Assessment of Forest Disturbances and Carbon Stock in Pantabangan-Carranglan Watershed, Philippines Using Remote Sensing

Abstract

Abstract. Forest disturbances contribute to the decrease in carbon sequestration potential and ecosystem services in a watershed. One of the important watersheds that is affected by land use changes and disturbances is the Pantabangan-Carranglan Watershed. The ability of the watershed to provide ecosystem services is affected by the existing land use and land cover (LULC) and its future trends. Therefore, this study aims to assess the changes in the LULC, forest disturbances, and potential carbon stock in the watershed using satellite images. The LULC types and indices used in detecting forest disturbances were classified and generated from the Landsat 8 satellite images covering two different years. The potential carbon storage in the watershed was estimated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Carbon model. The information generated can be used in the conduct of valuation studies and land use planning in the watershed.

Drivers and impacts of land use and land cover changes on ecosystem services provided by the watersheds in the Philippines: a systematic literature review

“…These categories explore the impacts of land cover changes on plant diversity (Sarmiento et al . 2019), carbon storage and cycling within watersheds (Dida et al . 2021) and the regulation of flood events (Pati 2014, Santillan et al .…”

“…This category includes sub-categories such as decreased carbon stock, decreasing forest resources, degradation of water quality, lower nutrient concentration of water, and water quality reduction. These impacts underscore the significant changes in environmental conditions resulting from LULC change, including the loss of carbon storage (Dida et al . 2021), depletion of forest resources (Briones et al .…”

“…In post-processing and analysis, several modelling tools are used by the different authors in measuring the impacts of land use and land cover changes. It include FRAGSTAT (Almarines et al 2022, Encisa-Garcia et al 2020, Estoque and Murayama 2013, Ramirez et al 2019), Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) (Almarines et al 2022, Carl Ureta et al 2022a, Dida et al 2021, Dida et al 2021), Soil and Water Assessment Tool (SWAT) (Arceo et al 2018, Briones et al 2016, Palao et al 2013), Hydraulic Model (Pati 2014, Santillan et al 2019), FOREST-SAGE and GEOMOD (Jardeleza et al 2019), Universal Soil Loss Equation (USLE) (Garcia 2016), and Terrset (Magpantay et al 2019).…”

Assessment of Forest Disturbances Using Remote Sensing: Case of Kaliwa River Forest Reserve (Krfr), Philippines

“…The Kaliwa River Forest Reserve (KRFR), Sierra Madre Mountain Range is one of the most vital forest reservations adjacent to urban areas that is very much affected by forest disturbances. The Sierra Madre Forest experienced forest losses from 2001 to 2010 (Perez et al, 2020;Dida et al, 2021).…”

“…One of the indices that is suitable for the detection of forest disturbances, in addition to the Normalized Difference Vegetation Index (NDVI) and Tasseled Cap Wetness Index (TCW), is the Normalized Difference Moisture Index or the NDMI (Lastovicka et al, 2020). Application of NDMI in the studies of Ochtyra (2020), Dida et al, (2021), andZhang et al, (2016) was also able to detect forest disturbances.…”