Modelling of Transformation Vegetation Index Using Landsat 7 ETM+ (Enhanched Thematic Mapper) Imagery for the Spatial Analysis of Production Estimation of Rice (Case Study in Sragen Regency, Central Java Province)

Utomowati, Rahning and Ahmad, and Nugraha, Setya (2012) Modelling of Transformation Vegetation Index Using Landsat 7 ETM+ (Enhanched Thematic Mapper) Imagery for the Spatial Analysis of Production Estimation of Rice (Case Study in Sragen Regency, Central Java Province). .

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    Abstract

    As an agricultural country, the agricultural sector in Indonesia is one of the important sectors of the construction sector in the main development. One of the agricultural commodities most important food in Indonesia is a rice, which is the staple food for more than 95 percent of the population.Based on the importance of rice as a staple food most of the people of Indonesia, the volume of rice production every year should be controlled, through the estimation of production. Various methods have been developed to estimation production of rice, one of which by using a remote sensing method. Through the analysis of satellite imagery can be reduced the levels of plant greenness (vegetation index) which can be used to estimate the age of the rice crop and productivity. Using the satellite imagery, acquisition of rice production data can be performed quickly and accurately, making it more efficient in terms of time, cost, and effort. The aims of the study are : (1). To create a model of the transformation vegetation index is most suitable used as the basis in production estimation of rice, (2). To asses the ability of Landsat 7 ETM+ imagery in the extraction data of rice fields area which is used for a basis for estimation production of rice. This research is a remote sensing research . The method of data collection used a digitally image interpretation, field observations, interviews, and review of documentation. The main data source is Landsat 7 ETM+ imagery, which is used for extraction rice fields data and production estimation of rice. From the Landsat 7 ETM + imagery derived of vegetation index information, information of land cover and land use as a basis for estimation production of rice. The transformation of vegetation index method used in this study is the transformation of NDVI and SAVI. Forms of research is descriptive qualitative analysis Productivity of rice data derived from measurements field. The data analysis used the spatial descriptions using analysis of Geographic Information Systems(GIS). Results of this research show that : (1). Based on the results of correlation between the productivity of rice with the brightness value, the correlation coefficient (r) between variables NDVI with productivity is 0.844 and the value of r ²= 0, 712, while the value of the correlation coefficient (r) between variables SAVI with productivity is 0.841 and the value of r ² = 0.707, so between SAVI and NDVI variables with productivity variables have positive correlation and strong correlation. Thus, the transformation of NDVI and SAVI indices can be used as the basis for estimation production of rice in the research area. The transformation of vegetation index NDVI is more suitable model, because it has value of correlation result is higher when compared to the value of the correlation transformation of vegetation index SAVI. (2), Based on the interpretation of test matrices, obtained accuracy of image interpretation of Landsat 7 ETM + is 90.22%. With reference to the standard interpretation of precision, accuracy test results are included in both categories, and meet the standards of accuracy of interpretation Thus, the Landsat 7 ETM+ imagery have a high accuracy for the extraction of rice fields of data required for estimation production of rice so an alternative method that can be used to estimate of rice production.

    Item Type: Article
    Subjects: H Social Sciences > HB Economic Theory
    Divisions: Fakultas Keguruan dan Ilmu Pendidikan
    Depositing User: Lynda Rahmawati
    Date Deposited: 28 Apr 2014 17:46
    Last Modified: 28 Apr 2014 17:46
    URI: https://eprints.uns.ac.id/id/eprint/13866

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