Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine
| Title: | Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine |
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| Authors: | Daniel Marc G. dela Torre, Jay Gao, Cate Macinnis-Ng, Yan Shi |
| Source: | Geo-spatial Information Science, Vol 24, Iss 4, Pp 695-710 (2021) |
| Publisher Information: | Taylor & Francis Group, 2021. |
| Publication Year: | 2021 |
| Collection: | LCC:Mathematical geography. Cartography LCC:Geodesy |
| Subject Terms: | phenology-based mapping, paddy type, google earth engine, sentinel-2, rice mapping, Mathematical geography. Cartography, GA1-1776, Geodesy, QB275-343 |
| More Details: | Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines. However, small farms are prevalent in the region, and current satellite-based mapping techniques do not distinguish between the two ecosystems at farm scales. This study developed an approach to rapidly map irrigated and rain-fed paddy rice in Iloilo, Philippines at 10 m resolutions using Google Earth Engine. This approach used an ensemble of classifiers based on time-series vegetation indices to produce dry and wet seasonal maps for the entire province. Results showed a predominance of rain-fed rice areas in both seasons, with irrigated rice making up only one-fourth of the total rice area. The overall accuracy was achieved at 68% for the dry season and 75% for the wet season based on ground-acquired points and very high-resolution imagery. The two types of paddies were classified at accuracies up to 87%. Furthermore, the land cover maps showed a strong agreement with the municipal statistics. The resultant maps complement current official statistics and demonstrate the prowess of phenology-based mapping to create paddy inventories in a timely manner to inform food security and agricultural policies. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1009-5020 1993-5153 10095020 |
| Relation: | https://doaj.org/toc/1009-5020; https://doaj.org/toc/1993-5153 |
| DOI: | 10.1080/10095020.2021.1984183 |
| Access URL: | https://doaj.org/article/6578d08930df4d6fbe54a0a0e2993fbb |
| Accession Number: | edsdoj.6578d08930df4d6fbe54a0a0e2993fbb |
| Database: | Directory of Open Access Journals |
| ISSN: | 10095020 19935153 |
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| DOI: | 10.1080/10095020.2021.1984183 |
| Published in: | Geo-spatial Information Science |
| Language: | English |