Indicator 15.1.1: Forest area as a proportion of total land area
Target 15.1: By 2020, ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands, in line with obligations under international agreements
Goal 15: Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
This indicator is defined as the proportion of forest area of the total land area of a country.
Forest is defined as land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. It does not include land that is predominantly under agricultural or urban land use. Additional detailed criteria are listed in FAO’s Forest Resource Assessment (FRA) 2020 Terms and Definitions Document available at: http://www.fao.org/3/I8661EN/i8661en.pdf. Forest area in Bangladesh is specifically identified by the summed area of Bamboo Forest, Forest Plantation, Hill Forest, Mangrove Forest, Mangrove Plantation, Plain Land Sal Forest, Rubber Plantation, Shrubs with scattered tree, Swamp Forest and Swamp Plantation land cover classes from the Land Cover Map. Total forest area of the reference year 2015 is used.
Total land area refers to the total surface area excluding the area covered by Rivers and Khals, Perennial Beels/Haors, Lake, Baor, and Pond land cover classes from the Land Cover Map. Total land area of the reference year 2015 is used.
Rationale and Interpretation:
The availability of accurate data on a country’s forest area is a key element for forest policy and planning within the context of sustainable development. Forest area as a proportion of total land area can provide a rough proxy for the extent to which the forests in a country are being conserved or restored.
Unit of measure:
The National Land Cover Representation System (NLRS) for Bangladesh, which defines the land cover classes, was developed following the Land Cover Classification System (Di Gregorio and Leonardi 2016) and Land Cover Meta Language (LCML) ISO 19144 (ISO 2012). There are 33 land cover classes.
The Land Cover Map 2015: http://geoportal.bforest.gov.bd/layers/geonode:national3
The National Land Cover Representation System (NLRS): http://bfis.bforest.gov.bd/library/land-representation-system-of-bangladesh/
Data collection methods:
For the NLRS, the initial legend classes for land cover map 2015 were derived during a national workshop with experts from different organizations working in relevant fields. These initial classes were further refined during map development process to develop the final legend. Some of the classes were extended from the NLRS (e.g., bamboo forest, rubber plantation, etc.), while some other classes were merged (e.g., short and long rotation plantation into forest plantation) when differences among these classes were not discernible from the available satellite images by visual interpretation. The final land cover map has 33 classes.
For the development of land cover map 2015, multi-spectral ortho (Level 3) SPOT6/7 four band images of 6-meter spatial resolution with maximum 10% cloud coverage were primarily used for the whole country. An Object-Based Image Analysis approach (i.e., multi resolution segmentation algorithm) was adopted to create image objects using the green, red and near-infrared bands of SPOT imagery. Meaningful image segments were directly assigned with land cover code by visual interpretation. Image segments not corresponding well to geo-objects were manually edited (i.e., manual digitization by visual interpretation of satellite image) before assigning an appropriate land cover code. Seasonal variations in land and water features are common in Bangladesh. Landsat 8 and Sentinel 2 images from different seasons were taken into consideration in visually interpreting areas having a seasonal variation (especially agricultural classes). Field data were collected from 1,144 locations across the country to characterize the classes of the NLRS.
Data collection calendar: 2020
Data release calendar: 2021
Data providers: Forest Department, Ministry of Environment, Forest and Climate Change
Data compilers: Forest Department, Ministry of Environment, Forest and Climate Change
Institutional mandate: Through the Statistical Act 2013, the Bangladesh Bureau of Statistics (BBS) is mandated to generate official statistics or provide guidance to other agencies for producing official statistics. Responsibilities for each ministry to support specific SDG indicators is outlined in the Mapping of Ministries by Targets in the implementation of SDGs aligning with 7th Five Year Plan (2016-20) document, which lists Ministry of Environment, Forest and Climate Change as the official Lead Ministry for this indicator. The Forest Department is the designated line agency within the Ministry for this indicator.
The formula of the indicator is given as follows:
Comments and limitations:
The Object-Based Image Analysis approach for delineating forested areas yields accurate estimates of forest area at a high resolution, but it is an atypical approach. Therefore, comparability across country borders may be limited due differences in methods.
Method of computation:
Forest area is the summed area of Bamboo Forest, Forest Plantation, Hill Forest, Mangrove Forest, Mangrove Plantation, Plain Land Sal Forest, Rubber Plantation, Shrubs with scattered tree, Swamp Forest and Swamp Plantation land cover classes from the Land Cover Map. Total land area is the rest of the surface area excluding the Rivers and Khals, Perennial Beels/Haors, Lake, Baor, and Pond land cover classes from the Land Cover Map.
Quality checking of land cover attributes is completed using multiple approaches including a spatial topology check, an attribute check, a consistency check, expert judgment and field validation.
Accuracy assessment analysis uses a pseudo-ground truth validation technique, with stratified random sampling by district and by land cover class. The most commonly used measures of accuracy (i.e., overall accuracy, user’s accuracy, producer’s accuracy) were estimated following the approach presented in Jalal et al. (2019).
The overall accuracy of the Land Cover Map 2016 was estimated at 89%. User’s accuracy ranged from 20% to 99% while producer’s accuracy ranged from 13% to 100%. The detail methodological process and results (including the accuracy, uncertainty and adjusted area estimates) of land cover 2015 are presented in Jalal et al. (2019).
This indicator can be disaggregated by geographical regions, forest types, soil types, forest development class, dominant tree species or tree species groups, among other dimensions.
Forest area previously published for Bangladesh in the Forest Resource Assessment (FRA) report is different from the statistic produced using the current approach because of methodological differences.
Official SDG Metadata URLhttps://unstats.un.org/sdgs/metadata/files/Metadata-15-01-01.pdf
Internationally agreed methodology and guideline URLFRA 2020 Terms and definitions: http://www.fao.org/3/I8661EN/i8661en.pdf
FRA 2020 Guidelines and Specifications: http://www.fao.org/3/I8699EN/i8699en.pdf
Di Gregorio A, Leonardi U (2016) Land Cover Classification System Software version 3 – User Manual. Food and Agriculture Organization of the United Nations, Rome, Italy
GoB. 2017. Land Representation System of Bangladesh (In Support of REDD+), Forest Department, Ministry of Environment, Forest and Climate Change, Government of the People’s Republic of Bangladesh. Available at: http://bfis.bforest.gov.bd/library/land-representation-system-of-bangladesh/
GoB (2020), Land Cover Atlas of Bangladesh 2015 (in support of REDD+), Forest Department, Ministry of Environment, Forest and Climate Change, Government of the People’s Republic of Bangladesh, Dhaka, Bangladesh. Available at: http://bfis.bforest.gov.bd/library/land-cover-atlas-of-bangladesh-2015/
ISO (2012) Geographic information — Classification systems — Part 2: Land Cover Meta Language (LCML). International Standard Organisation, Geneva, Switzerland
Jalal R, Iqbal Z, Henry M, et al (2019) Toward Efficient Land Cover Mapping: An Overview of the National Land Representation System and Land Cover Map 2015 of Bangladesh. IEEE J Sel Top Appl Earth Obs Remote Sens 12:3852–3861. Available at: https://doi.org/10.1109/JSTARS.2019.2903642
Planning Commission. Mapping of Ministries by Targets in the implementation of SDGs aligning with 7th Five Year Plan (2016-20): A Handbook. Support to Sustainable and Inclusive Planning (SSIP) Project, General Economics Division (GED), Planning Commission, 2017. Available at: http://bbs.portal.gov.bd/sites/default/files/files/bbs.portal.gov.bd/page/3acbc97e_6ba3_467b_bdb2_cfb3cbbf059f/A-Handbook-Mapping-of-Ministries_-targets_-SDG_-7-FYP_2016.pdf
This document was prepared based on inputs from Food and Agricultural Organization (FAO).
For focal point information for this indicator, please visit https://unstats.un.org/sdgs/dataContacts/