Multispectral Remote Sensing of Wetlands in Semi-Arid and Arid Areas: A Review on Applications, Challenges and Possible Future Research Directions

Abstract

Wetlands are ranked as very diverse ecosystems, covering about 4–6% of the global land surface. They occupy the transition zones between aquatic and terrestrial environments, and share characteristics of both zones. Wetlands play critical roles in the hydrological cycle, sustaining livelihoods and aquatic life, and biodiversity. Poor management of wetlands results in the loss of critical ecosystems goods and services. Globally, wetlands are degrading at a fast rate due to global environmental change and anthropogenic activities. This requires holistic monitoring, assessment, and management of wetlands to prevent further degradation and losses. Remote-sensing data offer an opportunity to assess changes in the status of wetlands including their spatial coverage. So far, a number of studies have been conducted using remotely sensed data to assess and monitor wetland status in semi-arid and arid regions. A literature search shows a significant increase in the number of papers published during the 2000–2020 period, with most of these studies being in semi-arid regions in Australia and China, and few in the sub-Saharan Africa. This paper reviews progress made in the use of remote sensing in detecting and monitoring of the semi-arid and arid wetlands, and focuses particularly on new insights in detection and monitoring of wetlands using freely available multispectral sensors. The paper firstly describes important characteristics of wetlands in semi-arid and arid regions that require monitoring in order to improve their management. Secondly, the use of freely available multispectral imagery for compiling wetland inventories is reviewed. Thirdly, the challenges of using freely available multispectral imagery in mapping and monitoring wetlands dynamics like inundation, vegetation cover and extent, are examined. Lastly, algorithms for image classification as well as challenges associated with their uses and possible future research are summarised. However, there are concerns regarding whether the spatial and temporal resolutions of some of the remote-sensing data enable accurate monitoring of wetlands of varying sizes. Furthermore, it was noted that there were challenges associated with the both spatial and spectral resolutions of data used when mapping and monitoring wetlands. However, advancements in remote-sensing and data analytics provides new opportunities for further research on wetland monitoring and assessment across various scales.

Leveraging Google Earth Engine platform to characterize and map small seasonal wetlands in the semi-arid environments of South Africa

“…Wetlands play a critical role in the hydrological cycle and sustaining livelihoods and aquatic life and biodiversity. They occupy transition zones between aquatic and terrestrial environments and share the characteristics of both zones (Gxokwe et al, 2020). Wetlands cover about 4-6% of the global land surface and are ranked amongst the very diverse ecosystems on earth (Mahdianpari et al, 2019).…”

“…The basis for sustainable management of wetlands is hinged on frequent monitoring of their ecohydrological dynamics to derive consistent and comparable information, which is lacking in most semi-arid regions, especially in sub-Saharan Africa (Mahdianpari et al, 2019). The availability of earth observation data offers an opportunity to map and monitor wetlands in a spatially explicit manner in different climatic regions, lacking monitoring systems (Gxokwe et al, 2020). The challenge however is that these data come in a range of spatial, spectral and temporal resolutions which presents difficulties mapping semiarid wetlands using coarse to medium resolution data such as Moderate Resolution Imaging Spectroradiometer (MODIS).…”

“…This results in difficulties when separating these systems from the surrounding landscapes using the coarse to medium spatial resolution data (Mahdianpari et al, 2020). High resolution data such as Wordview-2 and Satellite Pour I'Obeservation de la Terre (SPOT 6-7) are commercial and require complex processing algorithms and are therefore not feasible for monitoring spatial characteristics of semiarid wetland over large areas and overtime (Gxokwe et al, 2020).…”

Multispectral Image Change Detection Based on Single-Band Slow Feature Analysis

“…Remote sensing change detection is a technology that discovers the changes of ground objects by analyzing remote sensing images taken in different periods [1]. This technology has served in many fields including urban change analysis [2], environmental monitoring [3], land management [4], and natural disaster monitoring [5]. Multispectral remote sensing images are the most important data source in the field of optical remote sensing change detection.…”

An Assessment of Small Wetland Ecohydrological Dynamics Using Sentinel-2 MSI Derived Spectral Indices in Semi-Arid Environments of South Africa

“…Their ecological processes are strongly in uenced by hydrological processes, which control surface water and groundwater recharge dynamics, as well as inputs and outputs of dissolved matter and sediments. Despite covering a smaller proportion of land (3% − 8%), unprotected wetlands distributed across sub-Saharan Africa offer several ecohydrological, and socio-economic bene ts (Tiner et al, 2015;Marambanyika & Beckedahl, 2016;Gxokwe et al, 2020;Dzurume et al, 2021). These wetlands, for example, support the livelihoods of neighbouring rural communities and often-poor households with water, particularly in water-scarce areas.…”