Evaluation of the EO-1 Hyperion image for assessment of soil organic carbon in Faizabad Watershed, Tajikistan | |
| Author | Nazarmavloev, Farrukh |
| Call Number | AIT Thesis no.RS-11-10 |
| Subject(s) | Soils--Quality--Tajikistan--Faizabad Watershed Soils--Evaluation--Tajikistan--Faizabad Watershed |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. RS-11-10 |
| Abstract | Soil degradation monitoring and environmental management by using the up-to-date and accurate information of soil properties is very important. The conventional methods of soil analysis which are time consuming and expansive can be replaced by the remote sensing technologies for more rapid and efficient soil mapping. This study armed to evaluate space born image spectroscopy capacity for mapping soil organic carbon in the loess area with low to medium organic carbon content. The loess hills of Faizabad watershed in the western part of Tajikistan was selected as study area, where the soil erosion is considered the fastest and most wide spread soil degradation process and reduction of soil organic carbon has been identified as one of the key degradation processes. Soil samples (n=30) collected from the field where analyzed for organic carbon content by conventional method in the laboratory. The spectral reflectance of the samples was measured in the lab and in the field using ASD Field spectrometer (350-2500 nm). Hyperion image was acquired, preprocessed and atmospherically corrected using FLAASH model of ENYI. The total 160 bands have been selected for the analysis. The spectra of the samples site (n=23) were extracted from the Hyperion image (400-2500 nm). Partial Least Squares (PLS) regression with cross validation was used to develop calibrations models. The coefficients of determination in calibration (R2 ) and standard errors in cross validation (SECY) were 0.78 and 0.14 for laboratory reflectance spectra (n=30). For filed spectra (n=30), PLS regression result of R2 of 0.71 and SECY 0.16. and R2 of 0.67 and SECY of 0.18 of Hyperion image spectra (n=23) respectively. The SOC map was generated by applying the result of the PLS model to the Hyperion image. The result showed that predictions of SOC using the Hyperion spectra were less accurate than those of the lab and field spectra. However, for rapid and cost-effective approach, Hyperion demonstrated the good potential to predict soil organic carbon and digital soil mapping in the study area. |
| Year | 2011 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-11-10 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Other Field of Studies (No Department) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Honda, Kiyoshi |
| Examination Committee(s) | Tripathi, Nitin Kumar; Nagai, Masahiko; Wolfgramm, Bettina |
| Scholarship Donor(s) | University of Central Asia, Kyrgyz Republic |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2011 |