How to effectively use long-term remotely sensed data to analyze the process of tree and shrub encroachment into open protected wetlands.

Kopeć, Dominik; Sławik, Łukasz

doi:10.1016/j.apgeog.2020.102345

Cited by 10 publications

(6 citation statements)

References 48 publications

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“…This implies that, by moving from a resolution of 1 cm to a resolution of 20 cm, the photo-interpretation efficiency in tree detection was at least halved. In general, the cut off size of tree detection in our study was lower than the size of all the studies we were able to find in literature, e.g., [76,81,83,86], where the canopy area of non-detected shrubs and/or trees ranged from 1 to 1.6 m 2 . Interestingly, we found that the threshold values of the most accurate semi-automatic models were very close to the values observed for the photo-interpretation of the low-resolution image, which means that the performance of the semi-automatic classification models in larch detection was comparable to the classification carried out by the operator on the low-resolution image.…”

Section: Discussioncontrasting

confidence: 74%

Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits

et al. 2021

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Woody species encroachment on grassland ecosystems is occurring worldwide with both negative and positive consequences for biodiversity conservation and ecosystem services. Remote sensing and image analysis represent useful tools for the monitoring of this process. In this paper, we aimed at evaluating quantitatively the potential of using high-resolution UAV imagery to monitor the encroachment process during its early development and at comparing the performance of manual and semi-automatic classification methods. The RGB images of an abandoned subalpine grassland on the Western Italian Alps were acquired by drone and then classified through manual photo-interpretation, with both pixel- and object-based semi-automatic models, using machine-learning algorithms. The classification techniques were applied at different resolution levels and tested for their accuracy against reference data including measurements of tree dimensions collected in the field. Results showed that the most accurate method was the photo-interpretation (≈99%), followed by the pixel-based approach (≈86%) that was faster than the manual technique and more accurate than the object-based one (≈78%). The dimensional threshold for juvenile tree detection was lower for the photo-interpretation but comparable to the pixel-based one. Therefore, for the encroachment mapping at its early stages, the pixel-based approach proved to be a promising and pragmatic choice.

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Section: Discussioncontrasting

confidence: 74%

Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits

et al. 2021

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“…Depending on the species, accuracy of above 90% can be achieved [33,34], but the problem is the spectral variability of invasive species and the surrounding plants, which are prone to change due to agriculture activities, e.g., mowing and grazing, which causes changes in the proportion of the reflected spectrum from the soil, blooming flowers or dry blades of grass. All these elements make it difficult to identify invasion routes, but regular monitoring can identify changes [35]. Therefore, monitoring of invasive plants should be based on regular image acquisition, and the iterative method can be used to check the pattern of land cover of a given area.…”

Section: Introductionmentioning

confidence: 99%

Mapping Invasive Plant Species with Hyperspectral Data Based on Iterative Accuracy Assessment Techniques

2021

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Recent developments in computer hardware made it possible to assess the viability of permutation-based approaches in image classification. Such approaches sample a reference dataset multiple times in order to train an arbitrary number of machine learning models while assessing their accuracy. So-called iterative accuracy assessment techniques or Monte-Carlo-based approaches can be a useful tool when it comes to assessment of algorithm/model performance but are lacking when it comes to actual image classification and map creation. Due to the multitude of models trained, one has to somehow reason which one of them, if any, should be used in the creation of a map. This poses an interesting challenge since there is a clear disconnect between algorithm assessment and the act of map creation. Our work shows one of the ways this disconnect can be bridged. We calculate how often a given pixel was classified as given class in all variations of a multitude of post-classification images delivered by models trained during the iterative assessment procedure. As a classification problem, a mapping of Calamagrostis epigejos, Rubus spp., Solidago spp. invasive plant species using three HySpex hyperspectral datasets collected in June, August and September was used. As a classification algorithm, the support vector machine approach was chosen, with training hyperparameters obtained using a grid search approach. The resulting maps obtained F1-scores ranging from 0.87 to 0.89 for Calamagrostis epigejos, 0.89 to 0.97 for Rubus spp. and 0.99 for Solidago spp.

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“…The world's wetlands continue to be lost and degraded at an alarming rate as a result of human activities. Consequently, the essential benefits provided by wetlands to people continue to be seriously eroded (Kopeć and Sławik, 2020). Removing pressures on the ecological character of wetlands is the best practice for preventing further loss and degradation when this is not feasible (Kopeć and Sławik, 2020).…”

Section: Introductionmentioning

confidence: 99%

Man Invades Nature: Tracing the Dynamics and Trends of Anthropogenic Stressors Within a Coastal Wetland Environment

Okyere,

Adu-Boahen,

Mensah

2023

Journal of Social Sciences

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Coastal areas contain some of the most valuable resources on earth that are constantly under threat due to human development. Notable among these resources are wetlands, a delicate but beneficial asset to coastal dwellers. This study studied the growth of Winneba City into the Muni Lagoon catchment as well as its associated effects on the Ramsar Site. The study used satellites images for the years 1990, 2000, and 2019 to model encroachment within the catchment over the 30-year period. Stakeholders were purposively selected and interviewed to gain insight into the subject under discussion. The study revealed that there is a high rate of encroachment occurring within the lagoon catchment, evidenced in the form of residential structures and agricultural practices. The rate of encroachment has almost tripled within the period under study. These activities are likely to affect flora and fauna within the catchment. The encroachment has been successful as a result of a lack of clearly defined boundaries showing the extent of the wetland. The study recommends all the stakeholders come together and work with the Wildlife Division of the Forestry Commission to establish the boundaries of the wetland beyond which anthropogenic activities should not be allowed.

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How to effectively use long-term remotely sensed data to analyze the process of tree and shrub encroachment into open protected wetlands.

Cited by 10 publications

References 48 publications

Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits

Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits

Mapping Invasive Plant Species with Hyperspectral Data Based on Iterative Accuracy Assessment Techniques

Man Invades Nature: Tracing the Dynamics and Trends of Anthropogenic Stressors Within a Coastal Wetland Environment

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