vegetasi jenis 1 (488,7338 km2), vegetasi jenis 2 (373,3404 km2), dan lahan terbangun sebesar 433,1462 km2. ================================================================================================= Remote sensing methods can be divided into two systems, the active and passive system. Passive system uses solar energy to reflects the waves from the earth's surface so it can be received by the sensor. This system has the disadvantage that called "blank area", which is caused by the clouds that covered the earth's surface. While the active system uses waves emitted by the sensor, and the reflection received back by the same sensor. One of it is the SAR (Synthetic Aperture Radar), this system uses microwaves that have the ability to penetrate the cloud so the data obtained more significant. Radar has the ability to do recording in any weather, day or night. ALOS PALSAR imagery contains backscatter characteristics of the object on the earth’s surface. Radar image quality depends on the volume backscatter that received by the antenna. Backscatter values will be used as basis for determining the classification. ScanSAR ALOS PALSAR uses gamma filtering method to reduce the speckle noise, for further classified using KMeans and ISODATA methods. Classification class of radar imagery devided into vegetation, water bodies, and constructed land. Classification results show that the scanSAR ALOS PALSAR K-Means classification resulted in 3 classes of land cover, that are water body (127.7938 km2), vegetation (707.4445 km2), and constructed land (488.7484 km2). While the ISOData classification devides into 6 classes, that are water body (such as lakes, rivers, ponds) has 25.6006 km2, wet rice field / marsh (39.1675 km2), vegetation (673.1982 km2), forest (77.2798 km2), constructed land (262.63 km2), and land field (246.1106 km2). For comparison is used Landsat with accuracy of 78.8216% on a Maximum Likelihood classification that generated 4 cover classes, water bodies (28.7663 km2), vegetation type 1 (488.7338 km2), vegetation type 2 (373.3404 km2) , and constructed land amounted to 433.1462 km2.

Item Type: Thesis (Undergraduate)
Additional Information: RSG 621.367 Pro s
Uncontrolled Keywords: backscatter; klasifikasi; scanSAR ALOS PALSAR; tutupan lahan
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques
Divisions: Faculty of Civil Engineering and Planning > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User: - Taufiq Rahmanu
Date Deposited: 17 Oct 2019 08:03
Last Modified: 17 Oct 2019 08:03
URI: http://repository.its.ac.id/id/eprint/71251

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