About the Lab

Observation is one of the keys in unlocking the mysteries behind environmental phenomena. Considering its importance, the Predictions for the Environment and Application of Remote Sensing (PEARS) Laboratory under the Institute of Environmental Science and Meteorology (IESM) of the University of the Philippines focuses its research on environmental monitoring and forecasting. The laboratory utilizes satellite technology and other observation tools in order to assess the condition of environment.  The data that can be gathered from these methodologies are feed to computing machines to produce models. These models are the guide in determination of environmental predictions.

PEARS Lab houses researchers from the field of environmental science, meteorology, physics, statistics, chemistry and biology. Currently, the research projects implemented in the laboratory transcends on different environmental spheres. Lithosphere research involves crop classifications, forest cover change detection, soil moisture characterization, land productivity and crop vulnerability assessment. Hydrosphere research includes fish mapping and ocean productivity monitoring while atmospheric research involves weather and seasonal forecasting and impacts of climate change.

 


On-going Projects

The team is tasked to produce georeferenced (Level 1A) and calibrated radiances (Level 1B) products from the images obtained by Diwata-1. In parallel, a spectral library of high-quality data that will be used for ground-truthing and algorithm development will be built. In hosting these data to the science community, the project is tasked to form a science team that will ensure the integrity and maximize the utility of the data obtained from the microsatellite.

  • Remote Sensing of Coastal Habitats and Stressors (Project 9) of CoRVA
  • Suitability assessment and database development for enhanced mussel  culture management using geospatial technologies (Project-SSAM)

The Project is a research funded by DOST-PCAARRD through Grants-In-Aid Program and is currently implemented by University of the Philippines Visayas and University of the Philippines Diliman. The project aims to assess and analyze suitable areas for mussel culture in the Philippines using geospatial technologies.

  • Philippine Coral Reef and Mangrove Remote Sensing (PhilCoMaRS)

Phil-CoMaRS is a joint project of UP and DERN which aims to produce user-friendly coral reef and mangrove resource maps which can consulted in a regional and provincial scale. This is being done with the use of remote sensing techniques on Landsat satellite imagery reinforced with field validations. The effects of the warming ocean temperature due to past major ENSO events to coral health are also being characterized to evaluate the resilience of this coastal habitat.


Other Research Interests

  • Satellite Remote Sensing of the Environment
  • Seasonal and Climate Prediction
  • Climate Change and Variability
  • Complex Systems
  • Interdisciplinary Applications of Physics

 


Members

Principal Investigator/Faculty

Perez, Gay Jane, PhD

Project 5 of PHL-MICROSAT Program

  • Castro, Ellison
  • Felicio, Francisco Miguel
  • Felix, Mark Jayson
  • Fulgencio, Louisse Anne
  • Hilario, Atchong, PhD
  • Leonardo, Ellen Mae
  • Macapagal, Marco
  • Macayan, Nathaniel
  • Madalipay, Jasper
  • Nacario, Redmund
  • Namuco, Shielo
  • Vergel, Kaye Kristine

Project SSAM

  • Leonardo, Ellen
  • Quiambao, Emman

Phil-CoMaRS

  • Goliat, Raymond Jess
  • Grieta, Cindyleen Kate
  • Pangasinan, Jamaica

Publications

2017

  • JC Comiso, RA Gersten, LV Stock, J Turner, GJ Perez, and K Cho, “Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature,” Journal of Climate 30, 2251-2267 (ISI)

2016

  • GJ Perez, et al., “Forecasting and monitoring agricultural drought in the Philippines,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives 41, pp. 1263-1269
  • RAG Faelga, EC Paringit, GJ Perez, (…), FAM Tandoc, MV Malabanan, “Mangrove plantation forest assessment using structural attributes derived from LiDAR data,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives 41, pp. 617-623
  • RAG Faelga, EC Paringit, GJ Perez, (…), FAM Tandoc, GP Zaragosa, “Validation of the separability measure for Rhizophoraceae and Avicenniaceae using point density distribution from LiDAR,” Proceedings of SPIE – The International Society for Optical Engineering 9879,98791F
  • B Fallarcuna, GJ Perez, “Forest cover dynamics in the Philippines from Landsat-derived forest cover dataset (2000-2012),” Journal of the Philippine Geosciences and Remote Sensing Society Voume 2
  • RAG Faelga, EC Paringit, GJ Perez, (…), FAM Tandoc, GP Zaragosa, “Separability and Variability of Rhizophoraceae and Avicenniaceae in Natural Mangrove Forest Using Point Density Distribution from Lidar Data,” Journal of the Philippine Geosciences and Remote Sensing Society Volume 2

2015

  • JC Comiso, GJ Perez and LV Stock, “Enhanced Pacific Ocean Sea Surface Temperature and Its Relation to Typhoon Haiyan,” Journal of Environmental Science and Management Vol. 18 No. 1 (ISI)
  • C Saloma, GJ Perez, CA Gavile, JJ Ick-Joson, and C Palmes-Saloma, “Prior individual training and self-organized queuing during group emergency escape of mice from water pool,” PLOS ONE DOI:10.1371/journal.pone.0118508 (ISI)
  • GJ Perez, JC Comiso, “Monitoring Philippine Vegetation Using Satellite NDVI and EVI Data,” Journal of the Philippine Geosciences and Remote Sensing Society Volume 1
  • MD Macapagal and GJ Perez, “Detection of agricultural drought events in the Philippines using MODIS land products,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • B Fallarcuna, GJ Perez, “Quantifying forest cover changes in the Philippines from 2000-2012 from Landsat-derived global forest cover dataset,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • GM Macam, GJ Perez, “Evaluating the potential of downscaled CFSV2 for drought forecasting using MODIS and TRMM observations,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • EMC Leonardo, GJ Perez, “Predicting abundance of different tuna species in the Philippines,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • EMR Macapagal, GJ Perez, “Evaluation of Soil Moisture Estimates Derived from the Advanced Microwave Scanning Radiometer 2 (AMSR2) in the Philippines,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • RO Olivares, M Macapagal, GJ Perez, “Extreme value analysis of evaporative stress index as input to assess agricultural drought risk in the Philippines,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • J Pangasinan, MJ Felix, GJ Perez, “Performance of empirical Cl-a derivation algorithms on the coastal waters of Bagac and Polillo,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • RB Badrina, JS Combinido, GJ Perez, “Impact of land use change on weather research and forecasting (WRF) output: A case study for the Philippines,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia
  • MJ Felix, J Pangasinan, GJ Perez, “Estimation of chlorophyll-a concentration on oligotrophic open waters of the Philippines: A case study for Polillo,” ACRS 2015 – 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia

2014

  • GJ Perez and JC Comiso, “Seasonal and Interannual Variability of Philippine Vegetation as Seen from Space,” Philippine Journal of Science Vol. 143 No. 2 pp. 147-155 (ISI)
  • DM Dela Torre and GJ Perez, “Phenology-based classification of major crops areas in Central Luzon, Philippines from 2001-2013,” 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies
  • JP Punay, GJ Perez, “Evaluation of MODIS Cloud Product-derived rainfall estimates,” 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies

2013

  • EM Macapagal and GJ Perez, “Soil moisture studies in the Philippines using AMSR-E/AMSR2,” 34th Asian Conference on Remote Sensing 2013, ACRS 2013 4, pp. 3322-3329
  • J Punay and GJ Perez, “Rainfall retrieval algorithm using MODIS cloud mask and cloud products,” 34th Asian Conference on Remote Sensing 2013, ACRS 2013 2, pp. 1494-1500