Comparative Study of Landsat and Aster Data by Morphometric Analysis

In this paper, a case-study is presented to differentiate between Landsat and Aster data by morphometric analysis. For this the Aster and Landsat digital elevation model (DEM) data of the same study area was taken and then both the data was delineated for the same (common) outlet. The major differences found in between Landsat and Aster data after delineation are in the number of first order stream, axial length of streams, average width and size of watershed. The case study presented will be useful in demonstrating the fact that Landsat DEM has better accuracy than Aster DEM for land cover areas when the DEM data characteristic are kept similar

Simulation of ASTER data using AVIRIS images

The Advanced Thermal Emission and Reflectance Radiometer (ASTER) is a joint Japanese/US imaging instrument scheduled to fly on the first Earth Observing System (EOS) platform in 1998. The complement of scanners includes a visible, three channel module with forward-looking stereo capability, a six channel short wavelength infrared module, and a five channel thermal module. As part of the definition phase for the instrument design, AVIRIS data was used to simulate the short wave infrared (SWIR) bands to investigate the effects of widening two of the bands to increase the signal-to-noise ratio (SNR) versus loss of spectral separability due to uncertainty in the post-launch band positions

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite

Glacier mapping in high mountains using DEMs, Landsat and ASTER data

Glaciers are sensitive climate indicators and thus subject to monitoring of environmental and climate changes. Remote sensing techniques are often the only way to analyze glaciers in remote mountains and to monitor a large number of glaciers at the same time. Although several glacier mapping methods exist, often, results are still not good enough for in-depth conclusions. In particular, this is true for debris-covered glaciers. For the Bernina Group in the Swiss Alps and for the northern Tien Shan in Kazakhstan and Kyrgyzstan a glacier mapping was undertaken employing digital elevation models (DEMs). DEMs were generated from ASTER and SRTM3 data and compared with each other and -for the Bernina Group-compared with the Swiss DHM25L2. Whereas ASTER DEM elevations are too high on average, SRTM3 DEM elevations are slightly too low. However, both DEMs are of good use for glacier delineation. The glacier mapping approach includes Landsat TM4/TM5-ratio images, multispectral and morphometric analysis. Results are satisfying for debris-free and larger debris-covered glaciers in both study areas. The next step should be an automated glacier mapping method

Identifikasi Dan Klasifikasi Peruntukan Lahan Menggunakan Citra Aster (Landuse Identification and Classification Using Aster Multispectral Data)

ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) is classified as new sensor based on the TERRA satellite developed in the recent years. ASTER has been developed to provide image for monitoring environmental phenomenon. ASTER data offer more option for spatial resolution (60m, 30m and 15m) and more spectral resolution that suppose sufficient to capture main nomenclature of land use than usual imagery (e.g.: Landsat TM). This article shows the process of image treatment, classification, and interpretation of ASTER data to classify land use at Sampean Watershed. Two method of classification (supervised and unsupervised) are then compared to obtain the best classification. Methodology comprise of: pre-processing, survey, classification and interpretation. Classification is conducted using un-supervised and supervised methods. The classification results of these two methods are then compared to digital map (peta RBI). Supervised classification identified 7 main features of land use, while un-supervised classification only identified 3 main class of land use. The works show that supervised classification enhances the number of land use features identified and classified

Site Characterization Using Integrated Imaging Analysis Methods on Satellite Data of the Islamabad, Pakistan, Region

We develop an integrated digital imaging analysis approach to produce a first-approximation site characterization map for Islamabad, Pakistan, based on remote-sensing data. We apply both pixel-based and object-oriented digital imaging analysis methods to characterize detailed (1:50,000) geomorphology and geology from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. We use stereo-correlated relative digital elevation models (rDEMs) derived from ASTER data, as well as spectra in the visible near-infrared (VNIR) to thermal infrared (TIR) domains. The resulting geomorphic units in the study area are classified as mountain (including the Margala Hills and the Khairi Murat Ridge), piedmont, and basin terrain units. The local geologic units are classified as limestone in the Margala Hills and the Khairi Murat Ridge and sandstone rock types for the piedmonts and basins. Shear-wave velocities for these units are assigned in ranges based on established correlations in California. These ranges include Vs30-values to be greater than 500 m/sec for mountain units, 200–600 m/sec for piedmont units, and less than 300 m/sec for basin units. While the resulting map provides the basis for incorporating site response in an assessment of seismic hazard for Islamabad, it also demonstrates the potential use of remote-sensing data for site characterization in regions where only limited conventional mapping has been done

A System Development for Remote Sensing, and Interpretation for Rice Fields in the World Using Satellite Data

Remote Sensing Laboratory, Field Science Center, Graduate School of Agriculture Science, Tohoku University started at April 2004. For the studies and education at the laboratory we are now developing the system of remote sensing and GIS. Our system consists of ordinary PCs, one digitizer and one color laser printer. The PCs are assembled by us for the optimal performance and the low cost. Gigabit LAN connects each PC, and one PC is used as file server to store remote sensing images and GIS data such as digital maps, geocoded satellite images and digital elevation models (DEM). The file server has RAID system for safety storage from HD trouble. We use ARC/GIS as GIS software and many kinds of Remote Sensing software such as, ERDAS/Imagine, ENVI, eCognition, PG-Steamer and SILCAST. Using the developing system, we understand and teach for regional differences of agriculture especially with the interpretation of ASTER data analysis. A kind of project "Determination of Local Characteristics at Global Agriculture Using archive ASTER Data" was started at the middle of November 2005. We establish data processing system and get some results. Paddy rice fields analysis was started at first, we analyze 1) the Shonai Plains in Japan, 2) the Yangtze River delta in Middle-East China, 3) Mekong Delta in South Vietnam, 4) North-east Thai Plaines, Thailand, 5) Sacrament Valley, California, USA. The results of this studies are as follows, 1) Using ASTER images, we can easily understand agricultural characteristics of each local area. 2) ASTER data have high accuracy for location, and the accuracy is suitable for global study without the fine topographical maps, 3) By five years observation of ASTER, there are huge numbers of ASTER scenes, but not enough volumes for cloud free data for seasonal analysis. It means that follow-on program of ASTER is necessary, 4) We need not only paddy field, but also all crop fields and all area, 5) The studies are necessary to international corroboration.Original Pape

EAGLE 2006 – Multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest

EAGLE2006 - an intensive field campaign - was carried out in the Netherlands from the 8th until the 18th of June 2006. Several airborne sensors - an optical imaging sensor, an imaging microwave radiometer, and a flux airplane – were used and extensive ground measurements were conducted over one grassland (Cabauw) site and two forest sites (Loobos & Speulderbos) in the central part of the Netherlands, in addition to the acquisition of multi-angle and multi-sensor satellite data. The data set is both unique and urgently needed for the development and validation of models and inversion algorithms for quantitative surface parameter estimation and process studies. EAGLE2006 was led by the Department of Water Resources of the International Institute for Geo-Information Science and Earth Observation and originated from the combination of a number of initiatives coming under different funding. The objectives of the EAGLE2006 campaign were closely related to the objectives of other ESA Campaigns (SPARC2004, Sen2Flex2005 and especially AGRISAR2006). However, one important objective of the campaign is to build up a data base for the investigation and validation of the retrieval of bio-geophysical parameters, obtained at different radar frequencies (X-, C- and L-Band) and at hyperspectral optical and thermal bands acquired over vegetated fields (forest and grassland). As such, all activities were related to algorithm development for future satellite missions such as Sentinels and for satellite validations for MERIS, MODIS as well as AATSR and ASTER thermal data validation, with activities also related to the ASAR sensor on board ESA’s Envisat platform and those on EPS/MetOp and SMOS. Most of the activities in the campaign are highly relevant for the EU GEMS EAGLE project, but also issues related to retrieval of biophysical parameters from MERIS and MODIS as well as AATSR and ASTER data were of particular relevance to the NWO-SRON EcoRTM project, while scaling issues and complementary between these (covering only local sites) and global sensors such as MERIS/SEVIRI, EPS/MetOP and SMOS were also key elements for the SMOS cal/val project and the ESA-MOST DRAGON programme. This contribution describes the mission objectives and provides an overview of the airborne and field campaigns

Exploiting Sentinel-1 amplitude data for glacier surface velocity field measurements. Feasibility demonstration on baltoro glacier

The leading idea of this work is to continuously retrieve glaciers surface velocity through SAR imagery, in particular using the amplitude data from the new ESA satellite sensor Sentinel-1 imagery. These imagery key aspects are the free access policy, the very short revisit time (down to 6 days with the launch of the Sentinel-1B satellite) and the high amplitude resolution (up to 5 m). In order to verify the reliability of the proposed approach, a first experiment has been performed using Sentinel-1 imagery acquired over the Karakoram mountain range (North Pakistan) and Baltoro and other three glaciers have been investigated. During this study, a stack of 11 images acquired in the period from October 2014 to September 2015 has been used in order to investigate the potentialities of the Sentinel-1 SAR sensor to retrieve the glacier surface velocity every month. The aim of this test was to measure the glacier surface velocity between each subsequent pair, in order to produce a time series of the surface velocity fields along the investigated period. The necessary co-registration procedure between the images has been performed and subsequently the glaciers areas have been sampled using a regular grid with a 250 × 250 meters posting. Finally the surface velocity field has been estimated, for each image pair, using a template matching procedure, and an outlier filtering procedure based on the signal to noise ratio values has been applied, in order to exclude from the analysis unreliable points. The achieved velocity values range from 10 to 25 meters/month and they are coherent to those obtained in previous studies carried out on the same glaciers and the results highlight that it is possible to have a continuous update of the glacier surface velocity field through free Sentinel-1 imagery, that could be very useful to investigate the seasonal effects on the glaciers fluid-dynamics

Evaluation of ASTER GDEM ver2 using GPS measurements and SRTM ver4.1 in China

The freely available ASTER GDEM ver2 was released by NASA and METI on October 17, 2011. As one of the most complete high resolution digital topographic data sets of the world to date, the ASTER GDEM covers land surfaces between 83°N and 83°S at a spatial resolution of 1 arc-second and will be a useful product for many applications, such as relief analysis, hydrological studies and radar interferometry. The stated improvements in the second version of ASTER GDEM benefit from finer horizontal resolution, offset adjustment and water body detection in addition to new observed ASTER scenes. This study investigates the absolute vertical accuracy of the ASTER GDEM ver2 at five study sites in China using ground control points (GCPs) from high accuracy GPS benchmarks, and also using a DEM-to-DEM comparison with the Consultative Group for International Agriculture Research Consortium for Spatial Information (CGIAR-CSI) SRTM DEM (Version 4.1). And then, the results are separated into GlobCover land cover classes to derive the spatial pattern of error. It is demonstrated that the RMSE (19m) and mean (-13m) values of ASTER GDEM ver2 against GPS-GCPs in the five study areas is lower than its first version ASTER GDEM ver1 (26m and -21m) as a result of the adjustment of the elevation offsets in the new version. It should be noted that the five study areas in this study are representative in terms of terrain types and land covers in China, and even for most of mid-latitude zones. It is believed that the ASTER GDEM offers a major alternative in accessibility to high quality elevation data