Abstract
In this chapter we review some examples of general Land Use Cover (LUC) mapping at a supra-national level in America and Asia. These datasets provide a general overview of the land uses and covers in specific American or Asian regions, without focusing on any particular land use or cover. For Asia, we have only identified one dataset mapping the Himalayan region, whereas for America five different datasets were identified. Only three of these are reviewed here, as the other two (SERENA, South America 30 m) are not available for download. The most ambitious project of all those reviewed is NALCMS, which coordinates the production of a LUC map for the whole of North America (Canada, Mexico, USA) at detailed scales (30–250 m) and using the same classification legend. It is the only dataset of all those reviewed that provides a time series of LUC maps (2005, 2010 and 2015). The Himalaya Regional Land Cover database is a vector-based map that provides information on LUC changes over the period 1970/80–2007 at a scale of 1:350,000. The other two American datasets—LBA-ECO LC-08 (1 km, 1987/91) and MERISAM2009 (300 m, 2008/10)—are raster-based and only available for one date, therefore making change detection impossible.
You have full access to this open access chapter, Download chapter PDF
Similar content being viewed by others
Keywords
1 LBA-ECO LC-08—Land Cover Map of South America
| Product | |
LULC general / LULC thematic (vegetation) | ||
Dates | ||
1987 / 91 | ||
Formats | ||
Raster | ||
Pixel size 1 km | ||
Thematic resolution | ||
42 classes: 1 (a), 1 (ag), 27 (v), 7 (m), 3 (na)Footnote 1 | ||
Compatible legends | ||
None | ||
Extent | ||
South America | ||
Updating | ||
Not expected | ||
Change detection | ||
No (only one date) | ||
Overall accuracy | ||
Depending on the class. Expected to be >90% for 24 classes covering 85% of the map. Classes with an accuracy of <75% only cover 6.5% of the map | ||
Website of reference | Website Language English | |
https://daac.ornl.gov/LBA/guides/LC08_EOS_Maps.html#references | ||
Download site | ||
Availability | Format(s) | |
Open Access after registration | .tiff, .nc, .asc, .nitf, .img | |
Technical documentation | ||
Stone et al. (1994) | ||
Other references of interest | ||
– |
Project
The Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA) was an international project launched by the Brazilian scientific community in 1993. The main objectives were to study Amazonia and its role in the earth’s ecosystem as well as to understand LUC changes in the area and their environmental consequences.
As part of the project, a global LUC map covering South America was produced from imagery and data of the period 1987/91. Vegetation and soil maps for Brazil were also digitalized on the basis of previous resources. These maps are also available for any interested user as part of the same dataset.
Production method
The LBA LUC map was produced after unsupervised classification of AVHRR imagery, postprocessing and labelling of the classification results. Different sources of auxiliary data were used in the production of the dataset to overcome the limitations of the imagery, including a Global Vegetation Index (GVI) layer, the UNESCO’s Vegetation Map of South America, the Hueck’s Vegetationsskarte Von Sudamerika and a potential vegetation map of South America based on the Holdridge bioclimatic scheme.
Production description
Users can download the LUC map as a single raster file including the LUC information or as part of a data package including all the products produced within the LBA project. As part of these, we find different vegetation and soil maps for Brazil. In all cases, the download only includes the raster files and no auxiliary information is provided.
Downloads
RAR folder with all products | |
---|---|
– Raster file with LUC map – 3 raster files with Brazil vegetation maps at different levels of thematic resolution – 3 raster files with Brazil soil maps at different levels of thematic resolution |
SA_lc_Map_41class.tiff | |
---|---|
– Raster file with LUC map |
Legend and codification
Code | Label | Code | Label |
---|---|---|---|
0 | Off Map (Fill Value) | 21 | Secondary seasonal forest with agriculture |
1 | Tropical moist and semi-deciduous forest | 22 | Urban and degraded lands |
2 | Cleared tropical moist Forest | 23 | Degraded tropical seasonal forest |
3 | Unclassified | 24 | Mixed pine forest with secondary forest and agriculture |
4 | Water | 25 | Xerophytic scrubland |
5 | Savanna/Grasslands | 26 | Xerophytic littoral vegetation |
6 | Wet vegetation/Mixed | 27 | Montane grassland |
7 | Unclassified | 28 | Montane woodlands |
8 | Mangroves | 29 | Montane forests |
9 | Seasonally deciduous Woodlands. | 30 | Degraded montane grasslands |
10 | Forest (Bamboo dominated?) | 31 | Degraded montane woodlands |
11 | Secondary tropical moist forest with agriculture | 32 | Degraded montane forests |
12 | Pantanal grassland (seasonally flooded) | 33 | Cool deciduous shrublands |
13 | Tropical seasonal or deciduous forest | 34 | Bare soil/Rock |
14 | Agriculture | 35 | Cool deciduous woodlands |
15 | Gallery forests | 36 | Cool deciduous forests |
16 | Tropical open forests (mixed) | 37 | Snow/Rock |
17 | Cerrado (woodlands) degraded | 38 | Salt marsh community |
18 | Grasslands or Savanna with agriculture | 39 | Desert |
19 | Xerophytic woodlands with agriculture | 40 | Degraded temperate deciduous forest |
20 | Degraded xerophytic woodlands | 41 | Temperate deciduous forests |
2 NALCMS—North American Land Change Monitoring System
| Product | |
LULC general | ||
Dates | ||
2005, 2010, 2015 | ||
Formats | ||
Raster | ||
Pixel size | ||
30 m (2010, 2015) 250 m (2005, 2010) | ||
Thematic resolution | ||
19 classes: 1 (a), 1 (ag), 13 (v), 1 (m), 0 (na) | ||
Compatible legends | ||
FAO-LCCS | ||
Extent | ||
North America | ||
Updating | ||
Unknown | ||
Change detection | ||
Through change layers | ||
Overall accuracy | ||
Expected to be >79.9% | ||
Website of reference | Website Language English, Spanish, French | |
http://www.cec.org/north-american-land-change-monitoring-system/ | ||
Download site | ||
http://www.cec.org/north-american-land-change-monitoring-system/ | ||
Availability | Format(s) | |
Open Access | .tiff, .img, .mxd | |
Technical documentation | ||
Colditz et al. (2012, 2014a, b, c), Gebhardt et al. (2014), Homer et al. (2015), Jin et al. (2013, 2019), Latifovic et al. (2012, 2017) | ||
Other references of interest | ||
Yang et al (2018) |
Project
The NALCMS project started in 2006 fruit of the collaboration between the following Canadian, American and Mexican institutions: the Natural Resources Canada/Canada Centre for Remote Sensing (NRCan/CCRS), the United States Geological Survey (USGS) and the Mexican National Institute of Statistics and Geography (INEGI), National Commission for the Knowledge and Use of Biodiversity (CONABIO) and the National Forestry Commission of Mexico (CONAFOR). The project is also supported by the Commission for Environmental Cooperation (CEC), a body comprising all three North American countries.
The objective of the project was to create a homogeneous, coherent LUC dataset for North America that could be used for environmental monitoring at a continental scale, and which also addressed the needs and requirements of scientific and policy-making communities. Each country produced its own LUC map according to its needs and requirements. The purpose of the project was to coordinate the homogenization and harmonization of these national maps to create a single map of the whole North America.
Since it was launched in 2006, three LUC maps have been produced. Important improvements have been made over time. The most significant change was the improved spatial resolution of 30 m applied in the latest maps, compared to 250 m in the first edition.
Production method
There is no single production methodology for NALCMS. Each country is responsible for producing its own LUC map, according to its particular needs and interests.
The first edition of the product for 2005 was created via a classification of MODIS imagery at 250 m following a similar workflow for the three countries. In 2010, the initial map for 2005 at 250 m was revised, mapping only the LUC changes that happened over the period 2005–2010. LUC changes for Hawaii were not mapped in this update. Mapped changes were individually distributed through a specific change layer at 250 m for the period 2005–2010.
For 2015, Canada and the USA obtained their respective LUC maps after classification of Landsat imagery, while Mexico obtained its map via the classification of RapidEye (5 m) imagery resampled at 30 m. Whereas for Canada and Mexico the imagery mostly dates from 2015, most of the imagery used in the US map was from the year 2016. For 2010, the three countries obtained the map at 30 m from the classification of Landsat imagery. However, whereas most of the imagery for Canada and Mexico was captured in 2010, the images used to map USA were taken in 2011.
A change layer at 30 m for the period 2010–2015 was obtained by comparing the base LUC maps at the two different dates for Canada and USA. In Mexico, because different imagery sources had been used for the different reference years, the changes were individually extracted from Landsat imagery based on an independent change detection algorithm.
Product description
NALCMS can be separately downloaded for each of the reference years. A change layer for each mapped period is also available: 2005–2010 and 2010–2015. For those years for which more than one spatial resolution is available, users can download a separate product at each resolution.
The datasets at 250 m can be downloaded in different formats: GeoTIFF, ERDAS Imagine (.img), Map Exchange Document (.mxd) and as a georeferenced PDF file (GeoPDF). Datasets at 30 m are downloaded in a compressed file (.zip) in GeoTIFF. They can be downloaded for the whole of North America or individually for each of the mapped countries.
Different auxiliary information is provided with each downloaded product. Nonetheless, the metadata for all the available products can be downloaded separately from the dataset’s website.
Downloads
Land Cover, 2005–2010 (MODIS, 250 m), TIFF | |
---|---|
– Raster files with North America and Hawaii LUC maps (.tiff) – Metadata file (.doc) – Definitions of the different classes (.doc) [Only 2010 map] – Press release presenting the product (.doc) – Terms of use of the product (.doc) |
Land Cover Change, 2005–2010 (MODIS, 250 m), TIFF | |
---|---|
– Raster files with LUC changes (.tiff) – Layer style file for ArcGIS (.lyr) – Cross tabulation matrixes of change (in ha, percent and pixels) at two different classification schemes (.xlsx) – Metadata file (.doc)—Press release presenting the product (.doc) – Terms of use of the product (.doc) |
Land Cover, 2010–2015 (Landsat, 30 m), North America | |
---|---|
– Raster file with LUC map – Layer style files for ArcGIS (.lyr) in English, French and Spanish – Metadata file (.doc) |
Land Cover Change, 2010–2015 (Landsat, 30 m), North America | |
---|---|
– Raster files with gains and losses for the Forest, Shrubland, Grassland, Wetland, Cropland, Barren Land, Urban and Built-up, Water and Snow and Ice categories (.tiff) – Raster file with LUC changes – Metadata file (.doc) – Text document with a description of the dataset (.txt) |
Legend and codification
The change layers include a qualitative description of the classes at the two different points in time. In addition, the pixel values are formed by combining the class code for the land use at point 1 in time with the class code for the new land use at point 2. e.g. the code 1011 refers to a pixel that was Temperate or sub-polar grassland (10) on the first date assessed and had changed to Sub-polar or polar shrubland-lichen-moss (11) on the second.
Code | Label | Code | Label |
---|---|---|---|
1 | Temperate or sub-polar needleleaf forest | 11 | Sub-polar or polar shrubland-lichen-moss |
2 | Sub-polar taiga needleleaf forest | 12 | Sub-polar or polar grassland-lichen-moss |
3 | Tropical or sub-tropical broadleaf evergreen forest | 13 | Sub-polar or polar barren-lichen-moss |
4 | Tropical or sub-tropical broadleaf deciduous forest | 14 | Wetland |
5 | Temperate or sub-polar broadleaf deciduous forest | 15 | Cropland |
6 | Mixed forest | 16 | Barren lands |
7 | Tropical or sub-tropical shrubland | 17 | Urban |
8 | Temperate or sub-polar shrubland | 18 | Water |
9 | Tropical or sub-tropical grassland | 19 | Snow and Ice |
10 | Temperate or sub-polar grassland |
Practical considerations
Maps at 30 m and 250 m were obtained following a different workflow and are not comparable. The maps for Mexico for 2010 and 2015 were obtained from different imagery sources, which means that changes cannot be calculated by subtracting one map from the other and should only be studied using the change layer distributed by the production team.
No information is offered about the uncertainty of the change layers. They may be subject to important sources of uncertainty and may include a lot of technical or spurious changes that did not actually happen on the ground.
NALCMS is one of the products in the North American Environmental Atlas. Users can consult the different NALCMS layers online, together with a lot of other relevant geospatial information for North America, as part of the Atlas website at http://www.cec.org/files/atlas/. Users can also download any of the displayed layers, including the LUC maps, from the same website.
3 MERISAM2009—MERIS MAP 2009/2010 South America
| Product |
LULC thematic | |
Dates | |
2009/10 | |
Formats | |
Raster, Vector | |
Pixel size | |
300 m | |
Thematic resolution | |
11 classes: 0 (a), 3 (ag), 5 (v), 5 (m), 1 (na) | |
Compatible legends | |
None | |
Extent | |
South America | |
Updating | |
Not expected | |
Change detection | |
No (only one date) | |
Overall accuracy | |
Not specified | |
Website of reference | Website Language English |
Not available | |
Download site | |
Not available | |
Availability | Format(s) |
On request | .img, .shp |
Technical documentation | |
Hojas-Gascon et al. (2012) | |
Other references of interest | |
– |
Project
MERISAM is a map developed by the Joint Research Centre (JRC) of the European Commission as part of the regional LUC mapping efforts for South America. With the production of MERISAM, the JRC team aimed to overcome some of the limitations encountered during the production of GlobCover for South America. These referred mainly to spatial and thematic inaccuracies due to the limited number of MERIS images acquired and the method followed to produce the imagery mosaic required to carry out the classification.
The MERISAM dataset was used to assess LUC change in the first decade of the 21st century by comparing it with the GLC2000 dataset.
Production method
MERISAM was obtained after unsupervised classification of MERIS imagery for the period 2008–2010 using the ISODATA classification algorithm, which identified 100 different spectral classes. These were manually assigned to 6 LUC categories based on the information provided by auxiliary datasets, such as national vegetation maps and Google Earth imagery. FAPAR data, which provide information on the photosynthetic activity of the vegetation, were also used as auxiliary information to disaggregate the initial set of LUC categories.
Product description
Interested users can access this dataset by contacting the JRC team that produced it. The dataset includes the LUC map in two formats: raster (.img) and vector (.shp). The vector file was obtained by vectorizing the original raster file.
Downloads
MERISAM2009 | |
---|---|
– Raster file with LUC map (.img) – Vector file with LUC map (.shp) – Two versions of the scientific paper presenting the dataset (.pdf) |
Legend and codification
Here are the codes used to produce the raster version of the map.
Code | Label | Code | Label |
---|---|---|---|
1 | Evergreen forest | 6 | Sparse and barren |
2 | Dry forest and shrubs | 10 | Inland water |
3 | Dry open forest and shrubs | 41 | Grasslands and shrubs |
4 | Grasslands | 51 | Agriculture mosaic |
5 | Agriculture and pasture | 52 | Agriculture intensive |
0 | Background |
Practical considerations
This dataset is not directly available for download. Users wishing to access it must contact the JRC team that produced it (Hugh.EVA@ec.europa.eu, Rene.BEUCHLE@ec.europa.eu).
Although the dataset has been used to assess LUC changes by comparing it with GLC2000, this exercise has many limitations and uncertainties and is therefore not recommended.
4 The Himalaya Regional Land Cover Database
| Product | |
LULC general | ||
Dates | ||
2000 (base LUC map) 1970–2007 (LUC changes) | ||
Formats | ||
Vector | ||
Scale | ||
1:350,000 | ||
Thematic resolution | ||
35 classes: 1 (a), 7(ag), 15 (v), 7 (m), 0 (na) | ||
Compatible legends | ||
LCCS | ||
Extent | ||
Himalaya region | ||
Updating | ||
No | ||
Change detection | ||
Yes, through the change layer | ||
Overall accuracy | ||
Not specified | ||
Website of reference | Website Language English | |
http://www.fao.org/geonetwork/srv/en/main.home?uuid=46d3c2ef-72c3-4f96-8e32-40723cd1847b | ||
Download site | ||
http://www.fao.org/geonetwork/srv/en/main.home?uuid=46d3c2ef-72c3-4f96-8e32-40723cd1847b | ||
Availability | Format(s) | |
Open Access | .shp | |
Technical documentation | ||
– | ||
Other references of interest | ||
– |
Project
The Himalaya Regional Land Cover database was developed within the context of the Global Land Cover Network—Regional Harmonization Programme, promoted by the Food and Agriculture Organization of the United Nations (FAO) and UN Environment in collaboration with the Geographic Information for Sustainable Development (GISD) global partnership. The programme aimed to produce reliable, harmonized global land cover information, providing guidance and methodologies for the production of LUC information at national, regional and global levels.
Production method
The database was obtained by automatic segmentation of Landsat imagery for the reference year 2000 plus visual interpretation. The initial classification was refined by interpreting high resolution imagery from Google Earth.
A layer of LUC changes was obtained by assessing the base map (2000) against historical imagery for the periods 1970–80, 1990 and 2007. No maps for the other years of reference are available, but only the respective layers of changes.
Product description
The database is distributed at regional level in vector format for each of the countries and regions that make up the Himalayan region: Afghanistan, Bhutan, China-Yunnan Sheng, China-Xizang Zizhiqu, India, Nepal, Pakistan, Aksai Chin, Arunachal Pradesh, China/India, Jammu Kashmir and Myanmar. An additional vector layer with LUC changes for the period 1970–2007 is also included. The downloaded products consist solely of the vector layers with LUC data. No other auxiliary information is provided with the downloaded file.
A detailed legend for the product can be downloaded separately in Excel or mdb formats. A layer with the boundaries of the region and its administrative units is also available for download.
Downloads
Land Cover map (country/region) | |
---|---|
– Vector file with Land Cover map (.shp) |
Land change Himalaya region | |
---|---|
– Vector file with map of Land Cover changes (.shp) – Vector file with boundaries of the Himalaya region (.shp) |
Database
Himalaya Regional Land Cover Database |
---|
|
– Z007CODE: LUC Code |
– Z007USLB: LUC User Label |
– Z007PERC: Percentage of the LUC(s) making up the polygon |
– HECTARES: Area of the polygon, in hectares |
– AREA: Area of the polygon, in square meters |
– AGG |
– ZONE: UTM Zone |
– CODE 1: Code LUC 1 |
– CODE 2: Code LUC 2 |
– BOOLEAN1: LUC Label 1 |
– BOOLEAN 2: LUC Label 2 |
– LCCSMAIN1: Main LUC 1 |
– LCCSMAIN2: Main LUC 2 |
– AUTO_ID: Unique identifier for each polygon |
Legend and codification
Code | Label |
---|---|
1H | Herbaceous Crops |
1HI | Irrigated Herbaceous Crops |
1T | Tree Crop |
1S | Tea Crop |
1HSs | Small Herbaceous Crops in sloping land |
1HLMv | Large to Medium Herbaceous Crops in valley floor |
1HSv | Small Herbaceous Crops in valley floor |
2HCO | Closed to Open Herbaceous |
2HS | Sparse Herbaceous |
2HS//6BR | Sparse Herbaceous OR Bare Rock |
2HCO//1H | Closed to Open Herbaceous OR Rainfed Herbaceous Crops |
2SCO | Closed to Open Shrubs |
2SS | Sparse Shrubs with Sparse Herbaceous |
2SSd | Sparse Dwarf Shrubs with Sparse Herbaceous |
2SOd | Open Dwarf Shrubs with Sparse Herbaceous |
2TCOne//2TCObe | Closed to Open Needleleaved Trees OR Closed to Open Broadleaved Trees |
2TCOne | Closed to Open Needleleaved Trees |
2TCObe | Closed to Open Broadleaved Trees |
2TSne//2TSbe | Sparse Needleleaved Trees OR Sparse Broadleaved Trees |
2TSne | Sparse Needleleaved Trees |
2TSbe | Sparse Broadleaved Trees |
4HCOp | Closed to Open Permanently Flooded Herbaceous |
4SCOs | Closed to Open Seasonally Flooded Shrubs |
5UI | Urban and Industrial Areas |
6BR | Bare Rock |
6S | Bare Soil |
6GR | Rock Debris |
8ICE | Glacier |
8ICEr | Rocky Glacier |
8SN | Perennial Snow |
8SNs | Seasonal Snow |
8WNP | Non-Perennial Lakes |
8WBS | Bare Soil in seasonally flooded area |
8WP | Lakes |
8WF | Rivers |
Notes
- 1.
(a): artificial; (ag): agriculture; (v): vegetation; (m): mixed classes; (na): no data.
References
Colditz RR, Llamas RM, Ressl RA (2014a) Detecting change areas in Mexico between 2005 and 2010 using 250 m MODIS images. IEEE J Sel Top Appl Earth Obs Remote Sens 7:3358–3372. https://doi.org/10.1109/JSTARS.2013.2280711
Colditz RR, Llamas RM, Ressl RA (2014c) Annual land cover monitoring using 250M MODIS data for Mexico. Int Geosci Remote Sens Symp: 4664–4667. https://doi.org/10.1109/IGARSS.2014b.6947533
Colditz RR, López Saldaña G, Maeda P et al (2012) Generation and analysis of the 2005 land cover map for Mexico using 250m MODIS data. Remote Sens Environ 123:541–552. https://doi.org/10.1016/j.rse.2012.04.021
Colditz RR, Pouliot D, Llamas RM et al (2014c) Detection of North American land cover change between 2005 and 2010 with 250m MODIS Data. Photogram Eng Remote Sens 80:918–924
Gebhardt S, Wehrmann T, Ruiz MAM et al (2014) MAD-MEX: automatic wall-to-wall land cover monitoring for the mexican REDD-MRV program using all landsat data. Remote Sens 6:3923–3943. https://doi.org/10.3390/rs6053923
Hojas-Gascon L, Eva HD, Gobron N, Simonetti D, Fritz S (2012) The application of medium-resolution MERIS satellite data for continental land-cover mapping over South America results and caveats. Remote Sens Land Use Land Cover Princip Appl. https://doi.org/10.1201/b11964-27
Homer C, Dewitz J, Yang L et al (2015) Completion of the 2011 national land cover database for the conterminous United States—representing a decade of land cover change information. Photogramm Eng Remote Sensing 81:345–354. https://doi.org/10.1016/S0099-1112(15)30100-2
Jin S, Homer C, Yang L et al (2019) Overall methodology design for the United States national land cover database 2016 products. Remote Sens 11. https://doi.org/10.3390/rs11242971
Jin S, Yang L, Danielson P, Homer C, Fry J, Xian G (2013) A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sens Environ 132:159–175. https://doi.org/10.1016/j.rse.2013.01.012
Latifovic R, Homer C, Ressl R et al (2012) North American land change monitoring system. In: Giri C (ed) Remote sensing of land use and land cover: principles and applications. CRC Press, pp 303–324
Latifovic R, Pouliot D, Olthof I (2017) Circa 2010 land cover of Canada: local optimization methodology and product development. Remote Sens 9. https://doi.org/10.3390/rs9111098
Stone TA, Schlesinger P, Houghton RA, Woodwell GM (1994) A map of the vegetation of South America based on satellite imagery. Photogram Eng Remote Sensing 60:541–551
Yang L, Jin S, Danielson P et al (2018) A new generation of the United States National Land Cover Database: requirements, research priorities, design, and implementation strategies. ISPRS J Photogram Remote Sens 146:108–123. https://doi.org/10.1016/j.isprsjprs.2018.09.006
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2022 The Author(s)
About this chapter
Cite this chapter
García-Álvarez, D., Lara Hinojosa, J. (2022). General Land Use Cover Datasets for America and Asia. In: García-Álvarez, D., Camacho Olmedo, M.T., Paegelow, M., Mas, J.F. (eds) Land Use Cover Datasets and Validation Tools. Springer, Cham. https://doi.org/10.1007/978-3-030-90998-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-90998-7_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-90997-0
Online ISBN: 978-3-030-90998-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)