I.    Conceptual Framework

The Land Asset Accounts of the Philippines presents both the physical and monetary asset accounts for the country’s land resources. This publication primarily focuses on physical asset accounts for the years 2015 to 2020, in terms of land cover. The System of Environmental-Economic Accounting (SEEA) defines land cover as the observed physical and biological cover of the earth’s surface and includes natural vegetation and abiotic (non-living) surfaces. The monetary asset accounts are still being compiled and will be included in future publications.

The development of land asset accounts in the Philippines is part of a collaborative initiative by the Philippine Statistics Authority (PSA), the National Mapping and Resource Information Authority (NAMRIA), and the United Nations Statistics Division (UNSD) through the project “Environmental-Economic Accounting for Evidence-Based Policy in Africa and Asia”. The project aims to address the technical and institutional barriers to the establishment of routinely produced environmental-economic accounts at the national level. One of the strategies is to establish technical capacity to compile selected accounts regularly while contributing to the development of SEEA-compliant global databases. 

In the case of Land Asset Accounts, UNSD provides technical expertise and capacity-building support, equipping national agencies with tools and methods aligned with the SEEA. NAMRIA, on the other hand, serves as the primary data source and partner in preparing detailed land cover maps, while PSA takes the lead in the compilation of accounts and integrating geospatial data into national statistical systems. This partnership emphasizes a coordinated effort to monitor land use and cover changes in the Philippines, contributing to evidence-based policymaking and sustainable development planning.

The System of Environmental-Economic Accounting 2012 Central Framework (SEEA-CF), a multipurpose framework that quantitatively describes the interactions between the environment and the economy, serves as the guiding framework for this compilation. It is also a statistical framework that consists of a comprehensive set of tables and accounts that guide the compilation of consistent and comparable statistics and indicators for policymaking, analysis, and research.

The SEEA-CF covers measurement in three main areas: (1) the flows of resources within the economy and between the economy and the environment; (2) the economic activity and transactions related to the environment; and (3) the stocks and the changes in stocks of environmental assets, such as the land resources, which is the focus of this compilation.

The physical asset accounts for land describe the area of land and changes in the area of land over an accounting period. The land area of the country defines the scope of the land cover account. A basic physical asset account for land cover is presented by showing the opening and closing areas for different land cover types and various additions and reductions in those areas over the accounting period. 

II.    Data Sources

The data for estimating the physical asset accounts were gathered from the following: 
 

III.    Estimation Methodology

LAND COVER CHANGE MATRIX

The Land Cover Change Matrix serves as a fundamental component of the Land Asset Accounts of the Philippines. Based on SEEA-CF, it shows land cover at two different points in time. It shows the area of different land cover types at the beginning of the reference period (opening area), the increases and decreases of this area according to the land cover type it was converted from (in case of increases) or the type it was converted to (in the case of decreases) and, finally, the area covered by different land cover types at the end of the reference period (closing area).

The following Land Cover Change Matrix is derived from the steps outlined below:

A.    Identification of Gaps and Overlaps

Geometric errors, such as invalid polygons and inconsistencies, often arise during geoprocessing, digitizing, or data conversion and must be addressed to ensure data accuracy. Overlap and gap issues frequently occur during vector-to-raster conversion, leading to pixels with questionable or "NoData" values.

Topological checking is conducted to identify and correct inconsistencies, ensuring each pixel represents only one land cover class. The PSA compiles datasets with identified errors and forwards them to NAMRIA for adjustments.

B.    Adjustment of Vector Data

The adjustment process for addressing the overlap and gaps in land cover data involves identifying complex areas, categorizing them into scenarios, and applying adjustments. 
    
Overlapping polygons are addressed in two scenarios:

• Scenario 1: Large overlaps requiring manual intervention to assign the correct land cover.

• Scenario 2: Smaller overlaps that are automatically resolved by the software.

Similarly, gaps are corrected in three scenarios:

• Scenario 1: Large gaps needing manual land cover assignment 

• Scenario 2: Coastal gaps requiring deletion or reassignment to the “sea and ocean” land cover class.

• Scenario 3: Small gaps that are automatically combined with adjacent polygons.

C.    Rasterization

1.    Establish Data Resolution

• Determine the appropriate resolution (eg. 10m and 30m) based on the scale and requirement of the analysis. 

  • Note that the 10m and 30m resolutions are often negligible, with lower resolutions offering computational efficiency.

2.    Convert Vector to Raster

●    Rasterize the vector land cover datasets for 2015 and 2020. 
●    Apply the Maximum Area method for cell assignments to ensure the dominant land cover type within each pixel is represented.

3.    Address Misalignment in Coastal Zone

• Recognize that coastal zone changes may cause spatial mismatches between 2015 and 2020 datasets. 

  • Note that only pixels with data for both years contribute to the land cover change matrix, leaving “NoData” pixels not to be considered in the change analysis.

4.    Reassign “NoData” Pixels to “Sea and Ocean”

●    Perform the following steps to include “NoData” coastal pixels in the analysis. 
   a.    Adjust Boundaries 
        ■    Correct geometry, gaps, and overlaps in the 2015 and 2020 vector boundary datasets. 
   b.    Merge Boundaries
        ■    Combine the 2015 and 2020 datasets into a single vector dataset containing all polygons.

   c.    Union Polygons 
        ■    Union the merged vector dataset with itself to break the polygons at every overlapping or shared boundary. 
  d.    Dissolve Polygons 
       ■    Ensure a combined non-overlapping boundary that encompasses both years.
       ■    Add a buffer around the combined boundary using the territorial waters polygon of the Philippines.
  e.    Rasterized Combined Boundaries
       ■    Convert the combined boundary into a raster file. 
  f.    Reassign Pixels 
       ■    Use raster algebra to assign “NoData” pixels within the combined boundary to the “Sea and Ocean” land cover for both 2015 and 2020 datasets.

5.    Verify and Analyze

●    Ensure all coastal pixels are now classified, allowing them to contribute to the land cover change matrix.

6.    Generate Land Cover Change Matrix

●    Use the 2015 and 2020 adjusted rasters to generate the land cover change matrix map. 
●    Share the finalized rasters with PSA for further analysis, such as improbable transitions.

D.     Generating the Land Cover Change Matrix

The Semi-Automatic Classification Plugin (SCP) is a free, open-source tool for Quantum Geographic Information System (QGIS) that facilitates processing and raster calculations of satellite images. To generate a land cover change matrix, the post-processing tool is used to create a land cover change map.

1.    The process begins by importing land cover (LC) raster data for the two time periods. The post-processing tool is then run to detect land cover changes, and the data from the resulting Excel file is formatted into columns.

2.    Next, the raster is polygonized into a vector format in QGIS, with a new field called "LCChange" created. A lookup table is generated in Excel, which is then imported into QGIS and joined to the vector layer.

3.    Finally, using the “Field Calculator”, the area of each polygon is calculated in hectares. Statistics by category, focusing on land cover class, is saved as a CSV file, where the data is rearranged and checked for improbable transitions.

a.    Identification of Improbable Transitions with areas greater than 100 hectares:

Improbable transitions in land cover are identified through the collaboration of UNSD, NAMRIA, and PSA. Improbable transitions, such as inland water to closed forest or mangrove forest to brush/shrubs, are categorized as highly unlikely within a short timeframe, while others, like marshland to annual crop, are deemed probable due to agricultural expansion.

To streamline this process, a detailed Excel template, developed with the UNSD, highlights improbable transitions for better tracking and classification within the land cover change matrix. Improbable transitions with areas larger than 100 hectares are sent back to NAMRIA for adjustments.

The land cover change matrix is once again generated using the validated or adjusted datasets from NAMRIA. The resulting data is then entered into the Improbable Transitions Excel template for final review. If no more improbable transitions are identified, the resulting data is finalized and translated into SEEA tables.
 

TRANSLATION OF CHANGE MATRIX TO SEEA TABLE

1.    Data from the Land Cover Change Matrix is translated into SEEA tables by organizing the area of different land cover types into opening stocks at the start of the reference period.

2.    Increases in land cover area are recorded based on the land cover it converts from, categorized as managed expansion or natural expansion.

3.    Similarly, decreases are recorded based on the land cover it converts to, classified as managed regression or natural regression.

4.    Reappraisals, whether upward or downward, update land cover estimates using improved data, such as new or reinterpreted satellite imagery.

5.    Finally, the area of different land cover types at the end of the reference period is referred to as the closing stocks.
 

IV.    Definition of Terms

a.    Afforestation - Artificial establishment of forest on lands previously not covered with forest vegetation. 
b.    Annual cropland - Land cultivated with crops with a growing cycle under one year, which must be newly sown or planted for further production after harvesting. 
c.    Asset - A store of value representing a benefit or series of benefits accruing to an economic owner by holding or using the entity over a period of time. It is a means of carrying forward value from one accounting period to another.
d.    Bare areas - Land not covered by (semi-) natural or artificial cover. These include, among others, sand dunes, river wash, lahar-laden areas, and rocky or stony areas. 
e.    Built-up area - Composed of areas of intensive use with much of the land covered by structures. It includes cities, towns, villages, strip developments along highways, transportation, power, and communication facilities, and areas occupied by malls, shopping centers, industrial and commercial complexes, and institutions that may, in some instances, be isolated from urban areas.
f.    Closed Forest - Formation where trees in various stories and undergrowth cover a high proportion (>40 percent) of the ground and do not have a continuous dense grass layer. They are either managed or unmanaged forests, in an advanced state of succession, and may have been logged over one or more times, having kept their characteristics of forest stands, possibly with modified structure and composition.
g.    Downward Reappraisals - Reductions in the stock due to the use of updated information which permits a reassessment of the physical size of the stock 
h.    Forest Land - Land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10 percent.
i.    Grassland - Areas predominantly vegetated with grasses such as Imperata, Themeda, Saccharum spp., among others.
j.    Inland waters - Bodies of water surrounded by land (e.g. rivers, lakes, streams, mudflats, ponds/fishponds, dams, and reservoirs).
k.    Land - A unique environmental asset that delineates the space in which economic activities and environmental processes take place and within which environmental assets and economic assets are located.
l.    Land Cover - Refers to the observed physical and biological cover of the Earth's surface and includes natural vegetation and abiotic (non-living) surfaces.
m.    Land Use - Reflects both (a) the activities undertaken and (b) the institutional arrangements put in place for a given area for economic production, or the maintenance and restoration of environmental functions.
n.    Marshland - Natural area usually dominated by grass-like plants such as cat tails and sedges which are rooted in bottom sediments but emerge above the surface of the water. It contains emergence vegetation and usually develops in zones progressing from terrestrial habitat to open water. 
o.    Managed Expansion - Additions to stock due to human activity (e.g., conversion of crop areas into tree-covered areas). 
p.    Managed Regression - Reductions in stock due to human activity.  
q.    Natural Expansion of Forest and Other Wooded Land - An increase in the area of forest and other wooded land resulting from natural seeding, sprouting, suckering, or layering. 
r.    Natural Regression of Forest and Other Wooded Land - A decrease in an area of forest and other wooded land that occurs for natural reasons. 
s.    Open Forest - Formations with discontinuous tree layers with coverage of at least 10% and less than 40%. They are either managed or unmanaged forests, in the initial stage of succession.
t.    Perennial Cropland - Land cultivated with long-term crops that do not have to be replanted for several years after each harvest; harvested components are not timber but fruits, latex, and other products that do not significantly harm the growth of the planted trees or shrubs; orchards, vineyards, and palm plantations, coffee, tea, sisal, banana, abaca, etc. 
u.    Reforestation - The establishment of forest plantations on temporarily unstocked lands that are considered as forests. Also called artificial regeneration. 
v.    Upward Reappraisals - Additions to stock due to the use of updated information that permits a reassessment of the physical size of the stock.
 

Sources: 
System of Environmental – Economic Accounting (SEEA) 2012 Central 
Framework
Food and Agriculture Organization. (2010). Global forest resources assessment 2010. https://www.fao.org/forest-resources-assessment/past-assessments/fra-2010/en/
Department of Environment and Natural Resources. (2006). Philippines Official Reference for Forest-related Terms and Definitions. Forestry Management Bureau. https://forestry.denr.gov.ph/fmb_web/?publications=terms-and-definitions
Department of Environment and Natural Resources Memorandum Circular 2005-05
 

V.    Dissemination of Results and Revision
The current report focuses on physical land cover change between 2015 and 2020. Beginning with this Special Release, the Land Asset Accounts will be updated and made available on the PSA website as data inputs are available. The web release will include a press release, statistical tables, infographics, and social media cards.

List of Statistical Tables 
Table 1. National Land Asset Accounts
Table 2.1. Region I – Ilocos Region Land Asset Accounts
Table 2.2. Region II – Cagayan Valley Land Asset Accounts
Table 2.3. Region III – Central Luzon Land Asset Accounts
Table 2.4. Cordillera Administrative Region Land Asset Accounts
Table 2.5. National Capital Region Land Asset Accounts
Table 2.6. Region IVA – CALABARZON Land Asset Accounts
Table 2.7. MIMAROPA Region Land Asset Accounts
Table 2.8. Region V – Bicol Region Land Asset Accounts
Table 2.9. Region VI – Western Visayas Land Asset Accounts
Table 2.10. Region VII – Central Visayas Land Asset Accounts
Table 2.11. Region VIII – Eastern Visayas Land Asset Accounts
Table 2.12. Region IX – Zamboanga Peninsula Land Asset Accounts
Table 2.13. Region X – Northern Mindanao Land Asset Accounts
Table 2.14. Region XI – Davao Region Land Asset Accounts
Table 2.15. Region XII – SOCCSKSARGEN Land Asset Accounts
Table 2.16. Region XIII – Caraga Region Land Asset Accounts
Table 2.17. Bangsamoro Autonomous Region in Muslim Mindanao Land Asset Accounts

VI.    Citation

Philippine Statistics Authority. (20 December 2024). Technical Notes on Land Asset Accounts
https://psa.gov.ph/content/philippines-open-and-closed-forest-cover-grew-29-percent-2020

VII.    Contact Information

Ms. Virginia M. Bathan
Chief Statistical Specialist 
Environment and Natural Resources Accounts Division
8376-2041
enrad.staff@psa.gov.ph

For data request, you may contact:
Knowledge Management and Communications Division
(632) 8462-6600 locals 839, 833, and 834
info@psa.gov.ph