Package: BatchPlanet 1.0.0

BatchPlanet: Batch access and processing of PlanetScope imagery for spatiotemporal analysis in R

The `BatchPlanet` R package provides a reproducible and scalable workflow for accessing and processing PlanetScope satellite imagery, enabling environmental researchers to efficiently perform spatiotemporal analysis of high-resolution remote sensing data. The package streamlines the steps required to work with the Planet API, including the ordering and downloading of imagery, retrieving and cleaning pixel-level time series, and computing derived metrics such as the Enhanced Vegetation Index (EVI) and green-up/down time. This package has supported peer-reviewed research in predicting reproductive phenology in wind-pollinated trees (Song et al., 2025). Generalizable beyond phenological research, this tool is particularly suited for environmental research that involves large volumes of PlanetScope imagery across multiple sites and long time periods.

Authors:Yiluan Song [aut, cre], Alexandre R. Bevington [aut], Kenneth N. Reid [aut], Jiali Zhu [aut], Yi Liu [aut], Kai Zhu [aut]

BatchPlanet_1.0.0.tar.gz
BatchPlanet_1.0.0.zip(r-4.7-any)BatchPlanet_1.0.0.zip(r-4.6-any)BatchPlanet_1.0.0.zip(r-4.5-any)
BatchPlanet_1.0.0.tgz(r-4.6-any)BatchPlanet_1.0.0.tgz(r-4.5-any)
BatchPlanet_1.0.0.tar.gz(r-4.7-any)BatchPlanet_1.0.0.tar.gz(r-4.6-any)
BatchPlanet_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BatchPlanet/json (API)

# Install 'BatchPlanet' in R:
install.packages('BatchPlanet', repos = c('https://yiluansong.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zhulabgroup/batchplanet/issues

Pkgdown/docs site:https://zhulabgroup.github.io

On CRAN:

Conda:

5.71 score 7 stars 35 scripts 23 exports 127 dependencies

Last updated from:e5e2a0336f (on release). Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE189
source / vignettesOK271
linux-releaseNOTE233
macos-releaseNOTE307
macos-oldrelNOTE319
windows-develNOTE202
windows-releaseNOTE203
windows-oldrelNOTE156
wasm-releaseOK181

Exports:calculate_season_metricscalculate_season_metrics_batchclean_planetscope_time_seriesclean_planetscope_time_series_batchdetermine_seasonalitydownload_planetscope_imagerydownload_planetscope_imagery_batchdownload_sample_dataorder_planetscope_imageryorder_planetscope_imagery_batchread_data_productretrieve_planetscope_time_seriesretrieve_planetscope_time_series_batchsearch_planetscope_imageryset_api_keyset_bboxset_planetscope_parametersset_thresholdsvisualize_coordinatesvisualize_time_seriesvisualize_true_color_imageryvisualize_true_color_imagery_batchwhittaker_smoothing_filling

Dependencies:askpassbase64encbitbit64bslibcachemclassclassIntclicliprcodetoolscolorspacecommonmarkcpp11crayoncrosstalkcurldata.tableDBIdigestdoSNOWdotenvdplyre1071evaluatefarverfastmapfontawesomeforeachforecastfracdifffsgenericsggplot2ggtextgluegridtextgtablehighrhmshtmltoolshtmlwidgetshttpuvhttrimputeTSisobanditeratorsjpegjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleafletleaflet.providerslifecyclelitedownlmtestlubridatemagrittrmarkdownMASSmemoisemimenlmennetopensslotelpillarpkgconfigplotlypngprettyunitsprogresspromisesproxyptwpurrrR6rappdirsrasterRColorBrewerRcppRcppArmadilloRcppDEreadrrlangrmarkdowns2S7sassscalessegmentedsfshinyshinyWidgetssnowsourcetoolsspstinepackstringistringrsysterratibbletidyrtidyselecttimechangetimeDatetinytextzdbunitsurcautf8vctrsviridisLitevroomwithrwkxfunxml2xtableyamlzoo

1 Getting Started Workflow
Overview | 1 Read coordinate data | 2 Download PS data | 2.1 Set downloading parameters | 2.2 Order | 2.3 Download | 2.4 Visualize true color imagery | 3 Retrieve and process time series | 3.1 Retrieve time series | 3.2 Clean time series | 3.3 Calculate start/end of season metrics
Rendered fromworkflow.Rmdusingknitr::rmarkdown

Last update: 2026-03-10
Started: 2023-09-01

2 Customization and advanced usage
Direct search and order for a single site | Direct download from a single order | Visualize a single true color image | Direct retrieval of time series for a set of coordinates | Clean time series data in a single data frame | Calculate start/end of season metrics from a single data frame
Rendered fromcustomization.Rmdusingknitr::rmarkdown

Last update: 2026-02-09
Started: 2025-07-22

3 Miscellaneous time series processing tools
Gap-filling and smoothing | Determine seasonality
Rendered fromtools.Rmdusingknitr::rmarkdown

Last update: 2026-02-09
Started: 2025-07-22

Readme and manuals

Help Manual

Help pageTopics
Calculate start/end of season metrics for a single time seriescalculate_season_metrics
Calculate start/end of season metrics for time series from multiple sites and groupscalculate_season_metrics_batch
Clean a single PlanetScope time seriesclean_planetscope_time_series
Clean PlanetScope time series for multiple sites and groupsclean_planetscope_time_series_batch
Test for seasonality in a time series Using AIC-based model selectiondetermine_seasonality
Download a PlanetScope orderdownload_planetscope_imagery
Download PlanetScope imagery for multiple sites and yearsdownload_planetscope_imagery_batch
Download sample data from GitHubdownload_sample_data
Place a PlanetScope orderorder_planetscope_imagery
Order PlanetScope imagery for multiple sites and yearsorder_planetscope_imagery_batch
Read and combine processed data productsread_data_product
Retrieve a single set of PlanetScope time seriesretrieve_planetscope_time_series
Retrieve PlanetScope time series for multiple sites and groupsretrieve_planetscope_time_series_batch
Search for available PlanetScope imagerysearch_planetscope_imagery
Set or change the Planet API keyset_api_key
Generate a Bounding Box from Coordinate Dataset_bbox
Set PlanetScope API Parametersset_planetscope_parameters
Specify thresholds for detecting start/end of seasonset_thresholds
Visualize coordinates from a data framevisualize_coordinates
Visualize time series interactivelyvisualize_time_series
Visualize true-color raster imageryvisualize_true_color_imagery
Launch a Shiny App to Visualize True-Color Imageryvisualize_true_color_imagery_batch
Smooth and gap-fill a time series using Whittaker smoothingwhittaker_smoothing_filling