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Full catalog/bangladesh-landcover-2001-2020
bangladesh-landcover-2001-2020·dataset

How Bangladesh's Land Changed, 2001 to 2020

Annual land cover maps for 2001 and 2020
land NASA VEDA COG
In plain English

What it measures. Maps showing what covered the land across Bangladesh in 2001 versus 2020, simplified into four main types: water, cities, farmland, and natural vegetation. The pair of maps reveals how land use shifted over roughly two decades.

How it's made. Built from NASA's MODIS satellite yearly land-cover product, which classifies the globe at 500-meter resolution.

How & where you'd use it. Helps track urban growth, farmland change, and loss of natural areas to guide planning and environmental monitoring.

What's measured

bangladeshlandcover20012020

Coverage & cadence

  • Time span2001-01-01 → 2020-12-31
  • Spatial extent88.026, 20.742, 92.684, 26.635
  • FormatsCOG

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

The annual land cover maps of 2001 and 2021 were captured using combined Moderate Resolution Imaging Spectroradiometer (MODIS) Annual Land Cover Type dataset (MCD12Q1 V6, dataset link: https://lpdaac.usgs.gov/products/mcd12q1v006/). The actual data product provides global land cover types at yearly intervals (2001-2020) at 500 meters with six different types of land cover classification. Among six different schemes, The International Geosphere–Biosphere Programme (IGBP) land cover classification selected and further simplified to dominant land cover classes (water, urban, cropland, native vegetation) for two different years to illustrate the changes in land use and land cover of the country.

Get the data

veda_access.py
# NASA VEDA — open STAC API, anonymous (cloud-optimized GeoTIFFs)
from pystac_client import Client

cat = Client.open("https://openveda.cloud/api/stac")
col = cat.get_collection("bangladesh-landcover-2001-2020")
items = list(col.get_items())          # browse the analysis-ready COGs
# open an asset with rioxarray:
# import rioxarray; da = rioxarray.open_rasterio(items[0].assets["cog_default"].href)
NASA VEDA is an open STAC catalog — browse and stream the cloud-optimized GeoTIFFs anonymously (no login).