6,658 research outputs found
Perbandingan Akurasi Klasifikasi Penutup Lahan Hasil Penggabungan Citra ALOS AVNIR-2 dan ALOS PALSAR pada Polarisasi Berbeda dengan Transformasi Wavelet
Penggabungan citra merupakan salah satu alternatif dari penggunaan citra penginderaan jauh yang konvensional atau secara individu. Penelitian ini mengkaji peningkatan akurasi klasifikasi citra ALOS PALSAR yang digabungkan dengan citra ALOS AVNIR-2.Transformasi wavelet digunakan dalam proses penggabungan citra, mengacu pada kemampuannya mempertahankan kualitas spektral citra. Akurasi total dan indeks kappa pada citra ALOS AVNIR-2 85.26% dan 78.90%, pada citra gabungan I (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HH) 76.84% dan 67.06%, pada citra gabungan II (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HV) 71.58% dan 58.64%. Ditinjau dari hasil tersebut citra gabungan mempunyai akurasi yang lebih rendah daripada citra ALOS AVNIR, namun dibanding pada hasil klasifikasi citra ALOS PALSAR polarisasi HH (59.38% dan 45.97%) dan citra ALOS PALSAR polarisasi HV (64.06% dan 49.55%) proses penggabungan citra yang dilakukan menunjukkan peningkatan akurasi
Effect of Terrain Configuration on the Performance of SRTMv3 and ALOS PALSAR DEMs Over the Federal Capital Territory (FCT), Nigeria.
Digital Elevation Model (DEM) and its resulting parameters are essential terrain related information. DEM and the extracted information (slope, aspect, roughness etc.) have been identified as one of the most important and fundamental variables to various streams of engineering and planning designs which are the hall marks of development all over the world. Thus, to delineate the major surface and subsurface structures for evaluating the Planning framework for the Federal Capital City of Nigeria, analyzing the effects of terrain configuration of Shuttle Radar Topographic Mission (SRTMV3) and ALOS PALSAR DEM data is very crucial. Hence this paper aimed at examining the effects of terrain configuration of Shuttle Radar Topographic Mission (SRTMV3) and ALOS PALSAR DEM. The methodology involved data acquisition of ALOS PALSAR, SRTMV3 and Ortho DEMs, after which the ALOS PALSAR and SRTMV3 DEMs were resampled to 10m of the Ortho DEM, image classification and then an assessment of the impact of terrain configuration on DEM performance with horizontal profiles was carried out. The results revealed that SRTMV3 v3 performed better with close resemblance with the Ortho DEM on flat and undulating terrain while it underestimated the rolling terrain and overestimated the hilly and mountainous terrain. ALOS PALSAR DEM when compared against the Ortho DEM grossly overestimated all the terrain configuration in the study area. In all, the overall performance of SRTMV3 v3 had a close resemblance in performance to that of the Ortho DEM, while ALOS PALSAR had a significant difference in performance. It was therefore recommended that SRTMV3 v3 should be used as an alternative DEM source where high-resolution elevation data are not readily available. Keywords: ALOS PALSAR, Digital Elevation Model, SRTM, Terrain modelling. DOI: 10.7176/JEES/10-6-14 Publication date:June 30th 202
PEMANFAATAN CITRA SATELIT ALOS-PALSAR UNTUK PEMETAAN KELEMBABAN TANAH ( STUDI KASUS : WILAYAH KABUPATEN PASER, KALIMANTAN TIMUR )
Kelembaban tanah merupakan rasio kandungan air di bawah permukaan tanah yang merupakan parameter utama di berbagai bidang seperti hidrologi, pertanian dan meteorology. Sejalan dengan perkembangan teknologi, identifikasi kelembaban tanah dapat pula dilakukan melalui teknik penginderaan jauh. Salah satu citra penginderaan jauh yang dapat digunakan untuk estimasi nilai kelembaban tanah adalah citra satelit ALOS-PALSAR.
Penelitian ini bertujuan untuk mengetahui nilai kelembaban tanah berdasarkan citra satelit ALOS-PALSAR wilayah Kabupaten Paser. Data yang digunakan adalah data citra satelit ALOS-PALSAR polarisasi HH dan VV. Parameter penentu estimasi nilai kelembaban tanah adalah nilai hambur-balik dan nilai konstanta dielektrik. Nilai kelembaban tanah di estimasi dengan persamaan Dubois dkk.,(1995). Untuk mengetahui akurasi hasil estimasi nilai kelembaban tanah, dilakukan pengukuran sampel nilai kelembaban tanah di wilayah Kabupaten Paser dengan menggunakan soil moisture meter tester.
Hasil penelitian ini menunjukan rentang nilai kelembaban tanah di wilayah Kabupaten Paser berdasarkan citra satelit ALOS-PALSAR padabulan Mei tahun 2009 adalah 1 – 25 % Mv dengan klasifikasi berada pada kelas kelembaban tanah kering (Dry). Pada hasil uji akurasi dengan menggunakan 40 sampel pengukuran kelembaban tanah diperoleh nilai overall accuracy sebesar 87,5 %.
Kata Kunci : Kelembaban Tanah, Citra ALOS-PALSAR, Nilai Kelembaban Tanah
Perbandingan Akurasi Klasifikasi Penutup Lahan Hasil Penggabungan Citra ALOS AVNIR-2 dan ALOS PALSAR pada Polarisasi Berbeda dengan Transformasi Wavelet
Penggabungan citra merupakan salah satu alternatif dari penggunaan citra penginderaan jauh yang konvensional atau secara individu. Penelitian ini mengkaji peningkatan akurasi klasifikasi citra ALOS PALSAR yang digabungkan dengan citra ALOS AVNIR-2.Transformasi wavelet digunakan dalam proses penggabungan citra, mengacu pada kemampuannya mempertahankan kualitas spektral citra. Akurasi total dan indeks kappa pada citra ALOS AVNIR-2 85.26% dan 78.90%, pada citra gabungan I (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HH) 76.84% �dan 67.06%, pada citra gabungan II (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HV) 71.58% dan 58.64%. Ditinjau dari hasil tersebut citra gabungan mempunyai akurasi yang lebih rendah daripada citra ALOS AVNIR, namun dibanding pada hasil klasifikasi citra ALOS PALSAR polarisasi HH (59.38% dan 45.97%) dan citra ALOS PALSAR polarisasi HV (64.06% dan 49.55%) proses penggabungan citra yang dilakukan menunjukkan peningkatan akurasi.Kata kunci: Penggabungan citra, Wavelet, Akurasi, Wang bovic, Maximum likelihoo
Mapping annual forest cover by fusing PALSAR/PALSAR-2 and MODIS NDVI during 2007–2016
Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) HH and HV polarization data were used previously to produce annual, global 25 m forest maps between 2007 and 2010, and the latest global forest maps of 2015 and 2016 were produced by using the ALOS-2 PALSAR-2 data. However, annual 25 m spatial resolution forest maps during 2011–2014 are missing because of the gap in operation between ALOS and ALOS-2, preventing the construction of a continuous, fine resolution time-series dataset on the world's forests. In contrast, the MODerate Resolution Imaging Spectroradiometer (MODIS) NDVI images were available globally since 2000. This research developed a novel method to produce annual 25 m forest maps during 2007–2016 by fusing the fine spatial resolution, but asynchronous PALSAR/PALSAR-2 with coarse spatial resolution, but synchronous MODIS NDVI data, thus, filling the four-year gap in the ALOS and ALOS-2 time-series, as well as enhancing the existing mapping activity. The method was developed concentrating on two key objectives: 1) producing more accurate 25 m forest maps by integrating PALSAR/PALSAR-2 and MODIS NDVI data during 2007–2010 and 2015–2016; 2) reconstructing annual 25 m forest maps from time-series MODIS NDVI images during 2011–2014. Specifically, a decision tree classification was developed for forest mapping based on both the PALSAR/PALSAR-2 and MODIS NDVI data, and a new spatial-temporal super-resolution mapping was proposed to reconstruct the 25 m forest maps from time-series MODIS NDVI images. Three study sites including Paraguay, the USA and Russia were chosen, as they represent the world's three main forest types: tropical forest, temperate broadleaf and mixed forest, and boreal conifer forest, respectively. Compared with traditional methods, the proposed approach produced the most accurate continuous time-series of fine spatial resolution forest maps both visually and quantitatively. For the forest maps during 2007–2010 and 2015–2016, the results had greater overall accuracy values (>98%) than those of the original JAXA forest product. For the reconstructed 25 m forest maps during 2011–2014, the increases in classifications accuracy relative to three benchmark methods were statistically significant, and the overall accuracy values of the three study sites were almost universally >92%. The proposed approach, therefore, has great potential to support the production of annual 25 m forest maps by fusing PALSAR/PALSAR-2 and MODIS NDVI during 2007–2016
Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar
We present a technique and results of 2-D imaging of Faraday rotation and total electron content using spaceborne L band polarimetric synthetic aperture radar (PolSAR). The results are obtained by processing PolSAR data collected using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) on board the Advanced Land Observation Satellite. Distinguished ionospheric inhomogeneities are captured in 2-D images from space with relatively high resolutions of hundreds of meters to a couple of kilometers in auroral-, middle-, and low-latitude regions. The observed phenomena include aurora-associated ionospheric enhancement arcs, the middle-latitude trough, traveling ionospheric disturbances, and plasma bubbles, as well as ionospheric irregularities. These demonstrate a new capability of spaceborne synthetic aperture radar that will not only provide measurements to correction of ionospheric effects in Earth science imagery but also significantly benefit ionospheric studies
RIP CURRENTS SIGNATURES ZONE DETECTION ON ALOS PALSAR IMAGE AT PARANGTRITIS BEACH, INDONESIA
Having bay and gulf morphology as cresentic beach, Parangtritis coast has been known potentiallythreat by rip currents hazard. This study aims to identify and detect breaking wavesregion and surf zone on ALOS PALSAR images, and identify and extract the cove shapeshoreline morphology of Parangtritis beach. ALOS PALSAR Fine Beam Single (FBS) HH polarizationacquired on 2nd May 2007 and 17th June 2007, off nadir angle 34.3º, and in descendingmode level 1.0 were utilized to derive amplitude information using Sigmasar. Shorelinemorphology detection showed that the cusps system has not changed much during May toJune 2007 when PALSAR images acquired, but might have shifted individually. The use ofoptical sensor with the same spatial resolution, ALOS AVNIR-2, supports to distinguish theboundary and determine the shoreline morphology of Parangtritis beach
Karakterisktik Backscatter Citra Alos Palsar Polarisasi Hh dan Hv terhadap Parameter Biofisik Hutan di Sebagian Taman Nasional Kerinci Seblat
Synthetic Aperture Radar (SAR) is one kind of an active remote sensing system, utilizing microwave to records the earth surface. One of the SAR\u27s satellites is ALOS PALSAR which is capable of penetrating clouds so that the underlying objects can be identified. ALOS PALSAR has a polarization system operating with single beam polarization (HH or HV), dual polarization (HH + HV or VV + VH) and full polarization (HH + HV + VH + VV). This study aims to use the backscatter value of ALOS PALSAR\u27s image for monitoring and mapping the forest. The Utilization of ALOS PALSAR imagery to measure forest biophysical parameters and saturation levels identified based on backscatter sensitivity. Image extraction is done through image calibration where the digital value is converted to sigma naught backscatter value then the result of calibration unit is changed to decibels. Backscatter sensitivity depends on forest structure which can affect scattering mechanism. The backscatter value is also influenced by humidity and weather dynamics which can also affect the dielectric constant. The result of accurate classification of land use polarization fall in HH accuracy of 62,4%. Whereas for HV polarization accuracy obtained equal to 74,88%.
 
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