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1. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

Author: Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, Nguyen, Ngoc Bich, Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, and Nguyen, Ngoc Bich
Abstract: This research was carried out to test the potential of combining unmanned aerial vehicle (UAV) and remote sensing (RS) to support precision mapping of irrigation systems for paddy land. The study area is an urban/agricultural area of Central Vietnam. The Sentinel-2A imagery acquired on 30 June 2018 was interpreted according an object-based classification method aiming to map paddy land and irrigation systems for the Hoa Vang district; the total accuracy was 91.33% with a Kappa coefficient of 0.87. However, with the spatial resolution from the Sentinel-2A images (20 meters x 20 meters) it was difficult to classify paddy land and water from other objects within small and scattered parcel areas. This research was designed on five experimental flying zones, collecting 2,085 images by the UAV. With the very high spatial resolution data of the UAV, it was possible to clearly identify the boundaries of paddy land parcels, water sources such as rivers and lakes, and other objects such as canals and concrete irrigation systems. This classification derived from the orthogonal images from the five experimental zones using an object-based classification method, correcting the interpretation results of the Sentinel 2A images. Outcomes indicate that, the combination of UAV and RS can be applied to support precision mapping of irrigation systems for paddy land in urban agricultural areas., Nghiên cứu này được thực hiện nhằm thử nghiệm khả năng kết hợp giữa UAV với viễn thám trong hỗ trợ độ chính xác của bản đồ hệ thống nước tưới cho đất trồng lúa ở vùng nông nghiệp đô thị tại Miền trung Việt Nam. Ảnh viễn thám Sentinel- 2A thu nhận vào 30/6/2018 đã được giải đoán bằng phương pháp định hướng đối hướng để thành lập bản đồ hệ thống nguồn nước tưới cho huyện Hòa Vang vào năm 2018, với kết quả độ chính xác tổng số là 91,33% và hệ số kappa là 0,87. Mặc dù với kết quả giải đoán có độ chính xác cao nhưng với độ phân giải không gian của ảnh Sentinel-2A là 20m x 20m rất khó để phân loại được các vùng đất lúa có diện tích nhỏ và phân bố phân tán. Nghiên cứu này đã thiết kế 5 khu vực bay thử nghiệm với 2.085 ảnh để thu thập dữ liệu từ UAV. Có thể thấy rằng dữ liệu ảnh từ UAV với độ phân giải siêu cao có thể nhận diện và phân biệt được một cách rõ ràng không chỉ ranh giới của các thửa đất lúa, hệ thống nguồn nước như sông hồ, mà còn cả những đối tượng kênh mương thủy lợi nhỏ. Kết quả giải đoán các ảnh bay chụp bằng UAV sử dụng dụng phương pháp định hướng đối tượng, nghiên cứu này đã hiệu chỉnh được kết quả giải đoán ảnh Sentinel 2A. Kết quả cho thấy việc kết hợp dữ liệu viễn thám với UAV là hoàn toàn có khả năng sử dụng để hỗ trợ độ chính xác thành lập bản đồ hệ thống nguồn nước cho đất trồng lúa ở vùng nông nghiệp đô thị. more...
Published: 2020

2. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

Author: Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, Nguyen, Ngoc Bich, Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, and Nguyen, Ngoc Bich
Abstract: This research was carried out to test the potential of combining unmanned aerial vehicle (UAV) and remote sensing (RS) to support precision mapping of irrigation systems for paddy land. The study area is an urban/agricultural area of Central Vietnam. The Sentinel-2A imagery acquired on 30 June 2018 was interpreted according an object-based classification method aiming to map paddy land and irrigation systems for the Hoa Vang district; the total accuracy was 91.33% with a Kappa coefficient of 0.87. However, with the spatial resolution from the Sentinel-2A images (20 meters x 20 meters) it was difficult to classify paddy land and water from other objects within small and scattered parcel areas. This research was designed on five experimental flying zones, collecting 2,085 images by the UAV. With the very high spatial resolution data of the UAV, it was possible to clearly identify the boundaries of paddy land parcels, water sources such as rivers and lakes, and other objects such as canals and concrete irrigation systems. This classification derived from the orthogonal images from the five experimental zones using an object-based classification method, correcting the interpretation results of the Sentinel 2A images. Outcomes indicate that, the combination of UAV and RS can be applied to support precision mapping of irrigation systems for paddy land in urban agricultural areas., Nghiên cứu này được thực hiện nhằm thử nghiệm khả năng kết hợp giữa UAV với viễn thám trong hỗ trợ độ chính xác của bản đồ hệ thống nước tưới cho đất trồng lúa ở vùng nông nghiệp đô thị tại Miền trung Việt Nam. Ảnh viễn thám Sentinel- 2A thu nhận vào 30/6/2018 đã được giải đoán bằng phương pháp định hướng đối hướng để thành lập bản đồ hệ thống nguồn nước tưới cho huyện Hòa Vang vào năm 2018, với kết quả độ chính xác tổng số là 91,33% và hệ số kappa là 0,87. Mặc dù với kết quả giải đoán có độ chính xác cao nhưng với độ phân giải không gian của ảnh Sentinel-2A là 20m x 20m rất khó để phân loại được các vùng đất lúa có diện tích nhỏ và phân bố phân tán. Nghiên cứu này đã thiết kế 5 khu vực bay thử nghiệm với 2.085 ảnh để thu thập dữ liệu từ UAV. Có thể thấy rằng dữ liệu ảnh từ UAV với độ phân giải siêu cao có thể nhận diện và phân biệt được một cách rõ ràng không chỉ ranh giới của các thửa đất lúa, hệ thống nguồn nước như sông hồ, mà còn cả những đối tượng kênh mương thủy lợi nhỏ. Kết quả giải đoán các ảnh bay chụp bằng UAV sử dụng dụng phương pháp định hướng đối tượng, nghiên cứu này đã hiệu chỉnh được kết quả giải đoán ảnh Sentinel 2A. Kết quả cho thấy việc kết hợp dữ liệu viễn thám với UAV là hoàn toàn có khả năng sử dụng để hỗ trợ độ chính xác thành lập bản đồ hệ thống nguồn nước cho đất trồng lúa ở vùng nông nghiệp đô thị. more...
Published: 2020

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3. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

Author: Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, Nguyen, Ngoc Bich, Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, and Nguyen, Ngoc Bich
Abstract: This research was carried out to test the potential of combining unmanned aerial vehicle (UAV) and remote sensing (RS) to support precision mapping of irrigation systems for paddy land. The study area is an urban/agricultural area of Central Vietnam. The Sentinel-2A imagery acquired on 30 June 2018 was interpreted according an object-based classification method aiming to map paddy land and irrigation systems for the Hoa Vang district; the total accuracy was 91.33% with a Kappa coefficient of 0.87. However, with the spatial resolution from the Sentinel-2A images (20 meters x 20 meters) it was difficult to classify paddy land and water from other objects within small and scattered parcel areas. This research was designed on five experimental flying zones, collecting 2,085 images by the UAV. With the very high spatial resolution data of the UAV, it was possible to clearly identify the boundaries of paddy land parcels, water sources such as rivers and lakes, and other objects such as canals and concrete irrigation systems. This classification derived from the orthogonal images from the five experimental zones using an object-based classification method, correcting the interpretation results of the Sentinel 2A images. Outcomes indicate that, the combination of UAV and RS can be applied to support precision mapping of irrigation systems for paddy land in urban agricultural areas., Nghiên cứu này được thực hiện nhằm thử nghiệm khả năng kết hợp giữa UAV với viễn thám trong hỗ trợ độ chính xác của bản đồ hệ thống nước tưới cho đất trồng lúa ở vùng nông nghiệp đô thị tại Miền trung Việt Nam. Ảnh viễn thám Sentinel- 2A thu nhận vào 30/6/2018 đã được giải đoán bằng phương pháp định hướng đối hướng để thành lập bản đồ hệ thống nguồn nước tưới cho huyện Hòa Vang vào năm 2018, với kết quả độ chính xác tổng số là 91,33% và hệ số kappa là 0,87. Mặc dù với kết quả giải đoán có độ chính xác cao nhưng với độ phân giải không gian của ảnh Sentinel-2A là 20m x 20m rất khó để phân loại được các vùng đất lúa có diện tích nhỏ và phân bố phân tán. Nghiên cứu này đã thiết kế 5 khu vực bay thử nghiệm với 2.085 ảnh để thu thập dữ liệu từ UAV. Có thể thấy rằng dữ liệu ảnh từ UAV với độ phân giải siêu cao có thể nhận diện và phân biệt được một cách rõ ràng không chỉ ranh giới của các thửa đất lúa, hệ thống nguồn nước như sông hồ, mà còn cả những đối tượng kênh mương thủy lợi nhỏ. Kết quả giải đoán các ảnh bay chụp bằng UAV sử dụng dụng phương pháp định hướng đối tượng, nghiên cứu này đã hiệu chỉnh được kết quả giải đoán ảnh Sentinel 2A. Kết quả cho thấy việc kết hợp dữ liệu viễn thám với UAV là hoàn toàn có khả năng sử dụng để hỗ trợ độ chính xác thành lập bản đồ hệ thống nguồn nước cho đất trồng lúa ở vùng nông nghiệp đô thị. more...
Published: 2020

4. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

Author: Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, Nguyen, Ngoc Bich, Tran, Phuong Thi, Truong, Phuong Do Minh, Ho, Hoang Viet, Nguyen, Hai Thi, and Nguyen, Ngoc Bich
Abstract: This research was carried out to test the potential of combining unmanned aerial vehicle (UAV) and remote sensing (RS) to support precision mapping of irrigation systems for paddy land. The study area is an urban/agricultural area of Central Vietnam. The Sentinel-2A imagery acquired on 30 June 2018 was interpreted according an object-based classification method aiming to map paddy land and irrigation systems for the Hoa Vang district; the total accuracy was 91.33% with a Kappa coefficient of 0.87. However, with the spatial resolution from the Sentinel-2A images (20 meters x 20 meters) it was difficult to classify paddy land and water from other objects within small and scattered parcel areas. This research was designed on five experimental flying zones, collecting 2,085 images by the UAV. With the very high spatial resolution data of the UAV, it was possible to clearly identify the boundaries of paddy land parcels, water sources such as rivers and lakes, and other objects such as canals and concrete irrigation systems. This classification derived from the orthogonal images from the five experimental zones using an object-based classification method, correcting the interpretation results of the Sentinel 2A images. Outcomes indicate that, the combination of UAV and RS can be applied to support precision mapping of irrigation systems for paddy land in urban agricultural areas., Nghiên cứu này được thực hiện nhằm thử nghiệm khả năng kết hợp giữa UAV với viễn thám trong hỗ trợ độ chính xác của bản đồ hệ thống nước tưới cho đất trồng lúa ở vùng nông nghiệp đô thị tại Miền trung Việt Nam. Ảnh viễn thám Sentinel- 2A thu nhận vào 30/6/2018 đã được giải đoán bằng phương pháp định hướng đối hướng để thành lập bản đồ hệ thống nguồn nước tưới cho huyện Hòa Vang vào năm 2018, với kết quả độ chính xác tổng số là 91,33% và hệ số kappa là 0,87. Mặc dù với kết quả giải đoán có độ chính xác cao nhưng với độ phân giải không gian của ảnh Sentinel-2A là 20m x 20m rất khó để phân loại được các vùng đất lúa có diện tích nhỏ và phân bố phân tán. Nghiên cứu này đã thiết kế 5 khu vực bay thử nghiệm với 2.085 ảnh để thu thập dữ liệu từ UAV. Có thể thấy rằng dữ liệu ảnh từ UAV với độ phân giải siêu cao có thể nhận diện và phân biệt được một cách rõ ràng không chỉ ranh giới của các thửa đất lúa, hệ thống nguồn nước như sông hồ, mà còn cả những đối tượng kênh mương thủy lợi nhỏ. Kết quả giải đoán các ảnh bay chụp bằng UAV sử dụng dụng phương pháp định hướng đối tượng, nghiên cứu này đã hiệu chỉnh được kết quả giải đoán ảnh Sentinel 2A. Kết quả cho thấy việc kết hợp dữ liệu viễn thám với UAV là hoàn toàn có khả năng sử dụng để hỗ trợ độ chính xác thành lập bản đồ hệ thống nguồn nước cho đất trồng lúa ở vùng nông nghiệp đô thị. more...
Published: 2020

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4 results on '"Ho, Hoang Viet"'

1. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

2. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

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3. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

4. The potential of combining UAV and remote sensing in supporting precision mapping of irrigation systems for paddy land in urban agricultural areas: study case in the Hoa Vang district, Danang city, Central Vietnam

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