Daily MODIS Land Surface Temperature Data for the Analysis of the Heat Requirements of Grapevine Varieties

Zorer, R.; Rocchini, Duccio; Metz, Markus; Delucchi, L.; Zottele, Fabio; Meggio, Franco; Neteler, Markus

doi:10.1109/tgrs.2012.2226465

Cited by 19 publications

(12 citation statements)

References 28 publications

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“…Similarly, the warmest areas in Italy were classified as Region III and include the vicinity of Garda Lake, the Adige River Valley and low-elevation regions of Vicenza, Treviso and Pordenone. Region III permits the cultivation of red varieties such as Merlot and Cabernet Sauvignon, as well as local Italian Teroldego and Marzemino grapes (Zorer et al, 2013). By contrast, WI values for regions in northern New Zealand such as Kaitaia, the Bay of Islands, Whangarei and Matakana ranged from 1 268 to 1 694 GDD (Anderson et al, 2012).…”

Section: Winkler Index-wi (Growing Degree Days)mentioning

confidence: 99%

Phenology and Ripening of Vitis vinifera L. and Vitis labrusca L. Varieties in the Maritime Climate of Samsun in Turkey’s Black Sea Region

Köse

2016

SAJEV

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Section: Winkler Index-wi (Growing Degree Days)mentioning

confidence: 99%

Phenology and Ripening of Vitis vinifera L. and Vitis labrusca L. Varieties in the Maritime Climate of Samsun in Turkey’s Black Sea Region

Köse

2016

SAJEV

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“…Temperature time series are required for risk assessments of fast spreading agricultural pests, e.g., Drosophila suzukii, when using environmental indicators relevant for the respective species lifecycle. Agricultural suitability analyses, e.g., for grapevine varieties [38], rely on temperature time series. Studies of the consequences of the ongoing climate change, e.g., recent extreme temperature anomalies [39], are based on temperature time series, as well as investigations of the impact of global warming on local ecosystems in more detail [8,39].…”

Section: Spatial and Temporal Resolutionmentioning

confidence: 99%

Surface Temperatures at the Continental Scale: Tracking Changes with Remote Sensing at Unprecedented Detail

2014

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Abstract:Temperature is a main driver for most ecological processes, and temperature time series provide key environmental indicators for various applications and research fields. High spatial and temporal resolutions are crucial for detailed analyses in various fields of research. A disadvantage of temperature data obtained by satellites is the occurrence of gaps that must be reconstructed. Here, we present a new method to reconstruct high-resolution land surface temperature (LST) time series at the continental scale gaining 250-m spatial resolution and four daily values per pixel. Our method constitutes a unique new combination of weighted temporal averaging with statistical modeling and spatial interpolation. This newly developed reconstruction method has been applied to greater Europe, resulting in complete daily coverage for eleven years. To our knowledge, this new reconstructed LST time series exceeds the level of detail of comparable reconstructed LST datasets by several orders of magnitude. Studies on emerging diseases, parasite risk assessment and temperature anomalies can now be performed on the continental scale, maintaining high spatial and temporal detail. We illustrate a series of applications in this paper. Our dataset is available online for download as time aggregated derivatives for direct usage in GIS-based applications.

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“…Regression approaches have previously demonstrated accurate predictions of T air using solely LST or LST associated with ancillary variables [4,13,46,49,67]. In this application, models were divided into three groupings similar to the organization used by Benali et al [47], where they modeled instantaneous MODIS LST observations during the (i) daytime; (ii) night; and (iii) using both datasets combined (hereafter referred to as the daytime, night, and day-night models).…”

Section: Statistical Methods and Model Rankingmentioning

confidence: 99%

“…An abridged methodology is shown in Figure 3. Accurate LST measurements are highly dependent on the amount of cloud cover at the time of overpass, therefore a two-step filter process was adapted from Neteler [6] and Zorer et al [46] to obtain only the highest quality pixels for each observation plot. The first step used the integrated image bitword quality assessment (QA) flags to mask out cloud or corrupted image pixels.…”

Section: Modis Land Surface Temperature Observationsmentioning

confidence: 99%

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Estimating Understory Temperatures Using MODIS LST in Mixed Cordilleran Forests

et al. 2016

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Abstract:Satellite remote sensing provides a rapid and broad-scale means for monitoring vegetation phenology and its relationship with fluctuations in air temperature. Investigating the response of plant communities to climate change is needed to gain insight into the potentially detrimental effects on ecosystem processes. While many studies have used satellite-derived land surface temperature (LST) as a proxy for air temperature, few studies have attempted to create and validate models of forest understory temperature (T ust ), as it is obscured from these space-borne observations. This study worked to predict instantaneous values of T ust using daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST data over a 99,000 km 2 study area located in the Rocky Mountains of western Alberta, Canada. Specifically, we aimed to identify the forest characteristics that improve estimates of T ust over using LST alone. Our top model predicted T ust to within a mean absolute error (MAE) of 1.4 • C with an overall model fit of R 2 = 0.89 over two growing seasons. Canopy closure and the LiDAR-derived standard deviation of canopy height metric were found to significantly improve estimations of T ust over MODIS LST alone. These findings demonstrate that canopy structure and forest stand-type function to differentiate understory air temperatures from ambient canopy temperature as seen by the sensor overhead.

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Daily MODIS Land Surface Temperature Data for the Analysis of the Heat Requirements of Grapevine Varieties

Cited by 19 publications

References 28 publications

Phenology and Ripening of Vitis vinifera L. and Vitis labrusca L. Varieties in the Maritime Climate of Samsun in Turkey’s Black Sea Region

Phenology and Ripening of Vitis vinifera L. and Vitis labrusca L. Varieties in the Maritime Climate of Samsun in Turkey’s Black Sea Region

Surface Temperatures at the Continental Scale: Tracking Changes with Remote Sensing at Unprecedented Detail

Estimating Understory Temperatures Using MODIS LST in Mixed Cordilleran Forests

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