Journal Articles |
2020 |
Setiawan, Yudi; Rushayati, Siti Badriyah; Hermawan, Rachmad; Prasetyo, Lilik B; Wijayanto, Arif K The effect of utilization patterns of green open space on the dynamics change of air quality due to the Covid-19 pandemic in Jabodetabek region Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 10 (4), pp. 559-567, 2020, ISSN: 2460-5824. Abstract | Links | BibTeX | Tags: Covid-19, Kualitas udara, ruang terbuka hujau @article{Setiawan2020, title = {The effect of utilization patterns of green open space on the dynamics change of air quality due to the Covid-19 pandemic in Jabodetabek region}, author = {Yudi Setiawan and Siti Badriyah Rushayati and Rachmad Hermawan and Lilik B Prasetyo and Arif K Wijayanto}, url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/32550}, doi = {10.29244/jpsl.10.4.559-567}, issn = {2460-5824}, year = {2020}, date = {2020-12-31}, journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)}, volume = {10}, number = {4}, pages = {559-567}, abstract = {The Covid-19 pandemic has had a global impact on all sectors including the environment. The spread of covid-19 is very much influenced by human activity and mobility. Human activities are also closelyrelated to air pollutant emissions. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid-19. Jakarta and its surroundingarea (known locally as Jabodetabek) havehigh population density. Thesecities are economic and industrial centers. Air pollutant emissions in these cities are very high. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid. To anticipate this problem, the government made a Large-Scale Social Restriction Policy (PSBB). Limited human activities, in addition to having an impact on reducing the risk of humans being exposed to Covid-19 from the droplets released by tested-positive of Covid-19, also have an impact on reducing emissions of air pollutants so that they can reduce the risk of being exposed to Covid-19. Several variables that influence vulnerability and risk to exposure to Covid-19 are the distribution of settlements, roads, economic centers (markets, business centers, industrial centers), and human mobility. In this study, we will also analyze the role of green open space on the risk of exposure to Covid-19. Green open space plays an important role in reducing air pollutants so that it will also affect the risk of being exposed to Covid-19. This study aimedto 1) examine the distribution of air pollutants based on the vulnerability and risk of COVID-19 in Jakarta,Bogor, Depok, Tangerang, and Bekasi (Jabodetabek), and 2) examine the results of the overlay between land cover and vulnerability and risk to Covid-19}, keywords = {Covid-19, Kualitas udara, ruang terbuka hujau}, pubstate = {published}, tppubtype = {article} } The Covid-19 pandemic has had a global impact on all sectors including the environment. The spread of covid-19 is very much influenced by human activity and mobility. Human activities are also closelyrelated to air pollutant emissions. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid-19. Jakarta and its surroundingarea (known locally as Jabodetabek) havehigh population density. Thesecities are economic and industrial centers. Air pollutant emissions in these cities are very high. High concentrations of air pollutants during the Covid-19 pandemic will increase the risk of being exposed to Covid. To anticipate this problem, the government made a Large-Scale Social Restriction Policy (PSBB). Limited human activities, in addition to having an impact on reducing the risk of humans being exposed to Covid-19 from the droplets released by tested-positive of Covid-19, also have an impact on reducing emissions of air pollutants so that they can reduce the risk of being exposed to Covid-19. Several variables that influence vulnerability and risk to exposure to Covid-19 are the distribution of settlements, roads, economic centers (markets, business centers, industrial centers), and human mobility. In this study, we will also analyze the role of green open space on the risk of exposure to Covid-19. Green open space plays an important role in reducing air pollutants so that it will also affect the risk of being exposed to Covid-19. This study aimedto 1) examine the distribution of air pollutants based on the vulnerability and risk of COVID-19 in Jakarta,Bogor, Depok, Tangerang, and Bekasi (Jabodetabek), and 2) examine the results of the overlay between land cover and vulnerability and risk to Covid-19 |
Wijayanto, Arif K; Rushayati, Siti Badriyah; Hermawan, Rachmad; Setiawan, Yudi; Prasetyo, Lilik B Jakarta and Surabaya land surface temperature before and during the Covid-19 pandemic Journal Article AES Bioflux, 12 (3), pp. 213-221, 2020, ISSN: 2066-7647. Abstract | Links | BibTeX | Tags: Covid-19, Land Surface Temperature, urban heat island @article{Wijayanto2020, title = {Jakarta and Surabaya land surface temperature before and during the Covid-19 pandemic}, author = {Arif K Wijayanto and Siti Badriyah Rushayati and Rachmad Hermawan and Yudi Setiawan and Lilik B Prasetyo}, url = {http://www.aes.bioflux.com.ro/docs/2020.213-221.pdf}, issn = {2066-7647}, year = {2020}, date = {2020-12-02}, journal = {AES Bioflux}, volume = {12}, number = {3}, pages = {213-221}, abstract = {The first incidence of the novel coronavirus or Covid-19 was reported in late 2019, and in the following year, the disease was declared a global pandemic. In Indonesia, the first case was reported in early March, 2020, and ever since, the government has appealed to the public to reduce outdoor activities in order to curtail the spread of the virus. Consequently, many companies and institutions implemented the ‘Work from Home’ (WFH) policy. At the end of April, the provincial government of Jakarta issued large-scale social restrictions, locally called PSBB. These restrictions were later implemented in other cities such as Surabaya. Jakarta was the epicentre of the spread of the virus in Indonesia, followed by Surabaya, the second largest city in the country. Therefore, this study aimed to analyze the Thermal Humidity Index (THI) of both cities, before and during the pandemic. Data were obtained from the MODIS Terra Land Surface Temperature and Emissivity 8-Day Global 1km, from the 1st to 14th May, 2019 (before the pandemic), and during the same period the following year (during the pandemic). Furthermore, data analysis was carried out using Google Earth Engine (GEE), a cloud-based platform for geo-spatial data analysis. The hypothesis in this study was that the social restriction policy caused a difference in the THI before and during the pandemic. Therefore, this hypothesis was proven by the results, as the policy caused a decrease in the THI during the pandemic.}, keywords = {Covid-19, Land Surface Temperature, urban heat island}, pubstate = {published}, tppubtype = {article} } The first incidence of the novel coronavirus or Covid-19 was reported in late 2019, and in the following year, the disease was declared a global pandemic. In Indonesia, the first case was reported in early March, 2020, and ever since, the government has appealed to the public to reduce outdoor activities in order to curtail the spread of the virus. Consequently, many companies and institutions implemented the ‘Work from Home’ (WFH) policy. At the end of April, the provincial government of Jakarta issued large-scale social restrictions, locally called PSBB. These restrictions were later implemented in other cities such as Surabaya. Jakarta was the epicentre of the spread of the virus in Indonesia, followed by Surabaya, the second largest city in the country. Therefore, this study aimed to analyze the Thermal Humidity Index (THI) of both cities, before and during the pandemic. Data were obtained from the MODIS Terra Land Surface Temperature and Emissivity 8-Day Global 1km, from the 1st to 14th May, 2019 (before the pandemic), and during the same period the following year (during the pandemic). Furthermore, data analysis was carried out using Google Earth Engine (GEE), a cloud-based platform for geo-spatial data analysis. The hypothesis in this study was that the social restriction policy caused a difference in the THI before and during the pandemic. Therefore, this hypothesis was proven by the results, as the policy caused a decrease in the THI during the pandemic. |
2018 |
Setiawan, Yudi; Prasetyo, Lilik B; Pawitan, Hidayat; Liyantono, Liyantono; Syartinilia, Syartinilia; Wijayanto, Arif K; Permatasari, Prita A; Syafrudin, Hadi A; Hakim, Patria R Pemanfaatan Fusi Data Satelit Lapan-a3/IPB dan Landsat 8 Untuk Monitoring Lahan Sawah Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 8 (1), pp. 67–76, 2018, ISSN: 2460-5824. Abstract | Links | BibTeX | Tags: Landsat, LAPAN @article{setiawan2018pemanfaatan, title = {Pemanfaatan Fusi Data Satelit Lapan-a3/IPB dan Landsat 8 Untuk Monitoring Lahan Sawah}, author = {Yudi Setiawan and Lilik B Prasetyo and Hidayat Pawitan and Liyantono Liyantono and Syartinilia Syartinilia and Arif K Wijayanto and Prita A Permatasari and Hadi A Syafrudin and Patria R Hakim}, url = {https://journal.ipb.ac.id/index.php/jpsl/article/view/19754}, doi = {10.29244/jpsl.8.1.67-76}, issn = {2460-5824}, year = {2018}, date = {2018-01-01}, journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)}, volume = {8}, number = {1}, pages = {67--76}, abstract = {Increasing of economic development is generally followed by the change of landuse from agriculture to other function. If it occurs in large frequency and amount, it will threaten national food security. Therefore, it is necessary to monitor the agricultural land, especially paddy fields regarding to changes in landuse and global climate. Utilization and development of satellite technology is necessary to provide more accurate and independent database for agricultural land monitoring, especially paddy fields. This study aims to develop a utilization model for LAPAN-IPB satellite (LISAT) and other several satellites data that have been used for paddy field monitoring. This research is conducted through 2 stages: 1) Characterization LISAT satellite data to know spectral variation of paddy field, and 2) Development method of LISAT data fusion with other satellites for paddy field mapping. Based on the research results, the characteristics Red and NIR band in LISAT data imagery have a good correlation with Red and NIR band in LANDSAT 8 OLI data imagery, especially to detect paddy field in the vegetative phase, compared to other bands. Observation and measurement of spectral values using spectroradiometer need to be conducted periodically (starting from first planting season) to know the dynamics of the change related to the growth phase of paddy in paddy field. Pre-processing of image data needs to be conducted to obtain better LISAT data characterization results. Furthermore, it is necessary to develop appropriate algorithms or methods for geometric correction as well as atmospheric correction of LISAT data.}, keywords = {Landsat, LAPAN}, pubstate = {published}, tppubtype = {article} } Increasing of economic development is generally followed by the change of landuse from agriculture to other function. If it occurs in large frequency and amount, it will threaten national food security. Therefore, it is necessary to monitor the agricultural land, especially paddy fields regarding to changes in landuse and global climate. Utilization and development of satellite technology is necessary to provide more accurate and independent database for agricultural land monitoring, especially paddy fields. This study aims to develop a utilization model for LAPAN-IPB satellite (LISAT) and other several satellites data that have been used for paddy field monitoring. This research is conducted through 2 stages: 1) Characterization LISAT satellite data to know spectral variation of paddy field, and 2) Development method of LISAT data fusion with other satellites for paddy field mapping. Based on the research results, the characteristics Red and NIR band in LISAT data imagery have a good correlation with Red and NIR band in LANDSAT 8 OLI data imagery, especially to detect paddy field in the vegetative phase, compared to other bands. Observation and measurement of spectral values using spectroradiometer need to be conducted periodically (starting from first planting season) to know the dynamics of the change related to the growth phase of paddy in paddy field. Pre-processing of image data needs to be conducted to obtain better LISAT data characterization results. Furthermore, it is necessary to develop appropriate algorithms or methods for geometric correction as well as atmospheric correction of LISAT data. |
Setiawan, Yudi; Prasetyo, Lilik B; Pawitan, Hidayat; Permatasari, Prita A; Suyamto, Desi; Wijayanto, Arif K Identifying Areas Affected By Fires In Sumatra Based On Time Series Of Remotely Sensed Fire Hotspots And Spatial Modeling Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 8 (3), pp. 420–427, 2018, ISSN: 2460-5824. Abstract | Links | BibTeX | Tags: fire, hotspot @article{setiawan2018identifying, title = {Identifying Areas Affected By Fires In Sumatra Based On Time Series Of Remotely Sensed Fire Hotspots And Spatial Modeling}, author = {Yudi Setiawan and Lilik B Prasetyo and Hidayat Pawitan and Prita A Permatasari and Desi Suyamto and Arif K Wijayanto}, url = {http://journal.ipb.ac.id/index.php/jpsl/article/view/24760}, doi = {10.29244/jpsl.8.3.420-427}, issn = {2460-5824}, year = {2018}, date = {2018-01-01}, journal = {Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)}, volume = {8}, number = {3}, pages = {420--427}, abstract = {Wildfires threaten the environment not only at local scales, but also at wider scales. Rapid monitoring system to detect active wildfires has been provided by satellite remote sensing technology, particularly through the advancement on thermal infrared sensors. However, satellite-based fire hotspots data, even at relatively high temporal resolution of less than one-day revisit period, such as time series of fire hotspots collected from TERRA and AQUA MODIS, do not tell exactly if they are fire ignitions or fire escapes, since other factors like wind, slope, and fuel biomass significantly drive the fire spread. Meanwhile, a number of biophysical fire simulation models have been developed, as tools to understand the roles of biophysical factors on the spread of wildfires. Those models explicitly incorporate effects of slope, wind direction, wind speed, and vegetative fuel on the spreading rate of surface fire from the ignition points across a fuel bed, based on either field or laboratory experiments. Nevertheless, none of those models have been implemented using real time fire data at relatively large extent areas. This study is aimed at incorporating spatially explicit time series data of weather (i.e. wind direction and wind speed), remotely sensed fuel biomass and remotely sensed fire hotspots, as well as incorporating more persistent biophysical factors (i.e. terrain), into an agent-based fire spread model, in order to identify fire ignitions within time series of remotely sensed fire hotspots.}, keywords = {fire, hotspot}, pubstate = {published}, tppubtype = {article} } Wildfires threaten the environment not only at local scales, but also at wider scales. Rapid monitoring system to detect active wildfires has been provided by satellite remote sensing technology, particularly through the advancement on thermal infrared sensors. However, satellite-based fire hotspots data, even at relatively high temporal resolution of less than one-day revisit period, such as time series of fire hotspots collected from TERRA and AQUA MODIS, do not tell exactly if they are fire ignitions or fire escapes, since other factors like wind, slope, and fuel biomass significantly drive the fire spread. Meanwhile, a number of biophysical fire simulation models have been developed, as tools to understand the roles of biophysical factors on the spread of wildfires. Those models explicitly incorporate effects of slope, wind direction, wind speed, and vegetative fuel on the spreading rate of surface fire from the ignition points across a fuel bed, based on either field or laboratory experiments. Nevertheless, none of those models have been implemented using real time fire data at relatively large extent areas. This study is aimed at incorporating spatially explicit time series data of weather (i.e. wind direction and wind speed), remotely sensed fuel biomass and remotely sensed fire hotspots, as well as incorporating more persistent biophysical factors (i.e. terrain), into an agent-based fire spread model, in order to identify fire ignitions within time series of remotely sensed fire hotspots. |
2016 |
Wijayanto, Arif K; Seminar, Kudang B; Afnan, Rudi Mobile-based Expert System for Selecting Broiler Farm Location Using PostGIS Journal Article TELKOMNIKA Indonesian Journal of Electrical Engineering, 14 (1), pp. 360-367, 2016, ISSN: 23-2-9293. Abstract | Links | BibTeX | Tags: broiler, PostGIS @article{wijayanto2016mobile, title = {Mobile-based Expert System for Selecting Broiler Farm Location Using PostGIS}, author = {Arif K Wijayanto and Kudang B Seminar and Rudi Afnan}, url = {http://www.journal.uad.ac.id/index.php/TELKOMNIKA/article/view/2903}, doi = {10.12928/telkomnika.v14i1.2903}, issn = {23-2-9293}, year = {2016}, date = {2016-01-01}, journal = {TELKOMNIKA Indonesian Journal of Electrical Engineering}, volume = {14}, number = {1}, pages = {360-367}, abstract = {Massive development of broiler farms has led to many socio-environmental problems. Based on idea that broiler farm must be located at suitable location, an expert system for site selection based on the socio-environmental factors and sustainable principles is urgently needed to cope with this problem. The objective of this research was to develop a mobile-based expert system as a guidance for broiler farmers to choose best location for broiler farm. There were four factors considered in the system: 1) ecology and environmental impact, 2) economic and infrastructure, 3) natural condition, and 4) natural disaster vulnerability, each of which consists of sub-factors. A mobile-based expert system has been developed by using opensource web GIS server and PostgreSQL/PostGIS, and can be installed on Android device. As conclusion, a mobile-based expert system has been developed and can be used to determine suitable location for broiler farm development. }, keywords = {broiler, PostGIS}, pubstate = {published}, tppubtype = {article} } Massive development of broiler farms has led to many socio-environmental problems. Based on idea that broiler farm must be located at suitable location, an expert system for site selection based on the socio-environmental factors and sustainable principles is urgently needed to cope with this problem. The objective of this research was to develop a mobile-based expert system as a guidance for broiler farmers to choose best location for broiler farm. There were four factors considered in the system: 1) ecology and environmental impact, 2) economic and infrastructure, 3) natural condition, and 4) natural disaster vulnerability, each of which consists of sub-factors. A mobile-based expert system has been developed by using opensource web GIS server and PostgreSQL/PostGIS, and can be installed on Android device. As conclusion, a mobile-based expert system has been developed and can be used to determine suitable location for broiler farm development. |
2015 |
Wijayanto, Arif K; Seminar, Kudang B; Afnan, Rudi International Journal of Poultry Science, 14 (10), pp. 577, 2015. Abstract | Links | BibTeX | Tags: AHP, broiler @article{wijayanto2015suitability, title = {Suitability Mapping for Broiler Closed House Farm Using Analytical Hierarchy Process and Weighted Overlay with Emphasize on Environmental Aspects}, author = {Arif K Wijayanto and Kudang B Seminar and Rudi Afnan}, url = {https://scialert.net/abstract/?doi=ijps.2015.577.583}, doi = {10.3923/ijps.2015.577.583}, year = {2015}, date = {2015-01-01}, journal = {International Journal of Poultry Science}, volume = {14}, number = {10}, pages = {577}, publisher = {Asian Network for Scientific Information (ANSINET)}, abstract = {Massive development of broiler farms has led to many socio-environmental problems. A mapping based on the socio-environmental factors and sustainable principles is urgently needed to cope with this problem. The objective of this research was to create a suitability map for broiler farm development in Parung region, Indonesia-as study area. There were four factors considered in the mapping: (1) ecology and environmental impact, (2) economic and infrastructure, (3) natural condition and (4) natural disaster vulnerability, each of which consists of sub-factors. An Analytical Hierarchy Process (AHP) by using pairwise comparison method was applied to determine weight of each factor and sub-factor based on experts’ valuation. From the AHP process, natural condition was considered as the most important factor, followed by ecological and environmental impact factor. By considering weights resulted from the AHP, the spatial analysis and weighted overlay by GIS software were applied in the data processing and suitability map building. Suitability map for broiler farm in Parung region has been created and can be used as guidance for broiler farm development and also for local government as decision support tool to manage the farming area concerning ecology and environment factor.}, keywords = {AHP, broiler}, pubstate = {published}, tppubtype = {article} } Massive development of broiler farms has led to many socio-environmental problems. A mapping based on the socio-environmental factors and sustainable principles is urgently needed to cope with this problem. The objective of this research was to create a suitability map for broiler farm development in Parung region, Indonesia-as study area. There were four factors considered in the mapping: (1) ecology and environmental impact, (2) economic and infrastructure, (3) natural condition and (4) natural disaster vulnerability, each of which consists of sub-factors. An Analytical Hierarchy Process (AHP) by using pairwise comparison method was applied to determine weight of each factor and sub-factor based on experts’ valuation. From the AHP process, natural condition was considered as the most important factor, followed by ecological and environmental impact factor. By considering weights resulted from the AHP, the spatial analysis and weighted overlay by GIS software were applied in the data processing and suitability map building. Suitability map for broiler farm in Parung region has been created and can be used as guidance for broiler farm development and also for local government as decision support tool to manage the farming area concerning ecology and environment factor. |
Conferences |
2020 |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky 211 , E3S Web Conf., 2020, ISSN: 2267-1242. Abstract | Links | BibTeX | Tags: drone, UAV @conference{Rahman2020, title = {An experimental approach to exploring the feasibility of unmanned aerial vehicle and thermal imaging in terrestrial and arboreal mammals research}, author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani}, url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_02010/e3sconf_jessd2020_02010.html}, doi = {10.1051/e3sconf/202021102010}, issn = {2267-1242}, year = {2020}, date = {2020-11-25}, volume = {211}, publisher = {E3S Web Conf.}, abstract = {The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method.}, keywords = {drone, UAV}, pubstate = {published}, tppubtype = {conference} } The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method. |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky 211 , E3S Web Conf., 2020, ISSN: 2267-1242. Abstract | Links | BibTeX | Tags: drone, UAV @conference{Rahman2020b, title = {Possibility of applying unmanned aerial vehicle and thermal imaging in several canopy cover class for wildlife monitoring – preliminary results}, author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani}, url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_04007/e3sconf_jessd2020_04007.html}, doi = {10.1051/e3sconf/202021104007}, issn = {2267-1242}, year = {2020}, date = {2020-11-25}, volume = {211}, publisher = {E3S Web Conf.}, abstract = {Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime.}, keywords = {drone, UAV}, pubstate = {published}, tppubtype = {conference} } Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime. |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky 211 , E3S Web Conf., 2020, ISSN: 2267-1242. Abstract | Links | BibTeX | Tags: drone, UAV @conference{Rahman2020c, title = {An experimental approach to exploring the feasibility of unmanned aerial vehicle and thermal imaging in terrestrial and arboreal mammals research}, author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani}, url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_02010/e3sconf_jessd2020_02010.html}, doi = {10.1051/e3sconf/202021102010}, issn = {2267-1242}, year = {2020}, date = {2020-11-25}, volume = {211}, publisher = {E3S Web Conf.}, abstract = {The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method.}, keywords = {drone, UAV}, pubstate = {published}, tppubtype = {conference} } The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method. |
Rahman, Dede Aulia; Setiawan, Yudi; Wijayanto, Arif K; Aziz, Ahmad Abdul; Martiyani, Trisna Rizky 211 , E3S Web Conf., 2020, ISSN: 2267-1242. Abstract | Links | BibTeX | Tags: drone, UAV @conference{Rahman2020bb, title = {Possibility of applying unmanned aerial vehicle and thermal imaging in several canopy cover class for wildlife monitoring – preliminary results}, author = {Dede Aulia Rahman and Yudi Setiawan and Arif K Wijayanto and Ahmad Abdul Aziz and Trisna Rizky Martiyani}, url = {https://www.e3s-conferences.org/articles/e3sconf/abs/2020/71/e3sconf_jessd2020_04007/e3sconf_jessd2020_04007.html}, doi = {10.1051/e3sconf/202021104007}, issn = {2267-1242}, year = {2020}, date = {2020-11-25}, volume = {211}, publisher = {E3S Web Conf.}, abstract = {Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime.}, keywords = {drone, UAV}, pubstate = {published}, tppubtype = {conference} } Tropical rainforests are one of the important habitats on earth but are rarely explored because they are difficult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optimum flying height, sound level, temperature, and optimum flight time in each canopy cover class. The optimum height for animal detection is <50 m HAGL with a sound level that animals can still tolerate. Wildlife detected had body temperatures around 27 °C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (15–27°C), but were difficult to detect by mid-day. By that time, the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone but could be recognized from synchronized visual images taken during the daytime. |
Suyamto, Desi; Condro, Aryo Adhi; Prasetyo, Lilik B; Wijayanto, Arif K Assessing the Agreement between Deforestation Maps of Kalimantan from Various Sources Conference 556 (1), IOP Conf. Ser.: Earth Environ. Sci, 2020. Abstract | Links | BibTeX | Tags: deforestation @conference{Suyamto2020, title = {Assessing the Agreement between Deforestation Maps of Kalimantan from Various Sources}, author = {Desi Suyamto and Aryo Adhi Condro and Lilik B Prasetyo and Arif K Wijayanto}, url = {https://iopscience.iop.org/article/10.1088/1755-1315/556/1/012011/pdf}, doi = {10.1088/1755-1315/556/1/012011}, year = {2020}, date = {2020-09-22}, volume = {556}, number = {1}, publisher = {IOP Conf. Ser.: Earth Environ. Sci}, abstract = {Due to its multiscale impacts, deforestation of tropical rainforests had become a global concern. A number of stakeholders comprising government, research agencies, and NGOs; ranging from local to international levels; have developed their own forest monitoring systems for detecting forest loss. However, discrepancies on deforestation reports from various producers often trigger public debates; which mostly degenerate the productivity of efforts in providing salient, legitimate and credible data on deforestation. Thus, we should reconcile the dispute by acknowledging the deforestation data from all sources. This study assessed the agreement between deforestation maps from various sources. In this case, deforestation maps of Kalimantan within 2009-2013 period from 4 sources were used; i.e. deforestation maps from European Space Agency - Climate Change Initiative (ESA-CCI), Forest Watch Indonesia (FWI), Global Forest Watch (GFW), and Indonesian Ministry of Environment and Forestry (MoEF). We found that the inter-rater agreement between deforestation maps were relatively low, as indicated by Cohen's kappa (κ), ranging from slight (κ=0.18 between ESA-CCI and GFW) to fair (0.24 ≤ κ ≤ 0.35 for other pairs of sources); due to omission/commission disagreements (47.82% to 87.58%). It suggests that in order to reconcile the dispute, we should remove the omission disagreement by forming the union of deforestation maps. The results from further analyses proved that the union of deforestation maps increased the agreement to moderate (κ=0.44 between union map and FWI) and even substantial (κ=0.79 between union map and GFW). Findings of this study should support the implementation of one map policy.}, keywords = {deforestation}, pubstate = {published}, tppubtype = {conference} } Due to its multiscale impacts, deforestation of tropical rainforests had become a global concern. A number of stakeholders comprising government, research agencies, and NGOs; ranging from local to international levels; have developed their own forest monitoring systems for detecting forest loss. However, discrepancies on deforestation reports from various producers often trigger public debates; which mostly degenerate the productivity of efforts in providing salient, legitimate and credible data on deforestation. Thus, we should reconcile the dispute by acknowledging the deforestation data from all sources. This study assessed the agreement between deforestation maps from various sources. In this case, deforestation maps of Kalimantan within 2009-2013 period from 4 sources were used; i.e. deforestation maps from European Space Agency - Climate Change Initiative (ESA-CCI), Forest Watch Indonesia (FWI), Global Forest Watch (GFW), and Indonesian Ministry of Environment and Forestry (MoEF). We found that the inter-rater agreement between deforestation maps were relatively low, as indicated by Cohen's kappa (κ), ranging from slight (κ=0.18 between ESA-CCI and GFW) to fair (0.24 ≤ κ ≤ 0.35 for other pairs of sources); due to omission/commission disagreements (47.82% to 87.58%). It suggests that in order to reconcile the dispute, we should remove the omission disagreement by forming the union of deforestation maps. The results from further analyses proved that the union of deforestation maps increased the agreement to moderate (κ=0.44 between union map and FWI) and even substantial (κ=0.79 between union map and GFW). Findings of this study should support the implementation of one map policy. |
Inproceedings |
2019 |
Wijayanto, Arif K; Yusuf, Sri M; Pambudi, Wiwid A IOP Conference Series: Earth and Environmental Science, pp. 012004, IOP Publishing 2019. Abstract | Links | BibTeX | Tags: Landsat, LAPAN, spectral @inproceedings{wijayanto2019characteristic, title = {The Characteristic of spectral reflectance of LAPAN-IPB (LAPAN-A3) Satellite and Landsat 8 over agricultural area in Probolinggo, East Java}, author = {Arif K Wijayanto and Sri M Yusuf and Wiwid A Pambudi}, url = {https://iopscience.iop.org/article/10.1088/1755-1315/284/1/012004/meta}, doi = {10.1088/1755-1315/284/1/012004}, year = {2019}, date = {2019-01-01}, booktitle = {IOP Conference Series: Earth and Environmental Science}, volume = {284}, number = {1}, pages = {012004}, organization = {IOP Publishing}, abstract = {LAPAN-IPB Satellite which was developed by the National Agency of Aeronautics and Space (LAPAN) and Landsat 8 have quite equal specification. However, it is important to investigate the difference of characteristic between the two satellites since the Landsat 8 commonly used by Indonesian researcher in the agriculture field for years. The study was done in Probolinggo Regency which is located in East Java, Indonesia – has a large area of agriculture. Satellite data of LAPAN A3/IPB used in the analysis of its spectral characteristic over agricultural area was acquired on September 18, 2018, while the Landsat 8 image data was taken from acquisition date on September 12, 2018. Field data measurement was done by collecting spectral reflectance of some agricultural crops at study area consist of paddy, maize, sugar cane, and onion. Spectral reflectance from the four crops are quietly the same, except for paddy which has the lowest reflectance on peak of green band compared to other crops. Spectral profile of LAPAN-A3/IPB on Blue, Green and Red band are always lower than Landsat 8, while the NIR band is always higher. NDVI from Landsat 8 OLI ranged from -1 to 0.622844, while NDVI from LAPAN-A3/IPB ranged from -1 to 0.461655. NDVI from Landsat is able to differentiate water more clearly than LAPAN-A3/IPB, indicated by low NDVI value. It is concluded that LAPAN-A3/IPB has quite similar spectral characteristic compared to Landsat-8 OLI. Although there is some difference of spectral characteristic from some crops. It is recommended to consider the age or growth stage of each crop.}, keywords = {Landsat, LAPAN, spectral}, pubstate = {published}, tppubtype = {inproceedings} } LAPAN-IPB Satellite which was developed by the National Agency of Aeronautics and Space (LAPAN) and Landsat 8 have quite equal specification. However, it is important to investigate the difference of characteristic between the two satellites since the Landsat 8 commonly used by Indonesian researcher in the agriculture field for years. The study was done in Probolinggo Regency which is located in East Java, Indonesia – has a large area of agriculture. Satellite data of LAPAN A3/IPB used in the analysis of its spectral characteristic over agricultural area was acquired on September 18, 2018, while the Landsat 8 image data was taken from acquisition date on September 12, 2018. Field data measurement was done by collecting spectral reflectance of some agricultural crops at study area consist of paddy, maize, sugar cane, and onion. Spectral reflectance from the four crops are quietly the same, except for paddy which has the lowest reflectance on peak of green band compared to other crops. Spectral profile of LAPAN-A3/IPB on Blue, Green and Red band are always lower than Landsat 8, while the NIR band is always higher. NDVI from Landsat 8 OLI ranged from -1 to 0.622844, while NDVI from LAPAN-A3/IPB ranged from -1 to 0.461655. NDVI from Landsat is able to differentiate water more clearly than LAPAN-A3/IPB, indicated by low NDVI value. It is concluded that LAPAN-A3/IPB has quite similar spectral characteristic compared to Landsat-8 OLI. Although there is some difference of spectral characteristic from some crops. It is recommended to consider the age or growth stage of each crop. |
Sujaswara, Azwar A; Setiawan, Yudi; Prasetyo, Lilik B; Hudjimartsu, Sahid A; Wijayanto, Arif K Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137221, International Society for Optics and Photonics 2019. Abstract | Links | BibTeX | Tags: UAV @inproceedings{sujaswara2019utilization, title = {Utilization of UAV technology for vegetation cover mapping using object based image analysis in restoration area of Gunung Halimun Salak National Park, Indonesia}, author = {Azwar A Sujaswara and Yudi Setiawan and Lilik B Prasetyo and Sahid A Hudjimartsu and Arif K Wijayanto}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/1137221/Utilization-of-UAV-technology-for-vegetation-cover-mapping-using-object/10.1117/12.2540566.short}, doi = {10.1117/12.2540566}, year = {2019}, date = {2019-01-01}, booktitle = {Sixth International Symposium on LAPAN-IPB Satellite}, volume = {11372}, pages = {1137221}, organization = {International Society for Optics and Photonics}, abstract = {Halimun Salak Corridor (HSC) is an important area that connects the Mount Halimun and Mount Salak, and has important role of animals movements. As the corridor have become degraded over the last ten years, ecosystem restoration action is required. In order to monitor that restoration program, then, it is necessary to mapping the vegetation cover in the corridor. Unmanned Aerial Vehicle (UAV) technology is an alternative technology that can be used to provide a detail vegetation cover map based on a high resolution image. This research aim to mapping vegetation cover based on a combination of structural characteristics of height and vegetation indices by using Object Based Image Analysis (OBIA) method. Structural characteristics was defined from the canopy height model (CHM) using the Structure from Motion (SfM) method, meanwhile, several spectral indices (NDVI, NDWI, and SAVI) were produced from multispectral images. We applied Object Based Image Analysis (OBIA) to classify vegetation cover based on their structure and spectral characteristics. The results shown that the most dominant vegetation cover is the tree class, which is 70.74 ha (77.31 % of the 91.5 ha mapped area) and accuracy test revealed 73.11% of overall accuracy.}, keywords = {UAV}, pubstate = {published}, tppubtype = {inproceedings} } Halimun Salak Corridor (HSC) is an important area that connects the Mount Halimun and Mount Salak, and has important role of animals movements. As the corridor have become degraded over the last ten years, ecosystem restoration action is required. In order to monitor that restoration program, then, it is necessary to mapping the vegetation cover in the corridor. Unmanned Aerial Vehicle (UAV) technology is an alternative technology that can be used to provide a detail vegetation cover map based on a high resolution image. This research aim to mapping vegetation cover based on a combination of structural characteristics of height and vegetation indices by using Object Based Image Analysis (OBIA) method. Structural characteristics was defined from the canopy height model (CHM) using the Structure from Motion (SfM) method, meanwhile, several spectral indices (NDVI, NDWI, and SAVI) were produced from multispectral images. We applied Object Based Image Analysis (OBIA) to classify vegetation cover based on their structure and spectral characteristics. The results shown that the most dominant vegetation cover is the tree class, which is 70.74 ha (77.31 % of the 91.5 ha mapped area) and accuracy test revealed 73.11% of overall accuracy. |
Permatasari, Prita A; Amalo, Luisa F; Wijayanto, Arif K Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia Inproceedings Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137209, International Society for Optics and Photonics International Society for Optics and Photonics, 2019. Abstract | Links | BibTeX | Tags: UHI, urban heat island @inproceedings{permatasari2019comparison, title = {Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia}, author = {Prita A Permatasari and Luisa F Amalo and Arif K Wijayanto}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/1137209/Comparison-of-urban-heat-island-effect-in-Jakarta-and-Surabaya/10.1117/12.2541581.short?SSO=1}, doi = {10.1117/12.2541581}, year = {2019}, date = {2019-01-01}, booktitle = {Sixth International Symposium on LAPAN-IPB Satellite}, volume = {11372}, pages = {1137209}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, abstract = {Urban heat island is a condition when metropolitan area has warmer temperature that surrounding rural area. High population and activity inside the city can be the factors that trigger urban heat island. Indonesia has some large cities with big population. Jakarta and Surabaya are two largest and most populous cities in Indonesia. In this study, the effect of urban heat island in those two cities will be compared using Landsat 8 data in the period of 2018. The correlation between land surface temperature and the normalized difference vegetation index (NDVI) were analyzed to explore the impacts of the green areas on the urban heat island. The result showed the differences of surface temperature between two largest cities in Indonesia in 2018. The result also showed negative correlation between NDVI and surface temperature that indicates that the green area can decrease the effect on the urban heat island.}, keywords = {UHI, urban heat island}, pubstate = {published}, tppubtype = {inproceedings} } Urban heat island is a condition when metropolitan area has warmer temperature that surrounding rural area. High population and activity inside the city can be the factors that trigger urban heat island. Indonesia has some large cities with big population. Jakarta and Surabaya are two largest and most populous cities in Indonesia. In this study, the effect of urban heat island in those two cities will be compared using Landsat 8 data in the period of 2018. The correlation between land surface temperature and the normalized difference vegetation index (NDVI) were analyzed to explore the impacts of the green areas on the urban heat island. The result showed the differences of surface temperature between two largest cities in Indonesia in 2018. The result also showed negative correlation between NDVI and surface temperature that indicates that the green area can decrease the effect on the urban heat island. |
Permatasari, Prita A; Amalo, Luisa F; Wijayanto, Arif K Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia Inproceedings Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137209, International Society for Optics and Photonics International Society for Optics and Photonics, 2019. Abstract | Links | BibTeX | Tags: UHI, urban heat island @inproceedings{permatasari2019comparisonb, title = {Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia}, author = {Prita A Permatasari and Luisa F Amalo and Arif K Wijayanto}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/1137209/Comparison-of-urban-heat-island-effect-in-Jakarta-and-Surabaya/10.1117/12.2541581.short?SSO=1}, doi = {10.1117/12.2541581}, year = {2019}, date = {2019-01-01}, booktitle = {Sixth International Symposium on LAPAN-IPB Satellite}, volume = {11372}, pages = {1137209}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, abstract = {Urban heat island is a condition when metropolitan area has warmer temperature that surrounding rural area. High population and activity inside the city can be the factors that trigger urban heat island. Indonesia has some large cities with big population. Jakarta and Surabaya are two largest and most populous cities in Indonesia. In this study, the effect of urban heat island in those two cities will be compared using Landsat 8 data in the period of 2018. The correlation between land surface temperature and the normalized difference vegetation index (NDVI) were analyzed to explore the impacts of the green areas on the urban heat island. The result showed the differences of surface temperature between two largest cities in Indonesia in 2018. The result also showed negative correlation between NDVI and surface temperature that indicates that the green area can decrease the effect on the urban heat island.}, keywords = {UHI, urban heat island}, pubstate = {published}, tppubtype = {inproceedings} } Urban heat island is a condition when metropolitan area has warmer temperature that surrounding rural area. High population and activity inside the city can be the factors that trigger urban heat island. Indonesia has some large cities with big population. Jakarta and Surabaya are two largest and most populous cities in Indonesia. In this study, the effect of urban heat island in those two cities will be compared using Landsat 8 data in the period of 2018. The correlation between land surface temperature and the normalized difference vegetation index (NDVI) were analyzed to explore the impacts of the green areas on the urban heat island. The result showed the differences of surface temperature between two largest cities in Indonesia in 2018. The result also showed negative correlation between NDVI and surface temperature that indicates that the green area can decrease the effect on the urban heat island. |
Wijayanto, Arif K; Yusuf, Sri M; Pambudi, Wiwid A IOP Conference Series: Earth and Environmental Science, pp. 012004, IOP Publishing 2019. Abstract | Links | BibTeX | Tags: Landsat, LAPAN, spectral @inproceedings{wijayanto2019characteristicb, title = {The Characteristic of spectral reflectance of LAPAN-IPB (LAPAN-A3) Satellite and Landsat 8 over agricultural area in Probolinggo, East Java}, author = {Arif K Wijayanto and Sri M Yusuf and Wiwid A Pambudi}, url = {https://iopscience.iop.org/article/10.1088/1755-1315/284/1/012004/meta}, doi = {10.1088/1755-1315/284/1/012004}, year = {2019}, date = {2019-01-01}, booktitle = {IOP Conference Series: Earth and Environmental Science}, volume = {284}, number = {1}, pages = {012004}, organization = {IOP Publishing}, abstract = {LAPAN-IPB Satellite which was developed by the National Agency of Aeronautics and Space (LAPAN) and Landsat 8 have quite equal specification. However, it is important to investigate the difference of characteristic between the two satellites since the Landsat 8 commonly used by Indonesian researcher in the agriculture field for years. The study was done in Probolinggo Regency which is located in East Java, Indonesia – has a large area of agriculture. Satellite data of LAPAN A3/IPB used in the analysis of its spectral characteristic over agricultural area was acquired on September 18, 2018, while the Landsat 8 image data was taken from acquisition date on September 12, 2018. Field data measurement was done by collecting spectral reflectance of some agricultural crops at study area consist of paddy, maize, sugar cane, and onion. Spectral reflectance from the four crops are quietly the same, except for paddy which has the lowest reflectance on peak of green band compared to other crops. Spectral profile of LAPAN-A3/IPB on Blue, Green and Red band are always lower than Landsat 8, while the NIR band is always higher. NDVI from Landsat 8 OLI ranged from -1 to 0.622844, while NDVI from LAPAN-A3/IPB ranged from -1 to 0.461655. NDVI from Landsat is able to differentiate water more clearly than LAPAN-A3/IPB, indicated by low NDVI value. It is concluded that LAPAN-A3/IPB has quite similar spectral characteristic compared to Landsat-8 OLI. Although there is some difference of spectral characteristic from some crops. It is recommended to consider the age or growth stage of each crop.}, keywords = {Landsat, LAPAN, spectral}, pubstate = {published}, tppubtype = {inproceedings} } LAPAN-IPB Satellite which was developed by the National Agency of Aeronautics and Space (LAPAN) and Landsat 8 have quite equal specification. However, it is important to investigate the difference of characteristic between the two satellites since the Landsat 8 commonly used by Indonesian researcher in the agriculture field for years. The study was done in Probolinggo Regency which is located in East Java, Indonesia – has a large area of agriculture. Satellite data of LAPAN A3/IPB used in the analysis of its spectral characteristic over agricultural area was acquired on September 18, 2018, while the Landsat 8 image data was taken from acquisition date on September 12, 2018. Field data measurement was done by collecting spectral reflectance of some agricultural crops at study area consist of paddy, maize, sugar cane, and onion. Spectral reflectance from the four crops are quietly the same, except for paddy which has the lowest reflectance on peak of green band compared to other crops. Spectral profile of LAPAN-A3/IPB on Blue, Green and Red band are always lower than Landsat 8, while the NIR band is always higher. NDVI from Landsat 8 OLI ranged from -1 to 0.622844, while NDVI from LAPAN-A3/IPB ranged from -1 to 0.461655. NDVI from Landsat is able to differentiate water more clearly than LAPAN-A3/IPB, indicated by low NDVI value. It is concluded that LAPAN-A3/IPB has quite similar spectral characteristic compared to Landsat-8 OLI. Although there is some difference of spectral characteristic from some crops. It is recommended to consider the age or growth stage of each crop. |
Sujaswara, Azwar A; Setiawan, Yudi; Prasetyo, Lilik B; Hudjimartsu, Sahid A; Wijayanto, Arif K Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137221, International Society for Optics and Photonics 2019. Abstract | Links | BibTeX | Tags: UAV @inproceedings{sujaswara2019utilizationb, title = {Utilization of UAV technology for vegetation cover mapping using object based image analysis in restoration area of Gunung Halimun Salak National Park, Indonesia}, author = {Azwar A Sujaswara and Yudi Setiawan and Lilik B Prasetyo and Sahid A Hudjimartsu and Arif K Wijayanto}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11372/1137221/Utilization-of-UAV-technology-for-vegetation-cover-mapping-using-object/10.1117/12.2540566.short}, doi = {10.1117/12.2540566}, year = {2019}, date = {2019-01-01}, booktitle = {Sixth International Symposium on LAPAN-IPB Satellite}, volume = {11372}, pages = {1137221}, organization = {International Society for Optics and Photonics}, abstract = {Halimun Salak Corridor (HSC) is an important area that connects the Mount Halimun and Mount Salak, and has important role of animals movements. As the corridor have become degraded over the last ten years, ecosystem restoration action is required. In order to monitor that restoration program, then, it is necessary to mapping the vegetation cover in the corridor. Unmanned Aerial Vehicle (UAV) technology is an alternative technology that can be used to provide a detail vegetation cover map based on a high resolution image. This research aim to mapping vegetation cover based on a combination of structural characteristics of height and vegetation indices by using Object Based Image Analysis (OBIA) method. Structural characteristics was defined from the canopy height model (CHM) using the Structure from Motion (SfM) method, meanwhile, several spectral indices (NDVI, NDWI, and SAVI) were produced from multispectral images. We applied Object Based Image Analysis (OBIA) to classify vegetation cover based on their structure and spectral characteristics. The results shown that the most dominant vegetation cover is the tree class, which is 70.74 ha (77.31 % of the 91.5 ha mapped area) and accuracy test revealed 73.11% of overall accuracy.}, keywords = {UAV}, pubstate = {published}, tppubtype = {inproceedings} } Halimun Salak Corridor (HSC) is an important area that connects the Mount Halimun and Mount Salak, and has important role of animals movements. As the corridor have become degraded over the last ten years, ecosystem restoration action is required. In order to monitor that restoration program, then, it is necessary to mapping the vegetation cover in the corridor. Unmanned Aerial Vehicle (UAV) technology is an alternative technology that can be used to provide a detail vegetation cover map based on a high resolution image. This research aim to mapping vegetation cover based on a combination of structural characteristics of height and vegetation indices by using Object Based Image Analysis (OBIA) method. Structural characteristics was defined from the canopy height model (CHM) using the Structure from Motion (SfM) method, meanwhile, several spectral indices (NDVI, NDWI, and SAVI) were produced from multispectral images. We applied Object Based Image Analysis (OBIA) to classify vegetation cover based on their structure and spectral characteristics. The results shown that the most dominant vegetation cover is the tree class, which is 70.74 ha (77.31 % of the 91.5 ha mapped area) and accuracy test revealed 73.11% of overall accuracy. |
2017 |
Wijayanto, Arif K; Sani, Octo; Kartika, Nadia D; Herdiyeni, Yeni Classification model for forest fire hotspot occurrences prediction using ANFIS algorithm Inproceedings IOP Conference Series: Earth and Environmental Science, pp. 012059, IOP Publishing IOP Publishing, 2017. Abstract | Links | BibTeX | Tags: ANFIS, fire, hotspot @inproceedings{wijayanto2017classification, title = {Classification model for forest fire hotspot occurrences prediction using ANFIS algorithm}, author = {Arif K Wijayanto and Octo Sani and Nadia D Kartika and Yeni Herdiyeni}, url = {https://iopscience.iop.org/article/10.1088/1755-1315/54/1/012059/meta}, doi = {10.1088/1755-1315/54/1/012059}, year = {2017}, date = {2017-01-01}, booktitle = {IOP Conference Series: Earth and Environmental Science}, volume = {54}, number = {1}, pages = {012059}, publisher = {IOP Publishing}, organization = {IOP Publishing}, abstract = {This study proposed the application of data mining technique namely Adaptive Neuro-Fuzzy inference system (ANFIS) on forest fires hotspot data to develop classification models for hotspots occurrence in Central Kalimantan. Hotspot is a point that is indicated as the location of fires. In this study, hotspot distribution is categorized as true alarm and false alarm. ANFIS is a soft computing method in which a given inputoutput data set is expressed in a fuzzy inference system (FIS). The FIS implements a nonlinear mapping from its input space to the output space. The method of this study classified hotspots as target objects by correlating spatial attributes data using three folds in ANFIS algorithm to obtain the best model. The best result obtained from the 3rd fold provided low error for training (error = 0.0093676) and also low error testing result (error = 0.0093676). Attribute of distance to road is the most determining factor that influences the probability of true and false alarm where the level of human activities in this attribute is higher. This classification model can be used to develop early warning system of forest fire.}, keywords = {ANFIS, fire, hotspot}, pubstate = {published}, tppubtype = {inproceedings} } This study proposed the application of data mining technique namely Adaptive Neuro-Fuzzy inference system (ANFIS) on forest fires hotspot data to develop classification models for hotspots occurrence in Central Kalimantan. Hotspot is a point that is indicated as the location of fires. In this study, hotspot distribution is categorized as true alarm and false alarm. ANFIS is a soft computing method in which a given inputoutput data set is expressed in a fuzzy inference system (FIS). The FIS implements a nonlinear mapping from its input space to the output space. The method of this study classified hotspots as target objects by correlating spatial attributes data using three folds in ANFIS algorithm to obtain the best model. The best result obtained from the 3rd fold provided low error for training (error = 0.0093676) and also low error testing result (error = 0.0093676). Attribute of distance to road is the most determining factor that influences the probability of true and false alarm where the level of human activities in this attribute is higher. This classification model can be used to develop early warning system of forest fire. |
Suyamto, Desi; Prasetyo, Lilik B; Setiawan, Yudi; Wijayanto, Arif K Combining projective geometry modelling and spectral thresholding for automated cloud shadow masking in Landsat 8 imageries Inproceedings 2017 European Modelling Symposium (EMS), pp. 22–27, IEEE 2017. Abstract | Links | BibTeX | Tags: cloud, Landsat, spectral @inproceedings{suyamto2017combining, title = {Combining projective geometry modelling and spectral thresholding for automated cloud shadow masking in Landsat 8 imageries}, author = {Desi Suyamto and Lilik B Prasetyo and Yudi Setiawan and Arif K Wijayanto}, url = {https://ieeexplore.ieee.org/abstract/document/8356785}, doi = {10.1109/EMS.2017.15}, year = {2017}, date = {2017-01-01}, booktitle = {2017 European Modelling Symposium (EMS)}, pages = {22--27}, organization = {IEEE}, abstract = {The presence of cloud shadows in satellite imageries decreases the reflectance of the objects under the shades to relatively low intensities, leads to identification errors. Thus, cloud shadows detection is crucial in image processing steps. We integrated solar position modelling, projective geometry modelling, and spectral thresholding to detect cloud shadows in Landsat 8 imageries. We evaluated the algorithm using the window area of Mount Halimun-Salak, Bogor, West Java, Indonesia. The best rate accuracies of cloud shadow detection using the algorithm was obtained at producer's accuracy, user's accuracy and κ of 63.79%, 70.58%, and 0.66, respectively. Possibility of improving the algorithm for correcting the reflectance of the objects under the shades instead of removing is discussed.}, keywords = {cloud, Landsat, spectral}, pubstate = {published}, tppubtype = {inproceedings} } The presence of cloud shadows in satellite imageries decreases the reflectance of the objects under the shades to relatively low intensities, leads to identification errors. Thus, cloud shadows detection is crucial in image processing steps. We integrated solar position modelling, projective geometry modelling, and spectral thresholding to detect cloud shadows in Landsat 8 imageries. We evaluated the algorithm using the window area of Mount Halimun-Salak, Bogor, West Java, Indonesia. The best rate accuracies of cloud shadow detection using the algorithm was obtained at producer's accuracy, user's accuracy and κ of 63.79%, 70.58%, and 0.66, respectively. Possibility of improving the algorithm for correcting the reflectance of the objects under the shades instead of removing is discussed. |
2013 |
Seminar, Kudang B; Afnan, Rudi; Solahudin, Mohamad; Wijayanto, Arif K; Arifin, Moh Z; Fatikhunnada, Alvin DESIGN AND OPTIMIZATION OF AGRO-SCM FOR FOOD AND ENERGY A REMOTE MONITORING SYSTEM OF BROILERS' BEHAVIOR IN A MULTI-AGENT BROILER CLOSED HOUSE SYSTEM Inproceedings THE 3rd INTERNATIONAL CONFERENCE ON ADAPTIVE AND INTELLIGENT AGROINDUSTRY (ICAIA) 2015, 2013. @inproceedings{seminar2013design, title = {DESIGN AND OPTIMIZATION OF AGRO-SCM FOR FOOD AND ENERGY A REMOTE MONITORING SYSTEM OF BROILERS' BEHAVIOR IN A MULTI-AGENT BROILER CLOSED HOUSE SYSTEM}, author = {Kudang B Seminar and Rudi Afnan and Mohamad Solahudin and Arif K Wijayanto and Moh Z Arifin and Alvin Fatikhunnada}, year = {2013}, date = {2013-01-01}, booktitle = {THE 3rd INTERNATIONAL CONFERENCE ON ADAPTIVE AND INTELLIGENT AGROINDUSTRY (ICAIA) 2015}, keywords = {broiler}, pubstate = {published}, tppubtype = {inproceedings} } |
Publikasi Ilmiah
Journal Articles |
2020 |
The effect of utilization patterns of green open space on the dynamics change of air quality due to the Covid-19 pandemic in Jabodetabek region Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 10 (4), pp. 559-567, 2020, ISSN: 2460-5824. |
Jakarta and Surabaya land surface temperature before and during the Covid-19 pandemic Journal Article AES Bioflux, 12 (3), pp. 213-221, 2020, ISSN: 2066-7647. |
2018 |
Pemanfaatan Fusi Data Satelit Lapan-a3/IPB dan Landsat 8 Untuk Monitoring Lahan Sawah Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 8 (1), pp. 67–76, 2018, ISSN: 2460-5824. |
Identifying Areas Affected By Fires In Sumatra Based On Time Series Of Remotely Sensed Fire Hotspots And Spatial Modeling Journal Article Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 8 (3), pp. 420–427, 2018, ISSN: 2460-5824. |
2016 |
Mobile-based Expert System for Selecting Broiler Farm Location Using PostGIS Journal Article TELKOMNIKA Indonesian Journal of Electrical Engineering, 14 (1), pp. 360-367, 2016, ISSN: 23-2-9293. |
2015 |
International Journal of Poultry Science, 14 (10), pp. 577, 2015. |
Conferences |
2020 |
211 , E3S Web Conf., 2020, ISSN: 2267-1242. |
211 , E3S Web Conf., 2020, ISSN: 2267-1242. |
211 , E3S Web Conf., 2020, ISSN: 2267-1242. |
211 , E3S Web Conf., 2020, ISSN: 2267-1242. |
Assessing the Agreement between Deforestation Maps of Kalimantan from Various Sources Conference 556 (1), IOP Conf. Ser.: Earth Environ. Sci, 2020. |
Inproceedings |
2019 |
IOP Conference Series: Earth and Environmental Science, pp. 012004, IOP Publishing 2019. |
Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137221, International Society for Optics and Photonics 2019. |
Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia Inproceedings Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137209, International Society for Optics and Photonics International Society for Optics and Photonics, 2019. |
Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia Inproceedings Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137209, International Society for Optics and Photonics International Society for Optics and Photonics, 2019. |
IOP Conference Series: Earth and Environmental Science, pp. 012004, IOP Publishing 2019. |
Sixth International Symposium on LAPAN-IPB Satellite, pp. 1137221, International Society for Optics and Photonics 2019. |
2017 |
Classification model for forest fire hotspot occurrences prediction using ANFIS algorithm Inproceedings IOP Conference Series: Earth and Environmental Science, pp. 012059, IOP Publishing IOP Publishing, 2017. |
Combining projective geometry modelling and spectral thresholding for automated cloud shadow masking in Landsat 8 imageries Inproceedings 2017 European Modelling Symposium (EMS), pp. 22–27, IEEE 2017. |
2013 |
DESIGN AND OPTIMIZATION OF AGRO-SCM FOR FOOD AND ENERGY A REMOTE MONITORING SYSTEM OF BROILERS' BEHAVIOR IN A MULTI-AGENT BROILER CLOSED HOUSE SYSTEM Inproceedings THE 3rd INTERNATIONAL CONFERENCE ON ADAPTIVE AND INTELLIGENT AGROINDUSTRY (ICAIA) 2015, 2013. |
