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All Journal Indonesian Journal of Geography TELKOMNIKA (Telecommunication Computing Electronics and Control) Geoplanning : Journal of Geomatics and Planning
Rokhmatuloh Rokhmatuloh
Department Of Geography, Faculty Of Mathematics And Natural Science, Indonesia University
Computer Science & IT Earth & Planetary Sciences

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Roof materials identification based on pleiades spectral responses using supervised classification Ayom Widipaminto; Yohanes Fridolin Hestrio; Yuvita Dian Safitri; Donna Monica; Dedi Irawadi; Rokhmatuloh Rokhmatuloh; Djoko Triyono; Erna Sri Adiningsih
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 2: April 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i2.18155

Abstract

The current urban environment is very dynamic and always changes both physically and socio-economically very quickly. Monitoring urban areas is one of the most relevant issues related to evaluating human impacts on environmental change. Nowadays remote sensing technology is increasingly being used in a variety of applications including mapping and modeling of urban areas. The purpose of this paper is to classify the Pleiades data for the identification of roof materials. This classification is based on data from satellite image spectroscopy results with very high resolution. Spectroscopy is a technique for obtaining spectrum or wavelengths at each position from various spatial data so that images can be recognized based on their respective spectral wavelengths. The outcome of this study is that high-resolution remote sensing data can be used to identify roof material and can map further in the context of monitoring urban areas. The overall value of accuracy and Kappa Coefficient on the method that we use is equal to 92.92% and 0.9069.
Percent of building density (PBD) of urban environment: a multi-index approach based study in DKI Jakarta Province Ardiansyah Ardiansyah; Revi Hernina; Weling Suseno; Faris Zulkarnain; Ramadhani Yanidar; Rokhmatuloh Rokhmatuloh
Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3151.982 KB) | DOI: 10.22146/ijg.36113

Abstract

This study developed a model to identify the percent of building density (PBD) of DKI Jakarta Province in each pixel of Landsat 8 imageries through a multi-index approach. DKI Jakarta province was selected as the location of the study because of its urban environment characteristics.  The model was constructed using several predictor variables i.e.  Normalized Difference Built-up Index (NDBI), Soil-adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI), and surface temperature from thermal infrared sensor (TIRS). The calculation of training sample data was generated from high-resolution imagery and was correlated to the predictor variables using multiple linear regression (MLR) analysis. The R values of predictor variables are significantly correlated. The result of MLR analysis shows that the predictor variables simultaneously have correlation and similar pattern to the PBD based on high-resolution imageries. The Adjusted R Square value is 0,734, indicates that all four variables influences predicting the PBD by 73%.
A Preliminary Study of the Physico-Chemical Parameters and Potential Pollutant Sources in Urban Lake Rawa Besar, Depok, Indonesia Mangapul Parlindungan Tambunan; Kuswantoro Marko; Ratna Saraswati; Rokhmatuloh Rokhmatuloh; Revi Hernina
Indonesian Journal of Geography Vol 53, No 2 (2021): 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.60420

Abstract

Lake Rawa Besar is an urban lake surrounded by dense settlements and commercial areas that are currently experiencing physical and ecological pressures due to uncontrolled land-use change around the lake. Therefore, this preliminary study aimed to investigate the sustainable management of the lake in order to create a recreational destination area. It was carried out by ascertaining the lake water quality status through the analysis of the physical and chemical parameters and identifying the potential pollutant sources due to land use and human activities. The physical parameters include TDS, TSS, Turbidity, while the chemical parameters include Nitrate-N, Total Phosphate-P, and BOD. Furthermore, field surveys on 30 water samples were conducted once at noon and statistical analysis was used to ascertain the correlation between the physical and chemical parameters. Finally, Geographic Information System (GIS) tools were used to investigate the spatial distribution of the Physico-chemical parameters and the potential pollutant sources. The results showed that based on the six parameters of the water quality status, the lake was lightly polluted. It also showed that three parameters such as Turbidity, BOD, and TSS exceed the permissible limit with 93.3, 66.7, 43.7% of the total samples, respectively. Additionally, a strong correlation existed between BOD and Turbidity with r=0.95, while a medium correlation existed between Nitrate-N and Phosphate-P with r=0.40. The spatial distribution of the concentration of the physico-chemical parameters generally had a varied pattern,  however, Turbidity and BOD had a similar pattern, especially in the bank areas. Finally, domestic and organic wastes were indicated as pollutant sources, which increased eutrophication in the lake.
Monitoring Dynamics of Vegetation Cover with the Integration of OBIA and Random Forest Classifier Using Sentinel-2 Multitemporal Satellite Imagery Nurwita Mustika Sari; R. Rokhmatuloh; Masita Dwi Mandini Manessa
Geoplanning: Journal of Geomatics and Planning Vol 8, No 2 (2021)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.8.2.75-84

Abstract

The existence of vegetation in an area has an important role to maintain the carrying capacity of the environment and create a comfortable environment as a place to live. In an effort to create a sustainable environment, there are various pressures on vegetation that cause a decrease in vegetation area. Economic activity, population growth and other anthropogenic activities trigger the dynamics of vegetation cover in an area that causes land cover changes from vegetation to non-vegetation. Majalengka Regency as one of the areas with intensive regional physical development in line with the operation of BIJB Kertajati and the Cipali toll road became the study area in this research. This study aims to monitor the dynamics of vegetation cover with the proposed method namely the integration of the OBIA and Random Forest classifier using multi temporal Sentinel-2 satellite imagery. The results show that there is a decrease in the area of vegetation in the research area as much as 4,329.6 hectares to non-vegetation areas in the period 2016-2020. The vegetation area in 2020 is 84,716.07 hectares and non-vegetation area is 35,708 hectares. Thus, there has been a decrease in the percentage of vegetation area from 73.94% in 2016 to 70.35% in 2020, meanwhile for non-vegetation areas there has been an increase from 26.06% in 2016 to 29.65% in 2020.
The Spatial Model of Paddy Productivity Based on Environmental Vulnerability in Each Phase of Paddy Planting Rahmatia Susanti; S. Supriatna; R. Rokhmatuloh; Masita Dwi Mandini Manessa; Aris Poniman; Yoniar Hufan Ramadhani
Geoplanning: Journal of Geomatics and Planning Vol 8, No 2 (2021)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.8.2.127-136

Abstract

The national primary always growth and increase in line with the increase in population, such as the rise of rice consumption in Indonesia.  Paddy productivity influenced by the physical condition of the land and the declining of those factors can detected from the environmental vulnerability parameters. Purpose of this study was to compile a spatial model of paddy productivity based on environmental vulnerability in each planting phase using the remote sensing and GIS technology approaches. This spatial model is compiled based on the results of the application of two models, namely spatial model of paddy planting phase and paddy productivity. The spatial model of paddy planting phase obtained from the analysis of vegetation index from Sentinel-2A imagery using the random forest classification model. The variables for building the spatial model of the paddy planting phase are a combination of NDVI vegetation index, EVI, SAVI, NDWI, and time variables. The overall accuracy of the paddy planting phase model is 0.92 which divides the paddy planting phase into the initial phase of planting, vegetative phase, generative phase, and fallow phase. The paddy productivity model obtained from environmental vulnerability analysis with GIS using the linear regression method. The variables used are environmental vulnerability variables which consist of hazards from floods, droughts, landslides, and rainfall. Estimation of paddy productivity based on the influence of environmental vulnerability has the best accuracy done at the vegetative phase of 0.63 and the generative phase of 0.61 while in the initial phase of planting cannot be used because it has a weak relationship with an accuracy of 0.35.
Co-Authors Ardiansyah Ardiansyah Aris Poniman Ayom Widipaminto Dedi Irawadi Donna Monica Erna Sri Adiningsih Faris Zulkarnain Kuswantoro Marko Masita Dwi Mandini Manessa Nurwita Mustika Sari Rahmatia Susanti Ramadhani Yanidar Ratna Saraswati Revi Hernina S. Supriatna Tambunan, Mangapul Parlindungan Triyono, Djoko Weling Suseno Yohanes Fridolin Hestrio Yoniar Hufan Ramadhani Yuvita Dian Safitri