Pola spektral tanaman tebu (saccharum officinarum l.) Menggunakan spektrofotometer dan citra penginderaan jauh di kabupaten bantul

Karen Slamet Hardjo (Program Studi Penginderaan Jauh dan SIG, Departemen Teknologi Kebumian Sekolah Vokasi Universitas Gadjah Mada)
Like Indrawati (Program Studi Penginderaan Jauh dan SIG, Departemen Teknologi Kebumian, Sekolah Vokasi Universitas Gadjah Mada)

Jurnal Nasional Teknologi Terapan
Vol 2, No 1 (2018): MEI

Sugar becomes one of the commodities targeted to achieve Indonesia national food security. Sugar is produced from sugarcane (Saccharum officinarum L.), extensive plantations require effective and efficient handling and low cost. Remote sensing is a technology that is considered appropriate to answer those needs, through remote sensing image can be analyzed to the physical condition of sugar cane plant based on the spectral response recorded on the image. The spectral response captured by the sensor is expected to help analyze this plant in relation to plant growth, plant health, as well as the production of sugar yields in sugarcane. The lack of spectral pattern research, especially the in situ spectral pattern that is used as a reference for remote sensing data analysis, makes this research important to do. Bantul Regency is a region that has a large agricultural area, including sugar cane plantation. The method used in this research is digital data processing on remote sensing image to be analyzed spectral pattern especially in sugarcane which then compared with data of spectral pattern of sugar cane which is measured directly in the field using spectrophotometer. Spectral patterns obtained from two sources are then analyzed to determine the agility of sugarcane. The result of this research is give description about spectral pattern characteristic or reflectance pattern in sugar cane plant so it can be used for mapping of sugar cane plantation. The Sugar cane Plant reflected curve from the field measurements by spectrophotometer is noticeably smoother and has more wavelengths than the reflected curves of the Landsat 8 OLI Image. The distribution of sugar cane plant based on the spectral reflectance pattern of the object of field measurement is more relevant than the distribution of sugarcane based on the spectral reflection pattern of the object from Landsat 8 OLI Image. The classification of the field measurement spectral library and the Landsat 8 OLI Image shows that the spectral library of field measurements is better to serve as the basis for spectral-based mapping than the sampled spectral libraries in Landsat 8 OLI Image.