Uni-Bayreuth grafik-uni-bayreuth



Impacts on Agricultural Resources in a Complex Terrain


Von 09/2010

Projektleiter: Jonghan Ko
Bewilligung: Chonnam National University

Abstract 2011: Agricultural system simulation models are key tools for assessment of possible impacts of climate change on crop production and environmental quality. In this study, work is proposed to calibrate and validate the CERES-Rice 4.0 model to simulate paddy rice (Oryza sativa) production under elevated CO2 and temperature conditions in a temperature gradient chamber with CO2 fumigation (TGC-CF system). The experiments have been conducted at Chonnam National University, Gwangju, Republic of Korea (ROK) from 2009 to 2010. The model will then be used to simulate the current and future potential for rice production in the Haean Basin of Yanggu County, Gangwon Province, ROK. Simulations will be performed to explore the possible effects of climate change on the crop over 10 year periods centered on 2050 and 2075 with a projected climate change scenario for the region. The illustrated results from the CERES-wheat 4.0 module applied in the RZWQM2 model demonstrate the promise of the model for simulating climate change impacts on grain production. 

Keywords: climate change, crop modeling, TGC, yield


project description in detail from proceedings of 2011 TERRECO Science Conference GAP


Abstract 2013: Crop modeling and remote sensing are different techniques suitable for evaluation of crop growth and yield. Models can provide a continuous description of crop condition during the growing season although they may not provide information as accurately as that provided by remote sensing. Remotely sensed imagery can provide information for almost any spot on the earth’s surface but can provide information valid only at the time of image acquisition. By combining the advantages of remote sensing and simulation modeling, the strengths of one technology may make up for weaknesses in the other. An advantage of this procedure is that it can use infrequent observations to calibrate the model. These observations can be obtained through nondestructive techniques such as remote sensing.

An Unmanned Aerial Vehicle (UAV)-based remote sensing system can monitor terrestrial vegetation information more efficiently and widely than any other ground-based observation systems. In this study, we built up a Crop Information Delivery System (CIDS) using a multi-copter UAV equipped with 8 propellers and an Agricultural Digital Camera-Lite (ADC-L). As a CIDS component, a model that uses remote sensing data was formulated and evaluated using data obtained from the paddy rice field at Chonnam National University, Gwangju, Korea from 2009 to 2011. Reflectance data derived from the UAV system were used for determination of crop growth information by utilizing processed vegetation indices and/or bands information itself. For this purpose, we selectively used Normalized Difference Vegetation Index (NDVI). The reflectance data using the UAV system were successfully determined, and the estimated NDVI generally corresponded to the typical CROPSCAN-derived NDVI. In addition, simulated values of rice growth obtained with the developed model showed reasonable agreement with the corresponding measurements. The proposed model has relatively simple input requirements compared with other process-oriented rice models. It is potentially applicable to regional rice growth monitoring and yield mapping projects.

Key words: crop, information delivery system, modeling, remote sensing, UAV


Poster January 2013


Letzte Änderung 07.03.2013