• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.729-735
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• 2023

The Moderate resolution Imaging Spectroradiometer (MODIS) is a multispectral sensor that has been actively researched in various fields using diverse land and atmospheric products. MODIS was first launched over 20 years ago, and the demand for novel sensors that can produce data comparable to that obtained using MODIS has continuously increased. In this study, land products obtained using the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched in 2011 were introduced, including land surface temperature and vegetation indices such as the normalized difference vegetation index and enhanced vegetation index. These land products were compared with existing data obtained using MODIS to verify their local applicability in South Korea. Based on spatiotemporal monitoring of an extreme drought period in South Korea and the application of VIIRS land products, our results indicate that VIIRS can effectively replace MODIS multispectral sensors for agricultural drought monitoring.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1207-1217
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• 2022

Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.28-37
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• 2008

In this study, we perform land surface monitoring of NDVI (Normalized Difference Vegetation Index) variation by using remote sensing data during 1999-2005 over North Korea, which can't easily access to measure directly land surface characteristics due to one of the world's most closed societies. North Korea forest region has most abundant forest vegetation - so called Lungs of Korea in the Korea peninsula. NDVI represents vegetation activity used in many similar studies. In this study, we detect vegetation variation and analysis factors of the change over North Korea. By using variation of NDVI, we can infer that effect of drought over North Korea, and reduced vegetation indices by typhoon in North Korea. Land surface type except barren ground with decreased NDVI value is considered as when North Korea region was suffering from drought and typhoon effects, which show lower than mean of 7-year NDVI value. Especially, in recently, the food production of North Korea with political and economical issues can be inferred indirectly these trends by using estimated output data from this study.

• Journal of Ecology and Environment
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• v.41 no.2
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• pp.34-44
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• 2017

Background: Monitoring terrestrial vegetation cover condition is important to evaluate its current condition and to identify potential vulnerabilities. Due to simplicity and low cost, point intercept method has been widely used in evaluating grassland surface and quantifying cover conditions. Field-based digital photography method is gaining popularity for the purpose of cover estimate, as it can reduce field time and enable additional analysis in the future. However, the caveats and uncertainty among field-based vegetation cover estimation methods is not well known, especially across a wide range of cover conditions. We compared cover estimates from point intercept and digital photography methods with varying sampling intensities (25, 49, and 100 points within an image), across 61 transects in typical steppe, forest steppe, and desert steppe in central Mongolia. We classified three photosynthetic groups of cover important to grassland ecosystem functioning: photosynthetic vegetation, non-photosynthetic vegetation, and bare soil. We also acquired normalized difference vegetation index from satellite image comparison with the field-based cover. Results: Photosynthetic vegetation estimates by point intercept method were correlated with normalized difference vegetation index, with improvement when non-photosynthetic vegetation was combined. For digital photography method, photosynthetic and non-photosynthetic vegetation estimates showed no correlation with normalized difference vegetation index, but combining of both showed moderate and significant correlation, which slightly increased with greater sampling intensity. Conclusions: Results imply that varying greenness is playing an important role in classification accuracy confusion. We suggest adopting measures to reduce observer bias and better distinguishing greenness levels in combination with multispectral indices to improve estimates on dry matter.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.993-1001
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• 2017

Drought is a worldwide natural disaster with extensively adverse impacts on natural ecosystems, agricultural products, social communities and regional economy. Various global satellite observations, including SMAP soil moisture, GRACE terrestrial water storage, Terra and Aqua vegetation productivity, evapotranspiration, and satellite precipitation measures are currently used to characterize seasonal timing and inter-annual variations of regional water supply pattern, vegetation growth, drought events, and its associated influence ecosystems and human society. We suggest the satellite monitoring system development to quantify meteorological, eco-hydrological, and socio-ecological factors related to drought events, and characterize spatial and temporal drought patterns in Korea. The combination of these complementary remote sensing observations(visible to microwave bands) provide an effective means for evaluating regional variations in the timing, frequency, and duration of drought, and availability of water supply influencing vegetation and crop growth. This integrated drought monitoring could help national capacity to deal with natural disasters.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.2
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• pp.121-135
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• 2016

The present study is an analysis of the monitoring results of the four areas that underwent the experimental construction of Straw-net+seedspray, Vegetation media spray method(t=2cm), and Vegetation media spray method(t=3cm), with the purpose of selecting the adequate revegetation of cutting slopes in weathered granite soil. Cutting slopes are mostly designed in the Straw-net+seedspray method, but since weathered granite soil slopes tend to have an infertile soil quality that runs down, it is difficult for seed germination and growth. It is difficult to apply Straw-net+seedspray to weathered granite soil slopes considering the germination rate and coverage rate of the Straw-net+seedspray method, which accompanies erosion and scouring. The final conclusions are summarized as follows. First, Straw-net+seedspray has difficulty recruiting plants to infertile weathered granite soil, which results in a lower coverage rate and fewer species, so it is not adequate construction method. Second, Vegetation spraying methods with wet media are more advantageous in early revegetation. The wet construction methods are faster than the dry construction methods in terms of early germination and its early growth are more excellent. Third, when constructing Vegetation spray methods with dry media, it were more advantageous if the thickness was thicker. When the soil-media is thicker, the soil is resilient to droughts, so the thickness must be flexibly applied according to the soil quality and slant of the weathered granite soil slope. The present study is a monitoring result for some areas of Gangwon-do, so its results may differ from other areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.6
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• pp.1-12
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• 2006

Remote sensing cannot provide a direct measurement of vegetation index (VI) but it can provide a reasonably good estimate of vegetation index, defined as the ratio of satellite bands. The monitoring of vegetation in nearby urban regions is made difficult by the low spatial resolution and temporal resolution image captures. In this study, enhancing spatial resolution method is adapted as to improve a low spatial resolution. Recent studies have successfully estimated normalized difference vegetation index (NDVI) using improved resolution method such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra satellite. Image enhancing spatial resolution is an important tool in remote sensing, as many Earth observation satellites provide both high-resolution and low-resolution multi-spectral images. Examples of enhancement of a MODIS multi-spectral image and a MODIS NDVI image of Cheongju using a Landsat TM high-resolution multi-spectral image are presented. The results are compared with that of the IHS technique is presented for enhancing spatial resolution of multi-spectral bands using a higher resolution data set. To provide a continuous monitoring capability for NDVI, in situ measurements of NDVI from paddy field was carried out in 2004 for comparison with remotely sensed MODIS data. We compare and discuss NDVI estimates from MODIS sensors and in-situ spectroradiometer data over Ochang plain region. These results indicate that the MODIS NDVI is underestimated by approximately 50%.

• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.839-849
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• 2003

Drought is one of the major environmental disasters. Weather data, particularity rainfall, are currently the primary source of information widely used for drought monitoring. However, weather data are often from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely drought detection. Data from remote sensing platforms can be used to complements weather data in drought. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI)-based vegetation condition index(VCI) were used in this study These indices showed their excellent ability to detect vegetation stress due to drought. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the VCI index.