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"In Indonesia, there is now no operational sea surface temperature (SST) monitoring for such activities as oceanography, climatology or fishery. Indeed until 1986, LAPAN required NOAA data without atmospheric correction. It is even worse that local hardware constraints prevent any operational monitoring with mainframe computers. By analysing NOAA data with microcomputers, the methodology presented in this paper intends to fill this gap. It was tested with the study of large scale SST features in Indonesia from 1981-1985. This study stresses the possibility of an operational SST Monitoring in Indonesia, allowing simple data manipulation with a type of hardwarw equipment maintained locally and easily."

"As satellite oceanography matures, there is an increasing demand for quantitative satellite data. Numerous scientific users are concerned by the determination of Sea Surface Temperatures (SST), dynamical oceanography, deep water convection, and pollution. Numerous physical and technological factors prevent to achieve accurate satellite measurements of SST. The main contamination due to the atmosphere (water vapor) and can lead to errors up to 10 Kelvin. The variability of sea surface emissivity and the sensor noise lead also to errors. The use of radiometric correction permits to get SST maps with more or less good accuracy according to the type of processing. In Indonesia the reception of the GMS and NOAA data must be used for a systematic analysis of the accuracy of the remote sensed SST in order to get n automatic routine mapping of these SST."

"Pembangunan serta perkembangan kota di Indonesia terus berlangsung, menyebabkan peningkatan akan kebutuhan lahan terutama lahan untuk pemukiman. Peningkatan kebutuhan lahan menyebabkan perubahan tutupan lahan yang akan mempengaruhi suhu permukaan daratan di daerah tersebut, contohnya di Kota Malang Raya dimana suhu di perkotaan cenderung lebih tinggi dibandingkan daerah sekitarnya. Penelitian ini bertujuan untuk mengetahui pola spasial suhu permukaan daratan di Kota Malang Raya, kaitannya dengan ketinggian, tutupan lahan, kerapatan vegetasi dan kerapatan bangunan yang dilakukan dengan penginderaan jauh menggunakan Citra Landsat pada perekaman tahun 1996, 2001, 2013 dan 2016. Hasil penelitian menunjukan suhu permukaan daratan tertinggi berada di pusat Kota Malang dan Kota Batu sebagai pusat wilayah terbangun dengan kerapatan bangunan tinggi dan kerapatan vegetasi yang rendah. Suhu permukaan daratan tertinggi >27O C berada pada wilayah ketinggian.

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The construction and cities development in Indonesia still continues, that leads to increase land needs especially lands for living. The increased of landcover needs caused the lands changed which will affect the land surface 39 s temperature in the area, for example in the cities of Malang Raya that temperatures in urban areas tend to be higher than the surrounding area.

This research aims to know the spatial pattern of land surfaces temperature in the cities of Malang Raya, relation to land cover, vegetation density and built up density. Landsat Imagery do use on a recording in 1996, 2001, 2013 and 2016 as well as in relation to the difference in height in this region.

Research results showed the highest land surface temperature is in the centre of Malang and Batu city as the center of the build up area with high dencity of buildings low vegetation. The highest land surface temperature 27C is also located in the region of"

"The Indonesian spatiotemporal cloud cover distribution was quantified with the aid of GMS, Landsat and SPOT data. Iterative interactive factorial analyses grouped pixels with similar profiles into 18 classes for all land areas. For each class, statistics of Landsat and SPOT images, grouped by class, were used to verify, calibrate and improve class profiles. This led to quantified temporal profiles of probability of acquiring remotely sensed data with 10, 20, and 30 percent cloud cover, for any Indonesian land area."

"This is the next volume in series of Light Scattering Reviews. Volumes 1-5 have already been printed by Springer. The volume is composed of several papers ( usually, 10) of leading researchers in the respective field. The main focus of this book is light scattering, radiative transfer and optics of snow."

"Telah dikembangkan sistem pemantauan jarak jauh untuk stasiun monitoring kualitas udara. Sistem ini terdiri atas tiga komponen utama, sistem stasiun yang mempunyai fungsi sebagai akuisisi data untuk 7 buah sensor; sensor temperatur, kelembaban dan gas O2, O3, NO, CO and SO2, sistem master yang mempunyai fungsi sebagai pengumpul data dan pengendali stasiun dan server database yang mempunyai fungsi sebagai bank data kualitas udara. Perangkat lunak sistem pemantau jarak jauh dibuat berdasarkan standar SDI-12 untuk sensor berbasis mikroprosesor. Sistem pemantauan jarak jauh hasil rancangan telah diuji non stop selama 2 minggu dan menunjukkan hasi! yang baik tanpa dijumpai adanya error.

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Remote Monitoring Systems for Air Quality Stations. A remote monitoring system for air quality station has been design and developed. The system consist of three main units: stations, master, and server. Station collects and processes data from 7 sensors (temperature, humidity, and O2, Oj, NO, CO, and SO2 gas sensor), master system has a duty as data collector and station control and as air quality data bank is the server. Remote monitoring software was developed base on SDI-12 (A Serial-Digital Interface) standard for microprocessor-based sensor, The system has been tested and showed good results."

"Kebutuhan masyarakat terhadap pemahaman intensitas curah hujan serta distribusi secara spasial dan temporal penting terhadap kewaspadaan kebencanaan. Pengamatan curah hujan yang real-time yang disertai prakiraan dapat menjadi dasar yang kuat untuk membangun sistem peringatan dini, khususnya banjir bandang, di mana dapat diamati dari curah hujan yang sangat tinggi dengan rentang waktu pendek. Sistem pengamatan permukaan untuk unsur curah hujan secara otomatis sudah diterapkan di Indonesia menggunakan tipping bucket. Citra satelit Himawari 9 dapat memberikan gambaran curah hujan secara spasial. Informasi peringatan dini potensi membutuhkan sistem pengiriman dan penerimaan data yang andal menggunakan basis pengiriman data melalui internet dengan berbagai protokol MQTT. Tujuan penelitian ini adalah untuk merancang sistem akuisisi data monitoring curah hujan realtime dari penakar hujan otomatis serta merancang sisem peringatan dini cuaca dengan penimbang citra satelit dalam bentuk website. Penelitian ini mampu memonitor curah hujan secara realtime per sepuluh menit dengan ketersediaan data 94,45% dan dapat meningkat hingga 99,0% dan dapat memberikan peringatan dini dengan tingkat kepercayaan sangat tinggi sebesar 73,59% dan tingkat kepercayaan tinggi sebesar 20,77%. Terdapat peringatan dini dengan tingkat kepercayaan rendah sebesar 4,45% yang diakibatkan oleh hujan lokal dengan skala spasial kurang dari 5x5 km2. Peringatan dini yang dihasilkan ditampilkan dalam antarmuka website.

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The community's need to understand rainfall intensity and its spatial and temporal distribution is important for disaster awareness. Real-time rainfall observations accompanied by forecasts can be a strong basis for building an early warning system, especially for flash floods, where very high rainfall can be observed over a short time span. An automatic surface observation system for rainfall elements has been implemented in Indonesia using a tipping bucket. Himawari 9 satellite imagery can provide a spatial overview of rainfall. Potential early warning information requires a reliable data sending and receiving system using a data transmission base via the internet with various MQTT protocols. The aim of this research is to design a real-time rainfall monitoring data acquisition system from an automatic rain gauge and design a weather early warning system by weighing satellite images in the form of a website. This research is able to monitor rainfall in real time every ten minutes with data availability of 94.45% and can increase to 99.0% and can provide early warning with a very high level of confidence of 73.59% and a high level of confidence of 20.77% . There is an early warning with a low confidence level of 4.45% which is caused by local rain with a spatial scale of less than 5x5 km2. The resulting early warning is displayed in the website interface."

"The book focuses on the different aspects of sensing technology, i.e. high reliability, adaptability, recalibration, information processing, data fusion, validation and integration of novel and high performance sensors specifically aims to monitor agricultural and environmental parameters. "

"Pertambahan penduduk di daerah perkotaan merupakan salah satu alasan utamaterjadinya perubahan iklim lokal, dan berdampak besar pada daerah sekitarnya.Urbanisasi yang cepat dan daerah lahan terbuka yang digantikan oleh tutupan lahanbuatan yang berdampak negatif pada ekosistem yang mengakibatkan efek Urban HeatIsland (UHI). Hal tersebut berdampak merugikan pada lingkungan pemukiman danberimplikasi pada kesehatan manusia. Informasi indeks UHI yang akurat dapat sangatmembantu untuk mengambil strategi perencanaan kota yang efektif. Penelitian iniberkontribusi pada pengembangan sistem pemantauan suhu berbasis Internet of Thingsuntuk mendukung informasi indeks UHI. Sistem dirancang dengan menggunakan sensorsuhu DS18b20. Data dari sensor diolah oleh data logger dan dikirim ke servermenggunakan ESP8266. Sistem perancangan akan mengolah data dari sensor menjadiinformasi suhu perkotaan dan pedesaan serta indeks UHI. Selain itu, pendekatan LongShort Term Memory yang dihadirkan dalam penelitian ini diharapkan dapat bergunauntuk memprediksi indeks UHI dengan lebih akurat untuk mengantisipasi dampakpeningkatan indeks UHI. Hasil kalibrasi sensor suhu menunjukkan nilai koreksi pada setpoint 0 °C ,10 °C, 20 °C , 30 °C dan 40 °C sebesar 0,216 °C, 0,201 °C, -0,295 °C, -0,188°C dan -0,167 °C untuk sensor di daerah urban dan sensor yang dipasang di daerah ruralmemiliki nilai koreksi pada set point tersebut sebesar 0,116 °C, 0,267 °C, 0,165 °C, 0,294°C dan 0,211 °C . Hasil prediksi menunjukkan nilai MAE sebesar 0,55, RMSE sebesar0,78 dan akurasi sebesar 68,33%. Hasil penelitian ini menunjukkan sistem dapatdiimplementasikan sebagai alternatif untuk membantu dalam analisis UHI yang berbasisInternet of Things.Population growth in urban areas is one of the main reasons for local climate change, andhas a major impact on the surrounding area. Rapid urbanization and areas of open landreplaced by artificial land cover have a negative impact on the ecosystem resulting in theUrban Heat Island (UHI) effect. This has a detrimental impact on the residentialenvironment and has implications for human health. Accurate UHI index information canbe very helpful for adopting an effective urban planning strategy. This researchcontributes to the development of a temperature monitoring system based on the Internetof Things to support the UHI index information. The system is designed using theDS18b20 temperature sensor. The data from the sensor is processed by the data loggerand sent to the server using the ESP8266. The design system will process data fromsensors into urban and rural temperature information as well as the UHI index. Inaddition, the Long Short Term Memory approach presented in this study is expected tobe useful in predicting the UHI index more accurately to anticipate the impact ofincreasing the UHI index. The results of the temperature sensor calibration show acorrection value at set point 0 °C, 10 °C, 20 °C, 30 °C and 40 °C of 0.216 °C, 0.201 °C,-0.295 °C, -0.188 °C and -0.167 °C for sensors in urban areas and sensors installed inrural areas have correction values at the set point of 0.116 °C, 0.267 °C, 0.165 °C, 0.294°C and 0.211 °C . The prediction results show that the MAE value is 0.55, the RMSEvalue is 0.78 and the accuration is 68,33%. The results of this study indicate that thesystem can be implemented as an alternative to assist in the analysis of UHI based on theInternet of Things."