Kota Bandar Lampung memiliki topografi yang cukup beragam berupa lembah maupun punggungan bukit, dalam perkembangannya banyak kawasan pemukiman yang tersebar diantara perbukitan. Bencana longsor merupakan salah satu bencana yang sering terjadi di Indonesia. Perlu adanya kajian daerah rawan longsor beserta mitigasi bencana secara spesifik yang menjadi langkah konkrit dalam mengurangi angka korban jiwa maupun materi. Banyak faktor yang mempengaruhi rawan bencana longsor, yaitu: tingkat kemiringan dari kelerengan, tutupan lahan, jenis batuan dan tanah, serta didukung dengan data kejadian sebelumnya. Gambaran permukaan bumi khususnya daerah rawan longsor dapat direpresentasikan dalam peta, diawali dengan disusunnya dataset fundamental berdasarkan parameter yang berpengaruh kejadian longsor. Setiap parameter yang mempengaruhi kejadian longsor yang digunakan memiliki besar bobot yang berbeda dan terangkum dalam metode tumpang susun (Overlay). Meninjau area rawan di Kota Bandar Lampung terdapat sisa endapan gunungapi menghasilkan geomorfologi bukit terjal dimana penyusun batuannya adalah tuff dan breksi, yang kini bisa diamati di Kota Bandar Lampung, diantaranya adalah Bukit Sulah Sukarame, Bukit Koga Kedaton, Bukit Kaliawi dan Bukit Randu Tanjungkarang. Selain itu, terdapatnya banyak sesar yang berarah NW-SW sejajar orientasi Teluk Lampung, beberapa bukit di sekitarnya memiliki morfologi dengan curam. Batuan penyusunnya pun memiliki banyak rekahan, sehingga cenderung menjadikan lereng menjadi tidak stabil. Inilah yang membuat beberapa daerah di Kota Bandar Lampung rawan terjadi longsor.
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.
In early 2021, a rare extraterrestrial object passed at high speed, followed by a powerful boom, with a bright flare crossing the atmosphere and falling in Astomulyo Village, Punggur, Central Lampung, Indonesia. This object has been scientifically determining as a meteorite. Toward the spot where we first found it, we presented this object named Astomulyo meteorite. This research investigated its chemical properties using an X-ray fluorescence (XRF) analyzer. As the result, the major composition of this meteorite is Si (28.3-27.1%), Fe (22.1-19.8%), Mg (17.3-15.2%), Al (2.9-2.4%), Ca (1.7-1.9%), and S (1.0-0.97%). Its minor elements are Mn, Ni, Cr, P, and some trace elements such as Co, Ti, Sb, Sn, V, Cd, Zn. This meteorite suggested classifying as the H-Chondrites group. Fe, Ni, Al, and Ti enrichment occur on the meteorite’s surface. It is probably related to this meteorite origin and continuously processes until it falls to the Earth’s surface.
This research was conducted to 3D model our meteorite collection based on photo-capturing. This meteorite are from Astomulyo, Central Lampung, Indonesia. It entry the earth's atmosphere and was found on January 28, 2021. The chance of object degradation nearly appears over time, so It is very urgent to obtain the 3D model of the object for further research necessary. 3D modelling was carried out using a non-metric camera to conduct the close-range photogrammetry method. It applies to modelling the objects based on photo data using the concept of collinearity by using a central projection system on the camera to record. The collinearity will produce an object point between the camera center and the object cloud point. Hence, this process forms the object model from the appropriate image projection, the tie point with the triangular irregular network model. As a result, it produces the DTM (Digital Terrain Model) object formation using stand-alone photogrammetric software, raster graphics, and 3D modelling software.
Increased deforestation and draining of peatlands with the started of the drainage occurs quickly makes the availability of peatlands as carbon storage is even more alarming. The presence of peat land conversion greatly affect the hydrological balance of the ecosystem. The conversion of peatland have the massive effect with the increase of drainage constructions for land cultivation needs. This makes the neighborhood unity peat hydrology (KHG) which is wet into dry so prone to burning and experiencing land subsidence. Information of peatland degradation is presented in the spatio - temporal visualization using Space Time Cube (STC). The usability in order to determine the extent of the spatio - temporal visualization can be used by users to obtaining information peatland degradation in terms of effectiveness, efficiency and satisfaction for users. Drainage density built on KHG getting bigger every year with the index of medium density classification. Increasing the number of long-drainage occurs at 119.4934 km per year from 2000 to 2008 and 148.6954 km per year from 2008 to 2012. Based on observations in 12 years has increased the number of distribution Hotspot significantly in February. In May and September the spread of hotspots increased by the average number of hotspots at 15 points per month. The drainage development’s and distribution of hotspot has dominant occurs at the HTI in the KHG Peatland degradation is presented in Visualization spatio-temporal, which visualization is very effective, fairly efficient, and give satisfaction to the users in displaying information peatland degradation in time series.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.