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