scholarly journals Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description

2013 ◽  
Author(s):  
Gail Schmidt ◽  
Calli B. Jenkerson ◽  
Jeffrey Masek ◽  
Eric Vermote ◽  
Feng Gao
Keyword(s):  
Processing System ◽  
Adaptive Processing ◽  
Ecosystem Disturbance

scholarly journals MODEL KOREKSI ATMOSFER CITRA LANDSAT-7 (ATMOSPHERIC CORRECTION MODELS OF LANDSAT-7 IMAGERY)

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Fadila Muchsin ◽  
Liana Fibriawati ◽  
Kuncoro Adhi Pradhono
Keyword(s):  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Processing System ◽  
Line Of Sight ◽  
Adaptive Processing ◽  
Spectral Pattern ◽  
Ecosystem Disturbance ◽  
Corrected Image ◽  
Landsat 7 ◽  
Satellite Signal

Three methods of atmospheric correction, Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) and the model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), have been applied to the level 1T Landsat-7 image Jakarta area. The atmospheric corrected image is then compared with the TOA reflectance image. The results show that there is an improvement of the spectral pattern on the TOA reflectance image by the decrease of the reflectance value of each object by (1 - 11) % after the atmospheric correction of all models for visible bands (blue, green and red). In the NIR and SWIR bands there is an increase in the spectral value of about 1% to the TOA reflectance on all objects except wetland for the LEDAPS model. The percentage of the increase and the decrease in spectral values of 6S and FLAASH models have the same tendency. Analyzes were also performed on the NDVI values of each model, where NDVI values were relatively higher after atmospheric correction. The NDVI value of rice crop on FLAASH model is the same as 6S model that is equal to 0.95 and for wetland, it has the same value between FLAASH model and LEDAPS which is 0.23. NDVI value of entire scene for FLAASH model = 0.63, LEDAPS model = 0.56 and 6S model = 0.66. Before the atmospheric correction, the TOA is 0.45. Abstrak Tiga metode koreksi atmosfer diantaranya  Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) dan model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) telah diterapkan pada citra Landsat-7 level 1T wilayah Jakarta. Citra yang telah terkoreksi atmosfer dibandingkan dengan citra reflektan TOA. Hasilnya menunjukkan bahwa terdapat perbaikan pola spektral pada citra reflektan TOA dengan adanya penurunan nilai reflektan setiap obyek sebesar (1 – 11) % setelah dilakukan koreksi atmosfer pada semua model untuk kanal-kanal visible (blue, green dan red). Pada kanal NIR dan SWIR terjadi kenaikan nilai spektral yaitu sekitar 1% terhadap reflektan TOA pada semua objek terkecuali objek lahan basah untuk model LEDAPS. Persentase kenaikan dan penurunan nilai spektral model 6S dan FLAASH memiliki kecenderungan yang sama. Analisis juga dilakukan terhadap nilai NDVI masing-masing model, dimana nilai NDVI relatif lebih tinggi setelah koreksi atmosfer. Nilai NDVI tanaman padi pada model FLAASH sama dengan model 6S yaitu sebesar 0.95 dan untuk lahan basah memiliki nilai yang sama antara model FLAASH dan LEDAPS yaitu 0.23. Nilai NDVI seluruh scene untuk model FLAASH = 0.63, model LEDAPS = 0.56 dan model 6S = 0.66. Sebelum koreksi atmosfer (TOA) adalah 0.45. 

Tera-OP Reliable Intelligently Adaptive Processing System (TRIPS) Implementation

2008 ◽  
Author(s):  
Stephen W. Keckler ◽  
Doug Burger ◽  
Kathryn S. McKinley ◽  
Steve Crago ◽  
Richard Lethin
Keyword(s):  
Processing System ◽  
Adaptive Processing

Tera-Op Reliable Intelligently Adaptive Processing System (TRIPS)

2004 ◽  
Author(s):  
Stephen W. Keckler ◽  
Doug Berger ◽  
Michael Dahlin ◽  
Lizy John ◽  
Calvin Lin ◽  
...  
Keyword(s):  
Processing System ◽  
Adaptive Processing

scholarly journals A Study on Target Detection using Covariance Correlation Matrix of Spatial Adaptive Processing

2021 ◽  
Vol 12 (5) ◽  
pp. 236-242
Author(s):  
Kwan-Hyeong Lee
Keyword(s):  
Adaptive Algorithm ◽  
Correlation Matrix ◽  
Processing System ◽  
Direction Of Arrival ◽  
Phase Matching ◽  
Interference Signal ◽  
Adaptive Processing ◽  
Signal Phase ◽  
Optimal Weight ◽  
Phase Errors

In this paper, we study for direction of arrival estimation of the desired target in spatial adaptive processing system. The interference signal removed by using the optimal weight of the covariance correlation matrix in order to estimate desired target signal. The spatial adaptive processing system updates the weight of the direction of arrival algorithm to estimate the desired signal. The weight update use an adaptive algorithm such as MUSIC. The optimal weight is obtained by Lagrange multiplier and the covariance correlation matrix. The covariance correlation matrix applies signal phase matching and uses the output power spectrum of the direct of arrival algorithm to estimate the desired target direction. We compare the performance of the proposed method with the existing method by computer simulation. The existing method has poor resolution due to phase errors of 5o and -3o in the estimation of three targets [10o, 20o, 30o]. While, the method proposed in this study accurately estimated the desired three targets. This study proved that the proposed method is superior to the existing method as a result simulation result.

scholarly journals Implementación y evaluación del modelo Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS): estudio de caso en los Andes colombianos

2016 ◽  
pp. 83 ◽  
Author(s):  
G. M. Valencia ◽  
J. A. Anaya ◽  
F. J. Caro-Lopera
Keyword(s):  
Least Squares ◽  
Processing System ◽  
Temporal Patterns ◽  
Nonparametric Statistics ◽  
Temporal Variations ◽  
Surface Reflectance ◽  
Landsat Images ◽  
Robust Modeling ◽  
Ecosystem Disturbance ◽  
Colombian Andes

<p>This paper analyzes the reflectance obtained with a series of Landsat images processed with LEDAPS model in a region of the Colombian Andes. A total of 38 images of TM and ETM sensors were calibrated to surface reflectance using LEDAPS in order to determine difference among bands of the same sensor, difference between sensors and analyze temporal patterns. Exact nonparametric statistics allow to conclude that: a) surface reflectance for band 1–5 and 7 were significantly different and this difference remains among images of different dates; b) there are statistical similarities between the TM and ETM sensors bands; c) temporal variations on surface reflectance from the years 1986 to 2013 with the sensors studied are not statistically significant. These results are supported by the implementation of robust modeling with various methods resistant to unusual observations and other typical problems of the classical least squares modeling.</p>

All-optical antenna array adaptive processing system

1999 ◽  
Author(s):  
Paulo E. X. Silveira ◽  
Gregory Kriehn ◽  
Andrew M. Kiruluta ◽  
Samuel P. Weaver ◽  
Kelvin H. Wagner ◽  
...  
Keyword(s):  
Antenna Array ◽  
Processing System ◽  
Optical Antenna ◽  
Adaptive Processing ◽  
All Optical

Digital image processing methods applied to the study of annealing time on semiconductor-metal eutectic composites

1988 ◽  
Vol 46 ◽  
pp. 848-849
Author(s):  
J. Hefter
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Electronic Device ◽  
Processing System ◽  
Average Diameter ◽  
Eutectic Solidification ◽  
Metal Silicide ◽  
The Matrix ◽  
Microscopic Studies

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.

Digital Processing of STEM Images

1981 ◽  
Vol 39 ◽  
pp. 236-237
Author(s):  
A. V. Crewe ◽  
M. Ohtsuki
Keyword(s):  
High Resolution ◽  
Low Dose ◽  
Assembly Language ◽  
Processing System ◽  
Principal Component ◽  
Digital Processing ◽  
Image Analysis System ◽  
Black And White ◽  
Analysis System ◽  
Dose Imaging

We have assembled an image processing system for use with our high resolution STEM for the particular purpose of working with low dose images of biological specimens. The system is quite flexible, however, and can be used for a wide variety of images.The original images are stored on magnetic tape at the microscope using the digitized signals from the detectors. For low dose imaging, these are “first scan” exposures using an automatic montage system. One Nova minicomputer and one tape drive are dedicated to this task.The principal component of the image analysis system is a Lexidata 3400 frame store memory. This memory is arranged in a 640 x 512 x 16 bit configuration. Images are displayed simultaneously on two high resolution monitors, one color and one black and white. Interaction with the memory is obtained using a Nova 4 (32K) computer and a trackball and switch unit provided by Lexidata.The language used is BASIC and uses a variety of assembly language Calls, some provided by Lexidata, but the majority written by students (D. Kopf and N. Townes).

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Sign in / Sign up

Export Citation Format

Share Document