Evaluation of Satellite Image Correction Methods Caused by Differential Terrain Illumination

The problem due to differential terrain illumination on satellite imagery is experienced by most of areas which are on mountainous terrain. This may cause variations in reflectance of similar ground features which lead to a misclassification of land cover classes due to different topographic positions. This phenomenon most commonly occurred in the areas which are located on southern and northern hemisphere because of the low sun inclination. This problem has been a major interest for researchers to be solved prior to the land cover classification process. For satellite images which experience this kind of problem, topographic correction need to be applied in order to reduce the illumination effects prior to land cover classification process. This research is aimed at conducting topographic correction of multi spectral SPOT satellite data as well as evaluating the three topographic correction methods. They are Cosine which is based on Lambertian reflectance assumption, as well as Minnaert correction and C correction methods which are based on non-Lambertian reflectance assumption. The data used in this study are two scenes of SPOT images of forested mountainous area of Miyazaki Prefecture, Kyushu, Japan. Research steps had been conducted in this study including geometric correction, sample data collection for calculating Minnaert constants and C constants at location which represents the whole study area, topographic correction for two scenes SPOT images, and results analysis. The results show that Cosine method did not show good performance for the study area which is topographically dominated by rugged terrain. Whereas Minnaert method and C method gave satisfactory results as is indicated by the statistical data as well as visual interpretation. However the Minnaert correction method showed slightly better performance than the C correction method

Spatial Autocorrelation Analysis of Tuberculosis Cases (2016-2018) In Kebumen

Tuberculosis (TB) is one of the tenth highest causes of death in Indonesia and even worldwide. Tuberculosis is an infectious disease caused by an infection of Mycobacterium tuberculosis bacterium. Kebumen is one of the districts with high tuberculosis cases and tends to increase every year. Based on the high case number, it is necessary to start research that examines patterns of spread. Spatial analysis is a very useful tool to evaluate the spreading pattern of the tuberculosis disease according to its geographical location. The study aimed to spatially analyze tuberculosis spread pattern from 2016 to 2018 using the spatial autocorrelation method through Moran Index and Local Indicator of Spatial Association (LISA). The study showed that the spatial autocorrelation in the spreading patterns of tuberculosis occurred in Kebumen and had a clustered pattern because of Moran Index is positive. The results of the LISA analysis in the High-High quadrant showed that the high tuberculosis cases correlated with areas that also had high tuberculosis cases. Sixteen villages were included in the High-High quadrant

Influence of Spatial Abilities on Spatial Data Quality in Participatory Mapping

Participatory mapping (PM) method has become an alternative in spatial data collection activities for various mapping activities, including updating data on Rural & Urban Land and Building Tax (PBB-P2). From several experiences in PM application, various quality results have been found. Differences in the levels of spatial abilities of PM actors are assumed to affect the quality levels of PM results. Therefore, this study aimed to determine the effects of spatial abilities on the quality of spatial data generated in PM activities. It consisted of several stages of preparing instruments for measuring spatial abilities, collecting spatial data through PM, and correlation analysis. The instrument used to measure the levels of spatial abilities of 28 subvillage chiefs was the Purdue Spatial Visualization Test. The quality of PBB-P2 spatial data in 28 subvillages was randomly selected and assessed in terms of position, area, and geometric accuracies with reference to the land registration map from National Land Agency. Results indicated a positive correlation between the visual spatial ability and the spatial data quality of the PM results with a value of r = 0.823. Our findings are expected to be used as references for parties who carry out PM activities to be able to plan such activities

ANALISIS SPASIAL PENGGUNAAN LAHAN DAN KESESUAIAN TERHADAP RENCANA TATA RUANG WILAYAH DI KECAMATAN KEJAJAR, KABUPATEN WONOSOBO: (Spatial Analysis of Landuse Change and Its Conformity to the Regional Spatial Plan of Kejajar Sub District, Wonosobo Regency)

Pertumbuhan penduduk yang tinggi di Indonesia berakibat pada kebutuhan ruang yang memicu terjadinya perubahan lahan untuk memenuhi kebutuhan lahan untuk berbagai macam peruntukan. Hal ini juga terjadi di Kabupaten Wonosobo, khususnya Kecamatan Kejajar, dimana perubahan penggunaan lahan diindikasikan terjadi untuk memenuhi kebutuhan lahan untuk perkebunan sayur. Perubahan lahan yang terjadi diindikasikan menyebabkan ketidaksesuaian penggunaan lahan terhadap Rencana Tata Ruang Wilayah (RTRW). Kesesuaian penggunaan lahan wilayah Kabupaten Wonosobo mengacu pada Peraturan Daerah Kabupaten Wonosobo No. 2 Tahun 2011 tentang Rencana Tata Ruang Wilayah (RTRW) Kabupaten Wonosobo Tahun 2011-2031. Penelitian ini bertujuan untuk menganalisis perubahan penggunaan lahan tahun 2015 dan 2018 dan kesesuaian penggunaan lahan tahun 2018 terhadap RTRW di wilayah Kecamatan Kejajar, Kabupaten Wonosobo. Klasifikasi penggunaan lahan dilakukan menggunakan pendekatan interpretasi visualpada data citra satelit SPOT-7 tahun 2015 dan SPOT-6 tahun 2018. Analisis spasial temporal berbasis SIG dilakukan untuk mengidentifikasi perubahan penggunaan lahan tahun 2015 dan 2018. Sedangkan spatial overlay analysis dilakukan untuk mengevaluasi kesesuaian penggunaan lahan tahun 2018 terhadap RTRW. Berdasarkan analisis perubahan penggunaan lahan secara keseluruhan, luas perubahan penggunaan lahan adalah 241,413 ha dengan persentase sebesar 3,27%. Setiap desa memiliki perubahan penggunaan lahan yang bervariasi dan tidak terlalu signifikan. Berdasarkan analisis kesesuaian penggunaan lahan tahun 2018 terhadap Rencana Tata Ruang Wilayah (RTRW), lahan yang sesuai adalah 6.830,050 ha, dengan persentase kesesuaian sebesar 92,56%. Sedangkan penggunaan lahan seluas 549,007 ha tidak sesuai dengan RTRW, dengan persentase ketidaksesuaian sebesar 7,44%

Spatial Analysis of Kulon Progo District Development from 2007-2030 with Cellular Automata Markov Model

The construction of a new airport in Kulon Progo District as an embodiment of improving transportation infrastructure will have an effect on changes in spatial planning and land use. These changes can cause several impacts, so planning is needed as a preventive measure. Forms of planning are very diverse, ranging from the simplest to very complex. One of the alternatives is to make a simulation through a model approach with the Cellular Automata (CA) method, while the pattern of the direction of physical development of residential areas with the Global Moran’s Index. The research location focuses on three sub-districts in Kulon Progo District, which are the closest sub-districts to the airport construction sites, namely Kokap, Temon, and Wates Sub-districts. The main data used in this research are multi-temporal land use data, namely in 2007, 2012, and 2017. The data from the years of 2007 and 2012 are projected to become in the year 2017 and compared with the original data of 2017 to determine the level of suitability, resulting suitability of 91.53%. The final results of this research show predictions of the development of Kulon Progo District in 2030. In the span of 23 years, from 2007 to 2030, the allocation of residential land increased by 7.98% leaning west and south side. Results from the Global Moran’s Index show that the pattern of development in the Kulon Progo Regency area is random

Perancangan dan Evaluasi Aplikasi Peringatan Rawan Kecelakaan Lalu Lintas berbasis Android

Data kecelakaan dan pelanggaran lalu lintas di Daerah Istimewa Yogyakarta tahun 2016 sampai dengan tahun 2019 yang diperoleh dari Aplikasi Bappeda Dataku, menunjukkan trend yang meningkat setiap tahunnya. Untuk menekan angka kecelakaan lalu lintas, diperlukan upaya peningkatan keselamatan lalu lintas. Penelitian ini mencoba merancang sebuah aplikasi berbasis Android yang dapat dimanfaatkan oleh para pengendara lalu lintas. Aplikasi ini dirancang untuk memberikan peringatan kepada pengendara saat melintasi jalan yang memiliki riwayat kecelakaan tinggi agar pengendara dapat lebih berhati-hati. Data yang digunakan adalah data riwayat kecelakaan tahun 2019 dan 2020 yang meliputi jumlah kecelakaan dan lokasi kecelakaan khususnya di Daerah Istimewa Yogyakarta. Pengolahan data dilakukan untuk menentukan titik yang akan dijadikan sebagai titik rawan kecelakaan. Kriteria daerah rawan kecelakaan adalah jika suatu lokasi memiliki data kejadian kecelakaan lebih dari sepuluh kali dalam kurun waktu dua tahun. Perancangan sistem dilakukan melalui beberapa tahapan meliputi pengumpulan data dan lokasi kecelakaan, desai aplikasi baik sisi server dan client, perancangan user interface, serta pengujian hasil rancangan. Pengujian hasil rancangan meliputi uji fungsionalitas serta uji usabilitas. Hasil dari penelitian ini adalah sebuah aplikasi yang dapat memberikan informasi daerah rawan kecelakaan di Daerah Istimewa Yogyakarta. Sistem dapat memberikan peringatan dini jika pengguna mendekati area tersebut. Hasil evaluasi menunjukkan bahwa aplikasi dapat berjalan dengan baik sesuai fungsinya

DESAIN SISTEM INFORMASI BENCANA KOTA SEMARANG UNTUK PENGELOLAAN DATA BENCANA

Kota Semarang memiliki kondisi topografi yang bervariasi seperti dataran rendah, dataran tinggi, daerah perbukitan dan garis pantai yang dapat berpotensi terhadap berbagai bencana alam yang menimbulkan kerugian. Bencana yang sering terjadi di Kota Semarang, yaitu bencana banjir rob, tanah longsor, banjir, dan kekeringan perlunya sistem informasi bencana untuk mengelola data bencana dengan baik di dalam basisdata. Sistem informasi yang terintegrasi menyajikan peta bencanaterdiri dari bencanabanjir rob, tanah longsor, banjir, kekeringan, dan multi bencana yang berbasis website, sehingga masyarakat bisa mengakses informasi kebencanaan dengan mudah. Data yang digunakan berupa data spasial ancaman bencana, bangunan rumah yang terkena dampak bencana pada kelas bencana tinggi dan batas administrasi Kota Semarang. Metodologi penelitian yang digunakan berorientasi objek untuk tahapan analisis dan desain menggunakan diagram Unified Modeling Language (UML). Rancangan sistem dibangun menggunakan aplikasi tidak berbayar, yaitu QGIS sebagai aplikasi pengolah data spasial, MySQL sebagai aplikasi basisdata, dan bahasa pemrograman PHP. Visualisasi data spasial dilakukan di atas bidang peta onlineOpenStreetMap.Hasil dari penelitian ini adalah desain sistem informasi bencana kota Semarang yang dinamakan SINAN, yaitu sebuah Sistem Informasi Ancaman Bencana untuk mengelola dan menyajikan data ancaman bencana di Kota Semarang. Desain sistem informasi ini akan dikembangkan menjadi Sistem informasi bencana yang bertujuan untuk mempermudah masyarakat dan stakeholder dalam mendapatkan informasi bencana dengan teknologi berbasis geospatial.

Modernisation of DC-DC converter topologies for solar energy harvesting applications: A review

Solar photovoltaic (PV) power generation has become increasingly important as a renewable source of energy due to the many benefits it offers. These benefits include the ease with which it can be allocated; the absence of noise; the longer life; the absence of pollution; the shorter amount of time required for installation; the high mobility and portability of its parts; and the capability of its output power to meet peak load requirements. DC-DC converters are typically incorporated into solar energy harvesting systems because they allow for the more efficient exploitation of solar cells. One of the difficulties is in the selection of a suitable converter since this has an effect on the operation of the PV system. This study discusses the modernisation of several different DC-DC converter topologies for solar energy harvesting systems. Some of these topologies are boost, buck-boost, single-ended primary-inductance converter (SEPIC), Cuk, and flyback. The topologies have been compared so that detailed information on the complexity of the hardware, the cost of implementation, the efficiency of the energy transfer elements, the tracking efficiency, and the efficiency of the converters can be provided. This paper will be useful as a handy reference in choosing the best converter topology for solar energy harvesting applications