IDENTIFIKASI FASE PERTUMBUHAN PADI MENGGUNAKAN CITRA SAR (SYNTHETIC APERTURE RADAR) SENTINEL-1

Identifikasi fase pertumbuhan padi dilakukan untuk memperoleh informasi umur dan estimasi produksi padi. Identifikasi fase pertumbuhan tanaman padi terdiri atas tiga fase utama yaitu fase vegetatif, reproduktif, dan pematangan. Kemudian fase utama dijabarkan lebih rinci menjadi sembilan fase yaitu seedling, tillering, stem elongation, panicle, heading, flowering, milk grain, dough grain, dan mature grain. Pemantauan pertumbuhan padi dapat dilakukan menggunakan citra optis maupun radar. Penelitian ini menggunakan citra SAR Sentinel-1 dengan perekaman bulan November 2020 hingga Februari 2021, dan citra optis Sentinel-2. Citra SAR Sentinel-1A dapat menggambarkan pertumbuhan padi mengikuti fase tumbuh dengan mengektraksi nilai backscatter dari petak sawah yang dijadikan sampel penelitian. Hasilnya menunjukkan bahwa polarisasi tunggal VH memiliki korelasi paling baik yang menggambarkan nilai backscatter citra dan fase pertumbuhan padi dengan korelasi (R²) sebesar 0.77. Sedangkan algoritma Polarization Index (PI) memiliki korelasi (R²) 0.56. Kombinasi citra SAR Sentinel-1A dan Sentinel-2 dengan waktu perekaman yang sama atau mendekati dimanfaatkan untuk interpretasi training area dalam prose klasifikasi. Kombinasi RGB citra Sentinel-1 dan Sentinel-2 yang digunakan yaitu R=S2-B4 G=S2-B3 B=S1-VH. Klasifikasi fase pertumbuhan menggunakan algoritma random forest dengan komposit RGB (R=VV G=VH B=VV/VH) menghasilkan akurasi sebesar 75%

Monitoring active open-pit mine stability in the Rhenish coalfields of Germany using a coherence-based SBAS method

With the recent progress in synthetic aperture radar (SAR) technology, especially the new generation of SAR satellites (Sentinel-1 and TerraSAR-X), our ability to assess slope stability in open-pit mines has significantly improved. The main objective of this work is to map ground displacement and slope instability over three open-pit mines, namely, Hambach, Garzweiler and Inden, in the Rhenish coalfields of Germany to provide long-term monitoring solutions for open-pit mining operations and their surroundings. Three SAR datasets, including Sentinel-1A data in ascending and descending orbits and TerraSAR-X data in a descending orbit, were processed by a modified small baseline subset (SBAS) algorithm, called coherence-based SBAS, to retrieve ground displacement related to the three open-pit mines and their surroundings. Despite the continuously changing topography over these active open-pit mines, the small perpendicular baselines of both Sentinel-1A and TerraSAR-X data were not affected by DEM errors and hence could yield accurate estimates of surface displacement. Significant land subsidence was observed over reclaimed areas, with rates exceeding 500 mm/yr, 380 mm/yr, and 310 mm/yr for the Hambach, Garzweiler and Inden mine, respectively. The compaction process of waste materials is the main contributor to land subsidence. Land uplift was found over the areas near the active working parts of the mines, which was probably due to excavation activities. Horizontal displacement retrieved from the combination of ascending and descending data was analysed, revealing an eastward movement with a maximum rate of ∼120 mm/yr on the western flank and a westward movement with a maximum rate of ∼ 60 mm/yr on the eastern flank of the pit. Former open-pit mines Fortuna-Garsdorf and Berghein in the eastern part of Rhenish coalfields, already reclaimed for agriculture, also show subsidence, at locations reaching 150 mm/yr. The interferometric results were compared, whenever possible, with groundwater information to analyse the possible reasons for ground deformation over the mines and their surroundings

Persistent Scatterer Interferometry in the post-event monitoring of the Idukki Landslides

The monitoring of pre-failure movements and their evolution over time is necessary to assess the predisposing and triggering factors. This research focusses on assessing terrain displacements in the Idukki district (Kerala, India) over a year before the deadly disaster, which occurred in August 2018; this disaster was claimed to be a dreadful one as it took off hundreds of human lives and properties. The post-event Persistent Scatterers interferometric analysis on a stack of 20 Sentinel-1 images was performed to analyse the precursory deformations of the landslides. From the results obtained, the study region is estimated to have undergone a displacement of -26 to +19 mm/year, which indicates the instability of the terrain. Also it is evident that the occurrence of the landslides in August 2018, has been due to the effect of the torrential rainfall and the increase in the pore water inducing instability, thereby causing displacement in the region

PSINSAR COHERENCE BASED DISPLACEMENT ANALYSIS OF KRISHNA DELTA USING SENTINEL-1 INTERFEROMETRIC WIDE SWATH DATA

The problem of decorrelation leading to loss of coherence has been a major source of concern to identify the various problems of erosion and deposition in delta. In this study, Permanent Scatter Interferometric SAR (PsInSAR) technique was used to identify the Permanent Scatter Candidates (PSCs) to explore its potential in identifying displacement based on coherence of various features in delta during the dry and wet periods. PSCs are coherent over interferograms acquired during different time periods. The study was conducted using Sentinel-1 C-band Interferometric Wide (IW) swath datasets acquired from 25th October 2016 to 10th June 2017 over Krishna Delta. The datasets were deramped and stitched prior to co-registering the master and slave images. Interferograms were generated, phase unwrapped and filtered after which the PSCs were identified based on Amplitude Stability index. The problem of tropospheric phase delay causing decorrelation was removed based on the difference in the phase residual of the connected PSCs. Ps coherence map was generated showing coherence as low as 0.28 to 0.38 in mangroves due to volume decorrelation and 0.5 to 0.85 in village areas. A prominent feature, vernal pool exhibited high variation in coherence (0.28 to 0.45) depending on monsoon or summer season. An integrated cumulative displacement map was generated indicating the areas where erosion and deposition has taken place and these depositional values of certain deltaic features were in conjunction with coherence

Subsidence analysis in DKI Jakarta using Differential Interferometry Synthetic Aperture Radar (DInSAR) Method

Land subsidence in DKI Jakarta influenced by several key factors, including the number of buildings that increase the load above the surface. There are still many people who explore groundwater sources as the principal source of clean water. Also,  the soil type is dominated by alluvial. This alluvial deposit can be one of the parameters for soil deformation in the form of land subsidence and uplift in land surface because basically, alluvial soil types have a susceptibility to the load support power above. So that the land subsidence in DKI Jakarta is relatively continuous. To find out the land subsidence is used a high-tech method,  Differential Interferometry Synthetic Aperture Radar (DInSAR) satellite image of radar data (SAR Sentinel-1A) in 2017. The result shows the land subsidence in the average value of DKI Jakarta which is about -3.685 cm/year and the highest subsidence happened in the West Jakarta district about -5.850 cm/year in average

Application of Time Series InSAR (SBAS) Method using Sentinel-1A Data for Land Subsidence Detection in Surabaya City

We studied land subsidence occurrence in Surabaya, considering the rapid urban growth in the city. It is evidenced by the increasing number of buildings (e.g., houses, apartments, offices) that have been realized before 2015 and the increasing transport activities in the industrial area. Land subsidence is a vertical deformation on the land surface that can be caused by landslides, earthquakes, soil consolidation process, or even human-made activities, depending on the material characteristics of the area. In this study, Time-series InSAR (TS-InSAR), specifically the Small Baseline Subset (SBAS) method, is applied to obtain the Line-of-Sight (LOS) velocities and time-series LOS displacements in Surabaya between May 2015 and September 2017. We used 28 Sentinel-1A data (IW mode) acquired by using Terrain Observation with Progressive Scan (TOPS) operation with the spatial resolution of 5 ´ 20 m and covers the area of 250 km2. DEM SRTM with 30 m spatial resolution was used to reduce topography effect contribution in the interferograms. Based on the SBAS method, interferogram pair selection is applied with the maximum value of 150 m for the perpendicular baseline and 100 days for the temporal baseline. The DInSAR process successfully generated seventy-four (74) interferogram pairs, and then by using SBAS algorithm, the LOS velocity and time-series LOS displacement were estimated. The results showed the varying displacements respond with the significant subsidence occurred in the North, East, and Southeast part of Surabaya. The SBAS result confirmed that the LOS velocity over the Surabaya area between May 2015 and September 2017 ranges from -40 to +30 mm/year. Significant land subsidence occurred in the Asemrowo area (North Surabaya) with the value of LOS displacement velocity up to -45 mm/yr.

Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry

Land subsidence in urban environments is an increasingly prominent aspect in the monitoring and maintenance of urban infrastructures. In this study we update the subsidence information over Rome and its surroundings (already the subject of past research with other sensors) for the first time using Copernicus Sentinel-1 data and open source tools. With this aim, we have developed a fully automatic processing chain for land deformation monitoring using the European Space Agency (ESA) SentiNel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). We have applied this automatic processing chain to more than 160 Sentinel-1A images over ascending and descending orbits to depict primarily the Line-Of-Sight ground deformation rates. Results of both geometries were then combined to compute the actual vertical motion component, which resulted in more than 2 million point targets, over their common area. Deformation measurements are in agreement with past studies over the city of Rome, identifying main subsidence areas in: (i) Fiumicino; (ii) along the Tiber River; (iii) Ostia and coastal area; (iv) Ostiense quarter; and (v) Tivoli area. Finally, post-processing of Persistent Scatterer Inteferometry (PSI) results, in a Geographical Information System (GIS) environment, for the extraction of ground displacements on urban infrastructures (including road networks, buildings and bridges) is considered

Estimating Solar Energy Production in Urban Areas for Electric Vehicles

Cities have a high potential for solar energy from PVs installed on buildings\u27 rooftops. There is an increased demand for solar energy in cities to reduce the negative effect of climate change. The thesis investigates solar energy potential in urban areas. It tries to determine how to detect and identify available rooftop areas, how to calculate suitable ones after excluding the effects of the shade, and the estimated energy generated from PVs. Geographic Information Sciences (GIS) and Remote Sensing (RS) are used in solar city planning. The goal of this research is to assess available and suitable rooftops areas using different GIS and RS techniques for installing PVs and estimating solar energy production for a sample of six compounds in New Cairo, and explore how to map urban areas on the city scale. In this research, the study area is the new Cairo city which has a high potential for harvesting solar energy, buildings in each compound have the same height, which does not cast shade on other buildings affecting PV efficiency. When applying GIS and RS techniques in New Cairo city, it is found that environmental factors - such as bare soil - affect the accuracy of the result, which reached 67% on the city scale. Researching more minor scales, such as compounds, required Very High Resolution (VHR) satellite images with a spatial resolution of up to 0.5 meter. The RS techniques applied in this research included supervised classification, and feature extraction, on Pleiades-1b VHR. On the compound scale, the accuracy assessment for the samples ranged between 74.6% and 96.875%. Estimating the PV energy production requires solar data; which was collected using a weather station and a pyrometer at the American University in Cairo, which is typical of the neighboring compounds in the new Cairo region. It took three years to collect the solar incidence data. The Hay- Devis, Klucher, and Reindl (HDKR) model is then employed to extrapolate the solar radiation measured on horizontal surfaces β =0°, to that on tilted surfaces with inclination angles β =10°, 20°, 30° and 45°. The calculated (with help of GIS and Solar radiation models) net rooftop area available for capturing solar radiation was determined for sample New Cairo compounds . The available rooftop areas were subject to the restriction that all the PVs would be coplanar, none of the PVs would protrude outside the rooftop boundaries, and no shading of PVs would occur at any time of the year; moreover typical other rooftop occupied areas, and actual dimensions of typical roof top PVs were taken into consideration. From those calculations, both the realistic total annual Electrical energy produced by the PVs and their daily monthly energy produced are deduced. The former is relevant if the PVs are tied to a grid, whereas the other is more relevant if it is not; optimization is different for both. Results were extended to estimate the total number of cars that may be driven off PV converted solar radiation per home, for different scenarios