Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output

Moran, M. Susan; Jackson, R. D.; Slater, Philip N.; Teillet, Philippe

doi:10.1016/0034-4257(92)90076-v

Cited by 372 publications

(197 citation statements)

References 19 publications

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“…Methods and/or correction coefficients have been published for many radiometric correction techniques, including conversion to top-ofatmosphere reflectance (Chander and Markham 2003;Chander et al 2007), dark-object subtraction (Chavez 1988;Teillet and Fedosejevs 1995), measuring or estimating atmospheric aerosols to derive surface reflectance (Liang et al 2001;Thome 2001), applying radiative transfer functions (Moran et al 1992), empirical line calibration (Moran et al 2001), and haze removal (Richter 1996). More detailed reviews and summaries of radiometric image processing entailing terminology, sensor radiometric calibration, surface reflectance retrieval, image normalisation, and topographic corrections are available from Richards and Jia (1999), Liang et al (2001Liang et al ( , 2002, Peddle et al (2003), Schaepman-Strub et al (2006), and Vanonckelen et al (2013).…”

Section: What Sensors Are Available?mentioning

confidence: 99%

Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective

et al. 2016

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Section: What Sensors Are Available?mentioning

confidence: 99%

Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective

et al. 2016

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“…To overcome the lack of detailed in situ field data of atmospheric optical properties at the time of image acquisition, an image-based dark object subtraction (DOS) method was used (Chavez 1989(Chavez , 1996Moran et al 1992). This method is the simplest yet most widely used approach, suitable for areas with dense vegetation (Spanner et al 1990;Ekstrand 1994;Jakubauskas 1996;Huguenin et al 1997).…”

Section: Image Processing and Classificationmentioning

confidence: 99%

Historical and future land-cover changes in the Upper Ganges basin of India

Tsarouchi

Mijic

Moulds

et al. 2014

International Journal of Remote Sensing

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The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multitemporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (-9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.

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“…Several studies (Moran et al, 1992(Moran et al, , 1995Liang et al, 2002;González-Dugo and Mateos, 2008) have evaluated the accuracy of atmospheric correction algorithms by comparing the retrieved satellite reflectance with ground-based or aircraftbased radiometric measurements and vegetation indices obtained from various sensors. In this study, we compared VIs obtained from Landsat imagery (5 and 7) and a handheld radiometer (ASD-FieldSpec).…”

Section: Comparison Between Satellite-derived and Ground-derived Vegementioning

confidence: 99%

Integration of vegetation indices into a water balance model to estimate evapotranspiration of wheat and corn

Padilla

González‐Dugo

Jiménez-Gavilán

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract. Vegetation indices (VIs) have been traditionally used for quantitative monitoring of vegetation. Remotely sensed radiometric measurements of visible and infrared solar energy, which is reflected or emitted by plant canopies, can be used to obtain rapid, non-destructive estimates of certain canopy attributes and parameters. One parameter of special interest for water management applications, is the crop coefficient employed by the FAO-56 model to derive actual crop evapotranspiration (ET). The aim of this study was to evaluate a methodology that combines the basal crop coefficient derived from VIs with a daily soil water balance in the root zone to estimate daily evapotranspiration rates for corn and wheat crops at field scale. The ability of the model to trace water stress in these crops was also assessed. Vegetation indices were first retrieved from field hand-held radiometer measurements and then from Landsat 5 and 7 satellite images. The results of the model were validated using two independent measurement systems for ET and regular soil moisture monitoring, in order to evaluate the behavior of the soil and atmosphere components of the model. ET estimates were compared with latent heat flux measured by an eddy covariance system and with weighing lysimeter measurements. Average overestimates of daily ET of 8 and 11% were obtained for corn and wheat, respectively, with good agreement between the estimated and measured root-zone water deficit for both crops when field radiometry was employed. When the satellite sensor data replaced the field radiometry data the overestimation figures slightly changed to 9 and 6% for the same two crops. The model was also used to monitor the water stress during the 2009 growing season, detecting several periods of water stress in both crops. Some of these stresses occurred during stages like grain filling, whenCorrespondence to: F. L. M. Padilla (franciscol.munoz@juntadeandalucia.es) the water stress is know to have a negative effect on yield. This fact could explain the lower yield reached compared to local yield statistics for wheat and corn. The results showed that the model can be used to calculate the water requirements of these crops in irrigated areas and that its ability to monitor water stress deserves further research.

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Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output

Cited by 372 publications

References 19 publications

Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective

Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective

Historical and future land-cover changes in the Upper Ganges basin of India

Integration of vegetation indices into a water balance model to estimate evapotranspiration of wheat and corn

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