Autonomous Coastal Land Cover Assessment Using Polarimetric Decomposition of SAR Data

The  paper  reports  an  experiment  on  classification  using  fully polarimetric SAR data.  Many  reports have been presented mentioning test sites in  temperate  regions  utilizing  polarimetric  SAR  data  from  airborne  and/or spaceborne SAR sensors. However, few  studies are dedicated  to  tropical region which highly dynamic land uses are  observed.  Using the AirSAR Sungai Wain fully polarimetric data, capability to extract features in coastal region has been demonstrated  by  an  unsupervised  classification  technique  fed  by  the  CloudePottier decomposition theorem

Tropical Mangrove Mapping Using Fully-Polarimetric Radar Data

Although mangrove is one of important ecosystems in the world, it has been abused and exploited by human for various purposes. Monitoring mangrove is therefore required to maintain a balance between economy and conservation and provides up-to-date information for rehabilitation. Optical remote sensing data have delivered such information, however ever-changing atmospheric disturbance may significantly decrease thematic content. In this research, Synthetic Aperture Radar (SAR) fully polarimetric data were evaluated to present an alternative for mangrove mapping. Assessment using three statistical trees was performed on both tonal and textural data. It was noticeable that textural data delivered fairly good improvement which reduced the error rate to around 5-6% at L-band. This suggests that insertion of textural data is more important than any information derived from decomposition algorithm

Autonomous Coastal Land Cover Assessment Using Polarimetric Decomposition of SAR Data

The paper reports an experiment on classification using fully polarimetric SAR data. Many reports have been presented mentioning test sites in temperate regions utilizing polarimetric SAR data from airborne and/or spaceborne SAR sensors. However, few studies are dedicated to tropical region which highly dynamic land uses are observed. Using the AirSAR Sungai Wain fully polarimetric data, capability to extract features in coastal region has been demonstrated by an unsupervised classification technique fed by the CloudePottier decomposition theorem

Satellite Monitoring of Small-scale Farming Systems in Subang, Indonesia

Rice fields in Java, Indonesia have been in tremendous threat due to land policy weaknesses. In order to ensure food supply, satellite-based monitoring scheme has been chosen to accommodate quick data acquisition for agriculture planning. Nonetheless, detailed rice field map is lacking and it should be taken in consideration. WorldView-2 has the highest ground resolution to date, which is suitable to construct new rice distribution map in Indonesia. This paper shows that panchromatic data of the sensor have capability in identification of fragmented rice fields and clearly showed galengans. Red edge and Coastal bands introduced by WorldView-2 were found substantial to rice growth discrimination. In addition, various rice growth periods were detectable which helped to create of rice status map at appropriate accuracy

Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia

In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents

Rapid Assessment of Agriculture Vulnerability to Drought using GIS

Food production, particularly rice, has been one of the major concerns in Indonesia. Primary threats to production include agricultural land conversion and climate change. In this paper, a GIS-based approach is presented to assess agricultural drought. This approach was developed using the water balance technique, which accounts for spatial population data. We found that agricultural fields in the Upper Bengawan Solo basin were fairly vulnerable to drought, mainly due to expanding Surakarta (Solo) city

Simulasi Pemanfaatan Data Losat Untuk Pemetaan Padi

Simulation onthe Use of LOSAT Data for Rice Field Mapping. Since the launch of LAPAN-TUBSAT satellite in 2007, Indonesia has been developing mission on earth observation missions for various applications. The next generation mission, called LAPAN-ORARI Satellite (LOSAT), is currently under development and expected to be launched in 2011. In order to facilitate the applications, a thorough assessment of the sensor should be made. This paper presents an examination of simulated LOSAT data for rice monitoring and mapping purposes coupled with QUEST statistical tree. We found that three-band simulated LOSAT data were suitable for the task with reasonably high accuracy