R Client Library for Web Land Trajectory Service (WLTS)
Information on Land Use and Land Cover (LULC) is essential to support governments in making decisions about the impact of human activities on the environment, planning the use of natural resources, conserving biodiversity and monitoring climate change.
Currently, several projects systematically provide information on the dynamics of land use and cover. Well known projects include PRODES, DETER and TerraClass. These projects are developed by INPE and they produce information on land use and coverage used by the Brazilian Government to make public policy decisions. Besides these projects there are other initiatives from universities and space agencies devoted to the creation of national and global maps.
Although these projects follow open data policies and provide a rich collection of data, there is still a gap in tools that facilitate the integrated use of these collections. Each project adopts its own land use and land cover classification system, providing different class names and meanings for the elements of these collections. The forms of distribution of project data can be carried out in different ways, through files or web services. In addition, the data has different spatial and temporal resolutions and storage systems (raster or vector).
In this context, the Web Land Trajectory Service (WLTS) is a service that aims to facilitate the access to these approach consists of using a data model that defines a minimum set of temporal and spatial information to represent different sources and types of data, but with a focus on land use and land cover.
WLTS can be used in a variety of applications, such as validating land cover data sets, selecting training samples to support Machine Learning algorithms used in the generation of new classification maps.
If you want to know more about WLTS service, please, take a look at its specification.
To install the development version of rwlts, run the following
commands:
# load necessary libraries
library(devtools)
devtools::install_github("brazil-data-cube/rwlts")Importing rwlts package:
library(rwlts)rwlts implements the following WLTS operations:
| WLTS operations | rwlts functions |
|---|---|
/list_collections |
list_collections(URL,) |
/describe_collections |
describe_collection(URL, collection_id) |
/trajectory |
get_trajectory(URL, latitude, longitude) |
These functions can be used to retrieve information from a WLTS API
service. The code bellow creates a wlts object and list the available
collections of the WLTS API of the Brazil Data Cube project of the
Brazilian National Institute for Space Research INPE.
The first operation, list_collections, retrieves all available
collections in WLTS service.
wlts_bdc <- "https://brazildatacube.dpi.inpe.br/wlts/"
list_collections(wlts_bdc)
#> [1] "lapig_areas_pastagem" "terraclass_amazonia"
#> [3] "deter_amazonia_legal" "deter_cerrado"
#> [5] "ibge_cobertura_uso_terra" "prodes_amazonia_legal"
#> [7] "prodes_cerrado" "mapbiomas_caatinga-v5"
#> [9] "mapbiomas_cerrado-v5" "mapbiomas_amazonia-v5"
#> [11] "terraclass_amazonia-v2" "mapbiomas_pantanal-v5"
#> [13] "mapbiomas_pampa-v5" "terraclass_cerrado"
#> [15] "mapbiomas_mata_atlantica-v5"Each collection returned by the WLTS service can be used for retrieving
LULC trajectories. To get information about the collections, we use the
describe_collection function. This function returns the metadata of a
given collection, which includes the description and specific details.
The metadata also describes the spatio-temporal extent of the
collection.
In the code below, we retrieve the metadata from the
deter_amazonia_legal collection using the describe_collection
function.
describe_collection(wlts_bdc, "deter_amazonia_legal")
#> $classification_system
#> $classification_system$classification_system_id
#> [1] "21"
#>
#> $classification_system$classification_system_name
#> [1] "DETER Amazônia Legal"
#>
#> $classification_system$classification_system_version
#> [1] "1.0"
#>
#> $classification_system$type
#> [1] "Self"
#>
#>
#> $collection_type
#> [1] "Feature"
#>
#> $description
#> [1] "Alertas de Desmatamento da Amazônia Legal."
#>
#> $detail
#> [1] "O DETER é um levantamento rápido de alertas de evidências de alteração da cobertura florestal na Amazônia, feito pelo INPE. O DETER foi desenvolvido como um sistema de alerta para dar suporte à fiscalização e controle de desmatamento e da degradação florestal realizadas pelo Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) e demais órgãos ligados a esta temática. Mais informações acesse: http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/deter"
#>
#> $name
#> [1] "deter_amazonia_legal"
#>
#> $period
#> $period$end_date
#> [1] "2020-06-18"
#>
#> $period$start_date
#> [1] "2016-08-02"
#>
#>
#> $resolution_unit
#> $resolution_unit$unit
#> [1] "DAY"
#>
#> $resolution_unit$value
#> [1] 1
#>
#>
#> $spatial_extent
#> $spatial_extent$xmax
#> [1] -44.00039
#>
#> $spatial_extent$xmin
#> [1] -73.54909
#>
#> $spatial_extent$ymax
#> [1] 4.555376
#>
#> $spatial_extent$ymin
#> [1] -18.03644LULC trajectories can be extracted from collections. These LULC
trajectories in WLTS services are associated with a point (lat, long) in
geographic space. In rwlts, we can use the get_trajectory function
to retrieve trajectories. For example, in the code below, the point
(-54, -12) trajectory is retrieved from the mapbiomas_amazonia-v5
collection.
get_trajectory(wlts_bdc,
latitude = -12,
longitude = -54,
collections = "mapbiomas_amazonia-v5",
config = httr::add_headers("x-api-key" = "change-me"))
#> $query
#> NULL
#>
#> $result
#> # A tibble: 35 × 4
#> class collection date point_id
#> <chr> <chr> <chr> <int>
#> 1 Formação Florestal mapbiomas_amazonia-v5 1985 1
#> 2 Formação Florestal mapbiomas_amazonia-v5 1986 1
#> 3 Formação Florestal mapbiomas_amazonia-v5 1987 1
#> 4 Formação Florestal mapbiomas_amazonia-v5 1988 1
#> 5 Formação Florestal mapbiomas_amazonia-v5 1989 1
#> 6 Formação Florestal mapbiomas_amazonia-v5 1990 1
#> 7 Formação Florestal mapbiomas_amazonia-v5 1991 1
#> 8 Formação Florestal mapbiomas_amazonia-v5 1992 1
#> 9 Formação Florestal mapbiomas_amazonia-v5 1993 1
#> 10 Formação Florestal mapbiomas_amazonia-v5 1994 1
#> # … with 25 more rows
#>
#> attr(,"class")
#> [1] "wlts"The get_trajectory function returns a list of class wlts. This
object contains the query and result attributes. The query
attribute stores the query performed to retrieve the data. By default,
it will be NULL. For this information to be stored, the
query_info = TRUE parameter is required. For example:
get_trajectory(wlts_bdc,
latitude = -12,
longitude = -54,
collections = "mapbiomas_amazonia-v5",
query_info = TRUE,
config = httr::add_headers("x-api-key" = "change-me"))The result attribute stores the retrieved trajectories. The data is
stored in a tibble for easy manipulation, which has the columns:
class: LULC class;collection: Data Collection;date: Time instants of the trajectory;point_id: ID of the point that was queried.
The point_id column of the result tibble is used in rwlts to
identify the entry point. This ID is necessary since the
get_trajectory function can be used with vectors as input. For
example, the code below retrieves the trajectory of data from the
mapbiomas_amazonia-v5 collection for two points (-54, -12) and
(-54, -11.01).
get_trajectory(wlts_bdc,
latitude = c(-12, -11.01),
longitude = c(-54, -54),
collections = "mapbiomas_amazonia-v5",
config = httr::add_headers("x-api-key" = "change-me"))
#> $query
#> NULL
#>
#> $result
#> # A tibble: 70 × 4
#> class collection date point_id
#> <chr> <chr> <chr> <int>
#> 1 Formação Florestal mapbiomas_amazonia-v5 1985 1
#> 2 Formação Florestal mapbiomas_amazonia-v5 1986 1
#> 3 Formação Florestal mapbiomas_amazonia-v5 1987 1
#> 4 Formação Florestal mapbiomas_amazonia-v5 1988 1
#> 5 Formação Florestal mapbiomas_amazonia-v5 1989 1
#> 6 Formação Florestal mapbiomas_amazonia-v5 1990 1
#> 7 Formação Florestal mapbiomas_amazonia-v5 1991 1
#> 8 Formação Florestal mapbiomas_amazonia-v5 1992 1
#> 9 Formação Florestal mapbiomas_amazonia-v5 1993 1
#> 10 Formação Florestal mapbiomas_amazonia-v5 1994 1
#> # … with 60 more rows
#>
#> attr(,"class")
#> [1] "wlts"In this case, the point (-54, -12) will have point_id equal to 1,
while (-54, -11.01) will have point_id equal to 2.
In addition to multiple point retrieval, the get_trajectory function
allows multiple collections to be queried for the composition of the
trajectory. To do this, in the collections parameter, the collections
must be assigned. For example, data from the collections
mapbiomas_amazonia-v5 and terraclass_amazonia-v2 are retrieved in
the code below.
get_trajectory(wlts_bdc,
latitude = c(-12, -11.01),
longitude = c(-54, -54),
collections = c("mapbiomas_amazonia-v5", "terraclass_amazonia-v2"),
config = httr::add_headers("x-api-key" = "change-me"))
#> $query
#> NULL
#>
#> $result
#> # A tibble: 80 × 4
#> class collection date point_id
#> <chr> <chr> <chr> <int>
#> 1 Formação Florestal mapbiomas_amazonia-v5 1985 1
#> 2 Formação Florestal mapbiomas_amazonia-v5 1986 1
#> 3 Formação Florestal mapbiomas_amazonia-v5 1987 1
#> 4 Formação Florestal mapbiomas_amazonia-v5 1988 1
#> 5 Formação Florestal mapbiomas_amazonia-v5 1989 1
#> 6 Formação Florestal mapbiomas_amazonia-v5 1990 1
#> 7 Formação Florestal mapbiomas_amazonia-v5 1991 1
#> 8 Formação Florestal mapbiomas_amazonia-v5 1992 1
#> 9 Formação Florestal mapbiomas_amazonia-v5 1993 1
#> 10 Formação Florestal mapbiomas_amazonia-v5 1994 1
#> # … with 70 more rows
#>
#> attr(,"class")
#> [1] "wlts"Finally, the get_trajectory function, through the start_date and
end_date parameters, allows you to specify the time intervals used in
the trajectory. To exemplify its use, in the code below, trajectories
are retrieved for the points (-54, -12) and (-54, -11.01), from the
mapbiomas_amazonia-v5 and terraclass_amazonia-v2 collections in the
time interval [2003-01-01, 2004-01-01].
get_trajectory(wlts_bdc,
latitude = c(-12, -11.01),
longitude = c(-54, -54),
start_date = "2003-01-01",
end_date = "2004-01-01",
collections = c("mapbiomas_amazonia-v5","terraclass_amazonia-v2"),
config = httr::add_headers("x-api-key" = "change-me"))
#> $query
#> NULL
#>
#> $result
#> # A tibble: 6 × 4
#> class collection date point_id
#> <chr> <chr> <chr> <int>
#> 1 Formação Florestal mapbiomas_amazonia-v5 2003 1
#> 2 Formação Florestal mapbiomas_amazonia-v5 2004 1
#> 3 Vegetação Natural Florestal Primária terraclass_amazonia-v2 2004 1
#> 4 Formação Florestal mapbiomas_amazonia-v5 2003 2
#> 5 Formação Florestal mapbiomas_amazonia-v5 2004 2
#> 6 Vegetação Natural Florestal Primária terraclass_amazonia-v2 2004 2
#>
#> attr(,"class")
#> [1] "wlts"To visualize the trajectories and fully understand their time dynamics,
the rwlts package implements the Alluvial-based visualization method.
To create this plot, use the plot function, as shown in the example
below:
# import data from package
data("mt_500_mapbiomas_cerrado")
plot(mt_500_mapbiomas_cerrado)
Besides, you can fully customize the returned plot. This customization
is possible since the plot function returns a ggplot2 object.
library(ggplot2)
library(ggalluvial) # use to create plot
library(cowplot) # use different theme
plot(mt_500_mapbiomas_cerrado, show_count = TRUE) +
cowplot::theme_minimal_hgrid() +
labs(title = "Changes in Primavera do Leste (2004-2014)",
x = "Timeline",
y = "Number of points",
fill = "Class") +
theme(legend.position = "bottom",
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(values = c("#129912",
"#32CD32",
"#BDB76B",
"#FFD966",
"#FFFFB2"),
labels = c("Formação Florestal",
"Formação Savânica",
"Outras Lavouras Temporárias",
"Pastagem",
"Soja"))
The numbers inside each bar correspond to the quantity of points extracted in each year. You can see that according to the change of LULC classes, the quantity of points in each class also changes.
Copyright (C) 2021 INPE.
R client for WLTS is free software; you can redistribute it and/or modify it under the terms of the MIT License; see LICENSE file for more details.