ENHANCEMENT OF THE FIELD ASSESSMENT PROTOCOLS AND SUITABILITY MAPS FOR COCONUT

Autor: J. T. Francisco, J. D. Casisirano, A. C. Blanco, R. L. Rivera, L. H. Canja, M. D. Francisco, R. M. Barrientos
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-4-W8-2023, Pp 251-258 (2024)
Druh dokumentu: article
ISSN: 1682-1750
2194-9034
DOI: 10.5194/isprs-archives-XLVIII-4-W8-2023-251-2024
Popis: The crop suitability assessment particularly in coconut planting has not been revisited in over two decades. An in-depth analysis of the various factors affecting coconut farming was conducted. This involved the utilization of local remotely-sensed data on elevation, slope, soil type, and land cover. Global gridded data on rainfall and land surface temperature were acquired to supplement the local data. Each factor was given its corresponding weight assignments upon consultation with the experts from the Philippine Coconut Authority. Variable factors such as rainfall (15%) and temperature (10%) were given with lower scores than the permanent or nearly unchanging factors on elevation (25%), slope (25%), and soil type (25%). These individual factors were processed for the final multi-criteria weighted overlay analysis. Finally, the land cover map was used to remove areas deemed unsuitable for coconut planting. Results showed that about 20 million hectares of the country’s total land area are suitable for coconut planting with varying levels of suitability. Of the total suitable areas, only 3.64 million hectares (18%) were planted with coconuts based on the PSA data for 2021. One important factor to consider is that most of the areas not planted with coconut are devoted to other important land cover types like forests, perennials, and annual crops. The utilization of the open source Quantum GIS (QGIS) software proves to be essential in this kind of enormous data processing and analysis, coupled with the generation of very detailed coconut suitability data and maps on a nationwide scale.
Databáze: Directory of Open Access Journals
Externí odkaz: