Utility of AVHRR data for land degradation assessment: a case study

Bastin, Gary; Pickup, G.; Pearce, Graham

doi:10.1080/01431169508954432

Cited by 49 publications

(27 citation statements)

References 34 publications

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“…However, these authors point out to the need to analyse floristic composition in addition to net primary production as, in some cases, desirable species for animal foraging can be replaced by less palatable, drought-resistant species. However, such fine scale changes in vegetation communities or soil alteration cannot be measured at the scale of AVHRR data (Bastin et al, 1995). Also, a shift from grasslands to woodlands might account for a change in rain-use efficiency.…”

Section: Introductionmentioning

confidence: 98%

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

Diouf

Lambin

2001

Journal of Arid Environments

208

176

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Section: Introductionmentioning

confidence: 98%

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

Diouf

Lambin

2001

Journal of Arid Environments

208

176

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“…Tucker et al, 1983;Tucker et al, 1985;Justice & Hiernaux, 1986;Townshend & Justice, 1986;Tucker, 1986;Maselli et al, 1993;Bastin et al, 1995;Hobbs, 1995;Prince et al, 1995). A large number of these works show that remote sensing has been considered to be a useful method for studying arid and semi-arid ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing of the seasonal variability of vegetation in a semi-arid environment

Schmidt

Karnieli

2000

Journal of Arid Environments

141

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“…Next it provides the necessary spatial resolution to depict management related change. (Roy et al, 2015) and (Bastin et al, 1995) suggest a spatial scale or grain of one hectare is important to most landscape scale processes and monitoring programs in rangelands. Lastly and importantly the LFGC imagery aims to model the fractions of ground cover of a remotely sensed image pixel from field based observations.…”

Section: Landsat Fractional Ground Cover Data (Lfgc)mentioning

confidence: 99%

Assessing Landsat Fractional Ground-Cover Time Series Across Australia’s Arid Rangelands: Separating Grazing Impacts From Climate Variability

Barnetson

Phinn

Scarth

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of Australia. This work developed and tested a time-series, changepoint detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. Utilising the High Performance Computing power of the Google Cloud Compute Engine these cycles were segmented to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term and short term growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. During periods of ground cover decline, grazing utilisation was observed across four major grasslands. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

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Utility of AVHRR data for land degradation assessment: a case study

Cited by 49 publications

References 34 publications

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

Remote sensing of the seasonal variability of vegetation in a semi-arid environment

Assessing Landsat Fractional Ground-Cover Time Series Across Australia’s Arid Rangelands: Separating Grazing Impacts From Climate Variability

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