Sanjiwana Arjasakusuma

Universitas Gadjah Mada | UGM · Geographic Information Science

Hyperspectral sensor captures a large number of narrow and contiguous spectral bands, mostly covering from 400 to 2500 nm of electromagnetic spectrum. This characteristics offer recognition of high-detailed object spectral reflectance, which serve as basic information on object analysis using hyperspectral data. This research aims to study the appl...

This paper explores the suitability of remotely sensed data obtained from Landsat imaging sensors, in combination with ancillary forest inventory data, for the ecological monitoring and management of a production mangrove forest in Malaysia. An assessment is presented on the capabilities and limitations of utilizing Landsat Thematic Mapper data for...

New plantations can either cause deforestation by replacing natural forests or avoid this by using previously cleared areas. The extent of these two situations is contested in tropical biodiversity hotspots where objective data are limited. Here, we explore delays between deforestation and the establishment of industrial tree plantations on Borneo...

Ongoing global warming has triggered extreme climate events of increasing magnitude and frequency. Under this effect, a series of extreme climate events such as drought and increased rainfall during the El Nino Southern Oscillation (ENSO) are expected to be amplified in the coming years. Adequate mapping of regions with climate-sensitive vegetation...

Machine learning has been employed for various mapping and modeling tasks using input variables from different sources of remote sensing data. For feature selection involving high-spatial and spectral dimensionality data, various methods have been developed and incorporated into the machine learning framework to ensure an efficient and optimal comp...

The ability from remote sensing data to observe the same areas at different times of acquisition is beneficial for change detection analysis. Various sensors from passive to active sensors have been employed. However, the development of satellite hyperspectral sensors brings the premise of a more accurate change detection analysis. Our study aims t...

Data on the distribution patterns and locations of food crops are crucial for monitoring and controlling the sustainability of agricultural resources and guaranteeing food security. Plant classification based on machine learning has been widely used to detect food crop areas. However, there are still challenges in mapping plant types and plant area...

The efficient mapping of seaweed cultivation over large areas is essential for supporting sustainable management of coastal resources. This study introduces a novel Spectral-Spatial Deep Learning model that integrates spectral and spatial data from high-resolution remote sensing imagery to automate and improve the accuracy of seaweed cultivation ma...

The availability of a constellation remote sensing satellite system using very high resolution (VHR) synthetic aperture radar (SAR) is beneficial to obtain information from the earth surface in a detail and timely manner. However, the ability to perform digital image classification using SAR data using conventional per-pixel based or object-based m...

Machine learning and deep learning are currently widely used in various fields, including remote sensing for food security. However, there is no research that specifically examines the interests, developments, and trends of this research in the future. This study aims to examine the development of machine and deep learning research for mapping food...

Mount Merbabu National Park (TNGMb) is a forest area in the Mount Merbabu. Management and planting changes have caused many changes to the types of plants in TNGMb. Acacia decurrens is an invasive species and its presence in TNGMb can result in a decrease in the diversity of native vegetation types. This research aims to (1) map the distribution of...

Vegetation is a fundamental component of ecosystems that maintains carbon levels, hydrological cycles, mitigating greenhouse gases, and ensures climate stability. In recent years, the impacts of global climate change have led to changes in vegetation cover at various levels. Efforts to monitor changes in vegetation are important and beneficial for...

Mapping and inventory of the distribution and composition of mangrove vegetation structures are crucial in managing mangrove ecosystems. The availability of airborne LiDAR remote sensing technology provides capability of mapping vegetation structures in three dimensions. It provides an alternative data source for mapping and inventory of the distri...

The land-conversion of rice fields can reduce rice production and negatively impact food security. Consequently , monitoring is essential to prevent the loss of productive agricultural land. This study uses a combination of Sentinel-2 MSI, Sentinel-1 SAR, along with SRTM (elevation and slope data) to monitor rice fields land-conversion. NDVI, NDBI...

The forest ecosystem's pivotal role in the carbon cycle and its impact on the global carbon balance underscore the significance of understanding and mitigating factors that contribute to carbon emissions. This study employs a combination of hyperspectral remote sensing (PRISMA) and machine learning techniques (Random Forest) to estimate the carbon...

Early work in using satellite imagery to map seaweed production has shown there is potential for the information to be used to benefit the industry. Partnership for Australia-Indonesia Research has used refining and enhancing satellite image processing and analysis methods to develop a seaweed production mapping and monitoring system. This deep l...

Forest cover density (FCD) transformation and random decision forest (RDF) classification have been widely used for vegetation mapping. Nevertheless, a comparison of their capabilities in complex tropical landscapes is still rarely carried out. This study compared the two methods using Landsat-8 OLI imagery which includes the blue up to thermal ban...

Tumpahan minyak di laut dapat terdeteksi oleh citra satelit dengan sensor Synthetic Aperture Eadar (SAR) dan memungkinkan untuk diidentifikasi menggunakan berbagai macam metode baik terselia maupun tidak terselia. Salah satu metode terselia yang biasa digunakan adalah digitasi visual, namun metode ini sangat subjektif pada kapasitas interpreter. Un...

Plastic waste monitoring technology based on Earth observation satellites is one approach that is currently under development in various studies. The complexity of land cover and the high human activity around rivers necessitate the development of studies that can improve the accuracy of monitoring plastic waste in river areas. This study aims to i...

Forest fire is a recurring environmental problem in Indonesia. In 2019 there were extensive fires in Indonesia, affecting parts of Jambi and South Sumatra. Therefore, the government tries to continue making efforts to inventory the area of the fires using satellite remote sensing data. This study used the Landsat-8 and Sentinel-2 optical satellites...

Arenga obtusifolia or “langkap” is an invasive palm that interferes with the growth of native vegetation in Ujung Kulon National Park. This study aims to map A. obtusifolia distribution in Ujung Kulon using PRISMA hyperspectral imagery and MESMA (Multiple Endmember Spectral Mixture Analysis). 38 spectra samples for the A. obtusifolia, sand, wetland...

Mangroves can store carbon effectively with a value of about 1,023 Mg C/Ha and become one of the richest forests that store 4-20 billion tons of blue carbon globally. Remote sensing imagery can be used to map mangrove surface carbon stocks using radar and optical image sensors. Generally, forest carbon on earth is stored in two places, namely above...

Indonesia has experienced massive historical land and forest fire events, creating transnational environmental and socioeconomic issues. The extent of burned areas (BAs) is one of many indicators that reflect the magnitudes and impacts from fire events, and such information is also used for planning the response and recovery steps after the fire ev...

Satellite missions which collect hyperspectral data provide detailed spectral information at a lower cost than airborne missions. The newly launched PRISMA hyperspectral mission provides greater swath coverage than the previous Hyperion hyperspectral mission. This study aims to assess the potential use of bitemporal PRISMA datasets for change detec...

The island of Java as the center of activity in Indonesia is experiencing uncontrolled urbanization and industrialization. Urbanization and industrialization are sources of air pollution and increases in air temperature, which can increase the risk of health problems for humans and reduce the comfort level of the city. The assessment of the comfort...

Spatially explicit information on aboveground seagrass carbon stock (AGCseagrass) is required to understand the role of seagrass as a nature-based solution to mitigating and adapting to climate change. Remote sensing provides the most effective and efficient means to map AGCseagrass. This research aimed to assess the accuracy of multispectral image...

Surface temperature is one of the parameters in land–surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperatur...

Crop intensity information describes the productivity and the sustainability of agricultural land. This information can be used to determine which agricultural lands should be prioritized for intensification or protection. Time-series data from remote sensing can be used to derive the crop intensity information; however, this application is limited...

Remote sensing can make seagrass aboveground carbon stock (AGCseagrass) information spatially extensive and widely available. Therefore, it is necessary to develop a rapid approach to estimate AGCseagrass in the field to train and assess its remote sensing-based mapping. The aim of this research is to (1) analyze the Percent Cover (PCv)-AGCseagrass...

Seagrass is one community in benthic habitat that has tremendous benefits for the ecosystem, however the existence of seagrass has been frequently marginalized in recent decades. Seagrass beds functions as a blue carbon ecosystem which are able to absorb carbon higher than terrestrial vegetation. Therefore, it is important to detect and map the sea...

The identification of land cover and land use is necessary to support the strategic management of coastal areas. The utilization of remote sensing technology such as synthetic aperture radar (SAR) data has been widely used for mapping the distribution of land cover and land use. This application includes the detection of aquaculture ponds in coasta...

Actual evapotranspiration (ET) is an important variable used for hydrological cycle analysis, drought monitoring, and water resources management. Field measurement of ET requires a lot of time, money and also produces non-spatial ET values. Satellite-based estimations give advantages to calculate evapotranspiration at a regional scale. This study a...

The sustainability of the global savanna ecosystem is currently under threat from climate and anthropological change. Despite the immense threats, the existence of the savanna ecosystem is undervalued and understudied. This study examined the dynamics of the savanna ecosystem in the southern part of Southeast Asia (SEA) using MODIS leaf area index...

The availability of free Synthetic Aperture Radar (SAR) data of Sentinel 1A/B, with the high temporal resolution, has provoked the usage of time-series backscatter values from the SAR data for mapping paddy field extent and crop phenology. However, paddy field extent mapping over complex terrain areas is rarely conducted, and the effect of terrain...

Dual-polarized (VV and VH) Sentinel-1 Synthetic-Aperture Radar (SAR) Ground Range Detected (GRD) data are available in 9-m spatial resolution and 12-day repeat orbit. A constellation of two satellites, Sentinel 1A and Sentinel 1B, capture these data with ascending and descending orbits, thus increasing the revisit time at the equator to every six d...

Coastal regions are one of the most vulnerable areas to the effects of global warming, which is accompanied by an increase in mean sea level and changing shoreline configurations. In Indonesia, the socioeconomic importance of coastal regions where the most populated cities are located is high. However, shoreline changes in Indonesia are relatively...

The existence and services of mangrove ecosystems in Segara Anakan are threatened by changes in land use on land and global warming, which requires proper and intensive monitoring. The monitoring of mangrove and its trend over large areas can be done using multi-temporal remote sensing technology. However, remote sensing data is often contaminated...

The development of remote sensing (RS) technology has enabled the dynamics of various vegetation biophysical parameters to be monitored, such as the water content of vegetation, fraction of green vegetation, and fluorescence relating to photosynthesis. This study aims to estimate and compare the influence of climate and sea surface temperature (SST...

The rise of Google Earth Engine, a cloud computing platform for spatial data, has unlocked seamless integration for multi-sensor and multi-temporal analysis, which is useful for the identification of land-cover classes based on their temporal characteristics. Our study aims to employ temporal patterns from monthly-median Sentinel-1 (S1) C-band synt...

The accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simp...

Normalized difference vegetation index (NDVI) has been widely applied for monitoring vegetation dynamics. However, NDVI values are known to be profoundly affected by various external factors. In this study, the variation of NDVI values and trends among the several long-term NDVI datasets with resolution of 1, 4 and 8 km were assessed to understand...

The law number 4 : 2011 and Presidential Decree number 9 : 2016 policy in Indonesia regulates the management of standardization and unification of geospatial data called One Map Policy to achieved one geospatial information which is needed across the institution and ministries. Ministry of Energy and Minerals Resources (MEMR) of Republic Indonesia...

Massive deforestation in Indonesia drives the need for proper monitoring using appropriate technology and method. The continuing mission of Landsat sensor extends the observation to almost 30 years back, initiating the ability to monitor the dynamics of vegetation intensively. By taking the advantage of the Landsat archive, advanced semi-automatic...

Paddy field area and its cropping intensity are main information used to measure the crop production and the response of crop to changing climate conditions. Remote sensing technology has been used widely to map cropping pattern of paddy mostly using spectral analysis of multi temporal multispectral data of remote sensing. However, the cropping int...

Distinguishing the vegetation dynamics induced by anthropogenic factors and identifying the major drivers can provide crucial information for designing actionable and practical countermeasures to restore degraded grassland ecosystems. Based on the residual trend (RESTREND) method, this study distinguished the vegetation dynamics induced by anthropo...

This poster demonstrated the way to pre-process AVHRR-based NDVI NESDIS in order to generate monthly and complete long term observation from 1982 to 2016 in Indonesia.

Paddy field area and its cropping intensity are main information used to measure the crop production and the response of crop to changing climate conditions. Remote sensing technology has been used widely to map cropping pattern of paddy mostly using spectral analysis of multi temporal multispectral data of remote sensing. However, the cropping int...

Assessment of long time vegetation phenology is possible by using combination of vegetation indices (VI) data as the proxy of vegetation greenness provided by available remote sensing satellites. However, the VI observations are often lack of agreement and consistencies. We measured the consistencies and agreement of the various NDVI products befor...

The Karimunjawa Islands mangrove forest has been subjected to various direct and indirect human disturbances in the recent years. If not properly managed, this disturbance will lead to the degradation of mangrove habitat health. Assessing forest canopy fractional cover (fc) using remote sensing data is one way of measuring mangrove forest degradati...

The primary product is the closest processing level to the raw image acquired by the sensor. In the process of generating Primary Product, there are various methods of resampling used to generate this product. Among these various methods of resampling, it is not yet known how much of these resampling methods change the spectral value of the final r...

This paper discusses the capability assessment of ALOS data, particularly the AVNIR-2 and PRISM images to support various mapping activities. The studies were carried out with the support from The Remote Sensing Technology Center of Japan (RESTEC), and coordinated by LAPAN Indonesia. In order to assess the ALOS data capability, several image proces...