Remote Sensing and Geographic Information Techniques: Veritable Tools for Land Degradation Assessment

Abbas, Idowu Innocent; Fasona, Mayowa

doi:10.5923/j.ajgis.20120101.01

Cited by 6 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other studies suggest that degradation of the Niger Delta mangroves has occurred since at least the 1980's. Abbas and Fasona [76] and Abbas [49] found a roughly three-fold increase (10.6% to 32.2%) in mangroves and marshland classed as degraded between 1986 and 2008. Omo-Irabor et al [33] found a decrease of 15% in mangrove population between 1987 and 2002 by comparing Landsat imagery between those two years.…”

Section: Niger Delta Nigeriamentioning

confidence: 98%

Evaluation of the Continuous Monitoring of Land Disturbance Algorithm for Large-Scale Mangrove Classification

et al. 2021

View full text Add to dashboard Cite

Mangrove forests are of high biological, economic, and ecological importance globally. Growing within the intertidal zone, they are particularly vulnerable to the effects of climate change in addition to being threatened on local scales by over-exploitation and aquaculture expansion. Long-term monitoring of global mangrove populations is therefore highly important to understanding the impact of these threats. However, data availability from satellites is often limited due to cloud cover. This problem can be mitigated using a season-trend modelling approach such as Continuous Monitoring of Land Disturbance (COLD). COLD operates by using every available observation on a pixel-wise basis, removing the need for whole cloud free images. The approach can be used to better classify land cover by taking into account the underlying seasonal variability, and can also be used to extrapolate between data points to obtain more accurate long term trends. To demonstrate the utility of COLD for global mangrove monitoring, we applied it to five study sites chosen to represent a range of mangrove species, forest types, and quantities of available data. The COLD classifier was trained on the Global Mangrove Watch 2010 dataset and applied to 30 years of Landsat data for each site. By increasing the period between model updates, COLD was successfully applied to all five sites (2253 scenes) in less than four days. The method achieved an overall accuracy of 92% with a User’s accuracy of 77% and a Dice score of 0.84 for the mangrove class. The lowest User’s accuracy was for North Kalimantan (49.9%) due to confusion with mangrove palms. However, the method performed extremely well for the Niger Delta from the 2000s onwards (93.6%) despite the absence of any Landsat 5 data. Observation of trends in mangrove extent over time suggests that the method was able to accurately capture changes in extent caused by the 2014/15 mangrove die-back event in the Gulf of Carpentaria and highlighted a net loss of mangroves in the Matang Forest Reserve over the last two decades, despite ongoing management. COLD is therefore a promising methodology for global, long-term monitoring of mangrove extent and trends.

show abstract

Section: Niger Delta Nigeriamentioning

confidence: 98%

Evaluation of the Continuous Monitoring of Land Disturbance Algorithm for Large-Scale Mangrove Classification

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Land use-land cover change analysis enable planners and policy makers to have adequate knowledge on what should be done to have equitable development that will be sustainable and eco-friendly [1]. Land wh ich is the ult imate resource of the biosphere refers to a specific area of the earth surface with physical entity encompassing its topography and spatial nature [2].…”

Section: Introductionmentioning

confidence: 99%

An Assessment of Land Use/Land Cover Changes in a Section of Niger Delta, Nigeria

Abbas¹

2013

Self Cite

View full text Add to dashboard Cite

Re mote Sensing and GIS offer quick and efficient approach to the classification and mapping of land use/land cover changes over space and time. Info rmation on changes in resource classes, direction, area and pattern of land use-land cover classes form the basis for future planning. Specifically, the land use/land cover types for the years 1986 and 2008 were studied and compared. The data products used in the study are Landsat TM imagery of 1986 and Nigeriasat-1 imagery of 2008. The data sets were put into Arcview GIS environ ment for geo-referencing and on-screen digitization of the needed layers. The land use-land cover layers for 1986 and 2008 were therefo re generated. The magnitude, trend and annual rate of change analysis were generated fro m the land use-land covers for the years-1986 and 2008. The annual rate of change was then used as the basis for the p rojection of the 2050 land use-land cover situation of the study area. The findings show that there was high rate o f land use-land cover change leading to decimat ion of sources of livelihood and resettlement of the people.

show abstract

Land Use/Land Cover Change in Petroleum-Producing Regions of Nigeria

Matemilola

Adedeji

Enoguanbhor

2018

The Political Ecology of Oil and Gas Activities in the Nigerian Aquatic Ecosystem

View full text Add to dashboard Cite

Remote Sensing and Geographic Information Techniques: Veritable Tools for Land Degradation Assessment

Cited by 6 publications

References 4 publications

Evaluation of the Continuous Monitoring of Land Disturbance Algorithm for Large-Scale Mangrove Classification

Evaluation of the Continuous Monitoring of Land Disturbance Algorithm for Large-Scale Mangrove Classification

An Assessment of Land Use/Land Cover Changes in a Section of Niger Delta, Nigeria

Land Use/Land Cover Change in Petroleum-Producing Regions of Nigeria

Contact Info

Product

Resources

About