Lab

Caraga Center for Geo-Informatics

Featured research (4)

MInDSEt, or the Mindanao Integrated Data Sharing Environment, is an online geospatial data and information sharing facility/geospatial data infrastructure established in Caraga State University, Philippines. MInDSEt was developed using Geoserver for data storage and OGC services, and Geonode for data cataloguing and visualization. It was originally developed as data sharing facility of the stakeholders of the Geo-SAFER Mindanao, an R&D program which focused on generating detailed flood hazard maps of flood-prone river basins and watersheds in Mindanao, Philippines through numerical simulations using LiDAR-derived elevation datasets. Initially, MInDSEt was aimed to cater the needs for LiDAR-derived datasets (DTM, DSM) and flood hazard information (e.g., maps and GIS files) for Mindanao, as well as a venue to data sharing of its stakeholders that includes Geo-SAFER Mindanao implementing educational institutions and Local Government Units. Recently, MInDSEt's functionality was expanded to allow registered organizations and users to store and share any kind of geospatial data and information. One of the features of MInDSEt is its capability to categorize stored datasets as restricted (i.e., a specific organization or member of that organization can only access the data/information), controlled (i.e., data/information can be accessed by an organization or user after approval of data request), or public (i.e., anyone, even unregistered users can access the data. MInDSEt is also capable of handling externally stored data/information, wherein only the links to the external data/information are stored instead of the data/information files. This capability is advantageous to accommodate a greater amount of data/information with minimal effect to the facility's data storage. Through MInDSET, it is envisioned that geospatial datasets and information of Mindanao and for Mindanao will be come easily accessible by anyone.
The Caraga Region in Mindanao, Philippines, is considered a significant contributor in log production, specifically due to Falcata (Paraserianthes falcataria) plantations. Over 80% of the country's Falcata log production came from Caraga Region in 2019. Among the challenges faced by the tree-growers is finding a suitable location for the establishment of new plantations. We used MaxEnt, a machine learning Species Distribution Modeling (SDM) based on Maximum Entropy principles, for this study's Falcata plantation suitability modeling and mapping. This approach used 2,125 Falcata location points distributed in the region, biophysical factors (i.e., Elevation, Slope, Aspect, and the like), and bioclimatic factors (i.e., Annual Mean Temperature, Isothermality, and Annual Precipitation, among others). The model was found to have acceptable model performance based on the average training and test Area Under the Curve (AUC) values of 0.76 and 0.73. A 1 km x 1 km Falcata suitability map was generated using the model. The map shows that 12% of the region has high suitability, while 23% and 30% have moderate and low suitabilities. On the other hand, 35% of the region was not suitable for Falcata plantation establishment.
This project aimed to develop a geodatabase of Industrial Tree Plantations (ITPs) in Caraga Region using Remote Sensing (RS) and Geographic Information System (GIS). The geodatabase is expected to aid in the characterization of ITPs in terms of their types, locations, spatial arrangements, and total area. It also aims to provide a form of documentation of the spatial-temporal aspects of ITP growth and development, and management dynamics. An important part of the geodatabase development is mapping the species types, location and extent of ITPs. The project did this by applying machine learning techniques to available RS datasets and complemented by ground surveys. Another objective of the project is to determine areas suitable for establishing new ITPs through conduct of suitability analysis; and to conduct accessibility analysis of log production flow with the use of geodatabase. Among the major accomplishments of the project are: (i.) the maps and statistics of ITPs in Caraga Region generated through the analysis of satellite and airborne remote sensing images; (ii.) a PostgreSQL+PostGIS geodatabase of ITPs in the region, including an online geodatabase visualization portal accessible at https://geoitp.ccgeo.info; (iii.) the maps and statistics of areas suitable for ITPs; and (iv.) a characterization and analysis of the spatial location, accessibility, and capability of wood processing plants (WPPs) for log production vis-à-vis existing Falcata plantations in the region. Aside from the ITP geodatabase, the project has generated a significant number of maps and other data products. For these to be accessible and utilized by the public, these products have been uploaded to the Mindanao Integrated Data Sharing Environment (MInDSEt), an online data portal managed by the Caraga Center for Geo-Informatics, of Caraga Center for Geo-Informatics, Caraga State University, Butuan City, Philippines. Interested users can access the project outputs at http://mindset.ccgeo.info:82/organization/industrial-tree-plantation-itp-research-and innovation-center).

Lab head

Jojene Santillan
Department
  • Caraga Center for Geo-Informatics

Members (6)

Arthur M Amora
  • Researcher
Kendel Bolanio
  • Caraga State University
Jennifer Marqueso
  • Geo-SAFER Agusan Project
Arnaldo Gagula
  • Caraga State University
Marcia Coleen Marcial
  • City Government of Butuan
Jun Love Gesta
  • Caraga State University
Edsel Matt O. Morales
Edsel Matt O. Morales
  • Not confirmed yet
Linbert C. Cutamora
Linbert C. Cutamora
  • Not confirmed yet
Ronald M. Makinano
Ronald M. Makinano
  • Not confirmed yet
Meriam Makinano-Santillan
Meriam Makinano-Santillan
  • Not confirmed yet