Interpretation of vegetation of the northwest Ladoga region from high-resolution satellite imagery with the use of ordination on a complex of morphological and physiological features

A. N. Afonin, Yu V. Sokolova, N. N. Bardakov, I. O. Saharov

Research outputpeer-review

Abstract

Interpretation of vegetation was implemented with the use of high resolution imagery from satellites QuickBird-2 (2.4 and 0.6 m), GeoEye-1 (2 and 0.5 m) and WorldView-2 (2 and 0.5 m). The following morphological and physiological characteristics of objects were used as indicators for interpretation: morphometric features of cover projection of vegetation (tree crown) on snow, estimated by reflection of vegetation in the early spring image, and integral index of photosynthetic activity of vegetation, estimated by NDVI from summer image. Conceptual and methodological aspects of direct expert interpretation of vegetation by methods of classification with the use of raster algebra are considered. Validation of interpretation results by field observations showed 70−100% precision of mapping different types of vegetation (6 classes for level of formations and groups of formation). Accounting more morphological and physiological characteristics allows to increase the accuracy of interpretation. However, some problems of using high resolution images of (<1 m) should be noted. For example, the problem of inaccurate geometric correction of high resolution images, provided for the research, and different camera angles during acquisition of images. These factors do not allow to conduct precise comparison of multitemporal images and to use the abilities of change detection by texture features of vegetation cover on the pixel level. This raises generalization as the necessary step in interpretation of high resolution images by classification methods of raster algebra.

Original languageEnglish
Pages (from-to)147-156
Number of pages10
JournalSovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

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Satellite imagery
ordination
satellite imagery
vegetation
image resolution
Image resolution
raster
Algebra
QuickBird
NDVI
vegetation cover
Snow
pixel
imagery
snow
texture
Textures
Pixels
Cameras
Satellites

Scopus subject areas

  • Computer Science Applications
  • Computers in Earth Sciences
  • Computer Networks and Communications

Cite this

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title = "Interpretation of vegetation of the northwest Ladoga region from high-resolution satellite imagery with the use of ordination on a complex of morphological and physiological features",
abstract = "Interpretation of vegetation was implemented with the use of high resolution imagery from satellites QuickBird-2 (2.4 and 0.6 m), GeoEye-1 (2 and 0.5 m) and WorldView-2 (2 and 0.5 m). The following morphological and physiological characteristics of objects were used as indicators for interpretation: morphometric features of cover projection of vegetation (tree crown) on snow, estimated by reflection of vegetation in the early spring image, and integral index of photosynthetic activity of vegetation, estimated by NDVI from summer image. Conceptual and methodological aspects of direct expert interpretation of vegetation by methods of classification with the use of raster algebra are considered. Validation of interpretation results by field observations showed 70−100{\%} precision of mapping different types of vegetation (6 classes for level of formations and groups of formation). Accounting more morphological and physiological characteristics allows to increase the accuracy of interpretation. However, some problems of using high resolution images of (<1 m) should be noted. For example, the problem of inaccurate geometric correction of high resolution images, provided for the research, and different camera angles during acquisition of images. These factors do not allow to conduct precise comparison of multitemporal images and to use the abilities of change detection by texture features of vegetation cover on the pixel level. This raises generalization as the necessary step in interpretation of high resolution images by classification methods of raster algebra.",
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author = "Afonin, {A. N.} and Sokolova, {Yu V.} and Bardakov, {N. N.} and Saharov, {I. O.}",
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T1 - Interpretation of vegetation of the northwest Ladoga region from high-resolution satellite imagery with the use of ordination on a complex of morphological and physiological features

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AU - Sokolova, Yu V.

AU - Bardakov, N. N.

AU - Saharov, I. O.

PY - 2018/1/1

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AB - Interpretation of vegetation was implemented with the use of high resolution imagery from satellites QuickBird-2 (2.4 and 0.6 m), GeoEye-1 (2 and 0.5 m) and WorldView-2 (2 and 0.5 m). The following morphological and physiological characteristics of objects were used as indicators for interpretation: morphometric features of cover projection of vegetation (tree crown) on snow, estimated by reflection of vegetation in the early spring image, and integral index of photosynthetic activity of vegetation, estimated by NDVI from summer image. Conceptual and methodological aspects of direct expert interpretation of vegetation by methods of classification with the use of raster algebra are considered. Validation of interpretation results by field observations showed 70−100% precision of mapping different types of vegetation (6 classes for level of formations and groups of formation). Accounting more morphological and physiological characteristics allows to increase the accuracy of interpretation. However, some problems of using high resolution images of (<1 m) should be noted. For example, the problem of inaccurate geometric correction of high resolution images, provided for the research, and different camera angles during acquisition of images. These factors do not allow to conduct precise comparison of multitemporal images and to use the abilities of change detection by texture features of vegetation cover on the pixel level. This raises generalization as the necessary step in interpretation of high resolution images by classification methods of raster algebra.

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KW - Interpretation

KW - Interpretation indicators

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KW - Morphological

KW - Physiological indicators

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KW - Remote sensing data

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JO - СОВРЕМЕННЫЕ ПРОБЛЕМЫ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ ЗЕМЛИ ИЗ КОСМОСА

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