The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Francisco J Villalobos - One of the best experts on this subject based on the ideXlab platform.
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detection of water stress in an olive orchard with thermal remote sensing imagery
Agricultural and Forest Meteorology, 2006Co-Authors: G Sepulcrecanto, J A Sobrino, Pablo J Zarcotejada, J C Jimenezmunoz, Francisco J Villalobos, E De MiguelAbstract:Abstract An investigation of the detection of water stress in non-homogeneous crop canopies such as orchards using high-spatial resolution remote sensing thermal imagery is presented. An Airborne campaign was conducted with the Airborne Hyperspectral Scanner (AHS) acquiring imagery in 38 spectral bands in the 0.43–12.5 μm spectral range at 2.5 m spatial resolution. The AHS Sensor was flown at 7:30, 9:30 and 12:30 GMT in 25 July 2004 over an olive orchard with three different water-deficit irrigation treatments to study the spatial and diurnal variability of temperature as a function of water stress. A total of 10 AHS bands located within the thermal-infrared region were assessed for the retrieval of the land surface temperature using the split-window algorithm, separating pure crowns from shadows and sunlit soil pixels using the reflectance bands. Ground truth validation was conducted with infrared thermal Sensors placed on top of the trees for continuous thermal data acquisition. Crown temperature ( T c ), crown minus air temperature ( T c − T a ), and relative temperature difference to well-irrigated trees ( T c − T R , where T R is the mean temperature of the well-irrigated trees) were calculated from the ground Sensors and from the AHS imagery at the crown spatial resolution. Correlation coefficients for T c − T R between ground IRT Sensors and Airborne image-based AHS estimations were R 2 = 0.50 (7:30 GMT), R 2 = 0.45 (9:30 GMT) and R 2 = 0.57 (12:30 GMT). Relationships between leaf water potential and crown T c − T a measured with the Airborne Sensor obtained determination coefficients of R 2 = 0.62 (7:30 GMT), R 2 = 0.35 (9:30 GMT) and R 2 = 0.25 (12:30 GMT). Images of T c − T a and T c − T R for the entire field were obtained at the three times during the day of the overflight, showing the spatial and temporal distribution of the thermal variability as a function of the water deficit irrigation schemes.
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spatial variability of crop water stress in an olive grove with high spatial thermal remote sensing imagery
Precision agriculture '05. Papers presented at the 5th European Conference on Precision Agriculture Uppsala Sweden, 2005Co-Authors: G Sepulcrecanto, J A Sobrino, Pablo J Zarcotejada, J C Jimenezmunoz, Francisco J Villalobos, J V StaffordAbstract:The Airborne Hyperspectral Scanner (AHS) was used to acquire images with a 2.5 m spatial resolution in the visible, near infrared and thermal spectral regions over an olive orchard in southern Spain to study the spatial variability of water stress. The AHS Sensor was equipped with 20 channels of 20 nm bandwidth in the visible and near infrared region, 1 channel of 200 nm bandwidth, 42 channels of 13 nm bandwidth in the mid infrared, 7 channels of 300nm bandwidth for short-wave infrared, and 10 channels of 400nm in the long-wave infrared spectral region. Aircraft flights were scheduled at 7:30, 9:30 and 12:30 GMT in July 2004 to study the spatial and temporal variation of orchard tree temperatures as a function of the diurnal variation of water stress. Water and bare soil temperatures were measured simultaneously to the Airborne Sensor overflights to calibrate the thermal AHS imagery, acquiring atmospheric optical thickness at the time of image collection. Imagery was processed applying geometric, radiometric and atmospheric corrections. The high spatial resolution AHS data enabled the temperature of the top of the tree to be targeted, minimizing structural mixed pixel effects. Olive tree emissivities were measured in the field with a CIMEL instrument, and the soil emissivity was measured using a bottomless box. Water potential, photosynthesis, and stomatal conductance were measured weekly in olive trees under 3 different water stress treatments from June to November 2004 to track the effects of water stress on the trees’ condition and functioning. Infrared Sensors were placed on top of the trees for diurnal thermal data collection and validation of the thermal imagery collected. Results of the remote sensing thermal analysis show that this methodology allows mapping of the spatial variability of water stress with a potential applicability in precision agriculture for management of controlled deficit irrigation methods.
John D Bolten - One of the best experts on this subject based on the ideXlab platform.
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observations of soil moisture using a passive and active low frequency microwave Airborne Sensor during sgp99
IEEE Transactions on Geoscience and Remote Sensing, 2002Co-Authors: E G Njoku, W J Wilson, Simon Yueh, S J Dinardo, T J Jackson, V Lakshmi, John D BoltenAbstract:Data were acquired by the Passive and Active L- and S-band Airborne Sensor (PALS) during the 1999 Southern Great Plains (SGP99) experiment in Oklahoma to study remote sensing of soil moisture in vegetated terrain using low-frequency microwave radiometer and radar measurements. The PALS instrument measures radiometric brightness temperature and radar backscatter at L- and S-band frequencies with multiple polarizations and approximately equal spatial resolutions. The data acquired during SGP99 provide information on the sensitivities of multichannel low-frequency passive and active measurements to soil moisture for vegetation conditions including bare, pasture, and crop surface cover with field-averaged vegetation water contents mainly in the 0-2.5 kg m/sup -2/ range. Precipitation occurring during the experiment provided an opportunity to observe wetting and drying surface conditions. Good correlations with soil moisture were observed in the radiometric channels. The 1.41-GHz horizontal-polarization channel showed the greatest sensitivity to soil moisture over the range of vegetation observed. For the fields sampled, a radiometric soil moisture retrieval accuracy of 2.3% volumetric was obtained. The radar channels showed significant correlation with soil moisture for some individual fields, with greatest sensitivity at 1.26-GHz vertical copolarized channel. However, variability in vegetation cover degraded the radar correlations for the combined field data. Images generated from data collected on a sequence of flight lines over the watershed region showed similar patterns of soil moisture change in the radiometer and radar responses. This indicates that under vegetated conditions for which soil moisture estimates may not be feasible using current radar algorithms, the radar measurements nevertheless show a response to soil moisture change, and they can provide useful information on the spatial and temporal variability of soil moisture. An illustration of the change detection approach is given.
Jaewook Jung - One of the best experts on this subject based on the ideXlab platform.
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results of the isprs benchmark on urban object detection and 3d building reconstruction
Isprs Journal of Photogrammetry and Remote Sensing, 2014Co-Authors: Franz Rottensteiner, Uwe Breitkopf, Markus Gerke, Gun-ho Sohn, Jan Dirk Wegner, Jaewook JungAbstract:For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by Airborne Sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of Airborne image and laserscanner data, has been made available to the scientific community by ISPRS WGIII/4. Researchers were encouraged to submit their results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current Airborne Sensor data, but also common problems of state-of-the-art methods.
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THE ISPRS BENCHMARK ON URBAN OBJECT CLASSIFICATION AND 3D BUILDING RECONSTRUCTION
ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, 2012Co-Authors: Franz Rottensteiner, S. Benítez, Markus Gerke, Caroline Baillard, Jaewook Jung, Gun-ho Sohn, Uwe BreitkopfAbstract:For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by Airborne Sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of Airborne image and laserscanner data, has been made available to the scientific community. Researchers were encouraged to submit results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current Airborne Sensor data, but also common problems of state-of-the-art methods.
J A Sobrino - One of the best experts on this subject based on the ideXlab platform.
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land surface emissivity retrieval from Airborne Sensor over urban areas
Remote Sensing of Environment, 2012Co-Authors: R Oltracarrio, J A Sobrino, B Franch, Francoise NerryAbstract:Abstract In this paper we compare three different methodologies to retrieve land surface emissivity (LSE) over urban areas: the NDVI thresholds method, the temperature and emissivity separation (TES) algorithm and the temperature independent spectral indices (TISI) algorithm. The methodologies were applied to the Airborne Hyperspectral Scanner (AHS) imagery acquired during the Dual-use European Security IR Experiment 2008 (DESIREX 2008) experimental campaign over the city of Madrid (Spain). The images have a spatial resolution of 4 m. The retrieved values are compared to in situ data measured during the campaign at 4 sites. Results show a good performance of the TISI and the TES algorithms over urban surfaces, while the NDVI threshold method does not appear to be capable to distinguish between different artificial surfaces. The land surface temperature (LST) was retrieved with a split window algorithm, using the three different LSE products. Differences of up to 3 K were realized in some surfaces when different LSE maps were used. Over artificial urban surfaces TES and TISI showed better agreement with in-situ data than NDVI. Finally, the TES is the algorithm that best reproduces the LST over an urban area, without the requirement of high temporal resolution of the Sensor.
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detection of water stress in an olive orchard with thermal remote sensing imagery
Agricultural and Forest Meteorology, 2006Co-Authors: G Sepulcrecanto, J A Sobrino, Pablo J Zarcotejada, J C Jimenezmunoz, Francisco J Villalobos, E De MiguelAbstract:Abstract An investigation of the detection of water stress in non-homogeneous crop canopies such as orchards using high-spatial resolution remote sensing thermal imagery is presented. An Airborne campaign was conducted with the Airborne Hyperspectral Scanner (AHS) acquiring imagery in 38 spectral bands in the 0.43–12.5 μm spectral range at 2.5 m spatial resolution. The AHS Sensor was flown at 7:30, 9:30 and 12:30 GMT in 25 July 2004 over an olive orchard with three different water-deficit irrigation treatments to study the spatial and diurnal variability of temperature as a function of water stress. A total of 10 AHS bands located within the thermal-infrared region were assessed for the retrieval of the land surface temperature using the split-window algorithm, separating pure crowns from shadows and sunlit soil pixels using the reflectance bands. Ground truth validation was conducted with infrared thermal Sensors placed on top of the trees for continuous thermal data acquisition. Crown temperature ( T c ), crown minus air temperature ( T c − T a ), and relative temperature difference to well-irrigated trees ( T c − T R , where T R is the mean temperature of the well-irrigated trees) were calculated from the ground Sensors and from the AHS imagery at the crown spatial resolution. Correlation coefficients for T c − T R between ground IRT Sensors and Airborne image-based AHS estimations were R 2 = 0.50 (7:30 GMT), R 2 = 0.45 (9:30 GMT) and R 2 = 0.57 (12:30 GMT). Relationships between leaf water potential and crown T c − T a measured with the Airborne Sensor obtained determination coefficients of R 2 = 0.62 (7:30 GMT), R 2 = 0.35 (9:30 GMT) and R 2 = 0.25 (12:30 GMT). Images of T c − T a and T c − T R for the entire field were obtained at the three times during the day of the overflight, showing the spatial and temporal distribution of the thermal variability as a function of the water deficit irrigation schemes.
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spatial variability of crop water stress in an olive grove with high spatial thermal remote sensing imagery
Precision agriculture '05. Papers presented at the 5th European Conference on Precision Agriculture Uppsala Sweden, 2005Co-Authors: G Sepulcrecanto, J A Sobrino, Pablo J Zarcotejada, J C Jimenezmunoz, Francisco J Villalobos, J V StaffordAbstract:The Airborne Hyperspectral Scanner (AHS) was used to acquire images with a 2.5 m spatial resolution in the visible, near infrared and thermal spectral regions over an olive orchard in southern Spain to study the spatial variability of water stress. The AHS Sensor was equipped with 20 channels of 20 nm bandwidth in the visible and near infrared region, 1 channel of 200 nm bandwidth, 42 channels of 13 nm bandwidth in the mid infrared, 7 channels of 300nm bandwidth for short-wave infrared, and 10 channels of 400nm in the long-wave infrared spectral region. Aircraft flights were scheduled at 7:30, 9:30 and 12:30 GMT in July 2004 to study the spatial and temporal variation of orchard tree temperatures as a function of the diurnal variation of water stress. Water and bare soil temperatures were measured simultaneously to the Airborne Sensor overflights to calibrate the thermal AHS imagery, acquiring atmospheric optical thickness at the time of image collection. Imagery was processed applying geometric, radiometric and atmospheric corrections. The high spatial resolution AHS data enabled the temperature of the top of the tree to be targeted, minimizing structural mixed pixel effects. Olive tree emissivities were measured in the field with a CIMEL instrument, and the soil emissivity was measured using a bottomless box. Water potential, photosynthesis, and stomatal conductance were measured weekly in olive trees under 3 different water stress treatments from June to November 2004 to track the effects of water stress on the trees’ condition and functioning. Infrared Sensors were placed on top of the trees for diurnal thermal data collection and validation of the thermal imagery collected. Results of the remote sensing thermal analysis show that this methodology allows mapping of the spatial variability of water stress with a potential applicability in precision agriculture for management of controlled deficit irrigation methods.
Adriano Camps - One of the best experts on this subject based on the ideXlab platform.
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mir the microwave interferometric reflectometer a new Airborne Sensor for gnss r advanced research
International Geoscience and Remote Sensing Symposium, 2013Co-Authors: R Onrubia, Adriano Camps, D Pascual, A Alonsoarroy, Hyuk ParkAbstract:The use of Global Navigation Satellite Signals (GNSS) in reflectometric applications (GNSS-R) is highly extended in remote sensing applications, such as sensing sea state, soil moisture or ice layer characterization. There are two main techniques in this field: the conventional GNSS-R, that achieves high SNRs by cross-correlating the received signal with a replica of the transmitted one but, with a low resolution due to narrow bandwidth of the signals, and the interferometric GNSS-R, which achieves better resolutions but with lower SNRs since it directly correlates the direct and reflected signals. The Microwave Interferometric Reflectometer (MIR) is a new Sensor that will use high-directivity, multiband and steerable arrays to achieve higher SNRs in the interferometric technique. Additionally, it will also apply the conventional technique. All these capabilities will be applied simultaneously to two beams at each band (L1 and L5 / E1 and E5). This work describes this concept instrument and the first prototypes will be presented at the conference.
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a change detection algorithm for retrieving high resolution soil moisture from smap radar and radiometer observations
IEEE Transactions on Geoscience and Remote Sensing, 2009Co-Authors: Maria Piles, Dara Entekhabi, Adriano CampsAbstract:A change detection algorithm has been developed in order to obtain high-resolution soil moisture estimates from future Soil Moisture Active and Passive (SMAP) L-band radar and radiometer observations. The approach combines the relatively noisy 3-km radar backscatter coefficients and the more accurate 36-km radiometer brightness temperature into an optimal 10-km product. In preparation for the SMAP mission, an observation system simulation experiment (OSSE) and field experimental campaigns using the Passive and Active L- and S-band Airborne Sensor (PALS) have been conducted. We use the PALS Airborne observations and OSSE data to test the algorithm and develop an error budget table. When applied to four-month OSSE data, the change detection method is shown to perform better than direct inversion of the radiometer brightness temperatures alone, improving the root mean square error by 2% volumetric soil moisture content. The main assumptions of the algorithm are verified using PALS data from the soil moisture experiments held during June-July 2002 (Soil Moisture Experiment 2002) in Iowa. The algorithm error budget is estimated and shown to meet SMAP science requirements.