Application of Remote Sensing for Drought Monitoring with NDVI-based Standardized Vegetation Index in Nan Province, Thailand

Pachanaparn, Chatpong; Jeefoo, Phaisarn; Rojanavasu, Pornthep

doi:10.1109/ectidamtncon53731.2022.9720317

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…The findings of this study align with those of similar research on drought analysis using satellitebased data and spectral indices, such as studies conducted in upper northeastern Thailand and Mahasarakham province (Laosuwan et al, 2016;Rotjanakusol, & Laosuwan, 2018), drought detection by application of remote sensing technology and vegetation phenology (Uttaruk & Laosuwan, 2017b). The SVI is a helpful instrument that can provide information about the onset, scope, intensity, and duration of vegetative stress in close to real-time (Sruthi & Mohammed Aslam, 2015;Vicente-Serrane et al, 2015;Pachanaparn et al, 2022). The findings of this study offer a standard for accurately identifying the drought region in the EEC provinces of Chachoengsao, Chonburi, and Rayong.…”

Section: Discussionsupporting

confidence: 85%

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Thai Eastern Economic Corridor Drought Monitoring Using Terra/Modis Satellite-Based Data

Jeefoo¹

2023

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One of the main natural disasters that has an impact on the environment and economy of nations throughout the world is drought. It has an impact on the local vegetation's state. The study's main goal was to look for years of severe drought by looking at Thailand's Eastern Economic Corridor (EEC). To determine the vegetation condition in the research area between 2017 and 2021, the Normalized Vegetation Index (NDVI) from Terra/MODIS data was employed. The area with the NDVI difference from the average value of NDVI during the same time period was examined using the Standardized Vegetation Index (SVI). Through the vegetation index, the drought can be reflected in this. According to the study, the highest drought area covered an area of 216.36 km 2 in 2017. This was followed by years 2019 and 2020, which each covered an area of 212.65 km 2 , 211.23 km 2 , 197.09 km 2 , and 178.07 km 2 . Additionally, a statistical analysis of the monthly correlation between the SVI (independent variable) and rainfall (dependent variable) over the course of the five years revealed that the coefficient of determination R 2 was 0.

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Section: Discussionsupporting

confidence: 85%

“…The probability value of SVI = P (Zijk) of the standard score of NDVI to reflect the probability of plant conditions. The SVI analysis can be seen in the equation 3 (Uttaruk & Laosuwan, 2017a;Uttaruk & Laosuwan, 2019;Pachanaparn et al, 2022).…”

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confidence: 99%

Thai Eastern Economic Corridor Drought Monitoring Using Terra/Modis Satellite-Based Data

Jeefoo¹

2023

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“…The MODIS/Terra satellite-based data was designated to investigate drought monitoring. In general, tracking and monitoring of natural resources and the environment are done using MODIS/Terra data [17] and [18]. The spatial resolution of MODIS/Terra was 250 -1000 meters including 36 spectral band recording.…”

Section: Datamentioning

confidence: 99%

Drought Monitoring Using MODIS Satellite-Based Data in Kamphaeng Phet Province, Thailand

2024

IJG

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Drought is a lengthened dry period in natural climate pattern which is one of the top global concerns. Drought in Thailand has been a long occurring issue affecting serious impact on health, economy, energy, and especially agricultural sector. Less precipitation caused long term water levels by lowering river volume and underground water. Therefore, the drought problem in Thailand is becoming more frequent and more severe. Kamphaeng Phet province located at the upper central part of Thailand demonstrated as the most drought-prone area. The objective of this study was to develop an approach for drought monitoring in provincial scale. MOD13Q1 dataset retrieved from MODIS satellite passing in different periods of Kamphaeng Phet was employed to develop the approach. Normalized Vegetation Index (NDVI) was extracted from the MOD13Q1 dataset so as to detect the vegetation condition of the study area. Afterwards NDVI was essentially standardized into Standardized Vegetation Index (SVI) in order to examine the area where NDVI was different from average value (Deviation). The probability of SVI acquired from NDVI standard scores reflected vegetation states explaining density and drought of vegetation in each period of time and season. Time series analysis of drought was implemented using SVI variances in different seasons. Additionally, precipitation variable was also included to find statistical consistency between SVI and precipitation. The lowest average of SVI was referred as drought, and nearly 0 value described severe drought. It was found that the most severe drought of Kamphaeng Phet occurred in 2020. In 2021, 2019, and 2018 drought showed at severe, moderate, and low level, respectively. Using both NDVI and SVI approach can be applied for drought monitoring and mitigation. Preparedness measures and public awareness of drought mitigation in this area can be enhanced.

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“…The collection and processing of satellite images are performed using Google Earth Engine. The visualization of EVI and SVI values is refer to the United Nations Platform for Space-based Information for Disaster Management and Emergency Response -Knowledge Portal (UN-SPIDER) and relevant references [6][7][8][9][10]. The generated numerical tabulation data is analyzed using K-Means Clustering, with additional support from Silhouette coefficient calculations.…”

Section: Svi and Evimentioning

confidence: 99%

A decade drought monitoring through enhanced and standardized vegetation index in isolated karst environment: Nusa Penida Island, Bali, Indonesia

Harbowo,

Muliawati

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Nusa Penida is one of the regions in Indonesia that vunarablely experiences extreme drought. The worst drought occurred in December 2019, coinciding with the Covid-19 pandemic outbreak. At that time, drought caused major crises in many local primary economic aspects, such as clean-water crises and local crop failure. The situation worsened after the global pandemic lockdown was imposed. Many tourism-related hospitalities (i.e., hotels, resorts, and restaurants) also have crashed. Isolated karst islands such as Nusa Penida Island pose significant challenges for water and agricultural land management. Geologically, this area consists of hilly carbonate rock terrain, a lack of proper aquifers, low precipitation, and tend to had high concentrations of dissolved Ca and Mg in its water. These conditions make many areas less preferable for settlements and traditional agriculture. In this study, we assessed the area using geospatial data for drought monitoring. We analyzed weekly-22 years of data (18/02/2000-18/02/2022 or 507 weeks data) to understand the period pattern of seasonal droughts in Nusa Penida over the past decade. This study used compiled satellite raster-images data to compute the Enhanced Vegetation Index (EVI) to express the Standardized Vegetation Index (SVI), which is sensitive to vegetation change during drought. The results showed that the longest droughts in Nusa Penida occurred from December 2000 to October 2001 (20 weeks) and Feb 2002 to Jan 2023 (21 weeks). The worst droughts occurred in December 2019 (SVI: -1.903 to -1.236), 2006 (SVI: -1.872 to -1.374), and 2002 (SVI: up to -0.136). There are patterns in which droughts in Nusa Penida tend to occur towards the end of the year, including at the end of 2022. Additionally, we detected some evergreen areas in Nusa Penida that require further investigation. These areas potentially act as natural permanent aquifers even during droughts. Furthermore, this study provides more insights for other comprehensive research, especially to enhance mitigation policies for near-future drought periods in Nusa Penida.

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Application of Remote Sensing for Drought Monitoring with NDVI-based Standardized Vegetation Index in Nan Province, Thailand

Cited by 3 publications

References 5 publications

Thai Eastern Economic Corridor Drought Monitoring Using Terra/Modis Satellite-Based Data

Thai Eastern Economic Corridor Drought Monitoring Using Terra/Modis Satellite-Based Data

Drought Monitoring Using MODIS Satellite-Based Data in Kamphaeng Phet Province, Thailand

A decade drought monitoring through enhanced and standardized vegetation index in isolated karst environment: Nusa Penida Island, Bali, Indonesia

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