**6. Conclusions**

The Niger Delta Region (NDR) is an important ecosystem, providing numerous services to the millions of its human inhabitants. Despite its undisputable importance, it is under threat of degradation, mainly due to human pressure, and especially as a direct consequence of the activities related with the significant oil and gas reserves in the region. Understanding the extent of the problem requires an accurate assessment of the land cover dynamics in the region, which can only be achieved through the use of state-of-the-art remote sensing technologies and analytical techniques. Cloud contamination and gaps in the commonly employed Landsat archive makes this a fathomable task.

Here, we were able to accurately assess the land cover dynamics over a period of 25 years using the Google Earth Engine cloud computing platform to estimate spatial-temporal Landsat-based metrics in three epochs. Our results showed that mangroves, the lowland rainforests, and the freshwater forests have demonstrated a net loss, while the built-up areas have almost doubled in the period of study. By performing a land cover change intensity analysis, we were also able to demonstrate how highly intense these changes were. We also tested the ability of L-band SAR data in improving the Random Forests classifications of the main land cover types in the delta and found that these only improve the mapping of the urban and water classes, provided that more than one polarisation is available. Our results provide a valuable quantification of the land cover dynamics in the NDR and the first ever accurate assessment of the spatial extent of the degraded mangroves in the region. Such assessments are imperative for successfully addressing a number of the Sustainable Development Goals and achieving Land Degradation Neutrality by 2030, as envisaged by the United Nations LDN Target Setting Programme.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2072-4292/12/21/3619/s1, Table S1: Mathematical notation for Intensity Analysis [79], Table S2: Confusion matrix of the classification of the Landsat-based metrics centred around the year 1988, Table S3: Confusion matrix of the classification of the Landsat-based metrics centred around the year 2000, Table S4: Confusion matrix of the classification of the Landsat- and JERS-1-based metrics centred around the year 2000, Table S5: Confusion matrix of the classification of the Landsat-based metrics centred around the year 2013, Table S6: Confusion matrix of the classification of the Landsat-and ALOS PALSAR-2-based metrics centred around the year 2013, Table S7: Transition level intensity analysis FROM-class TO-class for 1988–2000 and 2000–2013 (all classes except Mangrove, which appears in Table 4), Table S8: Transition level intensity analysis TO-class FROM-class for 1988–2000 and 2000–2013.

**Author Contributions:** Conceptualization, I.I.N., E.S., S.K., G.C. and S.M.; methodology I.I.N., E.S., S.K. and T.P.H.; software: I.I.N., E.S., S.K. and T.P.H.; writing—original draft preparation: I.I.N., E.S., and S.K.; writing—review and editing: I.I.N., E.S., and T.P.H.; supervision: E.S., G.C. and S.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** Iliya I. Nababa was funded by Petroleum Technology Development Fund (PTDF), Nigeria (grant PTDF/ED/PHD/IIN/789/15).

**Acknowledgments:** The authors are grateful to the USGS for the Landsat data, to JAXA for the ALOS PALSAR-2 and JERS-1 data and to Google Earth Engine for providing access to the data and the processing environment. Oil spill data were obtained from the National Oil Spill Detection and Response Agency (NOSDRA), Nigeria (https://www. nosdra.gov.ng/ and https://oilspillmonitor.ng/). Oil wells were digitised in ArcMap 10.7 [67,68] using map of oil and gas infrastructure obtained from Shell Petroleum Development Company, Nigeria (https://www.shell.com.ng/). Pipeline data were digitised from very resolution basemap imagery in ArcMap 10.7 [67,68] and an oil and gas infrastructure map obtained from Shell Petroleum Development Company, Nigeria https://www.shell.com.ng/.

**Conflicts of Interest:** The authors declare no conflict of interest.
