The application of a remotely-sensed diversity index to monitor degradation patterns in a semi-arid, heterogeneous, South African landscape

Tanser, Frank; Palmer, Anthony R.

doi:10.1006/jare.1999.0568

Cited by 57 publications

(39 citation statements)

References 10 publications

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“…It has also been used in desertification evaluation (Tanser and Palmer, 1999;Seixas, 2000). In geostatistical modeling, the semivariogram γ (h) is one of geo-statistical pattern analysis tools used to measure spatial heterogeneity.…”

Section: Desertification Evaluation Factorsmentioning

confidence: 99%

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Modeling Desertification Change in Minqin County, China

Sun

Dawson

Li³

et al. 2005

Environ Monit Assess

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Monitoring environmental processes is becoming increasingly important wherever there is increasing population and economic development pressure placed on fragile environments. Remote sensing, digital image processing, and spatial analysis have proven to be useful technologies in both assessing and monitoring environmental change. In this study, they were used to assess desertification processes and change in Minqin County, China from 1988 to 1997. The results suggest that wind erosion was the dominant cause of desertification in more than half of the study area. Coupled with this were increases in salinization processes, affecting 33.62% of the land area in 1997. Overall, moderate desertification was found to be the dominant desertification grade (43.64% of total area), followed by extreme/severe desertification (26.15% of total area) in 1997. In addition, examination of landscape pattern changes indicated that desertification processes at the landscape level were becoming evident at increasing levels of fragmentation, complexity in shape, and isolation of patches. Major fluctuations in desertification type and grade were found at the fringes of oases, where an ongoing shift was taking place between cultivation, abandonment, and reclamation.

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Section: Desertification Evaluation Factorsmentioning

confidence: 99%

“…Satellite remote sensing has been widely used in monitoring desertification (Tripathy et al, 1996;Gao et al, 1998;Tanser and Palmer, 1999;Seixas, 2000). In addition, spatial heterogeneity and pattern analysis have also been used as a sensitivity measure of desertification change (Schleinger et al, 1990;Kepner et al, 2000).…”

Section: Introductionmentioning

confidence: 98%

Modeling Desertification Change in Minqin County, China

Sun

Dawson

Li³

et al. 2005

Environ Monit Assess

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“…The human vulnerability and implications of these negative changes on livelihoods of communities require proper and serious attention. Recent researches on semiarid environments have shown that land degradation resulting from such changes may lead to changes in the distribution of different types of vegetation cover, even when the total biomass is not necessarily changed (Tanser & Palmer, 1999). In many instances land degradation results in increased runoff and soil redistribution within the area through erosion and sedimentation processes (Payton et al, 1992;Yanda, 1995).…”

Section: Land-cover Change Modelingmentioning

confidence: 99%

From Land Cover to Landscape Structure: Change and Fragmentation Analysis in Korup National Park, Cameroon

Innocent¹,

Bitondo²

2012

JGG

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Can the designation of protected area status in a human inhabited ecosystem limit anthropogenic activities within the boundaries of the protected area? To attempt an answer to this question, we used the Central zone of Korup National Park, Cameroon as an example. Comparing two satellite imageries (1986 and 2000), it was possible to assess land cover transformations, and with the FRAGSTATS software it was possible to quantify the changes of landscape characteristics in the area fourteen years after the creation of the park in 1986. The results revealed an increase in exposed surfaces (15.61%), which came at the expense of forest-land-cover (-12.69%) and water bodies (-2.92%). Meanwhile, landscape metrics demonstrated significant changes including, an increase in the number and size of patch, diversity and fragmentation. Overall, structural metrics for landscape indicated that anthropogenic activities still continue within the boundaries of the park. The results confirm the effectiveness of the combined method of remote sensing and metrics.

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“…[8][9][10][11] Multispectral remote sensing detection of fire impact of vegetation is based on the reduction of foliage display 12 and soil charring and ash persistence surrounding sparsely vegetated areas. 13 Over longer periods, differences in vegetation response to fire and regrowth potentially may be detected as latent fire effects as a function of fire size and intensity.…”

Section: Introductionmentioning

confidence: 99%

“…[14][15][16] Spectral vegetation indices such as the simple ratio (SR), normalized difference vegetation index (NDVI), and the soil-adjusted vegetation index (SAVI) correlate well with vegetation changes such as leaf area index and biomass following fire. 11,[17][18][19][20] The normalized burn ratio (NBR) was also derived to detect fire effects in vegetation based on relative changes in near-infrared reflectance (NIR). 21 In addition, the NBR also includes the short-wave infrared (SWIR) region (2.08 to 2.35 μm) to account for soil reflectance changes associated with charring and mineral oxidation.…”

Section: Introductionmentioning

confidence: 99%

Fire effects in the northern Chihuahuan Desert derived from Landsat-5 Thematic Mapper spectral indices

White

Swint

2014

J. Appl. Remote Sens

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Abstract. Fire effects on desert ecosystems may be long-lasting based on ecological impact of fire in these environments which potentially is detected from multispectral sensors. To assess this, we analyzed changes in spectral characteristics from 1986 to 2010 of pixels associated with the location of fires that occurred between 1986 and 1999 in Big Bend National Park, USA, located in the northern Chihuahuan Desert. Using Landsat-5 Thematic Mapper (TM) data, we derived spectral indices including the simple ratio (SR), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and normalized burn ratio (NBR) from 1989, 1999, and 2010 from the TM data and compared changes in spectral index values for sites with and without observed fire. We found that the NDVI and SAVI had significantly different values over the time for burned sites of different fire sizes. When differences of the spectral indices were calculated from each time period, time since fire was correlated with the SR and NBR indices. These results showed that large fires potentially had a persistent and long-term change in vegetation cover and soil characteristics which were detected by the extraordinary long-data collection period of the Landsat-5 TM sensor. © The Authors.Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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The application of a remotely-sensed diversity index to monitor degradation patterns in a semi-arid, heterogeneous, South African landscape

Cited by 57 publications

References 10 publications

Modeling Desertification Change in Minqin County, China

Modeling Desertification Change in Minqin County, China

From Land Cover to Landscape Structure: Change and Fragmentation Analysis in Korup National Park, Cameroon

Fire effects in the northern Chihuahuan Desert derived from Landsat-5 Thematic Mapper spectral indices

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