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All Journal Journal of Regional and City Planning The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Azura Ulfa
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Humanities Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Environmental Science Social Sciences Transportation

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The Implementation of Zero Run-off and Agroforestry Concept Based on River Discharge in Belik Sub Watershed, Yogyakarta Arnellya Fitri; Azura Ulfa
Journal of Regional and City Planning Vol. 26 No. 3 (2015)
Publisher : The Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/jpwk.2015.26.3.4

Abstract

Daerah Aliran Sungai (DAS) Belik merupakan salah satu Daerah Tampungan Air (DTA) yang berada di daerah perkotaan Kabupaten Sleman. Akibat alih fungsi lahan pertanian menjadi lahan pemukiman yang padat menyebabkan semakin berkurangnya area resapan air hujan. Kurangnya area resapan air hujan menyebabkan kapasitas saluran drainase Sub Daerah Aliran Sungai (DAS) Belik pada saat hujan  tidak mampu menampung air sehingga banjir di sekitar saluran drainase terjadi. Tujuan penelitian ini untuk memberikan solusi dengan menggunakan konsep zero run-off  dalam upaya  mencegah genangan banjir di perkotaan yang kurang memiliki ruang terbuka hijau dan area resapan air hujan. Kajian debit banjir yang dilakukan pada sungai Belik menggunakan metode rasional dan metode SCS CN yaitu metode yang digunakan dalam penentuan debit puncak pada satu kejadian hujan. Perhitungan debit diperlukan untuk mengetahui besar limpasan maksimum pada drainase saluran DAS Belik. Metode hidrograf  SCS CN  menggunakan parameter tekstur tanah, tebal hujan, CN wilayah, retensi potensial maksimum air oleh tanah, dan kedalaman hujan efektif. Sedangkan metode rasional menggunakan parameter koefesien aliran, intensitas hujan, dan luas daerah pengaliran dalam menghitung debit limpasan. Keseluruhan hasil perhitungan kedua metode melebihi besar debit pengukuran langsung menggunakan Metode Slope Area, artinya keseluruhan hasil menunjukkan banjir atau limpasan permukaan yang melebihi kapasitas drainase.Kata kunci. Limpasan permukaan, metode SCS CN, metode rasional, zero run-off Belik Watershed is one of the Water Catchment Areas  located in urban areas of Sleman District. Land conversion from agricultural to residential area cause the descending of rain water catchment area. Lack of rain water catchment area can cause drainage channel capacity of Belik sub zone cannot hold rain water, so that flooding occurred around the drainage channel. The aim of this research is to give a way out to overcome the flood problem by using zero run-off concepts, to prevent the flood in urban area which does not have sufficient green room and rain water penetration area. The study of flood discharge using the rational method and SCS CN method which is a method used to determine peak flow when the rain pour in Belik sub zone. The discharge calculations are necessary to determine the maximum runoff drainage of Belik sub zone channel. The hydrograph SCS CN method uses soil texture parameters, thick of the rain, CN region, the maximum potential water retention by the soil, and the depth of the effective rain. Meanwhile, the rational method uses flow coefficient parameter, rainfall intensity, and area of drainage in calculating discharge runoff. All of the calculations results from both methods are bigger than the result using direct measurement with slope area method. This means that all of the result shows that flood or run off is bigger than the drainage capacity.Keywords. Run-off, SCS CN method, rational method, zero run-off
PLATFORM REEF LAGOON DETECTION FROM SENTINEL-2 IN PANGGANG ISLAND AND SEMAKDAUN ISLAND Wikanti Asriningrum; Azura Ulfa; Kholifatul Aziz; Kuncoro T. Setiawan; Dyah Pangastuti
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3804

Abstract

Processing of satellite image data for the detection of platform reef lagoons is intended as one of the geo-physical parameters of the reef landform. Panggang Island and Semakdaun Island were chosen to make the detection model because they are ideal for lagoon reef landforms and tapulang court reefs. This model is only valid in the continental shelf area and the back arc and small island tectonic type. Determination of this location is done to improve the accuracy of spectral-based data processing. Platform reefs are one of four classes of reef landforms. Sentinel-2A data with a spatial resolution of 10m, blue, green, red, and near infrared bands were selected to investigate their ability to detect lagoons. Processing of data by calculating the Optimum Index Factor (OIF) to produce a composite image and drawing transect lines to produce pixel values and spectral graphics of the lagoon. The results of data processing in the form of graphs, composite images and pixel values were built to realize a digital lagoon detection model. These results are used for lagoon growth stage analysis for the classification of three reef platform landforms, visually and digitally interpretation. This digital and visual detection system design is useful for monitoring coral reef ecosystems.
DETECTION OF WATER-BODY BOUNDARIES FROM SENTINEL-2 IMAGERY FOR FLOODPLAIN LAKES Azura Ulfa; Fajar Bahari Kusuma; A. A. Md. Ananda Putra Suardana; Wikanti Asriningrum; Andi Ibrahim; Lintang Nur Fadlillah
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3827

Abstract

The impact of climate and human interaction has resulted in environmental degradation. Consistent observations of lakes in Indonesia are quite limited, especially for flood-exposure lake types. Satellite imagery data improves the ability to monitor water bodies of different scales and the efficiency of generating lake boundary information. This research aims to detect the boundaries of flood-exposure type lake water bodies from the detection model and calculate its accuracy in Semayang Melintang Lake using Sentinel-2 imagery data. The characteristics of water, soil, and vegetation objects were investigated based on the spectral values of the composite image bands from the Optimum Index Factor (OIF) calculation, to support the lake water body boundary detection model. The Object-Based Image Analysis (OBIA) method is used for water and non-water classification, by applying the machine learning algorithms random forest (RF), support vector machine (SVM), and decision tree (DT). Model validation was conducted by comparing spectral graphs and lake water body boundary model results. The accuracy test used the confusion matrix method and resulted in the highest accuracy value in the SVM algorithm with an Overall Accuracy of 95% and a kappa coefficient of 0.9. Based on the detection model, the area of Lake Semayang Melintang in 2021 is 23392.30 ha. This model can be used to estimate changes in the area of the flood-exposure lake consistently. Information on the boundaries of lake water bodies is needed to control the decline in the capacity and inundation area of flood-exposure lakes for management and monitoring plans.
SPATIO-TEMPORAL ANALYSIS OF CHANGES IN CORAL REEF AREA USING LANDSAT 8 SATELLITE IMAGERY ON PARI ISLAND, KEPULAUAN SERIBU, DKI JAKARTA Faisal Akmal; Bambang Semedi; Azura Ulfa
International Journal of Remote Sensing and Earth Sciences Vol. 21 No. 1 (2024)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2024.v21.a3894

Abstract

Coral reefs are ecosystems that are sensitive to change. High pressure can cause damage to coral reefs. Monitoring the condition of coral reefs needs to be done to know the current condition. One way that can be used to monitor coral reefs is by utilizing remote sensing. The research was conducted to know the changes in the coral reef area and the factors that influence the changes in the coral reef area in Pari Island, Kepulauan Seribu, DKI Jakarta in the period 2013 to 2022. The research was conducted using Landsat 8 image data from 2013 to 2022. Image data processing was done with an object-based classification method. Coral cover measurements were conducted using the Line Intercept Transect (LIT) method. The results showed a change in coral reef area of 7.02 ha with the condition of live coral cover ranging from 27-43% which is included in the fair category. The results of field measurements show that the condition of water parameters falls into the unsuitable category. The increase in area that occurred was thought to be due to management activities carried out by the Pari Island community and activities carried out by LIPI in 2016, namely conducting coral reef restoration. The decrease in area is partly due to coastal reclamation activities, destructive tourist activities, and parameter conditions.
BIOMASS ESTIMATION MODEL AND CARBON DIOXIDE SEQUESTRATION FOR MANGROVE FOREST USING SENTINEL-2 IN BENOA BAY, BALI A. A. Md. Ananda Putra Suardana; Nanin Anggraini; Kholifatul Aziz; Muhammad Rizki Nandika; Azura Ulfa; Agung Dwi Wijaya; Abd. Rahman As-syakur; Gathot Winarso; Wiji Prasetio; Ratih Dewanti
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3797

Abstract

Remote sensing technology can be used to find out the potential of mangrove forests information. One of the potentials is to be able to absorb three times more CO2 than other forests. CO2 absorbed during the photosynthesis process, produces organic compounds that are stored in the mangrove forest biomass. Utilization of remote sensing technology is able to detect mangrove forest biomass using the density level of the vegetation index. This study focuses on determining the best AGB model based on the vegetation index and the ability of mangrove forests to absorb CO2. This research was conducted in Benoa Bay, Bali Province, Indonesia. The satellite image used is Sentinel-2. Classification of mangroves and non-mangroves using a multivariate random forest algorithm. Furthermore, the mangrove forest biomass model using a semi-empirical approach, while the estimation of CO2 sequestration using allometric equations. Mean Absolute Error (MAE) is used to evaluate the validation of the model results. The classification results showed that the detected area of Benoa Bay mangrove forest reached 1134 ha (OA: 0.98, kappa: 0.95). The best AGB estimation result is the DVI-based AGB model (MAE: 23,525) with a value range of 0 to 468.38 Mg/ha. DVI-based AGB derivatives are BGB with a value range of 0 to 79.425 Mg/ha, TAB with a value range of 0 to 547.8 Mg/ha, TCS with a value range of 0 to 257.47 Mg/ha, and ACS with a value range of 0 to 944.912 Mg/ha.
Co-Authors A. A. Md. Ananda Putra Suardana Abd. Rahman As-syakur Agung Dwi Wijaya Andi Ibrahim Arnellya Fitri Bambang Semedi Dyah Pangastuti Faisal Akmal Fajar Bahari Kusuma Gathot Winarso Kholifatul Aziz Kuncoro T. Setiawan Lintang Nur Fadlillah Muhammad Rizki Nandika Nanin Anggraini Ratih Dewanti Wiji Prasetio Wikanti Asriningrum