Conference Agenda

Overview and details of the sessions for this conference. Please select a date and a session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
S.6.1: SUSTAINABLE AGRICULTURE
Time:
Tuesday, 25/June/2024:
09:00 - 10:30

Session Chair: Dr. Qinghan Dong
Session Chair: Prof. Jinlong Fan
Room: Sala 1


57160 - Mon. Water Availability & Cropping

58944 - Multi-source EO Data 4 Crop Growth


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Presentations
09:00 - 09:45
Oral
ID: 247 / S.6.1: 1
Dragon 5 Oral Presentation
Sustainable Agriculture and Water Resources: 57160 - Monitoring Water Productivity in Crop Production Areas From Food Security Perspectives

Final report Of Monitoring Water Productivity In Crop Production Areas From Food Security Perspectives (ID 57160)

Qinghan Dong1, Liang Zhu3, Lachezar Hristov Filchev2, Ilina Kameniva2, Milen Chanev2, Petar Dimitrov2, Georgi Jelev2, Bingfang Wu3

1Flemish institute for technological research (VITO), Belgium; 2Space Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), Bulgaria; 3Aerospace Information Research Institute, Chinese Academy of Sciences, China

The "Final Report of Monitoring Water Productivity in Crop Production Areas from Food Security Perspectives" provides a comprehensive analysis of the efficient use of water resources in agriculture. The study focuses on optimizing water usage to enhance crop yields, ensuring sustainable food production, and addressing the challenges posed by water scarcity. Through advanced monitoring techniques and data analysis, the project identifies key factors influencing water productivity and proposes actionable strategies to improve it. This report underscores the critical link between water management and food security, offering valuable insights for policymakers, farmers, and stakeholders in the agricultural sector.

247-Dong-Qinghan_Cn_version.pdf
247-Dong-Qinghan_PDF.pdf


09:45 - 10:30
Oral
ID: 142 / S.6.1: 2
Dragon 5 Oral Presentation
Sustainable Agriculture and Water Resources: 58944 - Retrieving the Crop Growth information From Multiple Source Satellite Data to Support Sustainable Agriculture

Retrieving the Cropping Practices Information with Time Series of Multiple Source Satellite Data in Support of Sustainable Agricultural Management

Jinlong Fan1, Pierre Defourny2

1National Satellite Meteorological Center, China Meteorological Administration, China, People's Republic of; 2Universite Catholique de Louvain, Belgium

Abstract: The sentinel satellite series in Europe and the GF satellite series in China are providing the data options for agricultural monitoring as well as enhancing the capability of agricultural monitoring in general. With the time series of multiple source satellite data, it may increase the frequences of validly monitoring the cropping management practices along plough, sow, management and harvest during the whole crop growth cycle and thus it may provide timely and more information in support of the decision making for agricultural production management and sustainable development. Under the support of the Dragon program, two types of study areas were selected in this project. The first one is with big fields and good at the development of modern agriculture that is comparable with the European agricultural farms. Another one is the typic northern Chine fields with the conventional agricultural development that is challenging for the agricultural monitoring with remote sensing data. The crop types in the study areas are winter wheat, corn, soybean, rice, and vegetable, representing the irrigation agriculture and rain fed agriculture in northern China. This project has developed a suite of technology of retrieving the cropping practices on the satellite images and applied for the identification of rice field preparation readiness in spring, dryland and paddy field crop mapping in summer, harvest and plough progress in fall in the northeast China plain. Since 2021, a farm with a little bit less one million hectare crop land has been timely monitored with satellite images and the retrieved information has been used for the farm management decision making. At the same time, another study was carried out in the Jinzhong basin of Shanxi province in north China that is a national high tech agricultural development zone. The straw mulching in fall and the winter irrigation were identified on the satellite imges with adapted abovementioned method. With the heavy involvement of young scientists from Europe and China in this project, the satellite data finely processing, information retrieval algorithm and remote sense classification methods have been exchanged between European team and Chinese team. The finding from this project is expected to bring a step forward to support agricultural monitoring at fine scale and consolidate the theory framework of agricultural monitoring as well as enlarge the areas of remote sensing technology applications.

Keywords: Cropping Practices; Agricultural Monitoring; GF; Sentinel; Dragon Programme

142-Fan-Jinlong_Cn_version.pdf


 
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