NDVI analysis was calculated based on the ratio of the reflection of red and near infrared waves. Aims of this study is to determine the density condition and health level of oil palm plants that have entered the age of replanting using the NDVI index from Landsat 8 satellite imagery and evaluate the plant health level based on the NDVI index compared with the LSU data. The research was conducted at Afdeling 1 Rantau Baru Plantation, PT. Pusaka Megah Bumi Nusantara, which is a plantation with old oil palm plant that have entered a period of replanting (22-29 years). The NDVI analysis results show the NDVI value is 0.034-0.469. Object identification shows that non-vegetation objects have an NDVI index value of 0.034-0.245 and vegetation objects have a value of 0.273-0.454. The result of the NDVI index shows the density of oil palm plants are categorized in the high category (dense). These results are appropriate with the actual condition of oil palm plantations which have an average density of 118 trees/hectare. The average NDVI value for vegetation objects is 0.423, that indicates the plants are in fairly healthy condition. The level of plant health as the result of the NDVI analysis was in appropriate with the LSU data which showed that the content of macro and micro nutrients in the leaves was quite high. Therefore, NDVI analysis can be an alternative to evaluate the condition of oil palm plantations efficiently. Keywords: Landsat 8 sattelite imagery, NDVI index, Oil palm, Plant density, Plant health
Climate anomaly phenomena are increasing in frequency and duration along with the occurance of global warming phenomena. El Nino and La Nina climate anomalies have a direct impact on agriculture. This study aims to analyze the occurrence of extreme climate phenomena El Nino and La Nina in 2012-2022 in Indonesia and their impact on rainfall in South Sumatera Province which is one of the centers of oil palm plantations. The research was conducted by identifying sea surface temperature (SST) anomalies in the Pacific Ocean and classifying them into El Nino and La Nina strength levels or normal conditions. Based on the sea surface temperature anomaly, it is known that Indonesia experienced strong El Nino events in 2014-2015 and weak El Nino in 2019. El Nino causes a prolonged dry season and decreases the amount of rainfall. The La Nina phenomenon occurs in 2020-2022 with weak to moderate strength. La Nina causes a prolonged rainy season and an increase in the amount of rainfall. Normal conditions occurred in 2013, 2016, 2017 and 2018 which were marked by sst anomalies of not more than +0.5°C and -0.5 °C. During normal conditions, South Sumatra Province has an annual rainfall of 2,500 mm, rainfall is evenly distributed throughout the year, and dry months are less than 3 months that suitable for oil palm cultivation. In the last 10 years, Indonesia has experienced the El Nino and La Nina climate anomalies with increasing frequency, duration, and level of strength.
Citra satelit Sentinel 2 merupakan citra satelit resolusi sedang yang dapat dimanfaatkan untuk memantau kondisi kebun kelapa sawit menggunakan analisis Normalized Difference Vegetation Index (NDVI). Indeks NDVI merupakan indeks vegetasi yang dihitung berdasarkan rasio nilai reflektansi pada band merah dan inframerah dekat dari pelepah daun kelapa sawit. Penelitian ini bertujuan untuk menganalisis kondisi kerapatan dan kesehatan tanaman kelapa sawit tua (22-29 tahun) yang telah memasuki masa peremajaan. Penelitian dilakukan di Afdeling 1 Kebun Rantau Baru PT. Pusaka Megah Bumi Nusantara. Hasil penelitian menunjukkan nilai NDVI untuk tanaman kelapa sawit memiliki rentang 0,51 - 0,84. Berdasarkan index NDVI untuk tanaman kelapa sawit, diketahui bahwa kerapatan tanaman kelapa sawit termasuk dalam kategori tinggi dan tingkat kesehatannya termasuk dalam kategori sangat sehat. Kelas kerapatan tinggi hasil pengkelasan indeks NDVI sesuai dengan kondisi kerapatan tanaman di blok kebun kelapa sawit yang memiliki nilai rerata Satuan Pohon per hektar (SPH) 118 pohon/hektar. Kelas kesehatan tanaman hasil NDVI sesuai dengan data Leaf Sampling Unit (LSU) yang menunjukkan nilai kandungan makronutrien dan mikronutrien dalam jumlah yang cukup tinggi. Pemanfaatan citra satelit Sentinel 2 dapat menjadi alternatif untuk evaluasi kondisi kebun kelapa sawit secara cepat dan efisien.
La Nina is a climate anomaly that can cause extreme weather. La Nina is marked by a decrease in the sea surface temperature of the Pacific Ocean at the equator. La Nina can cause a prolonged rainy season for Asia including Indonesia. From mid-2020 to the end of 2022, Indonesia has experienced La Nina events. This study aims to determine changes in rainfall patterns and the number of rainy days during La Nina events. This research was conducted descriptively, using Pacific Ocean sea surface temperature (SST) data and rain data originating from the BMKG Climatology Station of Sultan Syarif Kasim II Pekanbaru from data for the last 10 years 2013-2022. The results of the study show that La Nina occurred from October 2020 to December 2022 with a weak to moderate level of La Nina strength. La Nina has increased the amount of rainfall 54-90% from normal conditions and increased the number of rainy days 11-70% compared to climate with normal conditions. Monthly rainfall is in the low to high category, while daily rainfall is included in the heavy rain category. The La Nina event has caused a prolonged rainy season for almost 3 years and has increased the amount of rainfall and rainy days.
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