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Showing posts from 2017

stream / river Network extraction from a DEM using ArcGIS Desktop

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Hello, this is the second part of my gis hydrology video tutorial at youtube. This time I am going to show you how to extract stream or river network from a DEM in ArcGIS, check it out  

watershed / river basin / catchment extraction in ArcGIS

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Hello, this is my newest published tutorial at youtube. In this tutorial I will show you how to delineate watershed, catchment or river basin from a DEM using ArcGIS Software. thanks for watching and subscribe me at youtube to get notified about future tutorial.

Perbedaan SRTM C-Band DEM dan SRTM X-Band DEM

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Saya tidak tahu apakah sudah banyak orang yang mengetahui apa tidak, tapi saya baru tahu belakangan ini bahwa DEM dari data SRTM itu ada dua versi. Bukan dua versi resolusi spasial (30 meter dan 90 meter) yang saya maksud, tetapi dari dua sensor SAR yang berbeda. Sebagaimana yang kita ketahui, SRTM adalah misi pemetaan topografi global menggunakan two pass interferometry along track menggunakan wahana pesawat ulang alik yang dipasangi sensor Radar SAR. Misi ini dilaksanakan tahun 2000 dan menghasilkan data DEM dengan resolusi 90 meter dan 30 meter untuk seluruh dunia (kecuali daerah dekat lintang tinggi). Misi SRTM dilaksanakan setelah misi pendahuluan sukses dilaksanakan tahun 1994 (misi SIR-C/X-SAR). Hanya misi tahun 1994 tidak dilaksanakan dalam konfigurasi interferometri, sehingga tidak dapat menghasilkan data DEM. Nah misi SRTM tahun 2000 menggunakan sensor dan wahana yang sama dengan misi tahun 1994, sehingga dalam misi ini terdapat dua sensor SAR, satu sensor beroperasi di

KML / KMZ to SHP / Shapefile Conversion in QGIS

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KML (Keyhole Markup Language) or its compressed form KMZ is the file format used in Google Earth or Google Maps products. This format has a similar structure to XML, so it could be opened in Text Editor without any problems. This format is flexible because it is could store vector data as well as raster data. Because it is designed as a geospatial data format in vector or raster, technically it is interoperable with common geospatial data formats like shapefile, geodatabase, MapInfo, or GeoJSON.  And because it is an interoperable geospatial data format, it can be converted into a more common GIS format like shapefile. Many GIS and Remote Sensing software have capabilities to read KML or KMZ and converted them into Shapefile for example. However, you must be careful when you try to convert KML data into Shapefile. It is because KML format stores the attribute data into HTML table, so if your software didn't have capabilities to convert HTML table into native DBF table used in Shape

removing clouds from aerial photographs/satellite imagery in ArcGIS

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DEM Interferometri Menggunakan ALOS PALSAR Data

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Setelah minggu lalu mencoba interferometri dengan Sentinel 1 dan ESA SNAP, minggu ini saya mencoba kembali percobaan interferometri untuk memperoleh DEM, tetapi menggunakan data ALOS PALSAR dan ENVI SARSCAPE. Percobaan saya lakukan dua kali, pertama menggunakan pasangan data ALOS PALSAR Level 1.1 FBS (Fine Beam Single) SLC, dan percobaan kedua menggunakan ALOS PALSAR Level 1.0 FBD (Fine Beam Double) RAW. Untuk pasangan data pertama selisih temporalnya cukup panjang, hampir 10 bulan, sementara untuk percobaan kedua selisih temporalnya lebih singkat, hanya 46 hari. Tahapan pemrosesan yang dilakukan di Percobaan pertama meliputi: 1. Data Import (Sarscape>Import Data>SAR Spaceborne>ALOS PALSAR) 2. Simulated Orbit Correction menggunakan DEM(Sarscape>General Tools>Orbit Correction>automatic Orbit Correction). DEM yang dipakai adalah SRTM90 3. Interferogram Generation (Sarscape>interferometry>Phase Processing>Interferometry Workflow>Interferogram Generation)

3D Raster buffering in ArcGIS

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DEM Interferometri Menggunakan Sentinel 1 SAR Data (Eksperimen)

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Sudah lama sekali saya tidak memperbarui blog ini dengan sebuah tulisan, dan kali ini ada sebuah momen yang saya rasa penting untuk saya tulis. Selain untuk arsip dari apa – apa yang telah saya pelajari, barangkali bisa bermanfaat juga untuk anda pembaca. Tulisan ini bermula dari ketertarikan saya mengikuti kurus penginderaan jauh radar/gelombang mikro yang diadakan oleh ESA (European Space Agency) dalam format online dengan judul ECHOES IN SPACE. Kursus ini gratis dan dapat diikuti siapa saja yang telah memiliki basic pengetahuan penginderaan jauh (cek link INI untuk berpartisipasi). Dari kursus ECHOES IN SPACE, pengetahuan penginderaan jauh system radar/SAR saya jauh meningkat, terutama tentang konsep – konsep teoritisnya, dan hubungannya dengan aplikasi praktisnya. Selama ini memang saya lebih banyak berkutat di penginderaan jauh system optik, dan jarang berkutat di Gelombang Mikro. Meskipun beberapa praktek teknis Radar seperti pembuatan komposit multipolarisasi, geocoding

How to Clip / Subset Raster Using Graphics in ArcGIS

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Creating a subset from larger raster datasets is one of the most basic tasks in Remote Sensing Digital Image Analysis. This task usually needs a dataset to be clipped using a certain extent/bounding box or following a defined polygon called Area of Interest (AOI). All Remote Sensing or GIS Software has this capability. The difference is the clipping implementation in some software is smarter and more effective than the others. Compared to other software, Clip or Subset Raster in ArcGIS can be considered as exceptionally well implemented. Raster clipping in ArcGIS could be done in a permanent-result way or temporary way.  The temporary way has more benefit instead of the permanent way. It can deal with huge datasets but not sacrificing processing time. It is super fast. The definition of the clipping area also flexible. You can use ArcMap View as Clipping extent, using loaded polygon shapefiles as AOI, or even graphic layer as the AOI. If you are curious about the latter, I already prep

clean polygon gap sliver multipart and polygon in polygon in ArcGIS

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How To Download JERS-1 Satellite Imagery Data From JAXA GPortal

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Fill DEM Holes, Voids or Gaps using ArcGIS / Koreksi dan perbaikan DEM di ArcGIS

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Gaps, Hole, or Void problems in a DEM could give some pain in the head for GIS users. gaps will cause the derivated data extracted from a DEM to mess up. Hillshade will lose the color grades, contour line will be jagged and causing a huge amount of wrongly generated lines (makes the filesize raised up exponentially too), slope or aspect data are not accurately mapped, and many others.  Gaps could arise due to the limitation of certain DEM extraction methods, or it happens because of the poor handling of DEM mosaicking. Certain DEM extraction methods like photogrammetric DEM extraction, UAV-based DEM, or interferometric DEM are prone to this gap or voids problem. DEM mosaicking from few sources of DEM that have different map projection is also prone to gaps/voids problem.  Fortunately, many GIS and RS software have provided tools dedicated to fix and correct these holes/gaps problem. DEM editing can be done manually using masking approach or pixel-by-pixel editing, or it could be done a

Satellite Imagery False Color Composite to Natural Color Composite Conversion in ArcGIS

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The ability to create natural color composites is common for the past of current operational earth observation satellites. Natural color composites can be described as RGB image composites that have a color composition just like our eyes perceive color. In natural color composites, water would have a blue color, vegetation is green, bare soil or built-up landcover would have brownish to reddish color. You can make natural color composites images using satellite data that has blue spectral region of the electromagnetic spectrum of the sun. Imagery from satellites such as Landsat, Sentinel-2, IKONOS, Quickbird, Worldview, Pleiades, Kompsat, Formosat, and many others have a blue band so generating natural color composites would be an easy matter.  Things are quite different if we have satellite data that didn't have Blue Band such as ASTER or SPOT. For these kinds of imagery, natural color composites generation must be simulated from the available bands. And the results sometimes woul

Image to Image Georeferencing in ArcGIS Pro ( for Aerial Photographs and Satellite Imagery)

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Georeferencing is a process to reference geospatial data into known and standardized coordinate system. Georeferencing is part of basic task that all GIS users must have ability to do it. Georeferencing can be done in 2D plane or 3D plane, and it can be applied into raster data and vector data. For Raster data, it could be georeferencing aerial photographs, satellite imagery, or scanned maps in image format. For Vector data, georeferencing usually is called spatial adjustment. Most of GIS and remote sensing software available on the market has this georeferencing ability, either for vector data or raster data.  As I already mentioned above, Georeferencing for raster data can be classified into two kinds of raster data. First is Scanned Maps in Image/PDF format, and second is for Satellite Imagery or Aerial Photographs. For earch type of data, the georeferencing procedures are little bit different. In this article I will talks about georeferencing satellite imagery and aerial photograph

Creating Spectral Indices ( NDVI , NDBI , NDWI etc ) in ArcGIS Pro (exam...

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How to Georeference Scanned Map in ArcGIS Pro

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Convert between geospatial data format using OGR GUI

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Cut and Fill Analysis using Contour line in ArcGIS

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Better Editing in ArcGIS using Feature Template

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LAPAN IPB Remote Sensing Satellite (LAPAN A3/LISAT) Now is available to download

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I have got information that I already verify by my self that my country newest remote sensing micro satellite LAPAN A3/LISAT data has been published. You can get the data by ordering to this site :  http://lisat.ipb.ac.id/order/ . Be sure you give the correct information in order to helping the operator to evaluate their product. You will be given an FTP URL accompanied with ID and Password via email you provided. All for free use. LISAT carries two sensors which are MSI (multispectral scanner), a medium resolution multispectral (4 band) imager working on visible blue spectrum to near infrared spectrum at 19 meter resolution and100 km swath width, and DSC (digital space camera), a panchromatic camera at 5 meter resolution and 10 km swath width. Right now, only the MSI data which available in the FTP. I hope they also provide the DSC data at the near future. All other information related to LISAT can you get by reading LISAT baseline information available at  https://directory.

Tutorial Singkat Drone/UAV Untuk Pemetaan Menggunakan Agisoft Photoscan: Bagian Pertama / Tingkat Dasar

Karena download count tutorial sederhana yang saya buat di Slideshare jumlahnya lumayan, saya memutuskan untuk mempublishnya juga di Gplay Book dengan harga sekian rupiah, monggo yang berminat untuk membeli, jangan pikirkan nominal yang anda buang, tapi pikirkan nominal yang anda bisa dapat jika anda menguasai teknik-tekniknya. hihihi dan saya tidak pernah ingin menjadi kapitalis murni, tutorial ini masih anda bisa dapatkan secara gratis di  slideshare.net Here is the Link to GPlay Book https://play.google.com/store/books/details?id=DQrADgAAQBAJ

How to Convert JERS-1 OPS Imagery from CEOS format to GeoTIFF or KMZ

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How to Convert JERS-1 OPS Data in CEOS format to GeoTiff or KMZ in order to use it in Current GIS/Remote Sensing Software  

Geocoding and Fusion Tables, Embedding Experiment

Test Geocoding and Fusion Tables Test Geocoding and Fusion Tables