Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Matongera, Trylee Nyasha; Mutanga, Onisimo; Dube, Timothy; Lottering, Romano

doi:10.1080/10106049.2016.1240719

Cited by 22 publications

(23 citation statements)

References 70 publications

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“…texture, canopy, leaf structure and orientation) and biochemical (e.g. chlorophyll and water content) properties of the plant ( (Matongera et al 2016a;Zhao et al 2009). This can best be demonstrated in Fig.…”

Section: Spectral Properties Of Aips In Remote Sensingmentioning

confidence: 82%

“…Also, the literature shows that invaded landscapes are more likely to remain dominated by one individual species for a very long time (Huang and Asner, 2009). Although literature highlights some positive ecological and economic impact of AIPs, such as the provision of habitat to local fauna (Matongera et al 2016a) and provision of fuelwood and carbon assimilation (Shackleton et al 2007), the recorded ecological destruction as a result of the alien invasion is farreaching. For instance, AIPs out-compete the indigenous plants for available natural resources (i.e.…”

Section: The Ecology and Spatial Distribution Of Aipsmentioning

confidence: 99%

“…Peerbhay et al 2016c;Evangelista et al 2009) noted that such approaches are not sustainable due to excessive capital, time and labor required, especially for large-scale applications. Furthermore, the use of traditional approaches like surveys are hampered by accessibility to the regions of interest, particularly in remote areas (Matongera et al 2016a(Matongera et al , 2016bCuratola Fernández et al 2013). Satellite remote sensing, on the other hand, has increasingly gained popularity as a plausible alternative in AIPs mapping (Dorigo et al 2012;Aitkenhead and Aalders, 2011;Gómez-Casero et al 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies (e.g. Matongera et al 2016a;Peerbhay et al 2016c;Niphadkar and Nagendra, 2016;Rocchini et al 2015;Bradley, 2014;Boyd and Foody, 2011;Huang and Asner, 2009;Lass et al 2005;Joshi et al 2004) have explored remote sensing approaches to optimize the detection and mapping of AIPs. For instance, Huang and Asner (2009) provided an overview of spatial, spectral and temporal sensor resolutions for the detection of AIPs based on structural and functional traits at various canopy levels.…”

Section: Introductionmentioning

confidence: 99%

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Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Royimani

Mutanga

Odindi

et al. 2019

Physics and Chemistry of the Earth, Parts A/B/C

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Detecting and mapping the occurrence, spatial distribution and abundance of Alien Invasive Plants (AIPs) have recently gained substantial attention, globally. This work, therefore, provides an overview of advancements in satellite remote sensing for mapping and monitoring of AIPs and associated challenges and opportunities. Satellite remote sensing techniques have been successful in detecting and mapping the spatial and temporal distribution of AIPs in rangeland ecosystems. Also, the launch of high spatial resolution and hyperspectral remote sensing sensors marked a major breakthrough to precise characterization of earth surface feature as well as optimal resource monitoring. Although essential, the improvements in spatial and spectral properties of remote sensing sensors presented a number of challenges including the excessive acquisition and limited temporal resolution. Therefore, the use of high spatial and hyperspectral datasets is not a plausible alternative to continued and operational scale earth observation, especially in financially constrained countries. On the other hand, literature shows that image classification algorithms have been instrumental in compensating the poor spatial and spectral resolution of remote sensing sensors. Furthermore, the emergence of robust and advanced nonparametric image classification algorithms have been a major development in image classification algorithms. Therefore, to address the inevitable challenges arising with satellite sensor development technology it is necessary to explore the use of robust and advanced non-parametric image classifiers with data provided by the new generation of multispectral sensors with improved spatial and spectral resolutions. This will promote longterm and large scale mapping of AIPs, especially in financially constrained countries.

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Section: Spectral Properties Of Aips In Remote Sensingmentioning

confidence: 82%

Section: The Ecology and Spatial Distribution Of Aipsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Royimani

Mutanga

Odindi

et al. 2019

Physics and Chemistry of the Earth, Parts A/B/C

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“…For example, Thamaga and Dube (2018a, b) have provided an overview of remote sensing on water hyacinth. Similarly, Matongera et al (2016) have reviewed the advancement and challenges of remote sensing in mapping and sensing Bracken fern invasive species. Bradley et al 2014 also provides a detailed description of the spectral, textural, and phenological approach of remote detection of invasive plants.…”

Section: Introductionmentioning

confidence: 99%

Integration of remote sensing and bioclimatic data for prediction of invasive species distribution in data-poor regions: a review on challenges and opportunities

2020

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Prediction and modeling using integrated datasets and expertise from various disciplines greatly improve the management of invasive species. So far several attempts have been made to predict, handle, and mitigate invasive alien species impacts using specific efforts from various disciplines. Yet, the most persuasive approach is to better control its invasion and subsequent expansion by making use of cross-disciplinary knowledge and principles. However, the information in this regard is limited and experts from several disciplines have sometimes difficulties understanding well each other. In this respect, the focus of this review was to overview challenges and opportunities in integrating bioclimatic, remote sensing variables, and species distribution models (SDM) for predicting invasive species in data-poor regions. Google Scholar search engine was used to collect relevant papers, published between 2005–2020 (15 years), using keywords such as SDM, remote sensing of invasive species, and contribution of remote sensing in SDM, bioclimatic variables, invasive species distribution in data-poor regions, and invasive species distribution in Ethiopia. Information on the sole contribution of remote sensing and bioclimatic datasets for SDM, major challenges, and opportunities for integration of both datasets are systematically collected, analyzed, and discussed in table and figure formats. Several major challenges such as quality of remotely sensed data and its poor interpretation, inappropriate methods, poor selection of variables, and models were identified. Besides, the availability of Earth Observation (EO) data with high spatial and temporal resolution and their capacity to cover large and inaccessible areas at a reasonable cost, as well as progress in remote sensing data integration techniques and analysis are among the opportunities. Also, the impacts of important sensor characteristics such as spatial and temporal resolution are crucial for future research prospects. Similarly important are studies analyzing the impacts of interannual variability of vegetation and land use patterns on invasive SDM. Urgently needed are clearly defined working principles for the selection of variables and the most appropriate SDM.

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Quantitative remote sensing of forest ecosystem services in sub-Saharan Africa’s urban landscapes: a review

Mngadi

Odindi

Mutanga

et al. 2022

Environ Monit Assess

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Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Cited by 22 publications

References 70 publications

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Integration of remote sensing and bioclimatic data for prediction of invasive species distribution in data-poor regions: a review on challenges and opportunities

Quantitative remote sensing of forest ecosystem services in sub-Saharan Africa’s urban landscapes: a review

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