The CWC data repository brings together information on wildlife corridors in India and makes it available to
all, from professionals to the general public. This comprehensive, spatially explicit, and dynamic web database
can be used for assistance in policy making, research, and conservation decisions. The data portal comprises an
interactive geographical map displaying the locations of wildlife corridors across India. Users can navigate to
select a corridor and extract information through downloadable corridor profiles - a report that documents all
available information about the wildlife corridor. Users can also have a quick view that gives a glimpse of the
status of a corridor through eight principal indicators:
-
Area of natural habitat
What percentage of the corridor area is natural habitat?
To calculate this indicator, land use categories from a 100m LULC layer from Copernicus Global Land Service
(2019) are reclassified into two separate classes - Natural land use class and Modified land use class. The
total percentage of area under the Natural land use class is then calculated using the open-source R package
landscapemetrics (Hesselbarth et al. 2019).
-
Area under legal protection
What percentage of the corridor area has legal protection?
Government maps from department records are assessed to identify the extent of corridor area granted varying
levels of protection under the forest department.
-
Threatened species richness
What is the extent of threatened species presence in the corridor?
Based on IUCN 1km resolution range maps for threatened species including amphibians, birds, mammals, crabs,
fish, plants, molluscs, odonata, and reptiles.
-
Average human population
What is the density of humans residing in the corridor?
A 1km resolution dataset from the WorldPop repository (2020) is utilised.
-
Human Modification Index Score
To what extent has the corridor landscape been modified by human activity?
The human modification of terrestrial systems dataset from NASA SEDAC (2016) is used, based on modelling of
anthropogenic stressors and their estimated impacts (Kennedy et al. 2019).
-
Landscape Complexity Index
What is the extent of different land uses in the corridor?
A 100m LULC layer from the ESA Copernicus Global Land Service repository (2019) is utilised, calculated using
landscapemetrics (Hesselbarth et al. 2019).
-
Land Use Change Index
How has land use changed in the corridor?
(Source - currently unavailable)
-
Natural Habitat Fragmentation Index
To what extent is the corridor area fragmented?
Calculated using clumpiness - a measure of the degree to which natural habitat is aggregated in a region.
Background layers
| LULC layer |
Dynamic classification of land cover. 100m global land cover from ESA Copernicus Global Land Service
(2019). |
| Satellite |
Sentinel-2 cloudless satellite basemap (2020). |
| Human Modification Index |
Extent of human modification based on anthropogenic stressors. 1km resolution from NASA SEDAC (2016). |
| Population Density |
Human population density across India (0 to 1000+ people/km²). |
| Threatened Species Richness |
Richness of threatened species based on IUCN range maps. |
Overlay layers
Protected Areas, National Highways, State Highways, Railway lines
References
| 1 |
Buchhorn, M. et al. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019. |
| 2 |
Hesselbarth, M. H. et al. (2019). landscapemetrics: An open-source R tool to calculate landscape
metrics. Ecography, 42(10), 1648-1657. |
| 3 |
WorldPop (2018). Global High Resolution Population Denominators Project. |
| 4 |
Kennedy, C. M. et al. (2020). Global Human Modification of Terrestrial Systems. NASA SEDAC. |
| 5 |
IUCN (2019). The IUCN Red List of Threatened Species - Spatial Data. |
| 6 |
OpenStreetMap (2022). https://openstreetmap.org. |