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All Journal Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian Majalah Geografi Indonesia JURNAL AGROTEKNOLOGI Forum Geografi GEA, Jurnal Pendidikan Geografi MAJALAH ILMIAH GLOBE UNM Geographic Journal BHUMI: Jurnal Agraria dan Pertanahan GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Iswari Nur Hidayati
Departement Of Geographic Information Science, Faculty Of Geography, Gadjah Mada University
Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences Other

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High Resolution Remote Sensing Data Application to Assess Parking Space in Urban Area Suharyadi Suharyadi; Iswari Nur Hidayati
Indonesian Journal of Geography Vol 52, No 3 (2020): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.57604

Abstract

The increase population in a large city such as Yogyakarta has caused an increase in the number of cars. The large number of cars created another problem of limited parking space in the city. Currently, there is a lack of a spatial approach to solve the problem of parking space. With the availability of high-resolution remote sensing data, the business area in the city can be mapped accurately. This study aims to map the business zone in Yogyakarta City and to estimate the needs of parking space for trade, service, and education centers in Yogyakarta City using remote sensing imagery. The business zone really needs a parking area because many people as producers for loading goods and consumers buy at these stores. The method used to estimate the vehicle parking space requirement is a combination of field surveys and the interpretation of remote sensing images. The field survey was used to obtain the characteristics of the visitors, and the volume of filled parking space. Meanwhile, remote sensing imagery was used to obtain spatial data of land use. The parking requirements of commercial buildings are 2.25-3.15 spaces per 100 m2, offices are 1.0-1.60 spaces per 100 m2, hotels are 0.25-0.35 spaces for each sleeping room, theaters are 0.06 spaces for every seat, hospitals are 0.60 spaces for each bed, and schools are 0.10 space for every student. This paper demonstrated the use of remote sensing to solve urban vehicle problems, and such information can be used for city planning.
Deteksi Permukiman Kumuh Menggunakan Informasi Spektral dan Tekstur Citra Multiresolusi Spasial (studi di sebagian Kota Yogyakarta) Achmad Fadhilah; Prima Widayani; Iswari Nur Hidayati
Geo Media: Majalah Ilmiah dan Informasi Kegeografian Vol 19, No 1 (2021): Geo Media: Majalah Ilmiah dan Informasi Kegeografian
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/gm.v19i1.40164

Abstract

Pemetaan dan identifikasi merupakan tahap awal dalam program peningkatan kualitas permukiman kumuh. Pemetaan permukiman kumuh saat ini masih menggunakan metode survei langsung yang membutuhkan banyak biaya, waktu, dan tenaga. Penelitian ini bertujuan untuk mendeteksi keberadaan permukiman kumuh menggunakan citra satelit multiresolusi spasial sebagai metode alternatif dalam mengidentifikasi permukiman kumuh. Citra yang digunakan dalam penelitian ini antara lain: Pleiades-1B, SPOT-7, dan Sentinel-2. Studi ini berlokasi di sebagian Kota Yogyakarta yang dibagi dua daerah penelitian. Algortima Support Vector Machine (SVM) digunakan untuk mengkelaskan permukiman kumuh dan bukan kumuh. Parameter yang digunakan dalam penelitian ini antara lain: Saluran multispektral, Grey Level Co-occurrence Matrx (GLCM), dan Normalized Difference Vegetation Index (NDVI). Validasi dilakukan dengan menggabungkan data sekunder peta permukiman kumuh dan hasil observasi lapangan. Hasil penelitian menunjukkan bahwa tingkat akurasi klasifikasi tertinggi dihasilkan dari layer Sentinel-2 GLCM 3x3 sebesar 56,26% pada daerah penelitian 1, sedangkan pada daerah penelitian 2 diperoleh dari layer Pleiades-1B GLCM 9x9 sebesar 66,17%.
A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI Iswari Nur Hidayati; R Suharyadi
Forum Geografi Vol 33, No 2 (2019): December 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i2.9179

Abstract

Impervious surface is one of the major land cover types of urban and suburban environment. Conversion of rural landscapes and vegetation area to urban and suburban land use is directly related to the increase of the impervious surface area. The impervious surface expansion is straight-lined with decreasing green spaces in urban areas. Impervious surface is one of indicator for detecting urban heat islands. This study compares various indices for mapping impervious surfaces using Landsat 8 OLI imagery by optimizing the different spectral characteristics of Landsat 8 OLI imagery. The research objectives are (1) to apply various indices for impervious surface mapping and (2) identifies impervious surfaces in urban areas based on multiple indices and provide recommendations and find the best index for mapping impervious surface in urban areas. In addition to utilizing the index, land use supervised classification method, maximum likelihood classification used for extracting built-up, and non-built-up areas. Accuracy assessment of this research used field data collection as primary data for calculating kappa coefficient, producer accuracy, and user accuracy. The study can also be extended to find the land surface temperature and correlate the impervious surface extraction data with urban heat islands.
Analisis Pan-Sharpening untuk Meningkatkan Kualitas Spasial Citra Penginderaan Jauh dalam Klasifikasi Tata Guna Tanah Iswari Nur Hidayati; Eni Susanti; Westi Utami
BHUMI: Jurnal Agraria dan Pertanahan Vol. 3 No. 1 (2017): Bhumi: Jurnal Agraria dan Pertanahan
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat, Sekolah Tinggi Pertanahan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (753.594 KB) | DOI: 10.31292/jb.v3i1.95

Abstract

Pan-sharpened transformation methods improve the quality of spatial resolution remote sensing imagery. This study used pan-sharpened analysis to improve the quality of image. Pan-sharpening method was used to increase spatial quality of each research object. The aims of reserach were to study image sharpening using Quickbird imagery (multispectral band and pancromatic band) and to calculate overall accuracy of land use classification base on pan-sharpened imagery classification. This study used Brovey transformation and Gram-Schmidt transformation for pan-sharpened process. The classification system used Suharyadi Classification scheme (2001) for urban areas. The results showed that Brovey transformation better than gram-schmidt transformation for the elements of texture, shape, pattern, height, and shading. Gram-Schmidt method was more suitable for the analysis concerned to its original color combination associated with the color or hue of the elements of visual interpretation. The accuracy of the study is  90.70%.Sebagian besar proses citra pan-sharpened yang diperoleh dengan formulasi berbagai algoritma yang sudah ditentukan merupakan representasi antara hubungan karakteristik dari resolusi spektral untuk meningkatkan kualitas secara visual dari citra itu sendiri. Hasil dari beberapa citra pan-sharpened tersebut menjadikan salah satu alternative untuk analisis visual citra penginderaan jauh. Penelitian ini mencoba melakukan analisis pan-sharpened untuk mendapatkan hasil yang lebih maksimal dalam berbagai kenampakan untuk setiap tata guna tanah perkotaan. Pemanfaatan pan-sharpening untuk meningkatkan kualitas spasial dari tiap objek penelitian akan dikaji agar mendapatkan masukan dalam pengembangan metode pan-sharpening untuk klasifikasi tata guna tanah di perkotaan. Penelitian ini menggunakan metode transformasi Brovey dan Gram-Schimdt untuk proses pan-sharpened. Sistem klasifikasi yang digunakan adalah sistem Klasifikasi Suharyadi (2001) untuk daerah perkotaan. Hasil penelitian ini menunjukkan bahwa metode Brovey lebih baik dalam penyajian untuk tekstur, bentuk, pola, tinggi, dan bayangan. Metode Gram-Schimdt lebih cocok untuk analisis yang lebih mementingkan perpaduan warna (komposit) aslinya terkait dengan warna ataupun rona dalam unsur interpretasi visual. Hasil akurasi penelitian penggunaan tanah yang digunakan dalam penelitian ini sebesar 90,70%.  
Prediction and Simulation of Land Use and Land Cover Changes Using Open Source QGIS. A Case Study of Purwokerto, Central Java, Indonesia Gian Felix Ramadhan; Iswari Nur Hidayati
Indonesian Journal of Geography Vol 54, No 3 (2022): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.68702

Abstract

Population size multiplies along with the increasing need for residential space. As often occurs in developing cities like Purwokerto, population growth is associated with land use/land cover (LULC) change to accommodate housing demand both in the present and future. Therefore, this study was intended to map LULC changes in three different years: 2008, 2013, and 2018, and predict the change in 2023. For LULC data extraction, a pixel-based digital classification with a maximum likelihood algorithm was applied to Landsat images. In addition, the LULC change prediction was modeled with Modules for Land Use Change Simulations (MOLUSCE) from the QGIS plugins. It used two algorithms: artificial neural network (ANN) with a multilayer perceptron (MLP) and cellular automata (CA). The LULC classifications for 2008, 2013, and 2018 were 88%, 86%, and 88% accurate, while the prediction was 75.26% accurate, with a kappa of 0.634. Predictions and simulations indicate fluctuations in LULC change in the City of Purwokerto periodically, especially for built-up land, showing growth that continues to increase significantly.
Developing an Extraction Method of Urban Built-Up Area Based on Remote Sensing Imagery Transformation Index Iswari Nur Hidayati; R Suharyadi; Projo Danoedoro
Forum Geografi Vol 32, No 1 (2018): July 2018
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v32i1.5907

Abstract

Studying urban areas using remote sensing imagery has become a challenge, both visually and digitally. Supervised classification, one of the digital classification approaches to differentiate between built-up and non-built-up area, used to be leading in digital studies of urban area. Then the next generation uses index transformation for automatic urban data extraction. The extraction of urban built-up land can be automatically done with NDBI although it has one limitation on separating built-up land and bare land. The previous studies provide opportunities for further research to increase the accuracy of the extraction, particularly using index transformation. This study aims to obtain the maximum accuracy of the extraction by merging several indices including NDBI, NDVI, MNDWI, NDWI, and SAVI. The merging of the indices is using four stages: merging of two indices, three indices, four indexes and five indices. Several operations were experimented to merge the indices, either by addition, subtraction, or multiplication. The results show that merging NDBI and MNDWI produce the highest accuracy of 90.30% either by multiplication (overlay) or reduction. Application of SAVI, NDBI, and NDWI also gives a good effect for extracting urban built-up areas and has 85.72% mapping accuracy.
Carbon Stock Estimation From Vegetation Biomass Using Spot-7 Imagery Rahmatika, Iklila; Hidayati, Iswari Nur; Suharyadi, R; Nurjani, Emilya
Indonesian Journal of Geography Vol 55, No 3 (2023): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.78690

Abstract

Vegetation absorbs carbon dioxide (CO2 ) emissions during photosynthesis. Covering more areas with trees will increase the CO2 absorption capacity more substantially than other vegetation like bushes, grasses, or rice fields. Trees convert the CO2 captured during photosynthesis into organic carbon to be stored in biomass. Woody trees account for approximately 60% of the total aboveground tree biomass, and trunks, where food reserves produced in photosynthesis are stored, have relatively large biomass compared to other parts of the tree. The biomass of a vegetation stand determines the optimization of air pollutant absorption in urban areas. Yogyakarta City is the center for tourism, education, and cultural activities in Indonesia, which is vulnerable to land-use conversion, a factor of the shrinking green space. This study aimed to estimate carbon stock from vegetation biomass in Yogyakarta City using the remote sensing product SPOT-7 imagery. To calculate the vegetation biomass, the diameter at breast height (DBH) of stands was measured in the field. Then, statistical analyses were performed to determine the correlation and regression between the actual or observed biomass and the Normalized Difference Vegetation Index (NDVI) value derived from the SPOT-7 image. The regression model used was y = 1.4277x – 0.0849. The total biomass produced in Yogyakarta City was estimated at 1,399,487.1 tonnes, which contained 643,764.1 tonnes of carbon stock.
Use of Remote Sensing and Geographic Information System for the Analysis of Urban Development: A Case Study of Banyumas Regency, Indonesia Renita, Ermie; Hidayati, Iswari Nur
Indonesian Journal of Geography Vol 56, No 1 (2024): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.79086

Abstract

The change in land-use/land-cover (LULC) is one of the physical factors in urban development and the rapid growth in population has necessitates the need for space, driven by high socio-economic activities. Banyumas is a regency that had experienced rapid population growth in the last two decades, establishing an activity and service center in the Barlingmascakeb region. This rapid population growth has led to massive changes in LULC. Therefore, this study aimed to observe the changes in LULC in 2000 and 2020 to determine the direction of urban development in Banyumas Regency within 20 years. Multispectral classification with a Maximum Likelihood algorithm was used to extract LULC information from Landsat images. The changes obtained by crosstab analysis on the multispectral classification results were used as a reference to observe the direction of urban development. This procedure used four quadrants according to the cardinal directions and Standard Deviational Ellipse (SDE). The result showed that LULC in the forest class experienced the highest change of 142,584.3 km², accounting for 48%. Based on the increase in built-up land over 20 years, the direction of urban development according to the cardinal directions showed that the most dominant increase was in quadrant II (Southeast), which is 56.44% or 21.95 km². It was concluded that the direction of urban development was oriented toward the southeast.
Evaluation of Settlement Distribution on Detailed Spatial Plan in Sewon District, Bantul Regency, Special Region of Yogyakarta 2018 – 2038 Magiswari, Vabbereina Jasmineputeri; Hidayati, Iswari Nur
Indonesian Journal of Geography Vol 56, No 2 (2024): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.79171

Abstract

Settlement as a place to live is one of the main needs that need to be met for the survival of human life. The need for settlement will increase along with the increase in population. The development of settlements in Sewon District. Bantul, Indonesia which is very dynamic requires monitoring to ensure that the distribution of settlements is in accordance with the spatial pattern plan that has been determined by the local government. Imagery as a remote sensing product which is then processed with the help of GIS [HV1] can be used in monitoring the distribution of settlements because it can provide more detailed information regarding land use, including settlements. This research aims to evaluate the distribution of settlements against the detailed spatial plan (RDTR) for the Sewon Urban Area (BWP) of Bantul Regency in 2018-2038. This study uses visual interpretation techniques of SPOT-7 PMS imagery in mapping existing settlement land, field surveys, and GIS processing. The research results show that mapping settlement land using imagery produces an overall accuracy of 95.20%. The settlement evaluation shows that there is a suitability of settlement land with the detailed spatial plan reaching 579.88 hectares or 87.26%, while the settlement land that is not in accordance with the detailed spatial plan is 9.62 hectares or 1.45%, and the settlement land that is temporarily not in accordance with the detailed spatial plan is 75.05 hectares or 11.29% of the total settlement area in Sewon District. Local governments must pay more attention to existing settlements with regular monitoring so that the existing settlements that are not in accordance with the detailed spatial plan will not expand. 
Interpreting Built-Up Areas on Sentinel-2 Imagery and Recognizing Slums in Semarang City Fathilda, Intan Khaeruli; Hidayati, Iswari Nur; Widayani, Prima
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2022: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.2963

Abstract

This research examines the interpretation of built-up areas on Sentinel-2 imagery using interpretation keys and recognizes the appearance of slums from remote sensing data. The use of interpretation keys in visual interpretation is the first step for interpreters to recognize objects in the image. The research objectives were: 1) to interpret built-up areas; 2) to recognize slum conditions based on visual interpretation of sentinel-2 imagery and; 3) to determine the affordability of remote sensing data for slum parameters. The method used is a visual interpretation that is carried out in stages on the classification of built-up areas and settlements. The introduction of slum conditions is done by object interpretation in slum delineation. The result of this study is the mapping of built-up areas in Semarang City from the visual interpretation method obtained an accuracy of 87.5%. The effective use of interpretation keys at the land cover interpretation level are shape, pattern, size, and color. The condition of slums with remote sensing is visually depicted on the key interpretation of shape and pattern. The affordability of remote sensing data for slum parameters has limitations. The ability to extract remotely sensed data for slum parameters can help narrow down field studies in assessing slum parameters.
Co-Authors Achmad Fadhilah Alke Caroline Helena Maru Andita, Aning Arlindita, Yazinka Puri Emilya Nurjani Eni Susanti Eni Susanti Fathilda, Intan Khaeruli Gian Felix Ramadhan Herdiansyah Herdiansyah Magiswari, Vabbereina Jasmineputeri Prima Widayani Projo Danoedoro Projo Danoedoro Projo Danoedoro Projo Danoedoro R Suharyadi R. Suharyadi Rahmatika, Iklila Renita, Ermie Suharyadi, R Suharyadi, R Westi Utami Wuri Handayani