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All Journal Indonesian Journal of Geography POSITRON Edumaspul: Jurnal Pendidikan Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Geoid - Journal of Geodesy and Geomatics
Sanjaya, Hartanto
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Other

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Monitoring the Urban Heat Island Phenomenon in Pontianak City, West Kalimantan, using Google Earth Engine Sari, Kartika; Sanjaya, Hartanto; Muhardi, Muhardi
POSITRON Vol 14, No 2 (2024): Vol. 14 No. 2 Edition
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Univetsitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/positron.v14i2.71475

Abstract

The urban heat island (UHI) phenomenon can cause the land surface temperature (LST) in the city center to be higher than in the surrounding area. The population of Pontianak City increases yearly, resulting in land cover changes and LST distribution. This research aims to monitor the UHI phenomenon by identifying the temporal distribution of LST in Pontianak City. This research analyses the Landsat 8 thermal band, which is converted into LST value based on the normalised difference vegetation index (NDVI). The land cover classification was conducted using a random forest algorithm and acquisition of confusion matrix classification accuracy value. This research utilizes the Google Earth Engine (GEE) platform because of its ability to process satellite data continuously and has data with a sizeable spatiotemporal dimension. The results show a strong relationship between urban development and LST distribution. Based on the land cover classification in 2014 and 2019, there is a significant change in the composition of the surface, namely, built-up land has increased, while open space and vegetation land have decreased. Time series analysis also shows that the average LST of built-up land, open space, and vegetation are 28.10℃, 22.80℃, and 21.56℃, respectively. The results of monitoring the UHI phenomenon can help in better urban spatial planning, especially in increasing green space, because it is proven effective in reducing land surface temperature.
Estimation of Nitrogen Content of Rice Crops Using Sentinel-2 Data Agustina, Heni; Jaelani, Lalu Muhamad; Sanjaya, Hartanto
Indonesian Journal of Geography Vol 56, No 3 (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.88571

Abstract

Nitrogen (N) is one of the most essential nutrients for rice crops. Farmers generally provide Nitrogen requirements in rice through fertilization, but the fertilization process is only based on an estimation without calculating the amount needed first. However, neither insufficient nor excessive nitrogen content is good for rice crops, and the nitrogen needs of rice crops are different at each growth stage. The nitrogen requirement in the generative phase is relatively high because the process of panicle formation and grain filling occurs at this stage. Several methods can be used to monitor nitrogen content in rice, one of which is using remote sensing methods. With the vegetation index approach, the nitrogen content of rice plants is estimated through data analysis of the light spectrum reflected by the leaf. Sentinel-2 satellite imagery was used in this research, and several vegetation indexes such as OSAVI, GNDVI, and SRRE were applied to form an estimation model using the regression method. From the results, three vegetation indexes positively correlate with nitrogen content in rice crops. The SRRE index gives the highest correlation coefficient value of 0.692, while the correlation coefficient value for GNDVI is 0.498, and OSAVI is only 0.470. The estimation map of the nitrogen content of rice crops was obtained based on the estimation model made by linear regression between SPAD-based nitrogen content data and the best vegetation index using the SRRE index. The analysis shows that the nitrogen content of rice plants estimated in the paddy fields of Karangjati Subdistrict is dominated by nitrogen values with optimum classification.
Estimation of Total Carbon Stock and Mangrove Health Index in Sidoarjo using Machine Learning Spectral Analysis Method of Sentinel-2A Satellite Imagery Alina, Aldea Noor; Yahya, Fahrul; Safitri, Dika Ayu; Sanjaya, Hartanto; Rahmawaty, Mitha Asyita
GEOID Vol. 20 No. 1 (2025)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v20i1.2553

Abstract

The mangrove ecosystem has the potential ability to absorb carbon dioxide better than other forest ecosystems. It is noted that mangrove forests have an important role in reducing the concentration of carbon dioxide in the air. Changes in land cover conditions, massive development of urban areas, and the large need for housing in the Sidoarjo are the main causes of the decline in the area of mangrove forests which have been converted into fish ponds and residential areas. This triggers a decline in the quality of mangroves and will directly impact on reducing the capacity to store carbon reserves in Sidoarjo Regency. Biomass estimation calculations were carried out using the NDVI algorithm from remote sensing results using Sentinel Imagery – 2A. Apart from that, the mangrove health index was also calculated using the GCI (Green Chlorophyll Index), SIPI (Structure Insensitive Pigment Index), NBR (Normalized Burn Ratio), and ARVI (Atmospherically Resistant Vegetation Index). Based on the calculation results, the value obtained for the coastal area of Sidoarjo Regency the TCS or total carbon stock ranged from 1.1679468503445e-09 to 84.3344 TonC/hectares. Meanwhile, the results of the mangrove health index calculation show that the condition of mangroves in the coastal area of Sidoarjo Regency has a sufficient mangrove health index, with the highest area being 637.77 hectares, while only 10.80 hectares are available has a good health index. The results of this study are expected to be one of the bases for decision-making and policies in the rehabilitation and conservation of mangrove in Sidoarjo.
Analysis of Mangrove Species Detection Performance on Multiresolution Satellite Imagery Using Linear Spectral Unmixing Fultriasantri, Indah; Alina, Aldea Noor; Jaelani, Lalu Muhamad; Sanjaya, Hartanto; Abdul Rasam, Abdul Rauf
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 19 No. 1 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v19i1.6548

Abstract

The Pamurbaya mangrove conservation area in East Surabaya is crucial for coastal protection, but it is vulnerable to degradation due to human activities and land-use changes. Species distribution maps are essential for understanding ecological functions, such as carbon sequestration, salinity tolerance, and ecosystem stability. This study utilizes multiresolution remote sensing data from WorldView-2 satellite imagery to map mangrove and detailed species-level. Random Forest is utilized to differentiate mangrove and non-mangrove, while Linear Spectral Unmixing allows for detailed mangrove species distribution. Further analysis was carried out to determine at what resolution the LSU works optimally. The imagery was served in 0.5 meter resolution and down-sampled to 5 meter, 10, 20, 30, and 50 meter resolutions. This study obtained that LSU were able to differentiate mangroves according to its endmember and working optimally at medium resolution (10–30 m), with overall accuracy increasing from 70% (10 m) to 75% (30 m) and Kappa value increasing from 53.7 to 60.41. High resolution (0.5–10 m) provides more detailed mapping but is optimal for species with small and scattered distributions. Meanwhile, low resolution (20–50 m) tends to cause overestimation or aggregation of species.
Mangrove Land Mapping and the Potential for Bivalve Diversity with Remote Sensing in the Pulau Dua Nature Reserve (As an Initial Study for the Development of Class X High School Ecosystem Biology Subconcept Learning Devices) Utari, Enggar; Sanjaya, Hartanto; Mahrawi, Mahrawi; Wahyuni, Indria; Marianingsih, Pipit; Nurlaita, Ita
Edumaspul: Jurnal Pendidikan Vol 7 No 2 (2023): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33487/edumaspul.v7i2.6639

Abstract

Bivalvia is an invertebrate animal that has a high level of diversity and a marine biological resource that has significant economic value. This research was conducted in November 2021, aiming to determine bivalve diversity, mapping of manrove land and the potential for bivalve diversity, the relationship between the results of analysis of the presence of water on bivalves diversity in the Pulau Dua Nature Reserve and the implications of research results in the field of education. The method used is the roaming method to determine bivalves diversity and remote sensing methods to map areas of potential bivalve diversity in Pulau Dua Nature Reserve. The results of observations found that the diversity of bivalves in Pulau Dua Nature Reserve was included in the medium diversity category with a value of 1.085. The results of the relationship between bivalve diversity and MNDWI are classified as having a strong relationship, namely the correlation coefficient (r) is 0.668. In the Pulau Dua Nature Reserve, it was found that areas with a high potential for bivalve diversity were found at coordinates 106.198956 6.018374. The results of this research were then carried out to analyze the material at KD 3.10 and KD 4.10 for class X SMA at school.
Co-Authors Abdul Rasam, Abdul Rauf Alina, Aldea Noor Fachry Abda El Rahman Fultriasantri, Indah Heni Agustina Jaelani, Lalu Muhamad Jayawarsa, A.A. Ketut Mahrawi, Mahrawi Muhardi Nurlaita, Ita Pipit Marianingsih Rahmawaty, Mitha Asyita Safitri, Dika Ayu Utari, Enggar Yahya, Fahrul