Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

Kolecka, Natalia; Kozak, Jacek; Kaim, Dominik; Dobosz, Monika; Ginzler, Christian; Psomas, A.

doi:10.5194/isprsarchives-xli-b8-931-2016

Cited by 5 publications

(4 citation statements)

References 7 publications

(9 reference statements)

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“…To date, no other study has attempted to perform wall-to-wall forest succession and agricultural land abandonment mapping over large areas in such detail and at a spatial resolution of 1 m. This study covers the entire Polish Carpathians and was based on a vegetation height model derived from digital elevation and surface models with a 1 m spatial resolution. Our previous studies [17,46,47], which were based on LiDAR point clouds and covered one sample tile of 2 × 2 km per commune, showed 13.9% forest succession over the region, which exceeds the 9.0% estimate derived from this study. The previous studies, however, were performed using object-based analysis, which might have included non-vegetated pieces of land in the secondary forest succession class and thus overestimated the actual rate of overgrown land.…”

Section: Discussioncontrasting

confidence: 90%

Wall-to-Wall Parcel-Level Mapping of Agricultural Land Abandonment in the Polish Carpathians

Kolecka

Kozak

2019

Land

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Accurate estimations of the extent of agricultural land abandonment (ALA) are critical to the sustainable management of agricultural resources and forestry, the understanding of ALA determinants, and the development of future agricultural policies. Although ALA is widespread in Europe, mapping it over large areas using remote sensing data is difficult as a result of the complexity of this phenomenon. This study aims to develop methods for a detailed wall-to-wall regional-scale mapping of ALA using vegetation height and secondary forest succession indicators. The rates and distribution of ALA were analyzed at the parcel and communal level in the Polish Carpathians using a high-resolution vegetation height model (VHM) derived from Light Detection and Ranging (LiDAR) point clouds and topographic data. Depending on the parcel-level secondary forest succession threshold (10, 20, and 50%), the regional ALA rates were 18.8, 9.0, and 2.1%, respectively. Regardless of the threshold, abandoned grasslands covered about three times more area than abandoned croplands. The highest ALA rates were observed in communes located in the western part of the study area, as well as east and south of Rzeszów. We found that areas receiving European Union Common Agricultural Policy payments very rarely showed signs of secondary forest succession and land abandonment. The developed method proved to be effective for detailed ALA mapping at various spatial scales.

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Section: Discussioncontrasting

confidence: 90%

Wall-to-Wall Parcel-Level Mapping of Agricultural Land Abandonment in the Polish Carpathians

Kolecka

Kozak

2019

Land

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“…Other authors performed several methodological approaches for the classification of AAL. For this purpose, we refer to these studies as other combined methods for AAL identification using RS datasets: agricultural inventory with LU models [60], long-term inventory data with a cropland density map [30], multiple classification models [28], expert opinion with biophysical models [66], light detection and ranging (LiDAR) data and digital elevation model with ancillary data [63], hybrid classification: unsupervised iterative self-organizing data analysis technique (ISODATA) classification algorithm combined with supervised maximum likelihood algorithm [42], and ISODATA combined with the supervised classification approach and multitemporal images [96].…”

Section: Discussionmentioning

confidence: 99%

A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe

et al. 2019

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This study aims to analyze and assess studies published from 1992 to 2019 and listed in the Web of Science (WOS) and Current Contents (CC) databases, and to identify agricultural abandonment by application of remote sensing (RS) optical and microwave data. We selected 73 studies by applying structured queries in a field tag form and Boolean operators in the WOS portal and by expert analysis. An expert assessment yielded the topical picture concerning the definitions and criteria for the identification of abandoned agricultural land (AAL). The analysis also showed the absence of similar field research, which serves not only for validation, but also for understanding the process of agricultural abandonment. The benefit of the fusion of optical and radar data, which supports the application of Sentinel-1 and Sentinel-2 data, is also evident. Knowledge attained from the literary sources indicated that there exists, in the world literature, a well-covered problem of abandonment identification or biomass estimation, as well as missing works dealing with the assessment of the natural accretion of biomass in AAL.

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“…The usage of remote sensing spatial data from different periods offers the possibility of monitoring changes taking place in the environment especially the process of forest succession (Falkowski et al, 2009;Prishchepov et al, 2012;Kolecka, 2016;Lasanta et al, 2017). Aerial and satellite imageries have been successfully used since the early 2000s to estimate the area of forested lands.…”

Section: Discussionmentioning

confidence: 99%

Forest succession mapping for post-agricultural areas using Sentinel-2, PlanetScope imageries and LiDAR data

2023

Advances in Geodesy and Geoinformation

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The research investigates the possibility of applying Sentinel-2, PlanetScope satellite imageries, and LiDAR data for automation of land cover mapping and 3D vegetation characteristics in post-agricultural areas, mainly in the aspect of detection and monitoring of the secondary forest succession. The study was performed for the tested area in the Biskupice district (South of Poland), as an example of an uncontrolled forest succession process occurring on post-agricultural lands. The areas of interest were parcels where agricultural use has been abandoned and forest succession has progressed. This paper indicates the possibility of automating the process of monitoring wooded and shrubby areas developing in post-agricultural areas with the help of modern geodata and geoinformation methods. It was verified whether the processing of Sentinel-2, PlanetScope imageries allows for reliable land cover classification as an identification forest succession area. The airborne laser scanning (ALS) data were used for deriving detailed information about the forest succession process. Using the ALS point clouds vegetation parameters i.e., height and canopy cover were determined and presented as raster maps, histograms, or profiles. In the presented study Sentinel-2, PlanetScope imageries, and ALS data processing showed a significant differentiation of the spatial structure of vegetation. These differences are visible in the surface size (2D) and the vertical vegetation structure (3D).

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Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

Cited by 5 publications

References 7 publications

Wall-to-Wall Parcel-Level Mapping of Agricultural Land Abandonment in the Polish Carpathians

Wall-to-Wall Parcel-Level Mapping of Agricultural Land Abandonment in the Polish Carpathians

A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe

Forest succession mapping for post-agricultural areas using Sentinel-2, PlanetScope imageries and LiDAR data

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