Global land-use and land-cover (LULC) data

# Global land-use and land-cover (LULC) data
## Tainá Rocha
### <img src = 'https://github.com/Tai-Rocha/tainaweb_en/raw/main/content/talk/LULC%20data/featured.jpg' width = '50%'> 
### October 2021

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About me 👩‍🎓
 - [Biology Bachelor's Degree ](#academic_1) [UFPA](https://portal.ufpa.br/) 
 - [MSc. Environmental biology](academic_2) [IECOS](https://www.museu-goeldi.br/)
 - [PhD Zoology](academic_3) [MPEG](https://www.museu-goeldi.br/)

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## Biodiversity distribution patterns

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.right-column[
<img src="img/spatia_ana_2.png" width="60%" style="display: block; margin: auto 0 auto auto;" />
]

About me 👩‍🎓
 - [Biologist](#academic_1) [UFPA](https://portal.ufpa.br/) 
 - [MSc. Environmental biology](academic_2) [IECOS](https://www.museu-goeldi.br/)
 - [PhD Zoology](academic_3) [MPEG](https://www.museu-goeldi.br/)

### Biodiversity distribution patterns

### Spatial analasyis of biodivesity and global changes

> Ecological Niche Models

> Climate data

> Land-use and land-cover data📌

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class: center

## Land-use land-cover (LULC)
<img src="img/paper.png" width="70%" style="display: block; margin: auto;" />
 
 
 Motivation 
 Goals 
 Methods 
 Results/ Main findings 
 Limitations 
 Conclusions and Perspectives

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## Motivation
## Land-use land-cover

- Important predictor of anthropogenic impacts and biodiversity threats (Gomes et al. 2020, 2021; Rosa et al. 2021)

- One of the main drivers of environmental change at multiple scales (Gomes et al. 2020, 2021; Rosa et al. 2021)
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- Ecosystem services ( InVEST modeling tool, Sharp et al.2020)📌

- Ecological niche models, as predictor or pos processing analysis 📌 (Eyringet al. 2016; Ruiz-Benito et al.
2020; Sobral-Souza et al. 2021)

## Thus...

Mapping land-use land-cover (LULC) changes through time is important and desirable for different purposes studies (Mantyka-Pringle et al. 2015; Titeux et al. 2017; Newbold 2018; Clerici et al. 2019; Hong et al. 2019; Jetz et al 2007; Powers and Jetz 2019)

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## Motivation
##### There are many LULC products
<img src="img/LULC_products.png" width="80%" style="display: block; margin: auto;" />
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## Motivation 
##### Today, we have two initiatives that provide a large time-series for Land-use
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<img src="img/Luh2_GCAM.png" width="85%" style="display: block; margin: auto;" />
LUH is part of CMIP, primary source in the reports of the Intergovernmental Panel on Climate Change (IPCC)

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## Motivation 
<img src="img/Xia and Yu, 2020.png" width="50%" style="display: block; margin: auto;" />
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### Besides, the format in which these data are available (NetCDF) seems to discourage their use

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## Motivation 
<img src="img/climate_data.png" width="70%" style="display: block; margin: auto;" />

- .tif or .asc format is usually required as input for ecology and biogeography analysis
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## Goals

- Make the LUH2 more accessible and in the format required for ecology and biogeography analysis

- Derive a new categorical data (LULC) from LUH2 (Land-use)

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## Methods

[Land-Use Harmonization (LUH2)- CMIP6](https://luh.umd.edu/data.shtml)

<img src="img/LU_states.png" width="65%" style="display: block; margin: auto;" />
- “primary” regards to intact land, undisturbed by human activities since 850

- “secondary” regards to land undergoing a transition or recovering from previous human activities (Hurrt et al. 2006; 2011; 2020)

- “forested” and “non-forested” are based on the aboveground standing stock of natural cover (> 2 kg/cm-²)
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### Methods
[CMIP6 Scenarios: Shared Socioeconomic Paths (SSP) and  Representative Concentration Pathway (RCP)](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change)

<img src="img/scenarios.png" width="54%" style="display: block; margin: auto;" />
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## Methods

<img src="img/workflow.png" width="85%" style="display: block; margin: auto;" />
[All codes are available at Github](https://github.com/Tai-Rocha/LUH2_Data)
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## Results/ Main findings

- States-files: LUH2 original data (continuous data) from years 850 to 2100 transformed into .tif format (16.056 files)

- LULC-files: the new categorical data created by combining the 12 States-files, also from 850 to 2100 transformed into .tif format (1.338 files)

- The data will be freely available at [ecoclimate](https://www.ecoclimate.org/) but is [available here](https://drive.google.com/drive/u/0/folders/1CTax7OVdFPwnOcv_v36bF-cO7V-RZmwq) for a while
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<img src="img/table_acu.png" width="90%" style="display: block; margin: auto;" />
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## Results/ Main findings
##### SSP5-RCP8.5

<img src="img/results_main.png" width="100%" style="display: block; margin: auto;" />
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## Results/ Main findings
- The major concern about primary forest decrease is habitat loss and biodiversity decline, especially of rare species (Chase et al. 2020; Horta and Santos 2020; Lima et al.2020). Others researched reach similar findings (Svensson et al. 2019, Shapiro et al. 2021)

- Brazil: recent governmental actions have promoted deforestation and forest fires (Escobar 2019; 2020; Amigo 2020; Silva et al. 2021; França et al. 2021; Qin et al. 2021; Vale et al. 2021)
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## Results/ Main findings
.right-colomun[
No quantitative difference between two scenarios
]
.left-colomun[
<img src="img/Fig4.png" width="55%" style="display: block; margin: auto;" />
]

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## Limitation

- The resolution (0.25	x	0.25	degree spatial	resolution)*

- Poor accuracy of urban land for some regions (Afrotropical, Indomalayan, Neotropical)

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## Conclusion and perspectives
<img src="img/paper.png" width="60%" style="display: block; margin: auto;" />
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- We provide the Land-use Harmonization data in a more friendly format 
- New data 
- We hope that the dataset provided here can be useful for different studies

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Reproduclible slides made with the R packages [xaringan](https://github.com/yihui/xaringan) and [xaringanthemer](https://github.com/gadenbuie/xaringanthemer) Slides link: https://tai-rocha.github.io/LULC_paper_presentation.github.io/ Code available at [Github](https://github.com/Tai-Rocha/LULC_paper_presentation.github.io)