Dataset Information

Satellite-based meteorological drought indicator to support food security in Java Island.

ABSTRACT: A meteorological drought refers to reduced rainfall conditions and is a great challenge to food security. Information of a meteorological drought in advance is important for taking actions in anticipation of its effects, but this can be difficult for areas with limited or sparse ground observation data available. In this study, a meteorological drought indicator was approached by applying the Standardized Precipitation Index (SPI) to satellite-based precipitation products from multiple sources. The SPI based meteorological drought analysis was then applied to Java Island, in particular to the largest rice-producing districts of Indonesia. A comparison with ground observation data showed that the satellite products accurately described meteorological drought events in Java both spatially and temporally. Meteorological droughts of the eight largest rice-producing districts in Java were modulated by the natural variations in El Niño and a positive-phase Indian Ocean Dipole (IOD). The drought severity was found to be dependent on the intensity of El Niño and a positive-phase IOD that occurs simultaneously, while the duration seems to be modulated more by the positive-phase IOD. The results demonstrate the potential applicability of satellite-based precipitation monitoring to predicting meteorological drought conditions several months in advance and preparing for their effects.

SUBMITTER: Siswanto S

PROVIDER: S-EPMC9165873 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Satellite-based meteorological drought indicator to support food security in Java Island.

Siswanto Siswanto S Wardani Kartika Kusuma KK Purbantoro Babag B Rustanto Andry A Zulkarnain Faris F Anggraheni Evi E Dewanti Ratih R Nurlambang Triarko T Dimyati Muhammad M Dimyati Muhammad M

PloS one 20220603 6

A meteorological drought refers to reduced rainfall conditions and is a great challenge to food security. Information of a meteorological drought in advance is important for taking actions in anticipation of its effects, but this can be difficult for areas with limited or sparse ground observation data available. In this study, a meteorological drought indicator was approached by applying the Standardized Precipitation Index (SPI) to satellite-based precipitation products from multiple sources. ...[more]

PMID: 35657941

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Project description:Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For other phenophases, RMSE are higher and rise up to 9-10 days in the case of the earliest spring phenophases.

Project description:BackgroundJava is the most populous island in the world. This high population and the extensive economic activities have significantly reduced the forest areas of the Island and have greatly increased the pressure on its plant diversity. Compared to those with a wide distribution, endemic plants with a narrow geographic range are more vulnerable to anthropogenic threats and environmental changes. As species lists are essential for knowledge of species diversity in areas with strong anthropogenic pressure, here we present a dataset of endemic plants of Java Island. The initial species list was manually extracted from the Plant of the World Online (POWO). Each species on the list was then confirmed for its endemism by checking its current distribution using peer-reviewed publications, online plant databases and herbarium specimen images stored on the Global Biodiversity Information Facility (GBIF). The dataset contains 652 species in 279 genera and 85 families. The family with the highest number of endemic species is Orchidaceae (142 species), followed by Rubiaceae (57 species), Acanthaceae (40 species), Apocynaceae (35 species) and Lauraceae (29 species). The growth form of the species is mostly trees (22.6%), followed by herbs (19.2%), epiphytes (16%), shrubs (12.4%), vines (11%) and geophytes (9.4%). Most of the species (89.7%) have not yet been assessed for their conservation status according to the IUCN Red List Categories and Criteria. There are only 55 species (8.3%) that have been conserved within ex situ collections. Furthermore, most of the species (79.8%) are not listed on the CITES appendices and there are only four species (0.6%) protected by national law.New informationOur contribution provides the first online list of accepted scientific names of Javan endemic plants species, together with all their synonyms. New to the dataset are: i) provision of local names of the species (if available), ii) the classification of species under eleven growth forms (tree, shrub, herb, annual, graminoid, geophyte, fern, vines, hydrophyte, parasite and epiphyte), iii) assignation of the extinction risk of species according to the IUCN Red List, iv) ex situ collection status of species and information on the protection status of the species according to (v) CITES and (vi) the national law of Indonesia.

Dataset Information

Satellite-based meteorological drought indicator to support food security in Java Island.

Publications

Satellite-based meteorological drought indicator to support food security in Java Island.

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