Evaluation of Rainfall Products DerivedFrom Satellites and Microwave Linksfor The Netherlands
Rios Gaona, Manuel F. ; Overeem, Aart ; Brasjen, A.M. ; Meirink, Jan Fokke ; Leijnse, Hidde ; Uijlenhoet, Remko - \ 2017
IEEE Transactions on Geoscience and Remote Sensing 55 (2017)12. - ISSN 0196-2892 - p. 6849 - 6859.
Cloud physical properties (CPP) - commercial microwave link (CML) - global precipitation measurement mission (GPM) - Integrated Multi-satellitE Retrievals for GPM (IMERG) - Meteorological radar - Meteosat Second Generation (MSG) - Microwave measurement - nighttime infrared (IR) precipitation estimation (NIPE) - radar - rain - Satellites - satellites. - Spaceborne radar - Spatial resolution
High-resolution inputs of rainfall are important in hydrological sciences, especially for urban hydrology. This is mainly because heavy rainfall-induced events such as flash floods can have a tremendous impact on society given their destructive nature and the short time scales in which they develop. With the development of technologies such as radars, satellites and (commercial) microwave links (CMLs), the spatiotemporal resolutions at which rainfall can be retrieved are becoming higher and higher. For the land surface of The Netherlands, we evaluate here four rainfall products, i.e., link-derived rainfall maps, Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) Final Run (IMERG--Global Precipitation Measurement mission), Meteosat Second Generation Cloud Physical Properties (CPP), and Nighttime Infrared Precipitation Estimation (NIPE). All rainfall products are compared against gauge-adjusted radar data, considered as the ground truth given its high quality, resolution, and availability. The evaluation is done for seven months at 30 min and 24,h. Overall, we found that link-derived rainfall maps outperform the satellite products and that IMERG outperforms CPP and NIPE. We also explore the potential of a CML network to validate satellite rainfall products. Usually, satellite derived products are validated against radar or rain gauge networks. If data from CMLs would be available, this would be highly relevant for ground validation in areas with scarce rainfall observations, since link-derived rainfall is truly independent of satellite-derived rainfall. The large worldwide coverage of CMLs potentially offers a more extensive platform for the ground validation of satellite estimates over the land surface of the Earth.
Rainfall estimation for hydrology using volumetric weather radar
Hazenberg, P. - \ 2013
Wageningen University. Promotor(en): Remko Uijlenhoet, co-promotor(en): Hidde Leijnse; G. Delrieu. - S.l. : s.n. - ISBN 9789461736307 - 232
regen - schatting - radar - hydrologie - meting - fouten - neerslag - rain - estimation - radar - hydrology - measurement - errors - precipitation
This thesis focuses specifically on weather radar rainfall measurements in strati form precipitation. In North-Western Europe this type of precipitation is most dominant in winter and leads to the largest hydro logical response of catchments. Unfortunately, the quality of uncorrected radar rainfall estimates starts decreasing at relatively close range from the radar for this type of precipitation. Therefore, as a first approach, a number of previously proposed radar error correction algorithms were applied in this thesis. The implementation of these methods shows a positive impact on the quality of the obtained precipitation measurements as compared to rain gauges. However, the traditional approach of applying a uniform Eulerian based algorithm for the entire radar umbrella to correct for VPR, limits its impact to improve the corrected weather radar precipitation measurements
Rainfall variability in the Netherlands from radars, rain gauges, and disdrometers
Beek, R. van de - \ 2013
Wageningen University. Promotor(en): Remko Uijlenhoet, co-promotor(en): Hidde Leijnse. - S.l. : s.n. - ISBN 9789461736437 - 128
regen - neerslag - radar - regenmeters - hydrologie - meteorologie - schattingen - schatting - meettechnieken - meetsystemen - nederland - rain - precipitation - radar - rain gauges - hydrology - meteorology - estimates - estimation - measurement techniques - measurement systems - netherlands
Chapter 1. This thesis presents studies on the variability of precipitation in the Netherlands from datasets collected by radars, rain gauges and disdrometers. Accurate rainfall estimates are highly relevant in hydrology, meteorology and climatology as precipitation has a large impact on society. Precipitation has been studied extensively in the past, although it is impossible to describe all processes and behavior involved. This thesis attempts to add to the knowledge on precipitation. In the first chapter a short overview of rainfall variability at different scales is presented together with the most common instruments for measuring precipitation.
Chapter 2. The spatial variability of daily rainfall accumulations is studied. Ninety-day averaged semi-variograms are created based on a 30-year data set gathered by automatic stations operated by the Royal Netherlands Meteorological Institute (KNMI). This is complemented by a one-year dataset of 10 gauges within a 5 km radius around CESAR (Cabauw Experimental Site for Atmospheric Research) in the center of the Netherlands. It is shown that it is possible to derive an average semi-variogram that describes the climatology of daily precipitation for each day of the year.
Chapter 3. The study of chapter 2 is extended by investigating accumulation intervals shorter than daily scales. These are at 12, 8, 6, 4, 3, 2 and 1-hour accumulation intervals. It is shown that at shorter temporal scales the behavior of semi-variograms of precipitation still shows a clear seasonal trend. At hourly and two-hourly accumulation intervals the signal of the range becomes fairly constant during the summer due to the limited accumulation period, the frequent occurrence of convective precipitation, and measurement errors. This illustrates the lower limit of using cosine functions to describe variogram parameters. By fitting a power-law function through the different cosine parameters it is possible to describe the semi-variance of precipitation at scales between 1 and 24 hours using a limited set of equations.
Chapter 4. Different sources of error affecting rainfall estimates by weather radar are identified. By focussing on precipitation near a C-band radar some of these sources are reduced, which allows to focus on a limited set of error sources. These are radar calibration, ground clutter, wet radome attenuation and variations in rain drop size distribution. An event that caused high precipitation amounts in a band along the center of the Netherlands and more than 50~mm near the radar between the 25th and the 27th of August 2010 is studied. Without any correction and by applying a standard Marshall-Palmer Z-R relation the radar is found to underestimate by approximately 50% with respect to the rain gauge measurements. Using the sun for calibration a correction of 1 dB is applied. Clutter is corrected by subtracting a clear sky clutter map as this proves to provide better results than the standard doppler filter. Wet-radome attenuation is corrected by looking at the amount of attenuation at a known strong clutter pixel near the radar. Disdrometer data near the radar are used to derive accurate Z-R relations specific to the precipitation of the event. These corrections combined provide very promising results with a slight overestimation of the quantitative precipitation estimates (QPE) from the radar by 5 to 8%.
Chapter 5. An extensive dataset of 195 precipitation events measured by an X-band radar (SOLIDAR) is used to study precipitation at a high spatial resolution of 120 m and a high temporal resolution of 16 s. This study shows the benefit of using such high resolution X-band radars over flat terrain. The errors in the radar measurements are first assessed and corrected as well as possible by considering different techniques. These errors are calibration, ground clutter and attenuation. Finally, five strongly different precipitation events are studied in detail to illustrate the strengths and weaknesses of the X-band weather radar.
Chapter 6. The variability and possible measurement methods of precipitation have been studied. It was shown that precipitation spatial and temporal variability has a clear statistical signal by analyzing variograms for different accumulation intervals. Weather radars were also shown to be able to give good estimates of precipitation at ground level as well as detailed information on the spatial variability. Some recommendations are given to perform follow up studies. For chapters 2 & 3 it is recommended to use a larger and more detailed dataset, which also incorporates Belgian and German data. This would allow the study of anisotropy in the semi-variograms as well as extending the analysis to accumulation times shorter than 1 hour and longer than 24 hours. For chapter 4 it is recommended to study pixels located further away from the radar. While other error sources would become more pronounced it would be possible to study the applicability of the proposed corrections at longer ranges. Studying the wet-radome attenuation with several strong clutter pixels near the radar would allow the study of wind-effects on wet-radome attenuation, possibly allowing corrections using measurements of (Doppler) wind-speed and direction. Finally, in chapter 5 it is recommended to study the successor of SOLIDAR, IDRA, which is currently operational at CESAR. This radar is a polarimetric radar, allowing a more detailed study of precipitation together with the data from other instruments at this location and the C-band radar of KNMI, which is located close to this location at approximately 23 km.
Comparison of regression and kriging techniques for mapping the average annual precipitation of Turkey.
Bostan, P.A. ; Heuvelink, G.B.M. ; Akyurek, S.Z. - \ 2012
International Journal of applied Earth Observation and Geoinformation 19 (2012). - ISSN 0303-2434 - p. 115 - 126.
spatial interpolation - rainfall - prediction - elevation - variables - radar
Accurate mapping of the spatial distribution of annual precipitation is important for many applications in hydrology, climatology, agronomy, ecology and other environmental sciences. In this study, we compared five different statistical methods to predict spatially the average annual precipitation of Turkey using point observations of annual precipitation at meteorological stations and spatially exhaustive covariate data (i.e. elevation, aspect, surface roughness, distance to coast, land use and eco-region). The methods compared were multiple linear regression (MLR), ordinary kriging (OK), regression kriging (RK), universal kriging (UK), and geographically weighted regression (GWR). Average annual precipitation of Turkey from 1970 to 2006 was measured at 225 meteorological stations that are fairly uniformly distributed across the country, with a somewhat higher spatial density along the coastline. The observed annual precipitation varied between 255 mm and 2209 mm with an average of 628 mm. The annual precipitation was highest along the southern and northern coasts and low in the centre of the country, except for the area near the Van Lake, Keban and Ataturk Dams. To compare the performance of the interpolation techniques the total dataset was first randomly split in ten equally sized test datasets. Next, for each test data set the remaining 90% of the data comprised the training dataset. Each training dataset was then used to calibrate and apply the spatial prediction model. Predictions at the test dataset locations were compared with the observed test data. Validation was done by calculating the Root Mean Squared Error (RMSE), R-square and Standardized MSE (SMSE) values. According to these criteria, universal kriging is the most accurate with an RMSE of 178 mm, an R-square of 0.61 and an SMSE of 1.06, whilst multiple linear regression performed worst (RMSE of 222 mm, R-square of 0.39, and SMSE of 1.44). Ordinary kriging, UK using only elevation and geographically weighted regression are intermediate with RMSE values of 201 mm, 212 mm and 211 mm, and an R-square of 0.50, 0.44 and 0.45, respectively. The RK results are close to those of UK with an RMSE of 186 mm and R-square of 0.57. The spatial extrapolation performance of each method was also evaluated. This was done by predicting the annual precipitation in the eastern part of Turkey using observations from the western part. Results showed that MLR, GWR and RK performed best with little differences between these methods. The large prediction error variances confirmed that extrapolation is more difficult than interpolation. Whilst spatial extrapolation benefits most from covariate information as shown by an RMSE reduction of about 60 mm, in this study covariate information was also valuable for spatial interpolation because it reduced the RMSE with on average 30 mm.
Microwave links for rainfall estimation in urban environment: insights from an experimental setup in Luxembourg city
Fenicia, F. ; Pfister, L. ; Kavetski, D. ; Matgen, P. ; Iffly, J.F. ; Hoffman, L. ; Uijlenhoet, R. - \ 2012
Journal of Hydrology 464-465 (2012). - ISSN 0022-1694 - p. 69 - 78.
path-averaged rainfall - dual-frequency - attenuation - resolution - fields - gauges - radar
Although the theoretical aspects of rainfall monitoring through microwave links are quite well established, only few practical applications have evaluated this technique in an operational setting. Microwave links are of particular interest in urban areas, where high frequency measurements are needed due to the fast hydrological response of the system, and link networks are usually already in-place. This study presents the first results of an on-going experiment in Luxembourg-City, which includes two dual-frequency links and several rain gauges at intermediate locations along the links. The experimental set-up allows comparing rain rate estimates based on the individual frequencies as well as estimates based on the difference between the two frequencies. We compared several models for expressing the relationship between attenuation and rain rate, including different baseline estimation methods such as the traditional constant-baseline model and a one-parameter model based on a first order low-pass filter. The models were evaluated using a Bayesian approach and subjected to posterior scrutiny based on several diagnostics. In contrast to previous research, our results indicated that estimates based on the attenuation difference appeared poorer than the estimates based on individual frequencies. The one-parameter baseline estimation method provided consistently better results than the traditional constant-baseline method, which justifies the increased model complexity. Uncertainty of model predictions was relatively large for low intensity rainfall, which highlights one of the limitations of this technique. Models were validated in different periods and on different links, in some cases demonstrating large bias. Model parameters were generally well-identifiable, though uncertainty in the rainfall predictions appeared under-estimated in some cases.
Climatology of daily rainfall semi-variance in The Netherlands
Beek, C.Z. van de; Leijnse, H. ; Torfs, P.J.J.F. ; Uijlenhoet, R. - \ 2011
Hydrology and Earth System Sciences 15 (2011)1. - ISSN 1027-5606 - p. 171 - 183.
spatial variability - daily precipitation - gauge measurements - extreme rainfall - united-states - radar - calibration - resolution - hydrology - sensitivity
Rain gauges can offer high quality rainfall measurements at their locations. Networks of rain gauges can offer better insight into the space-time variability of rainfall, but they tend to be too widely spaced for accurate estimates between points. While remote sensing systems, such as radars and networks of microwave links, can offer good insight in the spatial variability of rainfall they tend to have more problems in identifying the correct rain amounts at the ground. A way to estimate the variability of rainfall between gauge points is to interpolate between them using fitted variograms. If a dense rain gauge network is lacking it is difficult to estimate variograms accurately. In this paper a 30-year dataset of daily rain accumulations gathered at 29 automatic weather stations operated by KNMI (Royal Netherlands Meteorological Institute) and a one-year dataset of 10 gauges in a network with a radius of 5 km around CESAR (Cabauw Experimental Site for Atmospheric Research) are employed to estimate variograms. Fitted variogram parameters are shown to vary according to season, following simple cosine functions. Semi-variances at short ranges during winter and spring tend to be underestimated, but semi-variances during summer and autumn are well predicted.
Extreme value modeling of areal rainfall from weather radar
Overeem, A. ; Buishand, T.A. ; Holleman, I. ; Uijlenhoet, R. - \ 2010
Water Resources Research 46 (2010). - ISSN 0043-1397
neerslag - frequentieverdeling - duur - meteorologische waarnemingen - radar - precipitation - frequency distribution - duration - meteorological observations - radar - precipitation annual maxima - frequency estimation - reduction factors - intervals - curves - sites
An 11 year high-quality radar rainfall data set is used to abstract annual maximum rainfall depths for durations of 15 min to 24 h and area sizes of 6 to 1.7 × 103 km2 for the Netherlands. Generalized extreme value (GEV) distributions are fitted to the annual maxima. A new method is presented to describe the distribution of extreme areal rainfall depths by modeling GEV parameters as a function of both duration and area size. This leads to a semiempirical expression from which quantiles of extreme rainfall depths can be obtained for a chosen duration, area size, and return period. The uncertainties in these quantiles are calculated using the bootstrap method. Radar-based areal reduction factors (ARFs) are derived. These ARFs are comparable to those based on high-density rain gauge networks derived from the literature. It is concluded that radar data, after careful quality control, are suitable to estimate extreme areal rainfall depths
Buienradar brengt kans op extreme regenval in kaart
Overeem, A. - \ 2010
Het weer magazine : magazine voor de weerliefhebber 2010 (2010)4. - ISSN 1568-1629 - p. 31 - 33.
neerslag - regen - weersvoorspelling - radar - internet - meteorologische waarnemingen - riolering - pompstations - precipitation - rain - weather forecasting - meteorological observations - sewerage - pumping stations
De KNMI-neerslagradars maken elke vijf minuten scans over heel Nederland, waarna vrijwel gelijk de neerslagintensiteitsbeelden kunnen worden bekeken op internet. Aangetoond is dat deze buienradars ook geschikt zijn om de kans op extreme hoeveelheden neerslag te bepalen. Handige informatie voor de ontwerpers van rioleringen en gemalen.
Automatic prediction of high-resolution daily rainfall fields for multiple extents: the potential of operational radar
Schuurmans, J.M. ; Bierkens, M.F.P. ; Pebesma, E.J. ; Uijlenhoet, R. - \ 2007
Journal of Hydrometeorology 8 (2007)6. - ISSN 1525-755X - p. 1204 - 1224.
radar - regen - hydrologie - modelleren - voorspelling - hydrologische gegevens - meettechnieken - meteorologische waarnemingen - radar - rain - hydrology - modeling - prediction - hydrological data - measurement techniques - meteorological observations - gauge data - stochastic interpolation - geostatistics - variability - design - scales - model
This study investigates the added value of operational radar with respect to rain gauges in obtaining high-resolution daily rainfall fields as required in distributed hydrological modeling. To this end data from the Netherlands operational national rain gauge network (330 gauges nationwide) is combined with an experimental network (30 gauges within 225 km2). Based on 74 selected rainfall events (March¿October 2004) the spatial variability of daily rainfall is investigated at three spatial extents: small (225 km2), medium (10 000 km2), and large (82 875 km2). From this analysis it is shown that semivariograms show no clear dependence on season. Predictions of point rainfall are performed for all three extents using three different geostatistical methods: (i) ordinary kriging (OK; rain gauge data only), (ii) kriging with external drift (KED), and (iii) ordinary collocated cokriging (OCCK), with the latter two using both rain gauge data and range-corrected daily radar composites¿a standard operational radar product from the Royal Netherlands Meteorological Institute (KNMI). The focus here is on automatic prediction. For the small extent, rain gauge data alone perform better than radar, while for larger extents with lower gauge densities, radar performs overall better than rain gauge data alone (OK). Methods using both radar and rain gauge data (KED and OCCK) prove to be more accurate than using either rain gauge data alone (OK) or radar, in particular, for larger extents. The added value of radar is positively related to the correlation between radar and rain gauge data. Using a pooled semivariogram is almost as good as using event-based semivariograms, which is convenient if the prediction is to be automated. An interesting result is that the pooled semivariograms perform better in terms of estimating the prediction error (kriging variance) especially for the small and medium extent, where the number of data points to estimate semivariograms is small and event-based semivariograms are rather unstable.
Spaceborne radar monitoring of forest fires and forest cover change : a case study in Kalimantan
Sugardiman, R.A. - \ 2007
Wageningen University. Promotor(en): Reinder Feddes, co-promotor(en): Dirk Hoekman. - [S.l.] : S.n. - ISBN 9789085046042 - 190
tropische regenbossen - regenbossen - bosbranden - kroondak - remote sensing - radar - monitoring - digitaal terreinmodel - kalimantan - tropical rain forests - rain forests - forest fires - canopy - remote sensing - radar - monitoring - digital elevation model - kalimantan
The devastation of tropical rain forests has been proven to have a significant effect on global climate change. The sustainability of these forests becomes a major concern for the international community. The Indonesian Ministry of Forestry (MOF) is eager to carry on forest inventory activities and to generate forest resources information.Advanced spaceborne radar techniques are a very promising tool to monitor forests. This technique is complementary with the existing spaceborne optical imagery which suffers too much from cloud cover. Radar provide reliable information on a regular basis and has been applied in various types of applications e.g. forest classification.The approach presented in this thesis includes. Firstly, multi-temporal classification of spaceborne Synthetic Aperture Radar (SAR) data using Iterated Conditional Modes which is proposed as a fast step of Maximum Likelihood classification in order to circumvent the slow image segmentation step. Secondly, slope correction dealing with steep slopes that considerable has geometric distortion. Thirdly, textural analysis has been applied to derive additional information layers in multi-temporal classification from fine structures in the radar images.The study focuses on three test site areas i.e. Sungai Wain test site area, the Gunung Meratustest site area and the NASA AirSAR PacRim-II test site area.This area experienced long drought periods associated with the El Niño Southern Oscillation (ENSO)phenomenon. For this study the severe ENSO event of 1997 - 1998 is of particular interest.
Hydrometeorological application of a microwave link: 2. Precipitation
Leijnse, H. ; Uijlenhoet, R. ; Stricker, J.N.M. - \ 2007
Water Resources Research 43 (2007). - ISSN 0043-1397 - p. W04417 - W04417.
path-averaged rainfall - dual-frequency - attenuation - radar - band - resolution - hydrology - gauges - size
The suitability of a 27-GHz microwave link for measuring path-averaged precipitation is investigated. Theoretical analyses show that the specific attenuation of an electromagnetic signal at this frequency varies nearly linearly with the rainfall intensity, which is ideal for line-integrating instruments. The dependence of this relation on the drop size distribution and on the temperature is small, so that uncertainties in these variables do not play large roles in the estimation of rainfall intensity. Data from an experiment with a 4.89-km microwave link and a line configuration of seven tipping bucket rain gauges are used to test whether this instrument is indeed suitable for the estimation of path-averaged rainfall. Results from this experiment show that the attenuation due to wet antennas can have a significant effect on the retrieved rainfall intensity. However, when a two-parameter wet antenna correction function is applied to the link data, comparisons with the rain gauge data show that the instrument is indeed well suited for the measurement of path-averaged rainfall
Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns
Caracciolo, C. ; Prodi, F. ; Uijlenhoet, R. - \ 2006
Atmospheric Research 82 (2006)1-2. - ISSN 0169-8095 - p. 137 - 163.
regen - neerslag - meettechnieken - meetsystemen - meteorologische instrumenten - druppelgrootte - rain - precipitation - measurement techniques - measurement systems - meteorological instruments - droplet size - 2-dimensional video disdrometer - size distribution measurements - joss-waldvogel disdrometer - raindrop spectra - distributions - radar - hydrometeors
The performances of two couples of disdrometers based on different measuring principles are compared: a classical Joss¿Waldvogel disdrometer and a recently developed device, called the Pludix tested in Ferrara, Italy, and Pludix and the two-dimensional video disdrometer (2DVD) tested in Cabauw, The Netherlands. First, the measuring principles of the different instruments are presented and compared. Secondly, the performances of the two pairs of disdrometers are analysed by comparing their rain amounts with nearby tipping bucket rain gauges and the inferred drop size distributions. The most important rainfall integral parameters (e.g. rain rate and radar reflectivity) and drop size distribution parameters are also analysed and compared. The data set for Ferrara comprises 13 rainfall events, with a total of 20 mm of rainfall and a maximum rain rate of 4 mm h¿ 1. The data set for Cabauw consists of 9 events, with 25¿50 mm of rainfall and a maximum rain rate of 20¿40 mm h¿ 1. The Pludix tends to underestimate slightly the bulk rainfall variables in less intense events, whereas it tends to overestimate with respect to the other instruments in heavier events. The correspondence of the inferred drop size distributions with those measured by the other disdrometers is reasonable, particularly with the Joss¿Waldvogel disdrometer. Considering that the Pludix is still in a calibration and testing phase, the reported results are encouraging. A new signal inversion algorithm, which will allow the detection of rain drops throughout the entire diameter interval between 0.3 and 7.0 mm, is under development.
Radar techniques for identifying precipitation type and estimating quantity of precipitation
Sálek, M. ; Cheze, J.L. ; Handwerker, J. ; Delobbe, L. ; Uijlenhoet, R. - \ 2004
Luxembourg : Cost office (EUR 21368 EN) - ISBN 9789289800044 - 55
neerslag - regenmeters - radar - meteorologische waarnemingen - modellen - hydrologie - precipitation - rain gauges - radar - meteorological observations - models - hydrology
Tropical forest mapping at regional scale using the GRFM SAR mosaics over the Amazon in South America
Sgrenzaroli, M. - \ 2004
Wageningen University. Promotor(en): Reinder Feddes, co-promotor(en): Dirk Hoekman. - [S.l.] : S.n. - ISBN 9789058089953 - 260
tropische bossen - cartografie - regionale verkenningen - amazonas - remote sensing - landclassificatie - landsat - radar - wavelets - tropical forests - mapping - regional surveys - amazonas - remote sensing - land classification - landsat - radar - wavelets
The work described in this thesis concerns the estimation of tropical forest vegetation cover in the Amazon region using as data source a continental scale high resolution (100 m) radar mosaic as data source. The radar mosaic was compiled by the Jet Propulsion Laboratory (NASA JPL) using approximately 2500 JERS-1 L-band scenes acquired in the context of the Global Rain Forest Mapping project by the National Agency for Space Development of Japan (NASDA).
A novel classification scheme was developed for this purpose.The underpinning method is based on a wavelet signal decomposition/reconstruction technique. In the wavelet reconstruction algorithm, an adaptive wavelet coefficient threshold is introduced to distinguish wavelet maxima related to the transition between classes from maxima related to textural within-class variation.
Two image-labeling techniquesare tested and compared: i) a region-growing algorithm and ii) a per-pixel two-stage hybrid classifier.
The large data volume problem was tackled by developing a special purpose processing chain that works on partially overlapping tiles extracted from the mosaic
Quantitative validation and error analysis of the classifiers' performance and their generalization capability to regional scale are carried out using, as reference, maps derived from Landsat Thematic Mapper. A first result of the validation process is that the wavelet classifier provides a classification accuracy of 87% in forest/non-forest mapping. The analysis by site reveals that class degraded-forest is the major source of classification errors. The discrepancy between TM maps and SAR maps increases with increasing landscape spatial fragmentation.
A test on relative performances between the wavelet-based region growing segmentation technique and a conventional clustering technique (ISODATA) shows that the wavelet-based technique provides better accuracy and is capable of generalizing over the entire data set.
The issue of detecting the degraded-forest class - generally ignored by Amazonian deforestation mapping programs - is tackled using data acquired by both optical and SAR instruments . For optical data, a three-stage classification procedure is developed for detecting degraded forest classes in Landsat TM images. For SAR data, a multi-temporal speckle filtering technique is used to improve the signal to noise ratio.
Starting from the consideration that the discrepancy between TM maps and SAR maps increases with the landscape spatial fragmentation we test an inductive learning methodology, capable of correcting SAR regional-scale maps using local classification estimates at a higher resolution , is tested.
Finally some ideas and projects are put forward which are meant to be working hypotheses for future actions and practical approaches to reduce the pressure over the tropical forest ecosystem.
Parameterization of rainfall microstructure for radar meteorology and hydrology
Uijlenhoet, R. - \ 2002
Wageningen : Wageningen Agricultural University (Rapport / Wageningen University, Environmental Sciences, Sub-department Water Resources 109) - ISBN 9789058081568 - 279
regen - hydrologie - meteorologie - neerslag - remote sensing - radar - druppelgrootte - distributie - rain - hydrology - meteorology - precipitation - remote sensing - radar - droplet size - distribution
ENVISAT forest monitoring Indonesia
Hoekman, D.H. ; Vissers, M.A.M. ; Sugardiman, R.A. ; Vargas, J. - \ 2002
The RADARSAT International (RSI) RADARSAT-2 e-Newsletter 2 (2002)7. - p. 68 - 68.
remote sensing - radar - tropische regenbossen - geografische informatiesystemen - landclassificatie - vegetatie - bosbranden - monitoring - kalimantan - indonesië - remote sensing - radar - tropical rain forests - geographical information systems - land classification - vegetation - forest fires - monitoring - kalimantan - indonesia
To support the introduction of operational radar forest monitoring systems in Indonesian a demonstration is executed at the Tropenbos study area in East-Kalimantan. Interest focuses on fulfilling information needs relating to land cover change, fire risk and fire damage monitoring, with main emphasis on early detection.
Observatie van tropische bossen met beeldvormende radar
Hoekman, D.H. - \ 2002
Ecologie en ontwikkeling 10 (2002)1/2. - ISSN 0928-6470 - p. 16 - 18.
tropische bossen - remote sensing - radar - indonesië - nederland - internationale samenwerking - tropical forests - remote sensing - radar - international cooperation - indonesia - netherlands
Polarimetric data for tropical forest monitoring : studies at the Colombian Amazon
Quiñones Fernández, M. - \ 2002
Wageningen University. Promotor(en): R.A. Feddes; D.H. Hoekman. - Wageningen : Tropenbos International - ISBN 9789058087508 - 184
tropische bossen - monitoring - remote sensing - polarimetrie - radar - cartografie - ontbossing - biomassa - amazonia - colombia - tropical forests - monitoring - remote sensing - polarimetry - radar - mapping - deforestation - biomass - amazonia - colombia
An urgent need exists for accurate data on the actual tropical forest extent, deforestation, forest structure, regeneration and diversity. The availability of accurate land cover maps and tropical forest type maps, and the possibility to update these maps frequently, is of great importance for the development and success of monitoring systems. For areas like the Amazon the use of optical remote sensing systems as the source of information, is impeded by the permanent presence of clouds that affect the interpretation and the accuracy of the algorithms for classification and map production. The capabilities of radar systems to acquire cloud free images and the penetration of the radar waves into the forest canopy make radar systems suitable for monitoring activities and provide additional and complementary data to optical remote sensing systems. Information regarding forest structure, forest biomass, and vegetation cover and flooding can be associated with radar images because of the typical wave-object interaction properties of the radar systems.
In this thesis new algorithms for the classification of radar images and the production of accurate maps are presented. The production of specific maps is studied by applying the developed algorithms to two different study areas in the Colombian Amazon. The first site, San José del Guaviare, is a colonisation area with active deforestation activities and dynamic land cover change. The second area is a pristine natural forest with high diversity of landscapes.
A detailed statistical description of the polarimetric AirSAR data is made in terms of backscatter (gamma values), polarimetric phase difference and polarimetric correlation. This approach allows a better interpretation of physical backscatter mechanisms important for interpretation of images in relation to ground parameters. Theoretical cumulative probability density distributions (pdf) are used to describe the mean field values and the standard deviation for a class. A Gausian distribution is used to describe the field average gamma values; a circular Gausian distribution is used to describe the field average HH-VV phase difference and a Beta distribution is used to described the field average HH-VV phase correlation. The accuracy of the estimation of the field-averaged values depends on the level of speckle, i.e. number of independent looks. This effect is included in the calculation of the pdf's and therefore can be simulated.
For the Guaviare site the classification algorithm is used to assess the AirSAR data in the production of a land cover type map. Classification accuracies are calculated for different combinations of bands and level of speckle. An accuracy of 98.7% was calculated for a map when combining L-HV and P-RR polarisations. Confusion between classes are studied to evaluate the use of radar bands for monitoring activities, e.g. loss of forest or detection of new deforested areas. In addition a biomass map is created by using the empirical relationship between the combination of the same radar bands and the biomass estimations from 28 plots as measured in the field. The agreement of the biomass map with the land cover map is used to evaluate the biomass classification.
For the Araracuara site the classification algorithm is used to assess the use of polarimetric data for forest structural type mapping and indirect forest biophysical characterisation. 23 field-measured plots used for forest structural characterisation are used to assess the accuracy of the classification. A new SAR derived legend is more suitable for the SAR map allowing better physical interpretation of results. A method based on iterated conditional modes is introduced to create maps from the classified radar images, increasing in most of the cases the accuracy of the classification. The structural type map with 15 classes can be classified with accuracies ranging from 68% to 94% depending on the classification and the mapping approach. The relationship between forest structure and polarimetric signal properties is studied in detail by using a new decomposition of polarimetric coherence, based on a simple physical description of the wave-object interactions. The accuracy of the complex coherence is described using the complex Wishart distribution. In addition for the same area, a biomass map is created using the previous structural type characterisation as the basis for the classification, overcoming problems as the well know radar signal saturation.
The possibilities and restrictions of creating biomass maps with AirSAR polarimetric images are deeply investigated. Two different approaches are proposed depending on the terrain conditions. A theoretical exploration on the physical limits for radar biomass inversion is made by using a new interface model, called LIFEFORM that describes the layered tropical forest in terms of scatterers. The UTARTCAN scattering model is used to analyse the effect of flooding, forest structure and terrain roughness in the biomass inversion.
Development of a Stochastic Model of Rainfall for Radar Hydrology
Uijlenhoet, R. - \ 2002
Wageningen : Wageningen Agricultural University (Rapport / Wageningen University, Environmental Sciences, Sub-department Water Resources 110) - 54
hydrologie - stochastische modellen - radar - neerslag - regen - remote sensing - meteorologie - hydrology - stochastic models - radar - precipitation - rain - remote sensing - meteorology
Raindrop size distribution and radar reflectivity-rain rate relationships for radar hydrology
Uijlenhoet, R. - \ 2001
Hydrology and Earth System Sciences 5 (2001)4. - ISSN 1027-5606 - p. 615 - 627.
regen - radar - hydrologie - meting - rain - radar - hydrology - measurement
The conversion of the radar reflectivity factor Z (mm6m-3) to rain rate R (mm h-1) is a crucial step in the hydrological application of weather radar measurements. It has been common practice for over 50 years now to take for this conversion a simple power law relationship between Z and R. It is the purpose of this paper to explain that the fundamental reason for the existence of such power law relationships is the fact that Z and R are related to each other via the raindrop size distribution. To this end, the concept of the raindrop size distribution is first explained. Then, it is demonstrated that there exist two fundamentally different forms of the raindrop size distribution, one corresponding to raindrops present in a volume of air and another corresponding to those arriving at a surface. It is explained how Z and R are defined in terms of both these forms. Using the classical exponential raindrop size distribution as an example, it is demonstrated (1) that the definitions of Z and R naturally lead to power law Z-R relationships, and (2) how the coefficients of such relationships are related to the parameters of the raindrop size distribution. Numerous empirical Z-R relationships are analysed to demonstrate that there exist systematic differences in the coefficients of these relationships and the corresponding parameters of the (exponential) raindrop size distribution between different types of rainfall. Finally, six consistent Z-R relationships are derived, based upon different assumptions regarding the rain rate dependence of the parameters of the (exponential) raindrop size distribution. An appendix shows that these relationships are in fact special cases of a general Z-R relationship that follows from a recently proposed scaling framework for describing raindrop size distributions and their properties.