Assessment of crop damage using space remote sensing and GIS

Silleos, N.; Perakis, Κonstantinos; Petsanis, G.

doi:10.1080/01431160110040026

Cited by 39 publications

(26 citation statements)

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“…Peters et al 2000;Silleos et al 2002;de Leeuw et al 2014) due to various factors. Data sources include satellite imagery, cameras flown on light aircraft or unmanned aerial vehicles (UAV), and handheld (proximal) sensors.…”

Section: Previous Researchmentioning

confidence: 99%

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

Perry¹,

Nuttall²,

Wallace³

et al. 2017

Crop Pasture Sci.

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Abstract. Frost damage causes significant production losses and costs to Australian dryland wheat, and frost impacts are not expected to decline in the near future, despite global warming. Rapid estimation of frost damage to crops on a spatial basis would allow for timely management decisions to reduce the economic impact of frost events. In this paper, we take a first step in evaluating the utility of hyperspectral reflectance and active light fluorescence for detecting frost damage to wheat during its reproductive phase. Two experiments were conducted immediately after the first observation of frost damage, (i) in 2006, five plots in an existing trial were opportunistically subdivided to take spectral reflectance measurements on frost damaged plants along with yield measurements, and (ii) in 2015, a transect across 31 rows within a commercial paddock was established to evaluate spectral reflectance, fluorometer measurements, and yield along a gradient from non-frosted to frost damaged plants. The results of the hyperspectral reflectance data appeared variable in response across the two experimental sites where frost was observed in-crop. In 2006, hyperspectral-derived indices showed significant differences (P < 0.05) between measurements of frosted and non-frosted canopies, but this was not the case for observations taken in 2015, where the mean response was reversed between experimental sites for several of the indices. In contrast, fluorometer measurements in the 2015 trial resulted in higher correlations with yield and observed frost damage compared with the reflectance measurements. Seven of the nine fluorometer indices evaluated were correlated with yield (used as an indicator of frost damage) at P < 0.01. An index of compounds which absorbs at 375 nm, FLAV, had the best correlation coefficients of 0.91 and 0.90 for the two dates in 2015. The fluorescence index FLAV was selected to evaluate whether it could be used to classify the canopy as frost affected or not, using discriminant analysis for the 2015 transect data. The overall classification accuracy, defined as the number of correctly classified measurements (57) divided by the total number (62) was 92%. The present study was not able to provide insight into how rapidly the sensors could detect frost damage before detection with the naked eye, as the survey data constituted a transect based on early visual symptoms, however this study does provide important insight into what sensors and/or indices may be sensitive to 'seeing' early frost damage in-crop. The next steps, which build on this work and need to be resolved are (i) what is the nominal scale of measurements required, and for which portions of the plant canopy? (ii) How robust (over space and time) are any relationships between frost damage and index response? (iii) Can frost damage be detected before the onset of visual damage?

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Section: Previous Researchmentioning

confidence: 99%

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

Perry¹,

Nuttall²,

Wallace³

et al. 2017

Crop Pasture Sci.

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“…In recent years much attention has been paid on monitoring phenological changes and classification of different crop types using remote sensing observations (Bouvet and Le Toan, 2009;Hoekman, 2003;Liu et al, 2013;Juan M. Lopez-Sanchez et al, 2011). Issues like recognizing growth behaviour, cultivation problems and crop yield estimation have been worked by different researchers (Dhar et al, 2009;Ferencz et al, 2004;Silleos et al, 2002). Among different sensor data, radar remote sensing with its reliable and frequent imaging capability all-weather functionality, sensitivity to target geometrical structure and orientation, has enhanced further our capabilities for agricultural monitoring.…”

Section: Introductionmentioning

confidence: 99%

Phenological tracking og agricultural feilds investigated by using dual polarimetry tanDEM-X images

Mirzaee

Motagh

Arefi

et al. 2015

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

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ABSTRACT:Remote sensing plays a key role in monitoring and assessing environmental changes. Because of its special imaging characteristics such as high-resolution, capabilities to obtain data in all weather conditions and sensitivity to geometrical and dielectric properties of the features, Synthetic Aperture Radar (SAR) technology has become a powerful technique to detect small scale changes related to earth surface.SAR images contain the information of both phase and intensity in different modes like single, dual and full polarimetric states which are important in order to extract information about various targets. In this study we investigate phenological changes in an agricultural region using high-resolution X-band SAR data. The case study is located in Doroud region of Lorestan province, west of Iran. The purpose is to investigate the ability of copolar and interferometric coherence extracted from TanDEM-X dual polarimetry (HH/VV) in bistatic StripMap mode for tracking the phenological changes of crops during growing season. The data include 11 images acquired between 12. 06.2012 and 02.11.2012 and 6 images acquired between 30.05.2013 and 04.08.2013 in the CoSSC format. Results show that copolar coherence is almost able to follow phenological changes but interferometric coherence has a near constant behaviour with fluctuations mainly related to baseline variations.

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“…However, land surface temperature (LST) or near-ground air temperature retrieved from thermal infrared band(s) directly or indirectly, may not be readily available when frost occurs, because of the limitation of the revisit cycle or dense cloud cover. Alternatively, most studies employ various vegetation indices (VIs) derived from airborne or spaceborne sensors as the indicators of freeze injury, among which the normalized difference vegetation index (NDVI) is particularly widely applied (Silleos et al, 2002;Feng et al, 2009;Tan et al, 2009;Currit and St. Clair, 2010). The affected scope and degree of the freeze injury can be estimated using the difference of VI before and after freeze, or the deviation from a normal baseline.…”

Section: Introductionmentioning

confidence: 99%

“…The freeze injury issues have been intensively studied using remote sensing approach for forests (Olthof et al, 2004;King et al, 2005;Currit and St. Clair, 2010), and also crops, e.g., winter wheat (Silleos et al, 2002;Feng et al, 2009;Wang et al, 2012) and sugar-cane (Tan et al, 2009). The daily minimum temperature is definitely the foremost factor for the occurrence of freeze injury.…”

Section: Introductionmentioning

confidence: 99%

Assessing winter oilseed rape freeze injury based on Chinese HJ remote sensing data

Shu

Huang

Guo

et al. 2015

J. Zhejiang Univ. Sci. B

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Abstract:The winter oilseed rape (Brassica napus L.) accounts for about 90% of the total acreage of oilseed rape in China. However, it suffers the risk of freeze injury during the winter. In this study, we used Chinese HJ-1A/1B CCD sensors, which have a revisit frequency of 2 d as well as 30 m spatial resolution, to monitor the freeze injury of oilseed rape. Mahalanobis distance-derived growing regions in a normal year were taken as the benchmark, and a mask method was applied to obtain the growing regions in the 2010-2011 growing season. The normalized difference vegetation index (NDVI) was chosen as the indicator of the degree of damage. The amount of crop damage was determined from the difference in the NDVI before and after the freeze. There was spatial variability in the amount of crop damage, so we examined three factors that may affect the degree of freeze injury: terrain, soil moisture, and crop growth before the freeze. The results showed that all these factors were significantly correlated with freeze injury degree (P<0.01, two-tailed). The damage was generally more serious in low-lying and drought-prone areas; in addition, oilseed rape planted on south-and west-oriented facing slopes and those with luxuriant growth status tended to be more susceptible to freeze injury. Furthermore, land surface temperature (LST) of the coldest day, soil moisture, pre-freeze growth and altitude were in descending order of importance in determining the degree of damage. The findings proposed in this paper would be helpful in understanding the occurrence and severity distribution of oilseed rape freeze injury under certain natural or vegetation conditions, and thus help in mitigation of this kind of meteorological disaster in southern China.

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Assessment of crop damage using space remote sensing and GIS

Cited by 39 publications

References 0 publications

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

Phenological tracking og agricultural feilds investigated by using dual polarimetry tanDEM-X images

Assessing winter oilseed rape freeze injury based on Chinese HJ remote sensing data

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