Prediction of rice yields at pixel scale rather than county can benefit crop management and scientific understanding because it is useful for monitoring how respond to various agricultural systems environmental factors. In this study, we propose a methodology the early prediction yield combining model deep learning different throughout South North Korea. Initially, satellite-integrated models were applied obtain pixel-scale reference yield. Then, used as target labels in leverage advantages...

The diurnal sampling capability of geostationary satellites provides unprecedented opportunities for monitoring canopy photosynthesis at multiple temporal scales. At the scale, only can currently provide sub-daily data regular intervals, also it help to minimize gaps due clouds seasonal scale. However, potential has not been explored in depth. In this study, we tracked variations gross primary production (GPP) using product near-infrared reflectance vegetation and photosynthetically active...

Abstract Machine learning (ML) and deep neural network (DNN) techniques are promising tools. These can advance mathematical crop modelling methodologies that integrate these schemes into a process-based model capable of reproducing or simulating growth. In this study, an innovative hybrid approach for estimating the leaf area index (LAI) paddy rice using climate data was developed ML DNN regression methodologies. First, we investigated suitable regressors to explore LAI estimation based on...

Recent satellite missions have provided new perspectives by offering high spatial resolution, a variety of spectral properties, and fast revisit rates to the same regions. In this study, we examined utility both broadband red-edge information texture features for classifying paddy rice crops in South Korea into three different growth stages. The grown can be grouped early-maturing, medium-maturing, medium-late-maturing cultivars, each cultivar is known minimum maximum productivity....

Although data-driven methods including deep neural network (DNN) were introduced, there was not enough assessment about spatial characteristics when using limited ground observation as reference. This work aimed to interpret the feasibility of several machine learning approaches assess distribution solar radiation on Earth based Communication, Ocean, and Meteorological Satellite (COMS) Imager (MI) geostationary satellite. Four models selected (artificial (ANN), random forest (RF), support...

Abstract A practical approach to continuously monitor and provide real-time solar energy prediction can help support reliable renewable supply relevant security systems. In this study on the Korean Peninsula, contemporaneous radiation images obtained from Communication, Ocean Meteorological Satellite (COMS) Imager (MI) system, were used design a convolutional neural network long short-term memory predictive model, ConvLSTM. This model was applied predict one-hour ahead spatially map...

This study presents the construction and evaluation of a dataset for estimating solar energy using GK-2A satellite deep learning. The is currently utilized in real-time weather observations over Korean Peninsula. features 16 channels, producing radiative channel images at spatial resolutions ranging from 500 m to 2 km, with temporal intervals as short minutes depending on area. These data are used various fields, including meteorology, oceanography, vegetation monitoring, renewable energy....

Cloud detection is a crucial task in satellite remote sensing, influencing applications such as vegetation indices, land use analysis, and renewable energy estimation. This study evaluates the performance of cloud masks generated for KOMPSAT-3 KOMPSAT-3A imagery using DeepLabV3+ deep learning model with ResNet-101 backbone. To overcome limitations digital number (DN) data, Top-of-Atmosphere (TOA) reflectance was computed used training. Comparative analysis between DN TOA demonstrated...

Satellite remote sensing is an essential tool for crop monitoring over large areas. One of the most practical issues defining appropriate spatial resolution level in terms technical aspects such as orbit path, swath width, or revisit rate, particularly South Korea where major agricultural activity rice cultivation conducted mostly by private farmers on small parcels land. This study experimental approach to examine sensitivity vegetation indices three paddy crops at various resolutions...

Despite their potential as a naturally-available clean energy option, the renewable resources of Democratic People's Republic Korea (i.e., North Korea) have rarely been evaluated. Therefore, to estimate availability land surface solar irradiance necessary for applications and model available potential, physically-based models drawing on Communication, Ocean Meteorological Satellite (COMS) data associated statistics key atmospheric constituents, were employed. To assess wind resources, output...

Acquiring accurate and timely information on the spatial distribution of paddy rice fields corresponding yield is an important first step in meeting regional global food security needs. In this study, using dense vegetation index profiles meteorological parameters from Communication, Ocean, Meteorological Satellite (COMS) geostationary satellite, we estimated areas applied a novel approach based remote sensing-integrated crop model (RSCM) to simulate spatiotemporal variations Northeastern...

This study mapped the solar radiation received by slopes for all of Korea, including areas that are not measured ground station measurements, through using satellites and topographical data. When estimating insolation with satellite, we used a physical model to measure amount hourly based surface insolation. Furthermore, also considered effects topography Global Land One-Kilometer Base Elevation (GLOBE) digital elevation (DEM) actual incident according geometry. The mapping, integrating...

Monitoring crop conditions and forecasting yields are both important for assessing production determining appropriate agricultural management practices; however, remote sensing is limited by the resolution, timing, coverage of satellite images, modeling in its application at regional scales. To resolve these issues, Gramineae (GRAMI)-rice model, which utilizes data, was used an effort to combine complementary techniques modeling. The model then investigated capability monitor canopy growth...

To meet the growing demands of staple crops with a strategy to develop amicable strategic measures that support efficient North Korean relief policies, it is desirable task accurately simulate yield paddy (Oryza sativa), an important Asian food commodity. We aim address this grid-based crop simulation model integrated satellite imagery enables us monitor productivity Korea. Vegetation Indices (VIs), solar insolation, and air temperature data are thus obtained from Communication Ocean...

The monitoring of crop development can benefit from the increased frequency observation provided by modern geostationary satellites. This paper describes a four-year testing period 2010 to 2014, during which satellite images world's first Geostationary Ocean Color Imager (GOCI) were used for spectral analyses paddy rice in South Korea. A vegetation index was calculated GOCI data based on bidirectional reflectance distribution function (BRDF)-adjusted reflectance, then visually analyze...

The GRAMI crop growth model uses remote sensing data and thus has the potential to produce maps of yield. A pixel-based information delivery system (CIDS) simulate map rice (Oryza sativa) yield was developed using GRAMI. GRAMI-rice parameterized field obtained at Chonnam National University, Gwangju, Republic Korea, in 2011 2012. separately validated same research site 2009 2010. then integrated into CIDS two-dimensional (2-D) Simulated values agreed well with corresponding measurements both...

Geostationary Ocean Color Imager (GOCI) sensor onboard the COMS (Communication, and Meteorological Satellite) launched in 2010 was primarily designed to provide high-frequency observations around Korean Peninsula ensure thorough monitoring of ocean properties. Owing its pixel resolution 500 m large set spectral solar channels, GOCI can also be considered for applications related characterization vegetation retrieval aerosol properties over land. However, apply it full land, is mandatory...

The cryosphere is an essential part of the earth system for understanding climate change. Components cryosphere, such as ice sheets and sea ice, are generally decreasing over time. However, previous studies have indicated differing trends between Antarctic Arctic. South Pole also shows internal differences in trends. These phenomena indicate importance continuous observation Polar Regions. Albedo a main indicator analyzing change important variable with regard to radiation budget because it...

The Geostationary Ocean Color Imager (GOCI) of the Communication, Ocean, and Meteorological Satellite (COMS) increases chance acquiring images with greater clarity eight times a day is equipped spectral bands suitable for monitoring crop yield in national scale spatial resolution 500 m. objectives this study were to classify nationwide paddy fields project rice (Oryza sativa) production using grid-based GRAMI-rice model GOCI satellite products over South Korea from 2011 2014. Solar...

Recent developments in unmanned aerial system (UAS) require an urgent introduction to monitoring technologies of crop diagnostic information because their advantage manoeuvering tasks at a high-spatial resolutions and low costs user-friendly manner. In this study, advanced application method UAS remote sensing was performed using the grid GRAMI-rice model such that it can be driven weather data monitor spatiotemporal productivities rice (Oryza sativa). Remotely sensed for were supplied,...

Remote sensing is a useful technique to determine spatial variations in crop growth while modelling can reproduce temporal changes growth. In this study, we formulated hybrid system of remote and based on random-effect model the empirical Bayesian approach for parameter estimation. Moreover, relationship between reflectance leaf area index was incorporated into statistical model. Plant ground-based canopy data paddy rice were measured at three study sites South Korea. Spatiotemporal...