scholarly journals NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019

2021 ◽  
Vol 13 (12) ◽  
pp. 5969-5986
Author(s):  
Jichong Han ◽  
Zhao Zhang ◽  
Yuchuan Luo ◽  
Juan Cao ◽  
Liangliang Zhang ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Northeast Asia ◽  
Paddy Rice ◽  
Growth And Yield ◽  
Coefficient Of Determination ◽  
Linear Coefficient ◽  
Mixed Pixel ◽  
Coarse Spatial Resolution ◽  
Mixed Pixels ◽  
Yield Monitoring

Abstract. An accurate paddy rice map is crucial for ensuring food security, particularly for Southeast and Northeast Asia. MODIS satellite data are useful for mapping paddy rice at continental scales but have a mixed-pixel problem caused by the coarse spatial resolution. To reduce the mixed pixels, we designed a rule-based method for mapping paddy rice by integrating time series Sentinel-1 and MODIS data. We demonstrated the method by generating annual paddy rice maps for Southeast and Northeast Asia in 2017–2019 (NESEA-Rice10). We compared the resultant paddy rice maps with available agricultural statistics at subnational levels and existing rice maps for some countries. The results demonstrated that the linear coefficient of determination (R2) between our paddy rice maps and agricultural statistics ranged from 0.80 to 0.97. The paddy rice planting areas in 2017 were spatially consistent with the existing maps in Vietnam (R2=0.93) and Northeast China (R2=0.99). The spatial distribution of the 2017–2019 composite paddy rice map was consistent with that of the rice map from the International Rice Research Institute. The paddy rice planting area may have been underestimated in the region in which the flooding signal was not strong. The dataset is useful for water resource management, rice growth, and yield monitoring. The full product is publicly available at https://doi.org/10.5281/zenodo.5645344 (Han et al., 2021a). Small examples can be found from the following DOI: https://doi.org/10.17632/cnc3tkbwcm.1 (Han et al., 2021b).

scholarly journals AsiaRiceMap10m: high-resolution annual paddy rice maps for Southeast and Northeast Asia from 2017 to 2019

2021 ◽  
Author(s):  
Jichong Han ◽  
Zhao Zhang ◽  
Yuchuan Luo ◽  
Juan Cao ◽  
Liangliang Zhang ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Northeast Asia ◽  
Paddy Rice ◽  
Growth And Yield ◽  
Coefficient Of Determination ◽  
Linear Coefficient ◽  
Mixed Pixel ◽  
Coarse Spatial Resolution ◽  
Mixed Pixels ◽  
Yield Monitoring

Abstract. An accurate paddy rice map is crucial for food security, particularly for Southeast and Northeast Asia. The MODIS satellite data is useful for mapping paddy rice at continental scales but has a problem of mixed-pixel due to coarse spatial resolution. To reduce the mixed pixels, we designed a rule-based method for mapping paddy rice by integrating time-series Sentinel-1 and MODIS data. We demonstrated the method in generating annual paddy rice maps for Southeast and Northeast Asia in 2017–2019 (AsiaRiceMap10m). The resultant paddy rice maps were compared with available agricultural statistics at subnational levels and existing rice maps for some countries. The results show that the linear coefficient of determination (R2) between our paddy rice maps and agricultural statistics ranges from 0.80 to 0.97. The paddy rice planting areas in 2017 were spatially consistent with the existing maps in Vietnam (R2 = 0.93) and Northeast China (R2 = 0.99). The spatial distribution of the 2017–2019 composite paddy rice map is consistent with the rice map from the International Rice Research Institute. The paddy rice planting area may be underestimated in the region where the flooding signal is not strong. The dataset is useful for water resource management, rice growth, and yield monitoring. The full product is publicly available at https://doi.org/10.17632/j34b3jsvr9.1 (Han et al., 2021a). Find small examples here (https://doi.org/10.17632/cnc3tkbwcm.1) (Han et al., 2021b).

scholarly journals Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels

2019 ◽  
Vol 23 (2) ◽  
pp. 949-969
Author(s):  
Fugen Li ◽  
Xiaozhou Xin ◽  
Zhiqing Peng ◽  
Qinhuo Liu
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Heihe River ◽  
Natural Ecosystems ◽  
Evaporative Fraction ◽  
Mixed Pixel ◽  
Mixed Pixels

Abstract. Currently, applications of remote sensing evapotranspiration (ET) products are limited by the coarse resolution of satellite remote sensing data caused by land surface heterogeneities and the temporal-scale extrapolation of the instantaneous latent heat flux (LE) based on satellite overpass time. This study proposes a simple but efficient model (EFAF) for estimating the daily ET of remotely sensed mixed pixels using a model of the evaporative fraction (EF) and area fraction (AF) to increase the accuracy of ET estimate over heterogeneous land surfaces. To accomplish this goal, we derive an equation for calculating the EF of mixed pixels based on two key hypotheses. Hypothesis 1 states that the available energy (AE) of each sub-pixel is approximately equal to that of any other sub-pixels in the same mixed pixel within an acceptable margin of error and is equivalent to the AE of the mixed pixel. This approach simplifies the equation, and uncertainties and errors related to the estimated ET values are minor. Hypothesis 2 states that the EF of each sub-pixel is equal to that of the nearest pure pixel(s) of the same land cover type. This equation is designed to correct spatial-scale errors for the EF of mixed pixels; it can be used to calculate daily ET from daily AE data. The model was applied to an artificial oasis located in the midstream area of the Heihe River using HJ-1B satellite data with a 300 m resolution. The results generated before and after making corrections were compared and validated using site data from eddy covariance systems. The results show that the new model can significantly improve the accuracy of daily ET estimates relative to the lumped method; the coefficient of determination (R2) increased to 0.82 from 0.62, the root mean square error (RMSE) decreased to 1.60 from 2.47 MJ m−2(decreased approximately to 0.64 from 0.99 mm) and the mean bias error (MBE) decreased from 1.92 to 1.18 MJ m−2 (decreased from approximately 0.77 to 0.47 mm). It is concluded that EFAF can reproduce daily ET with reasonable accuracy; can be used to produce the ET product; and can be applied to hydrology research, precision agricultural management and monitoring natural ecosystems in the future.

scholarly journals Estimating Daily Evapotranspiration Based on a Model of Evapotranspiration Fraction (EF) for Mixed Pixels

2018 ◽  
Author(s):  
Fugen Li ◽  
Xiaozhou Xin ◽  
Zhiqing Peng ◽  
Qinhuo Liu
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Heihe River ◽  
Mixed Pixel ◽  
Before And After ◽  
Mixed Pixels

Abstract. Currently, applications of remote sensing evapotranspiration (ET) products are limited by the low resolution of satellite remote sensing data caused by land surface heterogeneities and the temporal scale extrapolation of the instantaneous latent heat flux (LE) based on satellite overpass time. This study proposes a simple but efficient model (EFAF) for estimating the daily ET of remotely sensed mixed pixels using a model of the evapotranspiration fraction (EF) and area fraction (AF). To accomplish this goal, we derive an equation for calculating the EF of mixed pixels based on two key hypotheses. Hypothesis 1 states that the available energy (AE) of each sub-pixel is approximately equal to that of any other sub-pixels in the same mixed pixel within an acceptable margin of bias and is equivalent to the AE of the mixed pixel. This approach simplifies the equation, and uncertainties and errors related to the estimated ET values are minor. Hypothesis 2 states that the EF of each sub-pixel is equal to that of the nearest pure pixel(s) of the same land cover type. This equation is designed to correct spatial scale errors for the EF of mixed pixels; it can be used to calculate daily ET from daily AE data. The model was applied to an artificial oasis located in the midstream area of the Heihe River using HJ-1B satellite data with a 300 m resolution. Results generated before and after making corrections were compared and validated using sites data from eddy covariance systems. The results show that the new model can significantly improve the accuracy of daily ET estimates relative to the lumped method; the coefficient of determination (R2) increased to 0.82 from 0.62, the root mean square error (RMSE) decreased to 1.60 from 2.47 MJ·m−2, and the mean bias error (MBE) decreased from 1.92 to 1.18 MJ·m−2.

scholarly journals Development and Verification of the Available Number of Water Intake Days in Ungauged Local Water Source Using the SWAT Model and Flow Recession Curves

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1511
Author(s):  
Jung-Ryel Choi ◽  
Il-Moon Chung ◽  
Se-Jin Jeung ◽  
Kyung-Su Choo ◽  
Cheong-Hyeon Oh ◽  
...  
Keyword(s):  
Water Supply ◽  
Water Intake ◽  
Water Resource Management ◽  
Assessment Tool ◽  
Swat Model ◽  
High Water ◽  
Coefficient Of Determination ◽  
Severe Drought ◽  
Regional Government

Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite high water supply ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92, 0.84, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.

scholarly journals Peran Pupuk Organik dalam Peningkatan Efisiensi Pupuk Anorganik pada Padi Sawah (Oryza sativa L.)

2015 ◽  
Vol 43 (1) ◽  
pp. 8
Author(s):  
Totong Siwanto ◽  
Sugiyanta , ◽  
Maya Melati
Keyword(s):  
Oryza Sativa L ◽  
Block Design ◽  
Organic Fertilizer ◽  
Biological Properties ◽  
Paddy Rice ◽  
Inorganic Fertilizer ◽  
Growth And Yield ◽  
Research Station ◽  
Randomized Block Design ◽  
Two Factors

ABSTRACT<br />Application of organic fertilizer into the soil is designated as a source of macro, micro nutrients and organic acids; it also acts as soil ameliorant that improve physical, chemical and biological properties of soil. Application of high rates organic fertilizer has a constraint namely the availability and ease of application. Therefore, it is necessary to learn the use of organic fertilizer with low rates to improve the efficiency of chemical fertilizers. This research was aimed to study the effect of organic and inorganic fertilizers on growth and yield of paddy rice, as well as the efficiency of N, P, K inorganic fertilizer. Field experiment was conducted at Sawah Baru Research Station, University Farm IPB, Bogor, West Java from September to December 2013. The experiment used Randomized Block Design consisted of two factors: rates of organic fertilizer (0, 250, 500, 750, and 1,000 kg ha-1), and rates of inorganic fertilizer (0, 100, 200, 300, and 400 kg ha-1). The results suggested that the application of 1,000 kg organic fertilizer ha-1 + 400 kg inorganic fertilizer ha-1 did not show significant interaction. Application of organic fertilizer alone up to 1,000 kg ha-1 resulted in low growth and yield. Increasing rates of  application up to 400 kg inorganic fertilizer ha-1 increased the growth and yield of paddy rice. The highest N efficiency was 89.19% at a rate of 500 kg organic fertilizer ha-1 + 200 kg inorganic fertilizer ha-1, whereas the highest efficiency of P and K, respectively were 69.55% and 92.52% at a rate of 750 kg organic fertilizer ha-1 + 300 kg inorganic fertilizer ha-1.<br />Keywords: NPK, organic fertilizer, paddy rice

scholarly journals Streamflow regionalization for the Mortes River Basin upstream from the Funil Hydropower Plant, MG

2020 ◽  
Vol 15 (3) ◽  
pp. 1 ◽  
Author(s):  
Jhones Da Silva Amorim ◽  
Rubens Junqueira ◽  
Vanessa Alves Mantovani ◽  
Marcelo Ribeiro Viola ◽  
Carlos Rogério de Mello ◽  
...  
Keyword(s):  
Resource Management ◽  
River Basin ◽  
Water Resource ◽  
Water Resource Management ◽  
Extreme Values ◽  
Kendall Test ◽  
Hydropower Plant ◽  
Coefficient Of Determination ◽  
Historical Series ◽  
Anderson Darling

 Maximum and minimum streamflow are fundamental for water resource management, especially for water rights. However, lack of monitoring and scarce streamflow data limit such studies. Streamflow regionalization is a useful tool to overcome these limitations. The study developed models for regionalization of the maximum and minimum reference streamflows for the Mortes River Basin (MRB) (Water Resources Planning and Management Unit - GD2), Southern Minas Gerais State. The study used long-term streamflow historical series provided by the Brazilian National Water Agency (ANA). Previous exploratory analysis was performed, and it was observed that the streamflow series are stationary according to the Mann-Kendall test. The estimation of the streamflow for different return periods (RP) was performed by fitting Probability Density Functions (PDFs) that were tested by the Anderson-Darling (AD) test. The Generalized Extreme Values (GEV) and Wakeby were the most appropriate PDFs for maximum and minimum streamflows, respectively. The streamflow models were fitted using a power regression procedure, considering the drainage area of the watersheds as inputs. The fittings reached the coefficient of determination (R2) greater than 0.90. Thus, the streamflow regionalization models demonstrated good performance and are a potential tool to be used for water resource management in the studied basin.

scholarly journals Validation of Diagram Scale for Leaf Spot Caused by Pestalotiopsis sp. in Coconut Seedlings

2020 ◽  
Vol 8 (2) ◽  
pp. 32
Author(s):  
Aline Figueiredo Cardoso ◽  
Fernanda Sarmento de Oliveira Louzano ◽  
Cássia Cristina Chaves Pinheiro ◽  
Paulo Manoel Pontes Lins ◽  
Gisele Barata Da Silva
Keyword(s):  
Linear Regression ◽  
Disease Severity ◽  
Cocos Nucifera ◽  
Linear Regression Analysis ◽  
Management Program ◽  
Coefficient Of Determination ◽  
Angular Coefficient ◽  
Linear Coefficient ◽  
Cocos Nucifera L ◽  
Diagrammatic Scale

The absence of a methodology to quantify Pestalotiopsis sp. in coconut plants (Cocos nucifera L.) justified the elaboration and validation of a diagrammatic scale containing seven values (2%, 5%, 10%, 15%, 20%, 40% and 60%) of disease severity, in a sampling under natural conditions of occurrence in the field. To elaborate the diagrammatic scale, 100 leaves of Cocos nucifera L. were obtained from an experimental field of Fazenda Reunidas Sococo in Santa Isabel, Pará. The images of these leaves were obtained with the aid of a digital camera. Subsequently, with the aid of Assess 2.0 APS software, the actual disease severity values were obtained in percentage terms. The validation of the proposed diagrammatic scale was performed by ten inexperienced evaluators who evaluated the projected images without the aid of the suggested scale, and later, with the aid of the scale. From the data obtained from the evaluators with and without scale, linear regression analysis was performed, relating the real severity and the estimated severity. The accuracy of the estimates was evaluated by the regression determination coefficient (R2) and the variance of the absolute errors. The accuracy of each evaluator was determined by the t-test applied to the angular coefficient of line (b) and the linear coefficient of line (a), both obtained by linear regression. Through the coefficient of determination values, It is possible to verify that the use of the scale gave greater accuracy to 100% of the evaluators with an average of 0.94 and 94% repeatability. The use of the diagrammatic spot scale for Pestalotiopsis sp. it enables future work with accuracy and precision, as well as optimizing disease control practices within a coconut tree nursery management program.

scholarly journals Study on the Effect of Surface Roughness on the Spectral Unmixing of Mixed Pixels

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Haonan Zhang ◽  
Xingping Wen ◽  
Junlong Xu ◽  
Dayou Luo ◽  
Ping He
Keyword(s):  
Surface Roughness ◽  
Spectral Decomposition ◽  
Spectral Characteristics ◽  
Mixing Model ◽  
Spectral Unmixing ◽  
Mirror Reflection ◽  
Reflectance Measurement ◽  
Mixed Pixel ◽  
Mixed Pixels ◽  
Spectral Mixing

In the spectrum measurement experiment, the roughness of the object surface is an essential factor that cannot be ignored. In this experiment, a group of mixed pixel samples with different mixing ratios were designed, and these samples were printed on four kinds of papers with different roughness. The spectral characteristics of mixed pixels with different roughness are quantitatively analyzed by using the measured spectral data. The linear spectral mixture model is used for spectral decomposition, and the effect of roughness on the unmixing precision of mixed pixels was studied. The surface roughness will affect the reflectivity of the mixed pixel. Specifically, the higher the roughness is, the higher the reflectivity of the sample is. This phenomenon is more noticeable when the proportion of white endmember (PWE) is large, and as the white area ratio decreases, the reflectance difference gradually decreases. When the surface roughness of the sample is less than 3.339 μm, the spectral decomposition is performed using a linear spectral mixing model in the visible light band. The average error of the unmixing is less than 0.53%, which is lower than the conventional standard spectral measurement error. In other words, when the surface roughness of the sample is controlled within a specific range, the effect of roughness on the unmixing accuracy of the mixed pixels is small, and this effect can be almost ignored. Multiple scattering within the pixels is the key to model selection and unmixing accuracy, when using the ASD FieldSpec3 spectrometer to perform spectral reflectance measurement and linear spectral unmixing experiments. If the surface roughness of the sample to be measured is less than the maximum wavelength of the spectrometer, the experimental results believe that the photon energy is mainly mirror reflection on the surface of the object and diffuse reflection. At this time, it is still a better choice to use a linear spectral mixing model to decompose the mixed pixels.

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