The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John B.; Koontz, Stephen R.; Hermans, C. J.

doi:10.3133/ofr20111031

Cited by 28 publications

(23 citation statements)

References 27 publications

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“…Because the topographic data of the study area was limited, and because of the difficulties in obtaining past data, it was decided to use satellite images. Landsat images were selected from among the various levels of spatial, spectral, radiometric and temporal resolution satellite images because of their long-term availability [45], cost-effectiveness, and timeliness [46]. The LU/LC layers were generated by using Landsat-4 TM satellite image from 2 August 1989, Landsat-7 ETM+ satellite image from 13 June 2000, and Landsat-8 OLI satellite image from 13 September 2013 (path/row: 175/31).…”

Section: Methodsmentioning

confidence: 99%

Urban Growth Simulation of Atakum (Samsun, Turkey) Using Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models

Öztürk

2015

Remote Sensing

147

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Abstract:In this study, urban growth of the Atakum District in Samsun, Turkey, was simulated by Cellular Automata-Markov Chain (CA-MC) and Multi-layer Perceptron-Markov Chain (MLP-MC) hybrid models in a geographical information system (GIS) environment. Historical land use/land cover (LU/LC) data were extracted from 1989, 2000 and 2013 Landsat TM/ETM+/OLI images. Using the LU/LC data for the years 1989 and 2000, the urban growth for 2013 was simulated using the CA-MC and MLP-MC models. The simulation results were compared with the 2013 LU/LC data to assess the validity of the simulation. The MLP-MC method provided the best results according to the validation based on the kappa index of agreement. Based on this result, the urban growth for the year 2025 was simulated using MLP-MC. The simulation estimated an urban growth rate of 35.2% between 2013 and 2025, an increase in the area of artificial surfaces from 1681.9 ha to 2274.3 ha and the destruction of 511.7 ha of agricultural land and 4.4 ha of forest. The results of this study demonstrate that the urban growth models provide a better understanding of the current patterns and temporal dynamics and can predict future changes according to past and current dynamics. The results also show that simulations are most accurate when using a model that best conforms to the changes in the given study area.

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Section: Methodsmentioning

confidence: 99%

Urban Growth Simulation of Atakum (Samsun, Turkey) Using Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models

Öztürk

2015

Remote Sensing

147

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“…However, these parameters cannot completely describe the quality of the image [6], and they are used primarily in technical fields and by technical people, such as satellite designers, satellite manufacturers, optical engineers or electric engineers; as a result, the parameters provide quality information and feedback for these technical workers. However, these parameters are unfamiliar and complicated to satellite image product users, which, according to a survey of the U.S. Geological Survey (USGS), may come from different fields, such as agriculture, environmental sciences and management, land use/land cover surveying and even education [7]. In this case, an indicator that can present a comprehensive evaluation of the overall image quality can assist image users to understand the usability of the image according to different tasks [8].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Li¹,

Luo²,

Zhu³

2014

Remote Sensing

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Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79.

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“…Las características especiales en la resolución espacial y espectral de las imágenes Landsat las hacen óptimas para el estudio de diferentes fenó-menos terrestres (Miller et al, 2011). Por ejemplo, para el análisis de los cambios rápidos y graduales en la cobertura vegetal, en el seguimiento de procesos ambientales; como la degradación y la desertificación (Almeida-Filho y Shimabukuro, 2002), la deforestación (Huang et al, 2007(Huang et al, , 2008(Huang et al, , 2010, la recuperación de la vegetación después de perturbaciones naturales (Lawrence y Ripple, 1999) e incendios forestales (Viedma et al, 1997;Roder et al, 2008;Jong et al, 2010;Houghton, 2012;Vasconcelos et al, 2013;Goodwin y Collett, 2014;Kane et al, 2013).…”

Section: Calibración Radiométrica De Imágenes De Satélite Landsatunclassified

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

2016

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Resumen: En este trabajo se hace un análisis de la reflectividad obtenida con una serie de imágenes Landsat procesadas con el modelo LEDAPS en una región de los Andes Colombianos. Fueron calibradas 38 imágenes de los sensores TM y ETM con el modelo LEDAPS con el fin de evaluar las diferencias de reflectividad entre las bandas de un mismo sensor, las diferencias entre sensores, y los patrones temporales. Se utilizaron pruebas estadísticas no paramétricas exactas que permitieron concluir: a) la reflectividad superficial entre bandas (1-5 y 7) es distinta y que esta diferencia se mantiene entre escenas de fechas distintas; b) al comparar las bandas de igual longitud de onda entre los sensores TM y ETM+ hay altas similitudes estadísticas entre las bandas; c) las variaciones temporales en reflectividad desde el año 1986 a 2013 con los sensores estudiados no son significativas. Estos resultados están sustentados con la implementación de modelación robusta con varios métodos resistentes a observaciones inusuales y otros problemas típicos de la modelación de mínimos cuadrados clásicos.Palabras clave: LEDAPS, Landsat, corrección atmosférica, prueba exacta de Wilcoxon-Mann-Whitney, modelo de Huber, regresión por mínimas desviaciones absolutas, mínimos cuadrados recortados, Bootstrap. Implementation and evaluation of the Landsat Ecosystem Disturbance Adaptive Processing Systems (LEDAPS) model: a case study in the Colombian AndesAbstract: 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.

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The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

Cited by 28 publications

References 27 publications

Urban Growth Simulation of Atakum (Samsun, Turkey) Using Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models

Urban Growth Simulation of Atakum (Samsun, Turkey) Using Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

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

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