Remote sensing technologies could make huge improvements in the sustainable management of palm oil plantations. The new monitoring methods may be able to transform the oil palm industry into a more environmentally-friendly practice while optimizing the production of palm oil.
Unfortunately, progress on the development of these geoinformation technologies is moving slowly. Environmental experts are expressing the need for a sense of urgency in the creation and implementation of remote oil palm plantation monitoring methods.
The oil palm industry is responsible for the destruction of large areas of tropical forest and ecosystems with high conservation value. The global demand for palm oil has also resulted in habitat degradation, climate change, and indigenous land rights abuse.
At the same time, global demand for oil palm production is rapidly increasing as palm oil has grown to become the most consumed oil in the world. Oil palms produce vegetable oil more cheaply than any other oil crop. More plantations are being developed, while existing plantations are being expanded.
Palm oil plantations are currently monitored using time-consuming, expensive land assessments. The high-resolution satellite imagery used for remote sensing will provide the same information more quickly and accurately.
The computerized geographic information will also meet the monitoring standards of palm oil industry certification agencies such as the Roundtable on Sustainable Palm Oil, or RSPO.
Use of remote sensing technologies will tackle the challenge of increasing oil palm production while reducing the negative impact on tropical forests and climate change. Illegal deforestation could be detected and disease and pest control problems could be identified sooner.
The authors of a report published in the journal Geo-spatial Information Science say the potential benefits are extensive. They say use of remote sensing imagery will improve the accuracy of yield prediction, and identify suitable land for plantation expansion while protecting forests with high carbon stocks or high conservation value.
Source: Geo-spatial Information Science