Monitoring desertification in a Savannah region in Sudan using Landsat images and spectral mixture analysis

Dawelbait, Mona; Morari, Francesco

doi:10.1016/j.jaridenv.2011.12.011

Cited by 112 publications

(65 citation statements)

References 41 publications

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“…Due to the NDVI (Normalized Difference Vegetation Index) and other vegetation indexes being highly affected by seasonal vegetation changes and rainfall variation [14,15], the rangeland degradation results tend to be overestimated in sparse vegetation areas. Here, the LSMA (Linear Spectral Mixture Analysis) method was selected to extract the vegetation coverage and bare-land rate in the study region for its simplicity, effectiveness, and interpretability [14,16].…”

Section: Lsma Methodsmentioning

confidence: 99%

“…For both the vegetation and bare-land layers, white light potions represented high vegetation/bare-land covered regions, and dark parts indicated the opposite. Spectral Mixture Analysis) method was selected to extract the vegetation coverage and bare-land rate in the study region for its simplicity, effectiveness, and interpretability [14,16]. In LSMA, the reflectance of each image pixel is presented as a linear combination of the reflectance of each endmember and its residual [17], which can be presented as Equation (1).…”

Section: Lsma Methodsmentioning

confidence: 99%

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Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China

Zhao

2017

Applied Sciences

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Section: Lsma Methodsmentioning

confidence: 99%

Section: Lsma Methodsmentioning

confidence: 99%

Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China

Zhao

2017

Applied Sciences

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“…Natural factors as a single force was one of the major driving forces of LCLUC processes in the region and could influence land degradation at the regional level of the landscapes [48]. "Wetland ecosystems are particularly sensitive to climate change that affects hydrology, biogeochemical processes, plant communities and ecosystem function" [49].…”

Section: Influence Of Climatic Factors On Elwnnr and Glhfnnrmentioning

confidence: 99%

Assessment of Land-Cover/Land-Use Change and Landscape Patterns in the Two National Nature Reserves of Ebinur Lake Watershed, Xinjiang, China

2017

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Abstract:Land-cover and land-use change (LCLUC) alters landscape patterns and affects regional ecosystems. The objective of this study was to examine LCLUC and landscape patterns in Ebinur Lake Wetland National Nature Reserve (ELWNNR) and Ganjia Lake Haloxylon Forest National Nature Reserve (GLHFNNR), two biodiversity-rich national nature reserves in the Ebinur Lake Watershed (ELW), Xinjiang, China. Landsat satellite images from 1972, 1998, 2007 and 2013 were used to calculate the dynamics of a land-cover and land-use (LCLU) transition matrix and landscape pattern index using ENVI 5.1 and FRAGSTATS 3.3. The results showed drastic land use modifications have occurred in ELWNNR during the past four decades. Between 1972Between and 1998Between , 1998Between and 2007Between , and 2007Between and 2013.50 km 2 (7.93%), 122.70 km 2 (3.87%), and 195.40 km 2 (6.16%) of wetland were turned into salinized land. In GLHFNNR both low and medium density Haloxylon forest area declined while high density Haloxylon forest area increased. This contribution presents a method for characterizing LCLUC using one or more cross-tabulation matrices based on Sankey diagrams, demonstrating the depiction of flows of energy or materials through ecosystem network. The ecological landscape index displayed that a unique landscape patches have shrunk in size, scattered, and fragmented. It becomes a more diverse landscape. Human activities like farming were negatively correlated with the landscape diversity of wetlands. Furthermore, evidence of degraded wetlands caused by air temperature and annual precipitation, was also observed. We conclude that national and regional policies related to agriculture and water use have significantly contributed to the extensive changes; the ELWNNR and GLHFNNR are highly susceptible to LCLUC in the surrounding Ebinur Lake Watershed.

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“…Although this method was designed primarily for HS image data analysis, it has frequently been used for mapping sub-pixel abundances using multispectral data (Dawelbait & Morari 2012;Pacheco & McNairn, 2010;Parente, Bishop, & Bell, 2009;Shanmugam, Ahn, & Sanjeevi, 2006;Vicente & de Souza Filho, 2011). The only condition is that the number of derived fractions (end members) is equal to or less than the number of bands.…”

Section: Aster End-member Definition and Image Unmixingmentioning

confidence: 99%

Application of high altitude and ground-based spectroradiometry to mapping hazardous low-pH material derived from the Sokolov open-pit mine

et al. 2012

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Monitoring desertification in a Savannah region in Sudan using Landsat images and spectral mixture analysis

Cited by 112 publications

References 41 publications

Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China

Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China

Assessment of Land-Cover/Land-Use Change and Landscape Patterns in the Two National Nature Reserves of Ebinur Lake Watershed, Xinjiang, China

Application of high altitude and ground-based spectroradiometry to mapping hazardous low-pH material derived from the Sokolov open-pit mine

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