Monitoring of Lake Ecosystem Parameter using Landsat Data (a Case Study: Lake Rawa Pening)

Bambang Trisakti and Nana Suwargana and Joko Santo Cahyono (2015) Monitoring of Lake Ecosystem Parameter using Landsat Data (a Case Study: Lake Rawa Pening). International Journal of Remote Sensing and Earth Sciences, 12 (1). pp. 71-81. ISSN 0216-6739

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Abstract

Most lakes in Indonesia have suffered (decrease in quality) caused by land conversion in the catchment area, soil erosion, and water pollution from agriculture and households. This study utilizes remote sensing data to monitor several parameters used as ecosystem status assessors in accordance with the guidelines of Lake Ecosystem Management provided by the Ministry of Environment. The monitoring was done at Lake Rawa Pening using Landsat TM/ETM+ satellite data over the period of 2000-2013. The data standardization was done for sun angle correction and also atmospheric correction by removing dark pixels using histogram adjustment method. RGB color composites (R: NIR + SWIR, G: NIR, B: NIR-RED) were used for water hyacinth identification; thus, the lake water surface area can be delineated. Further samples were collected for water hyacinth and water classification with Maximum Likelihood method. Total Suspended Matter (TSM) by Doxaran model and the water clarity from field measurement was correlated to build water clarity algorithm. The results show that Lake Rawa Pening was deterioting in term of quality during the period of 2000-2013; it can be seen from the dynamic rate of the shrinkage and the expansion of the lake water surface area, the uncontrolled distribution of water hyacinth which it covered 45% of the lake water surface area in 2013, the increased of TSM concentration, and the decreased of water clarity. Most parts of Rawa Pening’s water have clarity less than 2.5 m which indicated that the thropic status is hypertrophic class

Item Type: Article
Uncontrolled Keywords: lake ecosystem, Landsat, lake water surface area, TSS, water clarity
Subjects: Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Pemanfaatan Penginderaan Jauh > Pengolahan Data > Klasifikasi
Divisions: Deputi Penginderaan Jauh > Pusat Pemanfaatan Penginderaan jauh
Depositing User: Dinar Indrasasi
Date Deposited: 02 Sep 2021 23:30
Last Modified: 02 Sep 2021 23:30
URI: http://repositori.lapan.go.id/id/eprint/1231

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