ANALISIS HUBUNGAN PERSENTASE KANDUNGAN LEMPUNG DENGAN NILAI POLA RESPON SPEKTRAL TANAH PADA CITRA HYPERION SEBAGIAN DAERAH D.I YOGYAKARTA

• Main Authors: , ALFIATUN NUR K, , Drs. Projo Danoedoro, M.Sc, Ph.D.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2013
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/124101/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=64220
• Institution: Universitas Gadjah Mada

Clay fraction diameter has diameters less than 2 micron and it is the smallest fraction in soil. It takes an important role in the development of soil, even though the composition is smaller if it is compared to the overall composition of the soil. Soil fraction mapping is extremely important for environment planning and monitoring. Traditional mapping is less efficiently, thus remote sensing data are needed. High spectral information of hyperspectral data can be used to identify the spectral response of land detailly. Nevertheless, the image reflectance value depends on the characteristics of soil material, land cover condition, as well as atmospheric condition. On the other hand, hyperspectral image processing is more complex than multispektral image. This is caused by its large data dimensionality. The objective of this research is to analyze relationship between content of clay fraction percentage with spectral response and spectral values and also to map the distribution of clay fraction based on the image. This research used Hyperion image with date of record 29 October 2009, covering parts of D.I Yogyakarta. Hyperion has 242 channels, but only 118 channels are used in this study. Atmospheric correction is done by FLAASH method and geometric correction is done by nearest neighbor resampling method. PCA also carried out to reduce dimensionality of data. 30 soil samples were collected from open land with five different landform of type. An open land is determined by pure pixel analysis, visual interpretation and NDVI transformation. 17 samples were used as input to the linear regression and its rests were use on map accuracy testing. Spectral patterns of soil has the same pattern in all samples, which starts increasing in visible to infrared spectrum, then decreases in middle infrared spectrum. A high content of clay fraction causes a high moisture content, then it indirectly decreases reflectance intensity in all spectral range, particularly on the 2.1-2.3 �m. Channels that have the highest correlation is indicated by the bands 217 (2,324 m), with coefficient regression value 0.67. But the highest accuracy in mapping with linear regression model is indicated by band 214 that has Standard Error 14.78% and the maximum accuracy value 52,33%. The using of multiple regression is proven to be able to increase the accuracy. The highest accuracy on this model is showed by the model 4, with input band 13 and 214, which has standard error 13.66% and maximum accuracy 55,93%.