Abandoned Farmland Location in Areas Affected by Rapid Urbanization Using Textural Characterization of High Resolution Aerial Imagery

Abstract

Several studies have demonstrated that farmland abandonment occurs not only in rural areas, but is also closely interlinked with urbanization processes. Therefore, the location of abandoned land and the registration of the spatial information referring to it play important roles in urban land management. However, mapping abandoned land or land in the process of abandonment is not an easy task because the limits between the different land uses are not clear and precise. It is therefore necessary to develop methods that allow estimating and mapping this type of land as accurately as possible. As an alternative to other geomatics methods such as satellite remote sensing, our approach proposes a framework for automatically locating abandoned farmland in urban landscapes using the textural characterization and segmentation of aerial imagery. Using the city of Poznań (Poland) as a case study, results demonstrated the feasibility of applying our approach, reducing processing time and workforce resources. Specifically and by comparing the results obtained with the data provided by CORINE Land Cover, 2275 ha (40.3%) of arable land within the city limits were abandoned, and the area of abandoned arable land was almost 9.2% of the city’s area. Finally, the reliability of the proposed methodology was assessed from two different focuses: (i) the accuracy of the segmentation results (from a positional point of view) and (ii) the efficiency of locating abandoned land (as a specific type of land use) in urban areas particularly affected by rapid urbanization.

Geo-Informatics in Resource Management

“…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. Finally, Chen et al [18] estimated fraction vegetation cover on five grassland types using unmanned aerial images, applying the threshold method.…”

Automatic Positional Accuracy Assessment of Imagery Segmentation Processes: A Case Study

“…In this way, the resulting regions meet the main IS requirements; they are different from a visual perspective and have very similar statistical properties. However, real imagery regions do not share this homogeneous statistical behavior [13]. In agreement with this, the use of the pixel tone is not recommended.…”

“…Among these descriptors we can highlight the Local Binary Pattern (LBP). The LBP is a very efficient texture operator due to its discriminative power and, for this reason, it has become the most widely employed operator in textural IS [13][14][15][16].…”

“…In this sense, we must highlight the studies related to (i) automatic extraction of building features from VHR satellite imagery [17][18][19][20][21][22][23][24][25], (ii) automatic road network extraction from VHR aerial imagery [26][27][28][29] and (iii) vector-imagery conflation procedures based on the use of road intersectionspreviously extracted-as check points in order to develop matching procedures [14,16,30]. More recently, the applications of IS to GI have been aimed at obtaining the land information required to achieve sustainable urban development, avoiding problems caused by the unorganized urban sprawl [13,31,32]. Such is the case of the approaches of Stryjakiewicz et al [32] and Ruiz-Lendínez [13].…”

“…More recently, the applications of IS to GI have been aimed at obtaining the land information required to achieve sustainable urban development, avoiding problems caused by the unorganized urban sprawl [13,31,32]. Such is the case of the approaches of Stryjakiewicz et al [32] and Ruiz-Lendínez [13]. Both studies are focused on the municipal district of Pozna ń (Poland) and assess the degree of abandonment of agricultural farmland.…”