PEMANFAATAN FUSI DATA SATELIT LAPAN-A3/IPB DAN LANDSAT 8 UNTUK MONITORING LAHAN SAWAH

• Main Authors: Yudi Setiawan, Lilik Budi Prasetyo, Hidayat Pawitan, Liyantono Liyantono, Syartinilia Syartinilia, Arif Kurnia Wijayanto, Prita Ayu Permatasari, A Hadi Syafrudin, Patria Rachman Hakim
• Format: Article
• Language: English
• Published: Bogor Agricultural University 2018-02-01
• Series: Journal of Natural Resources and Environmental Management
• Subjects: LAPAN-A3/LAPAN-IPB; satellite; paddy field monitoring; climate change
• Online Access: https://journal.ipb.ac.id/index.php/jpsl/article/view/19754
• ISSN: 2086-4639; 2460-5824

Increasing of economic development is generally followed by the change of landuse from agriculture to other function. If it occurs in large frequency and amount, it will threaten national food security. Therefore, it is necessary to monitor the agricultural land, especially paddy fields regarding to changes in landuse and global climate. Utilization and development of satellite technology is necessary to provide more accurate and independent database for agricultural land monitoring, especially paddy fields. This study aims to develop a utilization model for LAPAN-IPB satellite (LISAT) and other several satellites data that have been used for paddy field monitoring. This research is conducted through 2 stages: 1) Characterization LISAT satellite data to know spectral variation of paddy field, and 2) Development method of LISAT data fusion with other satellites for paddy field mapping. Based on the research results, the characteristics Red and NIR band in LISAT data imagery have a good correlation with Red and NIR band in LANDSAT 8 OLI data imagery, especially to detect paddy field in the vegetative phase, compared to other bands. Observation and measurement of spectral values using spectroradiometer need to be conducted periodically (starting from first planting season) to know the dynamics of the change related to the growth phase of paddy in paddy field. Pre-processing of image data needs to be conducted to obtain better LISAT data characterization results. Furthermore, it is necessary to develop appropriate algorithms or methods for geometric correction as well as atmospheric correction of LISAT data.