Special Issue "Recent Advances of Remote Sensing in Monitoring Agro-Meteorological Disasters "

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: closed (30 June 2020).

Special Issue Editors

Prof. Koki Homma
Website1 Website2
Guest Editor
Graduate School of Agricultural Science, Tohoku University 468-1 Aramaki Aza-Aoba, Aoba, Sendai 980-8572, Japan
Interests: crop production; simulation model; farmers’ fields evaluation
Dr. Masayasu Maki

Guest Editor
Faculty of Food and Agricultural Sciences, Fukushima University 1 Kanayagawa, Fukushima 960-1296 Japan
Interests: Remote sensing, Crop monitoring, Disaster monitoring, Mapping
Dr. Mongkol Raksapatcharawong

Guest Editor
Faculty of Engineering, Kasetsart University, 50 Ngamwongwan Rd. Jatujak Bangkok 10900 Thailand
Interests: Crop/drought model development, remote sensing applications, big data analytic for smart agriculture

Special Issue Information

Dear Colleagues,

In recent years, the frequency and intensification of extreme weather have been increasing, which may be associated with global warming and climate change. Under such circumstances, the monitoring of meteorological disasters in agriculture and their impact assessment are very important issues for food security. Quantifying the disasters based on satellite observations is recommended for this purpose. It is necessary to monitor and assess disasters at the farmer level. As UAV technology is becoming more popular and easily accessible, monitoring can start at any level. Carrying out assessments immediately after a disaster can provide information that will help shape the countermeasures in such cases. Monitoring and assessment are also being tested in the field of agricultural insurance. Insurance assessment based on remote-sensing may increase fairness and decrease cost.

This Special Issue calls for papers on the monitoring of meteorological disasters in agriculture. It covers not only floods and droughts, but also production fluctuations due to high temperature, low solar radiation, and so on, from the country scale to the farmers’ field scale. The trials of impact assessment using simulation models are especially welcome to utilize remote-sensing monitoring. Further development in this topic is expected by introducing the latest findings in this Special Issue.

Prof. Koki Homma
Dr. Masayasu Maki
Dr. Mongkol Raksapatcharawong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

Open AccessArticle
Satellite-Based Drought Impact Assessment on Rice Yield in Thailand with SIMRIW−RS
Remote Sens. 2020, 12(13), 2099; https://doi.org/10.3390/rs12132099 - 30 Jun 2020
Abstract
Advances in remote sensing technologies have enabled effective drought monitoring globally, even in data-limited areas. However, the negative impact of drought on crop yields still necessitates stakeholders to make informed decisions according to its severity. This research proposes an algorithm to combine a [...] Read more.
Advances in remote sensing technologies have enabled effective drought monitoring globally, even in data-limited areas. However, the negative impact of drought on crop yields still necessitates stakeholders to make informed decisions according to its severity. This research proposes an algorithm to combine a drought monitoring model, based on rainfall, land surface temperature (LST), and normalized difference vegetation index/leaf area index (NDVI/LAI) satellite products, with a crop simulation model to assess drought impact on rice yields in Thailand. Typical crop simulation models can provide yield information, but the requirement for a complicated set of inputs prohibits their potential due to insufficient data. This work utilizes a rice crop simulation model called the Simulation Model for Use with Remote Sensing (SIMRIW–RS), whose inputs can mostly be satisfied by such satellite products. Based on experimental data collected during the 2018/19 crop seasons, this approach can successfully provide a drought monitoring function as well as effectively estimate the rice yield with mean absolute percentage error (MAPE) around 5%. In addition, we show that SIMRIW–RS can reasonably predict the rice yield when historical weather data is available. In effect, this research contributes a methodology to assess the drought impact on rice yields on a farm to regional scale, relevant to crop insurance and adaptation schemes to mitigate climate change. Full article
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