Quantifying dwarf shrub biomass in an arid environment: comparing empirical methods in a high dimensional setting

Zandler, Harald; Brenning, Alexander; Samimi, Cyrus

doi:10.1016/j.rse.2014.11.007

Cited by 84 publications

(77 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We estimate that the geo-location accuracy of the Landsat 8 imagery is below half a panchromatic pixel (i.e., 7.5 m), thereby giving confidence to the approach used in this study. Similarly accurate spatial registration of Landsat 8 was also recognized by Zandler et al [94].…”

Section: Discussionsupporting

confidence: 54%

Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest

et al. 2015

View full text Add to dashboard Cite

Accurate and timely maps of tree cover attributes are important tools for environmental research and natural resource management. We evaluate the utility of Landsat 8 for mapping tree canopy cover (TCC) and aboveground biomass (AGB) in a woodland landscape in Burkina Faso. Field data and WorldView-2 imagery were used to assemble the reference dataset. Spectral, texture, and phenology predictor variables were extracted from Landsat 8 imagery and used as input to Random Forest (RF) models. RF models based on multi-temporal and single date imagery were compared to determine the influence of phenology predictor variables. The effect of reducing the number of predictor variables on the RF predictions was also investigated. The model error was assessed using 10-fold cross ). This mapping approach is based on freely available Landsat 8 data and relatively simple analytical methods, and is therefore applicable in woodland areas where sufficient reference data are available.

show abstract

Section: Discussionsupporting

confidence: 54%

Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Models with a limited number of observations and a high number of predictors are sensitive to unreliable statistical parameter retrieval (Zandler, Brenning, & Samimi, 2015) and therefore 3 parameters were applied for model validation:…”

Section: Woody Cover Model Validation and Evaluationmentioning

confidence: 99%

Woody plant cover estimation in drylands from Earth Observation based seasonal metrics

Brandt

Hiernaux

Tagesson

et al. 2016

Remote Sensing of Environment

View full text Add to dashboard Cite

From in situ measured woody cover we develop a phenology driven model to estimate the canopy cover of woody species in the Sahelian drylands at 1 km scale. The model estimates the total canopy cover of all woody phanerophytes and the concept is based on the significant difference in phenophases of dryland trees, shrubs and bushes as compared to that of the herbaceous plants. Whereas annual herbaceous plants are only green during the rainy season and senescence occurs shortly after flowering towards the last rains, most woody plants remain photosynthetically active over large parts of the year. We use Moderate Resolution Imaging Spectroradiometer (MODIS) and Satellite pour l'Observation de la Terre (SPOT) -VEGETATION (VGT) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series and test 10 metrics representing the annual FAPAR dynamics for their ability to reproduce in situ woody cover at 43 sites (163 observations between 1993 and 2013) in the Sahel. Both multi-year field data and satellite metrics are averaged to produce a steady map. Multiple regression models using the integral of FAPAR from the onset of the dry season to the onset of the rainy season, the start date of the growing season and the rate of decrease of the FAPAR curve achieve a cross validated r 2 /RMSE (in % woody cover) of 0.73/3.0 (MODIS) and 0.70/3.2 (VGT). The extrapolation to Sahel scale shows agreement between VGT and MODIS at an almost nine times higher woody cover than in the global tree cover product MOD44B which only captures trees of a certain minimum size. The derived woody cover map of the Sahel is made publicly available and represents an improvement of existing products and a contribution for future studies of drylands quantifying carbon stocks, climate change assessment, as well as parametrization of vegetation dynamic models.

show abstract

“…The vegetation cover in the eastern Pamirs generally covers patches big enough to be detected by the resolution of the Landsat. High-resolution sensors may not offer a better performance [53], are impractical to apply to the total study area due to their high cost, and require a longer period of data analysis than medium spatial resolution image data [54].…”

Section: Landsat Datamentioning

confidence: 99%

Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs

2016

View full text Add to dashboard Cite

Abstract:We tested the Moment Distance Index (MDI) in combination with texture features for the summer vegetation mapping in the eastern Pamir Mountains, Tajikistan using the 2014 Landsat OLI (Operational Land Imager) image. The five major classes identified were sparse vegetation, medium-dense vegetation, dense vegetation, barren land, and water bodies. By utilizing object features in a random forest (RF) classifier, the overall classification accuracy of the land cover maps were 92% using a set of variables including texture features and MDI, and 84% using a set of variables including texture but without MDI. A decrease of the Kappa statistics, from 0.89 to 0.79, was observed when MDI was removed from the set of predictor variables. McNemar's test showed that the increase in the classification accuracy due to the addition of MDI was statistically significant (p < 0.05). The proposed method provides an effective way of discriminating sparse vegetation from barren land in an arid environment, such as the Pamir Mountains.

show abstract

Quantifying dwarf shrub biomass in an arid environment: comparing empirical methods in a high dimensional setting

Cited by 84 publications

References 65 publications

Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest

Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest

Woody plant cover estimation in drylands from Earth Observation based seasonal metrics

Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs

Contact Info

Product

Resources

About