Exercise 1: Experience capitalization

Sharing your experience is easy. Just comment on this pages and your contribution will appear like my comment here! Looking forward to reading about your experiences and if you have any questions PM me or write to [email protected] 

Good luck, Alice on behalf of e-Agriculture 

Hello Alice. My name is Victor Morales, I am currently in charge of the Tropical Forestry course at EARTH University. My experience is based on the use of remote sensors in unmanned aerial vehicles (spatial data collection, processing and analysis for decision making). We teach our students that there are "inexpensive" ways to do precision farming: we are adapting inexpensive remote sensors (https://www.mapir.camera/) on unmanned aerial vehicles (https: //store.dji. com / product / phantom-4). The platforms that link the remote sensors to the UAVs are designed and printed in 3D. For all, we make use of open programs or free access.
Part of our objectives is to teach our students to do digital photogrammetry, 3D mapping, generation of vegetation indexes, among others.

Greetings.

V.h.M.p.

1. Describe for what purpose the drones were used and in which context? Drones were used to record pictures, videos from the air. In agriculture, they were used to record and check the diffirent on farms. 
2. What challenges were faced using the drones? Law: you have to been licensed from autority to use drones in Vietnam. Cost: Drones are expensive compare with farmers' income in Vietnam. Technical: You need a database to analys what you record.
3. What lessons can be drawn from this experience? Develop a pilot drone and collect data in TraceVerified. 
4. Additional resources (list links to additional information on the experience if available). None, we start learning from TraceVerified.

Describe for what purpose the drones were used and in which context?

Geolocalisation and precision targeting.

What challenges were faced using the drones?

Privacy concerns, legal and property rights.

What lessons can be drawn from this experience?

A better legal and institutional framework needed to fully operate a safe drone operation and use locally and beyond.

Additional resources (list links to additional information on the experience if available).

Not of a greater diversity than this platform... :)

Hello everyone. I am Aditya from India working as Assistant Professor-cum-Junior Scientist at Bihar Agricultural University, Sabour. We are using drones in the agricultural context. It is used to monitor pest and disease incidence on the ground in the agricultural field. The challenges faced while using the drones was that fog and mist resulted in low resolution of the images. This was overcomed by using the drones particularly in the evening. Looking forward to learn the intricacies of drone training from this training programme.

Thank you for sharing your experiences with us! Do not hesitate to put in a bit more detailed information - I am sure other participants are interested to learn more about your experiences!

I'm Edson Natha, from Mozambique I work for ministry of land environment and rural development. I have no experience or direct participation in the use of drones in agricultural activities but I have already had experience in other activities such as tourism to capture aerial images.
However I believe that something should be done in terms of legislation to use these devices in Mozambique in a legal way.
I recall a situation in which a team of Dutch researchers who were going to do a mapping was arrested by the authorities on the grounds that they were flying over a drone for unjustified purposes

I am Abdelaziz Lawani and I work on the use of drones for biodiversity conservation and agriculture. 

The experience I am sharing here is related to a test we conducted a few weeks ago: "Testing the use of UAVs for protected areas management in wetlands: Case of the Mono Delta’s Transboundary Biosphere Reserve (TBR Mono)". I will present in the following lines a summary of the context of this test, the methodology used and some results. 

Context: 

Situated between Benin and Togo on the Mono river delta, which itself forms the southern border between the two countries, the TBR Mono contains natural habitats that are the refuge of many animal species, including the Red-bellied monkey (Cercopithecus erythrogaster).

The TBR Mono is made up of many sites, some of which are officially protected by the state and others that benefit from the conservation efforts of non-governmental organizations and local populations. Among the sites, three are part of the Ramsar Convention on Wetland Conservation. 

However, the sites are threatened by growing anthropogenic illegal practices such as poaching, logging and/or agricultural intrusions. We conducted a test to evaluate how UAVs can contribute to monitoring the areas under conservation. 

Methodology

We used the DJI Pro P3 and P4 for the test. The RBT is composed of many sites. On each site, we collect samples using Pix4DCapture to create flight plans and for capturing images. We flew the drones at different altitudes, used semi-automated and manual flight modes,  and analyze the data using Visualsfm, Meshlabs, QGIS, and Pix4Dmapper. 

Some Results 

From the images collected by the drones, we generated orthomosaic and digital surface and terrain models. 

1- The results of overlaying the orthomosaic images on initial zoning of the sites in Google Earth confirms that the data collected by the drones can be used for mapping. 

2- At higher resolutions, details on the images obtained with the drones were distinguishable while not on the satellite images of Google Earth 

3- On the images collected with the UAVs, we can distinguish various objects such as a five-meter-long agricultural workers' dwelling, tree branches about two meters long, and even corn plants separated by about 50 centimeters.

4- We tested the extent to which drones can be useful in calculating the area of conservation sites. Our results confirm that drones are effective since areas measured with the drones correspond to official measures.

5- We conducted a supervised classification using machine learning to evaluate the area of dense vegetation and agricultural fields. 

More results will be presented later

Challenges

We were working in wetlands: swamp forests and rivers. The use of drones in these settings is quite challenging since we needed "not-wet" areas to take off and land the drones. We then choose multirotors (the DJIs), and open areas to take off and land. 

Additional resources

To learn more, visit the link below. Scroll down to the bottom of the page to read about this experience. 

Link: https://sites.google.com/view/abdelawani/drone-project?authuser=0