<b>stampr</b>: Spatial-Temporal Analysis of Moving Polygons in <i>R</i>

Long, Jed A.; Robertson, Colin; Nelson, Trisalyn A.

doi:10.18637/jss.v084.c01

Cited by 10 publications

(10 citation statements)

References 20 publications

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“…For a deeper understanding of mangrove change, i.e. the development of new mangrove patches, the loss of patches and the expansion or contraction of patches already present, we used the geographic technique “spatial–temporal analysis of moving polygons” (STAMP), available through the ‘stampr’ R package [80]. To be able to run the STAMP analysis, 2004’ polygons had to be geographically corrected for the known issues in GE imagery position errors [81].…”

Section: Methodsmentioning

confidence: 99%

Mangroves in the Galapagos islands: Distribution and dynamics

2019

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Mangrove forests provide valuable coastal protection from erosion, habitat for terrestrial and marine species, nursery grounds for commercial fisheries and are economically important for tourism. Galapagos’ mangroves usually grow directly on solid lava and fragmented rocky shores, thereby stabilizing the sediment and facilitating colonisation by other plants and many animals. However, until very recently, only inaccurate data described mangrove coverage and its distribution. We mapped mangroves using freely available Google Earth Very High Resolution images based on on-screen classification and compared this method to three semi-automatic classification algorithms. We also analysed mangrove change for the period 2004–2014. We obtained an area of 3657.1 ha of fringing mangrove that covers 35% of the coastline. Eighty percent of mangrove cover is found in Isabela island, and 90% in the western and central south-eastern bioregions. The overall accuracy of mangrove classification was 99.1% with a Kappa coefficient of 0.97 when validated with field data. On-screen digitization was significantly more accurate than other tested methods. From the semi-automated methods, Maximum Likelihood Classification with prior land-sea segmentation yielded the best results. During the 2004–2014 period, mangrove coverage increased 24% mainly by expansion of existing mangroves patches as opposed to generation of new patches. We estimate that mangrove cover and growth are inversely proportional to the geological age of the islands. However, many other factors like nutrients, currents or wave exposure protection might explain this pattern. The precise localization of mangrove cover across the Galapagos islands now enables documenting whether it is changing over time.

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Section: Methodsmentioning

confidence: 99%

Mangroves in the Galapagos islands: Distribution and dynamics

2019

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“…Whenever significant differences were found, we performed post-hoc comparisons (Tukey's HSD) to test for differences between pair groups (Supplementary Material -Table SM3). STAMP analyses were conducted using R package "stampr" (Long et al, 2018), while the HLC analyses were performed with R package "vegan" (Oksanen et al, 2012).…”

Section: Spatiotemporal Changes On Roadkill Hotspots Patternsmentioning

confidence: 99%

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns

Medinas

Marques

Costa

et al. 2021

Journal of Environmental Management

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Wildlife roadkill hotspots are frequently used to identify priority locations for implementing mitigation measures. However, understanding the landscape-context and the spatial and temporal dynamics of these hotspots is challenging. Here, we investigate the factors that drive the spatiotemporal variation of bat mortality hotspots on roads along three years. We hypothesize that hotspot locations occur where bat activity is higher and that this activity is related to vegetation density and productivity, probably because this is associated with food availability. Statistically significant clusters of bat-vehicle collisions for each year were identified using the Kernel Density Estimation (KDE) approach. Additionally, we used a spatiotemporal analysis and generalized linear mixed models to evaluate the effect of local spatiotemporal variation of environmental indices and bat activity to predict the variation on roadkill hotspot locations and to asses hotspot strength over time. Between 2009 and 2011 we conducted daily surveys of bat casualties along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 509 casualties and we identified 86 statistically significant roadkill hotspots, which comprised 12% of the road network length and contained 61% of the casualties. Hotspots tended to be located in areas with higher accumulation of vegetation productivity along the three-year period, high bat activity and low temperature. Furthermore, we found that only 17% of the road network length was consistently classified as hotspots across all years; while 43% of hotspots vanished in consecutive years and 40% of new road segments were classified as hotspots. Thus, non-persistent hotspots were the most frequent category. Spatiotemporal changes in hotspot location are associated with decreasing vegetation production and increasing water stress on road surroundings. This supports our hypothesis that a decline on overall vegetation productivity and increase of roadside water deficit, and the presumed lower abundance of prey, have a significant effect on the decrease of bat roadkills. To our knowledge, this is the first study demonstrating that freely available remote sensing data can be a powerful tool to quantify bat roadkill risk and assess its spatiotemporal dynamics.

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“…However, it is important to consider the polygon nature of the object in some of evaluation methods such as k‐anonymity satisfaction, false‐identification, and non‐unique obfuscation. To calculate the distance between two polygons, several polygon distance methods can be used including centroid, minimum, and Hausdorff distance (Long et al, 2018; Maciąg, 2017). In this study, the centroid distance was used to calculate the distance between the original polygon and its obfuscated polygon.…”

Section: Methodsmentioning

confidence: 99%

Implementation of novel polygon‐based obfuscation methods to improve privacy of agricultural data

Nowbakht

O’Sullivan

Wall

et al. 2022

Transactions in GIS

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Geoprivacy protection is a significant concern when sharing data. To support sustainable land management by leveraging existing agricultural data, research is needed to identify how the polygon nature of static field parcels can be obfuscated to allow data sharing among individuals and organizations.In this study, five adaptive polygon-based obfuscation methods including PN*Rand, PDonut-k, PDensity-k, PAHilb, and PDonut_AHilb methods were developed and applied on the Irish Nutrient Management Planning Online (NMP Online) agricultural dataset. The polygon-based obfuscation methods introduced in this study were designed with the consideration of properties of spatial polygon objects including the spatial coordinates, shape and size of the polygon, topology, and spatial relationship between adjacent polygons that can be used to identify real-world objects. These methods were developed to guarantee that there is no false-identification and non-unique obfuscation which is important for static polygon objects in terms of accuracy and privacy protection. Qualitative approaches were developed to identify the optimal values of inner and outer radii of donut shape based on k-anonymity satisfaction and subsequently obtain the optimal value of k-anonymity. Several evaluation methods were implemented to compare the methods performance. Density-based methods particularly PDonut-AHilb provide the best trade-off between field parcel confidentiality and

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stampr: Spatial-Temporal Analysis of Moving Polygons in R

Cited by 10 publications

References 20 publications

Mangroves in the Galapagos islands: Distribution and dynamics

Mangroves in the Galapagos islands: Distribution and dynamics

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns

Implementation of novel polygon‐based obfuscation methods to improve privacy of agricultural data

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