| dc.description.abstract | The agricultural sector is experiencing obstacles in meeting food needs and managing agricultural resources, in responding to these obstacles, a touch of technology is needed that can support more optimal and efficient agricultural development. The technology used is remote sensing, with a wide coverage is expected to be able to record various conditions of agricultural land with limited coverage and can also predict soil organic carbon and total soil nitrogen. This study aims to determine the distribution of C-organic and nitrogen in the study area, while combining two methods, namely interpolation of data derived from lab analysis and Landsat-8 image modeling results.
The results showed the distribution of C-organic from laboratory analysis which was then spline interpolated to produce C-organic with a status divided into 4 classes, namely very low 13.58%, low 44.35%, medium 29.64%, and high 12.14%. While C-organic with image modeling produces a distribution with the status of two classes, namely medium and low. The distribution of soil organic carbon with medium values dominates around 96.71% of the entire research site area. Furthermore, the distribution of nitrogen from laboratory analysis which is then spline interpolated produces three classes, namely very low nitrogen status 15.50%, low nitrogen status 70.99% and medium nitrogen status 13.51%. While STN with image modeling produces total soil nitrogen distribution with two classes, namely very low with an area of 661 Ha or 3.3% and low 96.37%. Based on the validation test with paired T-test, the similarity between C-organic from laboratory analysis and soil organic carbon from image modeling is 20%. In nitrogen, the results of laboratory analysis with total nitrogen of image modeling soil have a similarity of 33%. | en_US |
