2.5 Klasifikasi Gambar
2.5.2 Klasifikasi Berbasis Piksel Dibandingkan Metode
Di masa lalu, klasifikasi berbasis piksel memainkan peran yang sangat penting terutama dalam mengklasifikasikan gambar beresolusi rendah (Yüksel et al., 2008). Namun, seringkali sulit untuk mendapatkan hasil yang memuaskan menggunakan resolusi spasial dan spektral yang lebih halus dalam memetakan LULC perkotaan heterogen karena variasi spektrum tinggi dalam kategori LULC yang sama sering terjadi (Rozenstein dan Karnieli, 2011). Ketika klasifikasi berbasis spektral per piksel diterapkan untuk klasifikasi LULC, setiap piksel dikelompokkan ke dalam kategori tertentu. Namun, karena frekuensi spasial yang tinggi, hasilnya akan berisik dan mengakibatkan ketidakakuratan dalam klasifikasi LULC (Riggan dan Weih, 2009). Selain itu, heterogenitas spektral dari LULC mengurangi keterpisahan antara kelas (Nichols, 2012) dan dengan demikian dapat menyebabkan efek 'garam dan merica' atau piksel “nakal” yang muncul dalam kelas (Shan dan Hussain, 2010).
Untuk meredakan kebingungan masalah heterogenitas ini, kemampuan pengenalan pola manusia yang berbeda, tidak ada dalam pengklasifikasi otomatis,
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telah diperiksa oleh banyak peneliti. Dua contoh kemampuan tersebut adalah penggunaan tekstur dalam klasifikasi dan pengelompokan berbasis objek. Analisis citra berbasis objek (OBIA) disarankan sebagai solusi efektif untuk masalah variasi spektrum tinggi dalam jenis LULC yang sama (Galletti dan Myint, 2014).
ENVI 5.3, tersedia dari Exelis Solusi Informasi Visual adalah salah satu contoh dari produk perangkat lunak baru-baru ini untuk melakukan OBIA (Exelis, 2015).
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III KESIMPULAN
Data yang diperoleh dari hasil analisis citra dapat digunakan untuk memonitoring penggunaan lahan dan panas permukaan lahan, sehingga bila mengancam keberlanjutan lingkungan dapat segera diambil tindakan pengendalian/pencegahan. Pemanfaatan citra satelit juga dapat dimanfaatkan tidak saja untuk bidang pengelolaan sumber daya alam, namun juga untuk tujuan ekonomi, mitigasi bencana, transportasi hingga pertahanan. Inovasi dan perkembangan teknologi RS dan GIS yang sangat cepat sangat bermanfaat dalam menghasilkan informasi penggunaan lahan dan suhu permukaan dengan hasil yang lebih akurat. Untuk itu diperlukan ketelitian dalam menentukan sumber data, jenis panjang gelombang citra yang dipilih, dan metode analisis yang tepat untuk mencapai tujuan penelitian yang ditetapkan.
Ketersediaan citra landsat dalam rentang waktu yang cukup panjang yaitu sejak 1972 menjadi salah satu alternatif sumber data yang dapat dimanfaatkan untuk menganalisis perubahan kondisi yang terjadi di masa lalu, hingga saat ini sehingga bisa dibuatkan model untuk memprediksi kondisi yang akan terjadi di masa mendatang. Ketersediaan data yang bisa diunduh secara gratis dan pemanfaatan informasi RS dan integrasi SIG untuk cakupan area yang luas menawarkan efisiensi biaya, waktu dan tenaga, bila dibandingkan menggunakan cara-cara tradisional yang harus melakukan survei langsung di lapangan.
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