Cenderawasih Hot Pool: The Frequent High Sea Surface Temperature Phenomena At Cenderawasih Bay, Papua

The term “warm pool” refers to a body of water with the characteristic of SST exceeding 28°C within a particular area and a relatively long period in an annual circle. However, there are regions with an annual mean SST measured above 30°C, and we classified them as hot pools because of the conditions of intense solar radiation and low wind speed. One of the Hot Pool spots was found in Indonesia, in Cenderawasih Bay. The present study examines the existence of the Cenderawasih Hot Pool using long-term observation of satellite SST data. In order to learn more about their mechanisms, we also analyzed surface wind, surface heat flux, and surface current data. The results show that SSTs in Cenderawasih Bay have a 50% chance of exceeding 30°C within the 13 years of study (2013-2015). Heat input comes from strong solar radiation, i.e., 50% of solar radiation is more than 200 W/m2. The location is also dominated by low wind speed, i.e., 80% wind speed of lower than 4 m/s, which caused the low latent loss in Cenderawasih Bay. Cenderawasih Bay is fully separated from surface currents during the dry and wet seasons since the easterly subsurface water flow does not enter the bay. The absence of strong currents prevents the mixing process, maintaining the high temperature in the surface layer. Those processes are discovered and they serve as compelling evidence to support Cenderawasih Bay as one of the Hot Pool areas within the Indonesian seas.

Rapid estimation of CO2 emissions from forest fire events using cloud-based computation of google earth engine

One of the main sources of greenhouse gases is forest fire, with carbon dioxide as its main constituent. With increasing global surface temperatures, the probability of forest fire events also increases. A method that enables rapid quantification of emissions is even more necessary to estimate the environmental impact. This study introduces the application of the Google Earth Engine platform to monitor burned areas in forest fire events in Mount Arjuno, Indonesia, during the 2016-2019 period, using Landsat-8 and Sentinel-2 satellite imageries. The events particularly affected grassland and tropical forest areas, as well as a fraction of agricultural areas, with a total estimated emission of 2.5 × 10³ tCO₂/km² burned area. Higher carbon dioxide emissions were also observed, consistent with the higher local surface temperature as well as the CO total column mixing ratio average retrieved from Sentinel-5 p Tropospheric Monitoring Instrument during the period of analysis.

GEMAR: web-based GIS for emergency management and ambulance routing

In this study, we developed a web-based emergency management system to provide timely treatments to patients in emergency conditions. With the integration of geospatial information and technologies, a global positioning system, and optimization technique, we designed a system consisting of two subsystems, emergency reporting and ambulance routing. The reporting subsystem helps in collecting emergency information in urban areas using geocoding and geolocation function, while the routing subsystem generates the optimal route for pick-up operation and selects the nearest hospital for patient delivery process. A committee of 10 experts comprising of seven medical experts and three GIS experts are invited to use the system. We performed system evaluation in terms of technology acceptance and usability issues. The technology acceptance's mean score ranged from 3.70 to 4.40, while the usability means score ranged from 4.00 to 4.50. The results indicated that the system provided user-friendliness features so that they are willing to use the system in the near future. The medical experts also perceived that the system was easy to operate and navigate. They stated that the two subsystems are helpful for clinical operators to understand a common situation in emergency handling. We used their feedback to further improve and refine the program.

Multiscale assessment of progress of electrification in Indonesia based on brightness level derived from nighttime satellite imagery

Availability of electricity can be used as an indicator to proximate parameters related to human well-being. Overall, the electrification process in Indonesia has been accelerating in the past two decades. Unfortunately, monitoring the country's progress on its effort to provide wider access to electricity poses challenges due to inconsistency of data provided by each national bureau, and limited availability of information. This study attempts to provide a reliable measure by employing nighttime satellite imagery to observe and to map the progress of electrification within a duration of 20 years, from 1993 to 2013. Brightness of 67,021 settlement-size points in 1993, 2003, and 2013 was assessed using data from DMSP/OLS instruments to study the electrification progress in the three service regions (Sumatera, Java-Bali, and East Indonesia) of the country's public electricity company, PLN. Observation of all service areas shows that the increase in brightness, which correspond with higher electricity development and consumption, has positive correlation with both population density (R² = 0.70) and urban change (R² = 0.79). Moreover, urban change has a stronger correlation with brightness, which is probably due to the high energy consumption in urban area per capita. This study also found that the brightness in Java-Bali region is very dominant, while the brightness in other areas has been lagging during the period of analysis. The slow development of electricity infrastructure, particularly in major parts of East Indonesia region, affects the low economic growth in some areas and formed vicious cycle.

Land use changes and GHG emissions from tropical forest conversion by oil palm plantations in Riau Province, Indonesia

Increasing prices and demand for biofuel and cooking oil from importer countries have caused a remarkable expansion of oil palm plantations in Indonesia. In this paper, we attempt to monitor the expansion of oil palm plantations on peat land and in tropical forests. We measure the GHG emissions from the land conversion activities at provincial scale. Using Landsat images from three different periods (1990s, 2000s and 2012), we classified LULC of the Riau Province, which is the largest oil palm producing region in Indonesia. A hybrid method of integration, generated by combining automatic processing and manual analysis, yields the best results. We found that the tropical rainforest cover decreased from ∼63% in the 1990s to ∼37% in the 2000s. By 2012, the remaining tropical rainforest cover was only ∼22%. From the 1990s to the 2000s, conversion of forests and peat lands was the primary source of emissions, total CO₂ emitted to the atmosphere was estimated at ∼26.6 million tCO₂.y^-1, with 40.62% and 59.38% of the emissions from conversion of peat lands and forests, respectively. Between 2000 and 2012, the total CO₂ emitted to the atmosphere was estimated at ∼5.2 million tCO₂. y^-1, with 69.94% and 27.62% of the emissions from converted peat lands and converted forests, respectively. The results show that in the Riau Province, the oil palm industry boomed in the period from 1990 to 2000, with transformation of tropical forest and peat land as the primary source of emissions. The decrease of CO₂ emissions in the period from 2000 to 2012 is possibly due to the enforcement of a moratorium on deforestation.