The Ngorongoro Conservation Area (NCA) has been designated a UNESCO World Heritage Centre because of its natural and cultural values (UNESCO 2010). The NCA is managed as ’multiple land-use area’ protecting not only the wildlife but also the interest of the resident Maasai pastoralists. Over the years, the wildlife populations were not dramatically affected by the human settlements (not-including poaching). However, in the early 1990s the government authorized the cultivation within the NCA, forbidden since 1975 which created an additional pressure in the environment.
In the last 50 years, the NCA has been through noticeable land cover changes. The earliest record of change in the NCA remotes back to the 1960s, when the dieback of the Lerai forest was firstly noticed. Despite the importance of studying the land cover patterns and changes for the ecosystem, very few studies investigated the vegetation status and even fewer produced detailed land cover maps in the NCA. The first detailed survey of the vegetation carried out in the NCA, was completed in 1972, just before the humans moved out of the Ngorongoro Crater itself. This study described different habitats and plants species around the NCA with particular focus in the Crater. Since then only study that attempted to quantify change within the NCA boundaries revealed an increase in woody vegetation, which is most likely due to the lack of fire.
Ngorongoro Crater Area
Land cover maps of the 10 main types
(derived from Landsat data for 1989, 2000 & 2019)
In recent years, remote sensing has been increasingly used to study vegetation around the world. The use of remote sensing methods, is easy, quick, cost free and provides the opportunity to study inaccessible areas as well as obtain historic data. Remote sensing also allows for the creation of high resolution maps of the study area, which are currently lacking for the NCA. The maps available either limited to the Crater, specific to certain plant species and/or, are of low resolution. Currently, the only multi-temporal study for the NCA using the remote sensing approach, and it would be of interest to compare those results with more up to date ones.
Our aim here is to carry out a multi-temporal study to quantify the land cover changes occurring in the NCA using Landsat imagery and producing detailed maps of the land cover/land use. We will determine if there have been significant losses of gains in forest, bushland and cultivation cover from 1989 to 2019. The Landsat data (30m resolution) is particularly useful to study land-cover change after 1982 when the Thematic Mapper TM was launched providing higher spatial resolution and more spectral bands. Landsat images often require pre-processing and be corrected for cloud cover and topography problems, due to climate conditions and terrain of the study areas. In addition to the pre-processing, the Random Forest (RF) classification algorithm, a powerful machine learning classifier that has shown high classification accuracy, will be used. The RF will be implemented using the ‘SuperClass’ function which takes as an input, the training data and the corrected Landsat image. The RF and ‘SuperClass’ have been successfully used to map land-cover in different environments.