sacrevert

142--UKOT--horizon-scanning

Code for work on UKOT plant horizon scanning materials

175-SoN2019

State of Nature plants 2019

dunescapeR

fRescalo

R rewrite of Hill (2012; 10.1111/j.2041-210X.2011.00146.x) fortran code

frescaloR

FRESCALO implemented in R

NPMSTrends2

Further dev work on NPMS species indicator

sacrevert/frescaloR

FRESCALO implemented in R

sacrevert/NPMStrends

Beginning work on data extracts and trends for NPMS species

sacrevert/142--UKOT--horizon-scanning

Code for work on UKOT plant horizon scanning materials

sacrevert/175-SoN2019

State of Nature plants 2019

sacrevert/BDA_R_demos

Bayesian Data Analysis demos for R

sacrevert/dunescapeR

sacrevert/fRescalo

R rewrite of Hill (2012; 10.1111/j.2041-210X.2011.00146.x) fortran code

sacrevert/NPMSTrends2

Further dev work on NPMS species indicator

sacrevert/createIDFneighbourhood

Frescalo neighbourhoods for the Ile-de-France

sacrevert/Cyprus-UTM-grids

Cyprus UTM 10km grid and function to create subdivisions in R

sacrevert/Ecology-Conservation

sacrevert/example-notebooks

Miscellaneous notebooks to use with Sentinel Hub

sacrevert/Frequency-rescaling-demo

Example of how frequency scaling using local occupancy (FreScaLO) works

sacrevert/frescaloNeighbourhoods

Various frescalo neighbourhoods

sacrevert/ISO-3166-Countries-with-Regional-Codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

sacrevert/occAssessSwedenEg

occAssess example using Swedish GBIF Cerambycidae data

sacrevert/RangeChangeSims

Range Change simulations

sacrevert/ROBITT

Risk-Of-Bias in Temporal Trends in Ecology (ROBITT)

sacrevert/ROBITT_ideas

Response to ROBITT workshop (some ideas presented in isoslides)

sacrevert/sen2mosaic

Building cloud-free mosaics of Sentinel-2 data for land cover mapping is difficult, with existing tools still under-development and frequently confusing.

sacrevert/shinyforms

Easily create questionnaire-type forms with Shiny

sacrevert/simpleFrescaloDemo

sacrevert/soaR

Species' occurrence analyses in R

sacrevert/starter-academic

🎓 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.

sacrevert/Topographical-Feature-Extraction-Using-Machine-Learning-Techniques-from-Sentinel-2A-Imagery-

The advancement in the satellite technology has made it possible to easily and frequently obtain the satellite images of most of the regions in the Earth. The satellite data contains abundant amount of information which can be very useful for variety of societal applications. However, manual identification of the land cover in a particular area is a very challenging and time-consuming task. we propose a method for classifying the land types from Sentinel 2A imagery using various models like random forest, SVM, Naive Bayes, Decision Tree (CART) and validate which model better classifies them. QGIS software is used to generate training data for the classifier. The analysis reveals that random forest classifier outperforms the rest of the classification methods in terms of better accuracy. This automated approach can be applied to large sets of data, reducing the need for manual labeling.

sacrevert/USSpensions

Calculations for USS pensions

sacrevert/visualiseFresNeighbours

Quick tool for visualising neighbourhoods used in Frescalo