Yi-Hyun Kim

Radar Vegetation Index for Estimating the Vegetation Water Content of Rice and Soybean

Vegetation water content (VWC) is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. Here, the radar vegetation index (RVI) was evaluated for estimating VWC. Analysis utilized a data set obtained by a ground-based multifrequency polarimetric scatterometer system, with a single incidence angle of 40°, during an entire growth period of rice and soybean. Temporal variations of the backscattering coefficients for the L-, C-, and X-bands, RVI, VWC, leaf area index, and normalized difference vegetation index were analyzed. The L-band RVI was found to be correlated to the different vegetation indices. Prediction equations for the estimation of VWC from the RVI were developed. The results indicated that it was possible to estimate VWC with an accuracy of 0.21 kg·m-2 using L-band RVI observations. These results demonstrate that valuable new information can be extracted from current and future radar satellite systems on the vegetation condition of two globally important crop types. The results are directly applicable to systems such as the proposed NASA Soil Moisture Active Passive satellite.

Polarimetric Backscattering Coefficients of Flooded Rice Fields at L- and C-Bands: Measurements, Modeling, and Data Analysis

The polarimetric backscattering coefficients (vv-, hh-, hv-, and vh-polarizations) of a flooded rice field are measured using L- and C-band ground-based polarimetric scatterometers. These measurements were made during the rice growth cycle, i.e., from the transplanting period to the harvest period (May to October 2006), to understand the feasibility of modeling and estimating rice growth. We also collected ground truth data that include fresh and dry biomasses, plant height, leaf area index, and leaf size. To study the incidence angle effect, the scatterometer data were collected at four different incidence angles, i.e., 30deg , 40deg, 50deg, and 60deg. In this paper, we show that the backscattering coefficients of a rice field can accurately be modeled using the radiative transfer theory. We also demonstrate that a polarimetric scatterometer is an effective tool for estimating rice growth. The hh-polarized backscattering coefficient is more sensitive to rice growth than its vv-polarization counterpart. The polarimetric ratio can be used to estimate rice growth accurately.

Predicting and mapping soil available water capacity in Korea

The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. This paper demonstrates a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000. We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols which are dominated by sandy materials. Profile available water capacity to a depth of 1 m was calculated and mapped for Korea. The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and 205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.

Retrieval of Wheat Growth Parameters With Radar Vegetation Indices

The radar vegetation index (RVI) has low sensitivity to changes in environmental conditions and has the potential as a tool to monitor vegetation growth. In this letter, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations made with a ground-based multifrequency polarimetric scatterometer system over an entire wheat growth cycle. We analyzed the temporal variations of backscattering coefficients for L-, C-, and X-bands; RVI; vegetation water content (VWC); and fresh weight. We found that the L-band RVI was highly correlated with both VWC (r = 0.98) and fresh weight (r = 0.98). Based upon these analyses, linear equations were developed for estimation of VWC (root-mean-square error (RMSE = 0.126 kg m-2)) and fresh weight (RMSE = 0.12 kg m-2). In addition, the results of the wheat study were combined with previous investigations with other crops (e.g., rice and soybean). We found that a single linear relationship between L-band RVI and VWC can be used for all crop types (RMSE = 0.47 kg m-2). These results clearly demonstrate the potential of RVI as a robust method for characterizing vegetation canopies. VWC is a key input requirement for retrieving soil moisture from microwave remote sensing observations. The results of this investigation will be useful for the Soil Moisture Active and Passive mission (2014), which is designed to measure global soil moisture.

Estimation of Paddy Field Area in North Korea Using RapidEye Images

Remotely sensed satellite images can be applied to monitor and obtain land surface information on inaccessible areas. We classified paddy field area in North Korea based on on-screen digitization with visual interpretation using 291 RapidEye satellite images covering the whole country. Criteria for paddy field classification based on RapidEye imagery acquired at different time of rice growth period was defined. Darker colored fields with regular shape in the images with false color composite from early May to late June were detected as rice fields. From early July to late September, it was hard to discriminate rice canopy from other type of vegetation including upland crops, grass, and forest in the image. Regular form of readjusted rice field in the plains and uniform texture when compared with surrounding vegetation. Paddy fields classified from RapidEye imagery were mapped and the areas were calculated by administrative district, province or city. Sixty six percent of paddy fields () were distributed in the west coastal regions including Pyeongannam-do, Pyeonganbuk-do, and Hwanghaenam-do. The paddy field areas classified from RapidEye images showed less than 1% of difference from the paddy field areas of North Korea reported by FAO/WFP (Food and Agriculture Organization/World Food Programme).

Radar Backscattering Measurement of a Paddy Rice Field using Multi-frequency(L, C and X) and Full-polarization

The objective of this study is to measure backscattering coefficients of paddy rice using L, C, X-bands scatterometer system with full polarization and various angles during a rice growth variables. The measurement was conducted at an experimental field located in National Institute of Agricultural Science and Technology (NIAST), Suwon, Korea. The rice cultivar was Japonica type, called Chuchung. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector netword analyzer (20 MHz ~ 20 GHz), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying a radar equation for the measured at incidence angles between 20deg and 60deg for full polarization (HH, VV, HV, VH), respectively, and compared with rice growth data such as plant height, stem number, fresh and dry weight and LAI that were collected at time of each scatterometer measurement simultaneously.

Continuous Monitoring of Rice Growth With a Stable Ground-Based Scatterometer System

Ground-based polarimetric scatterometers have been effective tools to monitor the growth of rice crop, with much higher temporal resolution than satellite synthetic aperture radar systems. However, scatterometer data obtained in every few days, as were the case for the previously reported studies, were not enough to address the effects of ever-changing weather conditions. In this letter, we constructed a highly stable X-, C-, and L-bands polarimetric scatterometer system in an air-conditioned shelter. The incidence and azimuth angles of the antenna were fixed to 40° and 0 °, respectively, to avoid uncertainty in repositioning error. Season-long daily backscattering coefficients from transplanting to harvesting were compared with rice growth data. Total fresh weight, leaf area index, and plant height were highly correlated with L-HH (0.97, 0.96, and 0.88, respectively) due to the deeper penetration and the dominance of double bounce in lower frequency. High-quality backscattering data clearly revealed the dual-peaked pattern in X-band, among which X-VV correlated best with grain dry weight and gravimetric grain water content (0.94 and 0.92, respectively) due to the better interaction of grain and rice canopy with microwave of higher frequency. These results will be useful in retrieving crop biophysical properties and determining the optimum microwave frequency and polarization necessary to monitor crop conditions.

Assessing Southern-type Garlic Suitability with regards to Soil and Temperature Conditions

This study was carried out to evaluate the land suitability for southern-type garlic cultivation associated with both temperature and soil constraints. The suitability analysis was conducted with hourly temperature data from 2001 to 2010 at all fifty seven meteorological stations and the soil-based suitability map of garlic provided by Rural Development Administration. Firstly the temperature data were processed by the growth stages (germinating, bulbing, and winter vegetation season), and then were adopted to limit the irrelevant lands. Next, as a result of overlaying each soil and temperature suitability map, the total 274,339 ha of area was mapped as highly suitable or suitable for southern-type garlic cultivation and the top four of the largest classified si-guns were identified as Naju, Jeongeup, Gochang, and Jinju. On the other hand, the statistical records of KOSIS (KOrea Statistical Information Service) showed lower amount of cultivation area than the analyzed results in the major production sites, Goheung, Sinan, Haenam, and Muan. However, it should not be regarded as exceptional because farmer’s preference might not correspond to potential land usability.

Estimation of Corn and Soybean Yields Based on MODIS Data and CASA Model in Iowa and Illinois, USA

The crop growing conditions make accurate predictions of yield ahead of harvest time difficult. Such predictions are needed by the government to estimate, ahead of time, the amount of crop required to be imported to meet the expected domestic shortfall. Corn and soybean especially are widely cultivated throughout the world and a staple food in many regions of the world. On the other hand, the CASA (Carnegie-Ames-Stanford Approach) model is a process-based model to estimate the land plant NPP (Net Primary Productivity) based on the plant growing mechanism. In this paper, therefore, a methodology for the estimation of corn/soybean yield ahead of harvest time is developed specifically for the growing conditions particular to Iowa and Illinois. The method is based on CASA model using MODIS data, and uses Net Primary Productivity (NPP) to predict corn/soybean yield. As a result, NPP at DOY 217 (in Illinois) and DOY 241 (in Iowa) tend to have high correlation with corn/soybean yields. The corn/soybean yields of Iowa in 2013 was estimated to be 11.24/3.55 ton/ha and Illinois was estimated to be 10.09/3.06 ton/ha. Errors were 6.06/17.58% and -10.64/-7.07%, respectively, compared with the yield forecast of the USDA. Crop yield distributions in 2013 were presented to show spatial variability in the state. This leads to the conclusion that NPP changes in the crop field were well reflected crop yield in this study.

Classification of Soil Desalination Areas Using High Resolution Satellite Imagery in Saemangeum Reclaimed Land

This study was aimed to classify soil desalination area for cultivation using NDVI (Normalized difference vegetation index) of high-resolution satellite image because the soil salinity affects the change of plant community in reclaimed lands. We measured the soil salinity and NDVI at 28 sites in the Saemangeum reclaimed land in June 2013. In halophyte and non-vegetation sites, no relation was found between NDVI and soil salinity. In glycophyte sites, however, we found that the soil salinity was below 0.1% and NDVI ranged from 0.11 to 0.57 which was greater than the other sites. So, we could distinguish the glycophyte sites from the halophyte sites and non-vegetation, and classify the area that soil salinty was below 0.1%. This technique could save the time and labor to measure the soil salinity in large area for agricultural utilization.