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DEM ( Digital Elevation Model ) extraction is one of popular topic in GIS and Remote Sensing. There are so many ways and methods to produce a DEM. You can use survey data in points format then interpolate it to became raster DEM, or using contour lines to generate DEM. Almost every GIS and Remote Sensing can do this kind of analysis. The better approach and yielding a better result is using Photogrammetry techniques. For photogrammetry, you needs satellite imagery or aerial photographs that has image overlap between flight line that later can be opened together in a photogrammetric software, and then from the overlaps, height and elevation information could be reconstructed and sampled together in their respective grids, and finally a DEM has been created.  Recent development of survey technology has introduce us to LIDAR technology that enabling us to get a DEM in superfine resolution and covering large area. UAV technology is also progressed so much even photogrammetry survey can be

Tulisan ini berangkat dari postingan saya dua tahun yang lalu di SINI dan di SINI . Setelah lewat dua tahun, saya semakin memahami konsep, proses dan metode teknis dari INSAR. Kunci pentingnya sudah saya kemukakan di dua postingan di atas, yaitu koherensi. Koherensi yang bagus hanya dapat diperoleh jika, (1) selisih waktu perekaman citra SAR nya sesingkat mungkin (terutama untuk frekuensi C-Band)  (2) perpendicular baseline lengthnya cukup panjang tapi juga tidak terlalu panjang (100- 1000 m) Kemarin, saya akhirnya mengetahui proses download data SAR yang lengkap dari ESA (akan saya posting tutorialnya di youtube channel geo2004). Dari situ saya memperoleh informasi tentang adanya tandem mission antara satelit ERS-1 dan ERS-2 pada tahun 1995-1997, yang memungkinkan untuk memperoleh data SAR interferometri dengan selisih waktu 1 hari. Saya kemudian mendownload satu pair untuk wilayah Yogyakarta (direkam pada tanggal 21 mei 1996 dan 22 mei 1996), dan memprosesnya di ESA SNAP. Ber

This article is a continuation from my previous post about how to perform Wind Direction and Speed Estimation from SAR data. In previous post that you can also read from this blog, I have shown how to directly measure Wind Speed and Wind Direction using ENVISAT-ASAR data. And you can also perform this kind of analysis using other kind SAR Sensors like ALOS PALSAR, Sentinel-1 or ERS.  Now for this post, I will talks about post-processed wind speed and wind direction data generated from Sentinel-1 SAR data. Why Post-Processed ? because ESA already publish wind data from Sentinel-1 into Sentinel-1 OCN Product. So if you are using this OCN product, you dont have to generate Wind Speed and Wind Direction by yourself.  The video tutorial below demonstrate how to get those wind parameters data from Sentinel-1 OCN Product, using ESA-SNAP Software. Hopefully it will find some use to you out there. 

SAR (Synthetic Aperture Radar) data can have many information about earth surface that cant be obtained from Optical or thermal imagery. One of them is Ocean Winds data. Using SAR data, you can perform wind speed and direction estimation at the ocean area by analyzing the winds streaks that well recorded in SAR data. This wind speed and direction is an essential data in Oceanography or Marine Geomorphology because this data can be used for coastal dynamic analysis. On the other hand, direct wind measurement in the field sometimes costly and hard to do.  I am going to deliver this topic into two parts. First is about how to measure wind speed and direction using SAR Data, and second is how to get post processed wind direction and speed data from publicly available SAR data.  Now about how to directly measure wind speed and direction from SAR data, I already made a tutorial about how to do it in ESA-SNAP. ESA SNAP is a remote sensing software developed by European Space Agency (ESA) dedi

SAR data can be used for many types of applications. Distinct characteristics compared to optical imagery makes SAR data stand out in its own way. One of the applicable use of SAR data is for maritime transport monitoring. SAR data with its unique backscatter mechanism could be used for ship detection and tracking. This is possible because the body of the ship double bouncing the radar backscatter when it is returned to the sensor, so the recorded energy would be doubling out and makes the ships look so bright in the SAR images compared to the water background that has low pixels value. And because radar SAR imagery is geocoded to a known coordinate system, finding the ship's coordinates at a certain time is also quite easy.  Now if we have operational SAR satellites that have a short temporal revisit (one day for example), the ship's detection, and tracking would be better because we could monitor the ship's position daily. We don't have this kind of service right now

Sentinel Satellite Imagery is known for the popularity on geospatial data sources in recent years. First, it is free to use and free to download, second, it is ranging from medium resolution to high resolution, third, it comes from Optical Remote Sensing Spectrum to Microwave SAR Spectrum. It is all gives a comprehensive and holistic data usage experience for the users. The data access and download support are also easy and straightforward. You can access it from Copernicus SciHub, USGS earth explorer, ASF Data Facility, and many geoportals developed by EU Agencies or Private companies. Sentinel data is also stored in AWS (Amazon Web Services) and has declared as an open repository/buckets in AWS, so you can also use the data in a cloud computing environment. This is why many users have been using the sentinel data in clouds (for example, Google Earth Engine Users have been used the AWS repo for the last few years, and many geospatial algorithms or automated processing code have been d