Pemanfaatan citra landsat 8 OLI dan sistem informasi geografis untuk pemetaan kandungan bahan organik tanah dikabupaten Karanganyar Jawa Tengah

Anisa Nurwidia Akbari,

2016 | Skripsi |

Soil organic matter are components which determine soil fertility and related with crop production. Information of soil organic matter is needed by society, especially society in Karanganyar District which is the main sector is in agriculture. But soil organic matter is distributed in wide area, so measuring soil organic matter manually will need so much time, cost and energy. Application of remote sensing imagery and geographic information system is an alternative method to obtain information about content of soil organic matter in wide area coverage with more efficient time, cost and energy. The purposes of this study are to determine the ability of Landsat 8 imagery for soil organic matter modeling using clay mineral index approach, and make soil organic matter map in Karanganyar District based on digital image processing of Landsat 8 imagery and application of Geographic Information System (GIS). The method used in this study is linier regression between the value of clay minerals index and the percentage of soil organic matter from the laboratory test result. Clay minerals index used as texture approach, because soil with fine texture (contain more clay minerals) usually have more percentage of organic materials than soil with sand texture (Allison, 1973). Clay minerals index is calculated from ratio between pixel value of band 6 (SWIR 1) and band 7 (SWIR 2) in Landsat 8 imagery. Regression analysis was also carried out among the percentage of soil organic matter with other variables, which will be used as a comparison. Information of soil organic matter percentage derived from soil sample which taken directly from the field and then being tested in laboratory. The location of soil sampling is determined by variety of slope, variety of clay minerals index values and land cover in the form of open land. The result of this study showed that clay minerals index can be used to estimate soil organic matter in the study area when it combined with other variables such as pixel values in band 5 (near infrared) and slope variable. The estimation results of soil organic matter content in the study area with clay minerals index and the pixel values in the band 5 approach produces the most accurate value among the five models, with Standard Error Estimate (SE) of 1,69 and map maximum accuracy is 53,83 %. While the estimation results of soil organic matter content in the study area with clay minerals index and slope approach produce fairly accurate value with Standard Error (SE) of 2,88 and map maximum accuracy is 21.31%.

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