scholarly journals Automated classification of the vegetation cover of Mediterranean landscape using spectral-textural and topographic features of high spatial resolution satellite imagery

2021 ◽  
Vol 18 (2) ◽  
pp. 51-63
Author(s):  
A. Khatib ◽  
◽  
V.A. Malinnikov ◽  
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Vegetation Cover ◽  
High Spatial Resolution ◽  
Automated Classification ◽  
Topographic Features ◽  
Mediterranean Landscape

scholarly journals Evaluación espacial del comportamiento fenológico de la vegetación mediante imágenes satelitales distrito de chiara-ayacucho 2000-2015

2021 ◽  
Vol 2 (4) ◽  
pp. 5743-5758
Author(s):  
Jorge Luis Lozano Rodríguez ◽  
Juan Carlos Chang Chang Fun ◽  
Oscar Enrique Tang Cruz ◽  
Milagros Rocio Menacho Angeles ◽  
Hernán Oscar Cortez Gutiérrez ◽  
...  
Keyword(s):  
Decision Making ◽  
Statistical Methods ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Thematic Maps ◽  
Toma De Decisiones ◽  
Multitemporal Analysis

La presente investigación se realizó el análisis de las imágenes satelitales MODIS-Terra 250m x 250m de resolución espacial y determinar el comportamiento fenológico de la cobertura vegetal del distrito de Chiara. El objetivo de esta investigación es dar a conocer y demostrar la importancia de la metodología utilizada (imágenes de satélite MOD13Q1) para el análisis multitemporal de la vegetación, mediante el uso del software ENVI, IDL, ArcGIS. En este sentido, se ha logrado describir el comportamiento de la vegetación en el periodo de los dieciséis años, y determinar una variabilidad del área de vegetación en las estaciones anuales de verano, otoño, invierno y primavera y estimar mediante métodos estadísticos la variabilidad del NDVI. Los principales resultados obtenidos son: La variación fenológicos de los ecosistemas, según la estacionalidad climática de las áreas estudiadas. En este sentido, los cambios y variaciones son explicados en base a las características de pixeles de colores. Los resultados obtenidos pueden servir como insumo para mejorar el proceso y clasificación de las imágenes de satélite con el objeto de elaborar mapas temáticos y contribuir a la mejor toma de decisiones en cuanto al uso adecuado de los calendarios agrícolas definidos para cultivos anuales y/o transitorios instalados en dicho distrito.   The present research was the analysis of the satellite imagery MODIS-Terra 250m x 250m of spatial resolution and determine the phenological behavior of the vegetation cover of the district of Chiara. The objective of this research is to make known and demonstrate the importance of the methodology used (satellite images MOD13Q1) for multitemporal analysis of vegetation, using the software ENVI, IDL, ArcGIS. In this sense, it has been possible to describe the behavior of vegetation in the sixteen-year period, and to determine a variability of the vegetation area in the annual seasons of summer, autumn, winter and spring and to estimate by means of statistical methods the variability of NDVI. The main results obtained are the phenological variation of the ecosystems, according to the climatic seasonality of the studied areas. In this sense, changes and variations are explained based on the characteristics of colored pixels. The results obtained can serve as input to improve the processing and classification of satellite images in order to produce thematic maps and contribute to better decision making regarding the proper use of the defined agricultural calendars for annual and / or transient crops Installed in that district.

High spatial-resolution classification of urban surfaces using a deep learning method

2021 ◽  
pp. 107949
Author(s):  
Yifan Fan ◽  
Xiaotian Ding ◽  
Jindong Wu ◽  
Jian Ge ◽  
Yuguo Li
Keyword(s):  
Deep Learning ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Learning Method

scholarly journals Shrub Fractional Cover Estimation and Mapping of San Clemente Island Shrubland Based on Airborne Multispectral Imagery and Lidar Data

2020 ◽  
Vol 12 (21) ◽  
pp. 3608
Author(s):  
Kelsey Warkentin ◽  
Douglas Stow ◽  
Kellie Uyeda ◽  
John O’Leary ◽  
Julie Lambert ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Coastal Sage Scrub ◽  
Surface Model ◽  
Lidar Data ◽  
Shrub Cover ◽  
Fractional Cover ◽  
Major Factors ◽  
San Clemente Island

The purpose of this study is to map shrub distributions and estimate shrub cover fractions based on the classification of high-spatial-resolution aerial orthoimagery and light detection and ranging (LiDAR) data for portions of the highly disturbed coastal sage scrub landscapes of San Clemente Island, California. We utilized nine multi-temporal aerial orthoimage sets for the 2010 to 2018 period to map shrub cover. Pixel-based and object-based image analysis (OBIA) approaches to image classification of growth forms were tested. Shrub fractional cover was estimated for 10, 20 and 40 m grid sizes and assessed for accuracy. The most accurate estimates of shrub cover were generated with the OBIA method with both multispectral brightness values and canopy height estimates from a normalized digital surface model (nDSM). Fractional cover products derived from 2015 and 2017 orthoimagery with nDSM data incorporated yielded the highest accuracies. Major factors that influenced the accuracy of shrub maps and fractional cover estimates include the time of year and spatial resolution of the imagery, the type of classifier, feature inputs to the classifier, and the grid size used for fractional cover estimation. While tracking actual changes in shrub cover over time was not the purpose, this study illustrates the importance of consistent mapping approaches and high-quality inputs, including very-high-spatial-resolution imagery and an nDSM.

scholarly journals Satellite imagery of lengthy territories with complex configuration with the account of attitude and positioning errors

2019 ◽  
Vol 75 ◽  
pp. 01013
Author(s):  
Dmitriy Mozgovoy ◽  
Dmitriy Svinarenko ◽  
Roman Tsarev ◽  
Tatiana Yamskikh
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
High Spatial Resolution ◽  
Program Control ◽  
Complex Configuration ◽  
Positioning Errors ◽  
Satellite Attitude ◽  
The Impact

A method for monitoring attitude and positioning errors when taking satellite imagery of lengthy territories with complex configuration using an ultra-high spatial resolution optical-electronic scanner is described in the article. The results of modeling the system of automatic satellite attitude program control during the process of imagery are presented. Given these results, the impact of attitude and positioning errors during satellite imagery was estimated on the coverage percentage of the territory to be imaged.

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