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Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information Sari, Nurwita Mustika; Kushardono, Dony
Forum Geografi Vol 29, No 1 (2015): Forum Geografi
Publisher : Forum Geografi

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The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale Â remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this Â study, proposed a novel method to Â execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.

The Relationship between the Mixed Pixel Spectral Value of Landsat 8 OLI Data and LAPAN Surveillance Aircraft (LSA) Aerial-Photo Data Sari, Nurwita Mustika; Chulafak, Galdita Aruba; Zylshal, Zylshal; Kushardono, Dony
Forum Geografi Vol 31, No 1 (2017): July 2017
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v31i1.3500

Medium resolution satellite data such as Landsat is very potential for mixed pixel (mixel) to occur. Indonesian land use diverse especially urban areas makes high potential mixel in the first Landsat pixel size of 30 meters x 30 meters on the actual condition. Aircraft multispectral aerial photo data LAPAN Surveillance Aircraft (LSA) with a spatial resolution reached 58 cm can display objects in more detail in these sizes. The purpose of this research is to study mixel on Landsat data with multispectral data LSA as a complement Landsat data. The method proposed in this study is a visual interpretation with GEOBIA method for classification of land cover, and then test the validity of the sample to be used in research, and the use of such vegetation index NDVI to see the connection between vegetation index data of vegetation index LSA with Landsat data. The results showed that the regression equation obtained by regression between NDVI of Landsat data and NDVI of Â LSA with a significance of less than 0.05 is y = 0.732x - 0102 with a value of R2 = 0.887. Through these results we can conclude that the NDVI values on both the data related to one another.

Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information Sari, Nurwita Mustika; Kushardono, Dony
Forum Geografi Vol 29, No 1 (2015): July 2015
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v29i1.792

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale Â remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this Â study, proposed a novel method to Â execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.

GIS APPLICATION FOR EVALUATION OF TRADE AND SERVICES AREA DEVELOPMENT IN SERANG CITY, BANTEN PROVINCE Aji, Adam Hastara; Rachmita, Nurina; Sari, Nurwita Mustika; Kushardian, Benedictus
Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments) Vol. 5, No. 2
Publisher : UI Scholars Hub

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Trade and service area is an area that facilitates trade transactions and services between people in need (demand side) and people who sell services (supply-side). In determining trade areas and services, SMCE or Spatial Multi-Criteria Evaluation or spatial evaluation techniques consider many different criteria when making decisions. The method used in this paper is SMCE with Weight Overlay technique using four variables, namely roads, slopes, settlements and rivers. Weighting carried out in the analysis was made with various simulations, namely Simulation A with the same weight weighting on each variable 25%, simulation B with dominant weighting on one of the variables with a composition of 55%:15%:15%:15% and simulation C gave the highest weight to the most influential variables and gave the lowest weight to the variables that were less influential for the Trade and Service Area. In this Simulation, the road network's weight is 30%, settlements are 25%, slopes are 25%, and the rivers are 20%. The total area of 23.5 Km2 or about 8.8% of Serang City area located in the city centre with excellent accessibility, not far from residential areas, a safe distance from the river, and an area with flat marbles.

UTILIZATION OF SPOT 6/7 AND LANDSAT TO ANALYZE OPEN GREEN SPACE AND BUILT AREA IN SURABAYA CITY Ardha, Mohammad; Sari, Nurwita Mustika; Mukhoriyah, Mukhoriyah
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 21, No 1 (2024)
Publisher : Ikatan Geografi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2024.v21.a3904

The migration of people from rural to urban areas is a common phenomenon nowadays. One of the goals of urbanization is in the city of Surabaya. The increase in population causes the need for housing and the need for life to increase. One of the many changes in land use is the change of land into built-up land. The increase in the area of built-up land currently raises a new phenomenon where the area of open space is reduced due to changes in land use, one of the changes in land use is from green open space to built-up land. This study aims to see the extent to which the growth trend of green open space and built-up land in the city of Surabaya by using the NDVI method to see the trend of changes in green open space in the city of Surabaya and NDBI for the land built in the city of Surabaya. The data used in this study are SPOT 7 images for green open space and Landsat 8 for built land. Based on this method, green open space in the city of Surabaya in 2015 was 29.19%, in 2016 it was 21.22%, then in 2017 it was 24.54 %, and in 2018 it was 27.60%. While for Built land in 2015, it was 26.43%, in 2016 it was 26.44%, in 2017 it was 30.99% and in 2018 it was 42.88%. Other results were also obtained for the change of green open space into the land. awakened has increased every year, namely from 2015 to 2016 by 2.67%, from 2016 to 2017 by 4.43%, and from 2017 to 2018 by 8.08%. As for the land built into green open space, namely 2015 to 2016 of 2.01%, 2016 to 2017 of 2.84%, 2017 to 2018 of 2.72%. The conclusion from this activity is that NDVI can be used to see the level of vegetation density which can indicate the existence of green open space in urban areas. And NDBI can show the existence of built-up land. The city of Surabaya, has stable green open space, while the built land continues to increase every year.

Analysis of urban environmental comfort using Landsat-8 multitemporal data and Artificial Neural Network Sari, Nurwita Mustika; Kushardono, Dony; Mukhoriyah, Mukhoriyah; Kustiyo, Kustiyo; Manessa, Masita Dwi Mandini
Journal of Degraded and Mining Lands Management Vol. 12 No. 3 (2025)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2025.123.7591

The presence of greenery in urban residential and office areas can improve the comfort of residents who live in these environments. In an urban setting, vegetation serves an ecological purpose by absorbing carbon dioxide, supplying oxygen, lowering the temperature to produce a tolerable microclimate, acting as a water catchment area, and reducing noise. Urbanization and anthropogenic activity-driven growth of urban and sub-urban regions put stress on the local vegetation and have the potential to lower environmental comfort. To promote the creation of a sustainable urban environment, a thorough analysis of the urban environment is required. Applications for remote sensing in all spectral, geographic, and temporal dimensions have increasingly adopted the usage of deep learning methods with artificial neural networks. This study attempted to predict the application of remote sensing data for analyzing environmental comfort in metropolitan areas based on multitemporal Landsat-8 data. The study area is Greater Jakarta. The approach was based on supervised classification with neural network techniques and land parameters like surface temperature, brightness index, greenness index, and wetness index. According to the study's findings, the proposed method could accurately predict that very uncomfortable classes predominated in Jakarta, Bogor, Depok, Tangerang, Bekasi, and surrounding areas by more than 92%. In addition to being densely populated with communities, urban environments are uncomfortable due to a lack of vegetation cover, which increases surface temperatures. In the future, this research can provide input for similar research, especially in the use of deep learning Artificial Neural Network methods for environmental analysis.

KLASIFIKASI PENUTUP LAHAN BERBASIS OBJEK PADA DATA FOTO UAV UNTUK MENDUKUNG PENYEDIAAN INFORMASI PENGINDERAAN JAUH SKALA RINCI Sari, Nurwita Mustika; Kushardono, Dony
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 11 No. 2 (2014)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v11i2.3304

The need of spatial information from detailed-scale remote sensing is increasing. Unmanned Aerial Vehicle or UAV become one of vehicles that is expected to obtain such information. Production of land cover spatial information using UAV photo data requires appropriate method for classification. This study proposes an object-based classification method for land cover based on Haralick texture information namely homogeneity, contrast, dissimilarity, entropy, angular second moment, mean, standard deviation, and correlation. As a comparison method, a conventional land cover-object-based classification is implemented using the same information features, there are brightness, compactness, and density. The result shows that method using texture feature in object-based classification has reached 95.22% accuracy or 17.5% difference that is much better than conventional method that reaches 77.71%.

DETEKSI GEJALA ERUPSI STROMBOLIAN GUNUNGAPI RAUNG JAWA TIMUR MENGGUNAKAN NORMALIZED THERMAL INDEX DARI DATA MODIS Suwarsono, Suwarsono; Hidayat, Hidayat; Suprapto, Totok; Yulianto, Fajar; Sari, Nurwita Mustika; Parwati, Parwati; Asriningrum, Wikanti
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 2 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i2.3315

Geologically, most of Indonesia is located on subduction zone of the Pacific ring of fire that causes many emerging active volcanoes. The existence of active volcanoes has an implications that the volcanic eruption could occur at any time. This study aims to detect the precursors of volcanic eruption by using parameters NTI (Normalized Thermal Index) derived from MODIS data. Volcanic object selected is Raung Volcano in East Java, where around June to July 2015 showed an increase in volcanic activity and was erupted. Data processing method includes processing of Landsat-8 for the determination of the area of interest (caldera and active crater), MODIS image processing for NTI measurement, and analysis of spatial and temporal patterns of NTI. The results showed that the precursors of a volcanic eruption can be detected from the increasing of the NTI value in the kaldera and its value which relatively higher than in the surrounding area. NTI parameters have proven to have a good ability to distinguish between the kaldera and other objects during eruption period. In case of Raung Volcano, NTI value = 0.06 can be applied as a threshold value for the eruption of this volcano.

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