Ekosistem mangrove merupakan ekosistem peralihan antara darat dan laut yang memiliki potensi, peran dan fungsi sangat besar dalam kehidupan. Untuk memperoleh informasi keberadaan hutan mangrove yang terbaru dapat diperoleh melalui data penginderaan jauh. Pemanfaatan teknologi penginderaan jauh sangat efisien karena data yang mudah diperoleh dan harga yang relatif murah.selain itu kelebihannya adalah memiliki resolusi temporal serta cakupannya yang luas dan mampu menjangkau daerah yang terpencil sehingga dapat digunakan untuk keperluan monitoring. Penelitian ini bertujuan untuk mengidentifikasi kerapatan ekosistem mangrove dengan menggunakan transformasi indeks vegetasi serta menguji beberapa indeks vegetasi dalam hal ini NDVI, NDWI dan SAVI dalam hal efektifitas dalam identifikasi jenis dan kerapatan mengrove. Berdasarkan hasil analisis citra Sentinel dengan menggunakan transformasi indeks NDVI, SAVI, dan NDWI untuk identifikasi kerapatan vegetasi pada transformasi NDVI didominasi kelas kerapatan tinggi yaitu pada rentang nilai 0,67 1 yaitu seluas 46975,96 Ha, pada transformasi SAVI didominasi kelas kerapatan sangat jarang yaitu pada rentang nilai 0,99 1,38 yaitu seluas 48775,18 Ha, pada transformasi NDWI didominasi kelas kerapatan rendah yaitu pada rentang nilai 0,1 0,17 yaitu seluas 27442,26 Ha. Berdasarkan hasil uji akurasi yang dilakukan menggunakan 30 sampel uji diperoleh akurasi sebesar 83,33%.
Mangrove ecosystem monitoring aims to provide information on a regular basis to be used as a reference in sustainable management activities in an effort to maintain the functions and services of the mangrove ecosystem. Mangroves have a very high level of threat to exploitation, namely logging and land conversion which can cause increasingly damaged conditions. This study aims to map changes in mangrove density by comparing several methods using multi-temporal data. The satellite image data used are Landsat images in 2010, 2015 and 2020. The research method used is the transformation of the vegetation indices ARVI, DVI, EVI, GNDVI, MSAVI, NDVI, RVI and TSAVI. Based on the results of the analysis carried out, the identification of mangrove density shows that the index value is in the range -1 – 18.31 with the division of density classes into 5 classes, namely very low, low, medium, high and very high. The mangrove class is in the range of values from 0.4 to 0.8 with a medium to very high density class. The results of the map accuracy test which were validated using 30 samples in the field obtained an accuracy of 84.38%. This accuracy value is quite good with the multi-temporal image used is of medium resolution.
The Way Kuripan River is one of the rivers in Bandar Lampung which overflows during the rainy season. Downstream of the river passes through several subdistrict, is Pesawahan, and Kota Karang. The purpose of the study is to analyze the river water level when the rainy season arrives. Based on survey research, the upstream of Way Kuripan River in the Betung Hills has a river width of ± 20 m and river depth of 4,51 m. While the downstream of the river width of ± 10 m and river depth of 2,78 m. Analyze using the Graphic Integration Method. Obtained, upstream water level of the river during the rainy season is 3.0793 m < 4.51 m. This is considered safety because the water discharge is still accommodated by the river. However, not with downstream conditions, the river water level reaches 5,216 m > 2.78 m. As a result, the watershed passed through (Pesawahan and Kota Karang subdistrict), experiences flooding due to overflowing water discharge.
Agriculture plays an essential role in national economic development. This fact made agricultural land one of the main unique production factors irreplaceable due to its importance in the agricultural business processes. However, a persistent problem of arable land conversion and land degradation have become more massive throughout the years. Meanwhile, the continuation of existing agricultural land and transformation into new agricultural land is inherently small. This research aimed to map agricultural land in sustainable agricultural development. Several transformative vegetation indices: NDVI, SAVI, and TSAVI, applied SPOT 6/7 satellite imagery in Lampung Province. Results show that the TSAVI value is the highest, with a 1.80 value, which indicates that this index value is very dense vegetation. Meanwhile, the NDVI index, which has a minimum value of -1.02, suggests that this index value is a non-vegetation object. However, high or low value does not indicate the rigorousness and Accuracy of an index. All three indices’ results are then overlaid with the satellite imagery classification process result. The accuracy result shows that the agricultural land has a maximum of 100% producer accuracy while the user accuracy value is 87.87%. Overall, for NDVI, the Accuracy was valued at 90.25%, which could be classified as a reasonable classification result. SAVI has a PA value of 97.85%, UA 85.20% and OA 86.63%, while the TSAVI Index has a PA value of 98.23%, UA 86.16% and OA 87.63%. This accuracy value indicates that the map has good results but judging from the magnitude of the highest accuracy value obtained from NDVI, it can be concluded that NDVI is the best index to determine paddy fieldsKeywords: Agricultural Land, SPOT 6/7, NDVI, SAVI, TSAVI.
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