• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.3
• /
• pp.182-196
• /
• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.8 no.2
• /
• pp.33-40
• /
• 2005

The objective of this research was to find an indirect method to estimate spectral reflectance and NDVI(Normalized Difference Vegetation Index) efficiently, using the spectroradiometer and NOAA AVHRR satellite data. For collecting RS base data, used spectro-radiometer that measures reflection characteristics between 300~1,100nm was used and measured the reflection of vegetation from paddy rice during the growing season at Chungbuk national university's farm in 2002. The feasibility of detecting the temporal variation in the spectral reflectance and NDVI in paddy rice were conducted on eight growth stages. AVHRR data were collected in eight different months over a one year period in 2002. The results were compared with those obtained by analyzing NDVI characteristics. The spectral reflectance and NDVI of paddy rice have a great effect on the growth condition. Considerably, NDVI was increased by developing muscle fiber tissue at the near infrared wavelength until the Booting stage. Then the NDVI increased until the Maturity stage and then decreased until harvest. The highest month was at July and the lower month was at March. The difference NDVI analysis using March and another months data was conducted, the results were provided information on the growth condition of crops.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.53 no.3
• /
• pp.75-82
• /
• 2011

This study refers to the derivation of simple crop yield prediction equation by using KOMPSAT-2 derived vegetation index. For a 1.25 ha small farm area located in the middle part of South Korea, the KOMPSAT-2 panchromatic and multi-spectral images of 31th August 2008, 17th November 2008, and 10th September 2009 were used. The field spectral reflectance during growing period for the 6 crops (rice, potato, corn, red pepper, garlic, and bean) were measured using ground spectroradiometer and the yield was investigated. Among the 6 vegetation indices (VI), the NDVI and ARVI between measured and image derived showed high relationship with the coefficient of determination of 0.85 and 0.95 respectively. Using the 3 years field data, the NDVI and ARVI regression curves were derived, and the yields were tried to compare with the maximum VIs value.

• Journal of the Korean earth science society
• /
• v.27 no.7
• /
• pp.787-803
• /
• 2006

The drought index has been developed, based on a $8.6{\mu}m$ surface emissivity in the $8-12{\mu}m$ MODIS channels over the African Sahel region (10-20 N, 13 W-35 W) and the Seoul Metropolitan Area (SMA: 37.2-37.7 N, 126.6-127.2 E). The emissivity indicates the $SiO_2$ strength and can vary interannually by vegetation, water vapor, and soil moisture, as a potential indicator of drought conditions. In a well-vegetated region close to 10 N of the Sahel, the Normalized Difference Vegetation Index (NDVI) showed high sensitivity, while the emissivity did not. On the other hand, the NDVI experienced negligible variability in a poorly vegetated region near 20 N, while the emissivity reflected sensitively the effects of atmospheric water vapor and soil moisture conditions. Seasonal variations of the emissivity (0.94-0.97) have been examined over the SMA during the 2003-2004 period compared to NDVI (or Enhanced Vegetation Index; EVI). Here, the dryness was more severe in urban area with less vegetation than in suburban area; the two areas corresponded to the north and south of the Han river, respectively. The emissivity exhibiting a significant spatial correlation of ${\sim}0.8$ with the two indices can supplement their information.

• Journal of Information Processing Systems
• /
• v.1 no.1 s.1
• /
• pp.102-106
• /
• 2005

As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

• Korean Journal of Agricultural Science
• /
• v.50 no.2
• /
• pp.165-180
• /
• 2023

This study investigated 62 nested quadrat plots of Jinaksan to identify community classification and changes of the vegetation by using the phytosocial method and analyzed importance values. Vegetation types were classified into 8 communities: Quercus mongolica community, Q. variableis community, Q. aliena community, Pinus densiflora, Q. acutissima, Zelkova serrata, Carpinis laxiflora, and C. tschonoskii. The significance value was highest in Q. mongolica (62.75) followed by P. densiflora (55.16), Q. variabilis community (25.03), Z. serrata (22.17), Q. aliena (18.30), Prunus serrulata var. pubescens (16.86), C. laxiflora (13.25), Q. acutissima (10.72), C. tschonoskii (10.08), Q. serrata (8.02), Fraxinus sieboldiana (6.93), Acer pseudosieboldianum (6.73), and Styrax obassis (5.73). Quercus mongolica displayed a stable distribution pattern, presenting a reverse J-shaped curve from the diameter at breast height (DBH) analysis, and it was judged that current state would be maintained for a certain period. In addition, P. densiflora is expected to dominate for the time being and Quercus species are expected to gradually decrease.

• Journal of Korean Society of Forest Science
• /
• v.96 no.5
• /
• pp.591-601
• /
• 2007

Spatial information on forest biomass is an important factor to evaluate the capability of forest as a carbon sequestrator and is a core independent variable required to drive models which describe ecological processes such as carbon budget, hydrological budget, and energy flow. The objective of this study is to understand the relationship between satellite image and field data, and to quantitatively estimate and map the spatial distribution of forest biomass. Landsat Enhanced Thematic Mapper (ETM+) derived vegetation indices and field survey data were applied to estimate the biomass distribution of mountainous forest located in Gwangneung Experimental Forest (230 ha). Field survey data collected from the ground plots were used as the dependent variable, forest biomass, while satellite image reflectance data (Band 1~5 and Band 7), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and RVI (Ratio Vegetation Index) were used as the independent variables. The mean and total biomass of Gwangneung catchment area were estimated to be about 229.5 ton/ha and $52.8{\times}10^3$ tons respectively. Regression analysis revealed significant relationships between the measured biomass and Landsat derived variables in both of deciduous forest ($R^2=0.76$, P < 0.05) and coniferous forest ($R^2=0.75$, P < 0.05). However, there still exist many uncertainties in the estimation of forest ecosystem parameters based on vegetation remote sensing. Developing remote sensing techniques with adequate filed survey data over a long period are expected to increase the estimation accuracy of spatial information of the forest ecosystem.

• Korean Journal of Remote Sensing
• /
• v.29 no.6
• /
• pp.621-629
• /
• 2013

Desertification monitoring as a main portion for understand desertification, have been conducted by many scientists. However, the stage of research remains still in the level of comparison of the past and current situation. In other words, monitoring need to focus on finding methods of how to take precautions against desertification. In this study, Vegetation Temperature Condition Index (VTCI), derived from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), was utilized to observe the distribution change of vegetation. The index can be used to monitor drought occurrences at a regional level for a special period of a year, and it can also be used to study the spatial distribution of drought within the region. Techniques of remote sensing and Geographic Information System (GIS) were combined to detect the distribution change of vegetation with VTCI. As a result, assuming that the moisture condition is the only main factor that affects desertification, we found that the distribution of vegetation in Bulgan, Mongolia could be predicted in a certain degree, using VTCI. Although desertification is a complicated process and many factors could affect the result. This study is helpful to provide a strategic guidance for combating desertification and allocating the use of the labor force.

• Journal of Korean Society for Atmospheric Environment
• /
• v.24 no.4
• /
• pp.423-438
• /
• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Journal of Forest and Environmental Science
• /
• v.32 no.2
• /
• pp.196-204
• /
• 2016

In this study, vegetation succession and the rate of consequent topsoil development were investigated in shallow landslide scars of sedimentary rock slopes covered by volcanic ashes and pumice in Kagoshima prefecture, Japan. Seven shallow landslide scars of different ages were selected as study areas. In the initial period after the occurrence of a shallow landslide, deciduous broad-leaved trees such as Mallotus japonicus or Callicarpa mollis were occupied in the areas. Approximately 30 years after the landslide, evergreen broad-leaved trees such as Cinnamomum japonicum invaded in the areas, already existed present deciduous broad-leaved trees. After 50 years, the summit of the canopy comprised evergreen broad-leaved trees such as Castanopsis cuspidata var. sieboldii and Machilus thunbergii. Moreover, the diversity of vegetation invading the site reached the maximum after 15 years, followed by a decrease and stability in the number of trees. The total basal areas under vegetation increased with time. It was concluded that the vegetation community reaches the climax stage approximately 50 years after the occurrence of a shallow landslide in the study areas, in terms of the Fisher-Williams index of diversity (${\alpha}$) and the prevalence of evergreen broad-leaved trees. Moreover, according to the results of topsoil measurement in the study areas, the topsoil was formed at the rate of 0.31 cm/year. The development of topsoil usually functions to improve the multi-faceted functions of a forest. However, when the increased depth of topsoil exceeds the stability threshold, the conditions for a shallow landslide occurrence are satisfied. Therefore, we indicated to control the depth of topsoil and strengthen its resistance by forest management in order to restrain the occurrence of shallow landslides.