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Abstrak :
Informasi tentang kandungan bahan organik (BO) diperlukan untuk pemantauan dan pengelolaan lingkungan serta digunakan dalam praktek budidaya tanaman. Dalam penelitian ini dicobakan untuk memetakan kandungan bahan organik tanah di daerah Malang Selatan dengan menggunakan teknik penginderaan jauh (inderaja). Data inderaja yang digunakan adalah citra Landsat TM (Thematic Mapper) (band 1, 2, 3, 4, 5, 7). dan dipilih area yang memiliki nilai Normalized Difference Soil Index (NDSI) lebih dari 0,3. Data ground-truth diperoleh dengan menganalisis kandungan BO dan contoh-contoh tanah dengan menggunakan metode Black-Walkey. Hasil analisis menunjukkan bahwa penggunaan nilai derajat keabuan dan citra asli dapat digunakan untuk menduga kandungan bahan organik tanah. Penerapan persamaan regresi dengan menggunakan nilai derajat keabuan citra asli untuk menduga kandungan bahan organik tanah memperlihatkan bahwa tanah di daerah penelitian umumnya memiliki kandungan bahan organik sedang (meliputi 63,18% dari luas area penelitian).

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Application of Remote Sensing for Mapping Soil Organic Matter Content. Information organic content is important in monitoring and managing the environment as well as doing agricultural production activities. This research tried to map soil organic content in Malang using remote sensing technology. The research uses 6 bands of data captured by Landsat TM (Thematic Mapper) satellite (band 1, 2, 3, 4, 5, 7). The research focuses on pixels having Normalized Difference Soil Index (NDSI) more than 0.3. Ground-truth data were collected by analysing organic content of soil samples using Black-Walkey method. The result of analysis shows that digital number of original satellite image can be used to predict soil organic matter content. The implementation of regression equation in predicting soil organic content shows that 63.18% of research area contains of organic in a moderate category.

Abstrak :
Papua has been experiencing heavy logging activity in its forests for decades . However, only several studies focused on the effect of logging in the forest ecosystem. This research was aimed to analyze recovery processes of the forest ecosystem. The research was conducted in the logged tropical rainforest in South Papua using ecological approach which used tree communities as biotic and soil condition as abiotic indicators. Data were collected in the logging area of PT Tunas Timber Lestari located in the tropical rainforest of South Papua. There were five groups of forests used in this research i.e. unlogged, one year post selectively-logged, five years post selectively-logged, ten years post selectively-logged and fifteen years post selectively-logged forests. Thirty nested plots were laid on each forest group. Canonical Correspondence Analysis (CCA) was applied to analyze the understory and upperstory plant communities. Understory and upperstory plant communities formed different patterns due to logging. Plant communities in the ten and fifteen years post-selectively logged forests were not similar to those in the unlogged forest. Soil organic matter (SOM) content in the selectively logged forests was lower than that in the unlogged forest. These occurrences indicated that the selectively logged forests were still recovering and required more than fifteen years to be fully recovered.