The Efficacy Analysis of Determining the Wooded and Shrubbed Area Based on Archival Aerial Imagery Using Texture Analysis

Abstract

Open areas, along with their non-forest vegetation, are often threatened by secondary succession, which causes deterioration of biodiversity and the habitat’s conservation status. The knowledge about characteristics and dynamics of the secondary succession process is very important in the context of management and proper planning of active protection of the Natura 2000 habitats. This paper presents research on the evaluation of the possibility of using selected methods of textural analysis to determine the spatial extent of trees and shrubs based on archival aerial photographs, and consequently on the investigation of the secondary succession process. The research was carried out on imagery from six different dates, from 1971 to 2015. The images differed from each other in spectral resolution (panchromatic, in natural colors, color infrared), in original spatial resolution, as well as in radiometric quality. Two methods of textural analysis were chosen for the analysis: Gray level co-occurrence matrix (GLCM) and granulometric analysis, in a number of variants, depending on the selected parameters of these transformations. The choice of methods has been challenged by their reliability and ease of implementation in practice. The accuracy assessment was carried out using the results of visual photo interpretation of orthophotomaps from particular years as reference data. As a result of the conducted analyses, significant efficacy of the analyzed methods has been proved, with granulometric analysis as the method of generally better suitability and greater stability. The obtained results show the impact of individual image features on the classification efficiency. They also show greater stability and reliability of texture analysis based on granulometric/morphological operations.

Ecosystem transformation following the mid-nineteenth century cessation of Aboriginal fire management in Cape Pillar, Tasmania

“…imagery for the year of 1946), texture parameters for four different sliding windows that have been used in similar studies (e.g. Chen et al 2020;Kupidura et al 2019;Murray et al 2010): 9 × 9, 15 × 15 and 21 × 21.…”

“…We classified the aerial photographs using the 'RStoolbox' R package (Leutner et al 2019) and Random Forest algorithm, which have been shown to provide accurate vegetation classification results (e.g. Chen et al 2020;Kupidura et al 2019). For each photograph, we generated a training dataset which included the following vegetation classes: burnt, heathland, scrub and forest.…”

Geo-Informatics in Resource Management

“…For images obtained with sensors on-board manned aerial platforms, there are three contributions. Firstly, Przemyslaw et al [16] assessed the applicability of texture analysis to study the dynamics of the succession of trees and shrubs using aerial imagery acquired in six different years in various phenological periods, resulting in an effective method for determining the extent of wooded and shrubbed areas. Ruiz-Lendínez [17] located and mapped abandoned farmlands, applying textural characterization on high spatial resolution aerial imagery.…”

Survey of Medicinal and Aromatic Plants and Determine Its Landscaping Values in Home Gardens and Malls in Cairo Festival City, Cairo Governorate, Egypt

“…Furthermore, texture is one of the most serious spatial features of chosen terrain coverage classes. Since it does not have an unambiguous mathematical definition, in practice, picture processing utilizes a variety of texture analysis methods (Kupidura et al, 2019). Nevertheless, the texture of the foliage was coarse in 3 species; the medium texture in 6 species, fine texture was recorded in 9 species.…”