ID: 51937
Title: Effect of hostacycline on kinetics of immune response of Indian major carp of Aeromonas hydrophila vaccine
Author: Ayub Ali
Editor: Dr. S. Palanichamy
Year: 2008
Publisher: Palani Paramount Publications, Vol 23, No 4 , December 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Journal of Ecobiology-An International Journal for Scientific Research on Environmental Biology, Toxicology and Inter Relations
Keywords: Hostacycline, Immune response, Carp, Aeromonas hydrophila vaccine
Abstract: Effect of hostacycline on kinetics of antibody production of Indian major carp, Labeo rohita (Hamilton) was studied using heat killed whole cell Aeromonas hydrophila vaccine. Hostacycline was administered either by intraperitoneal injection or through feed at therapeutic dose. Hostacycline treatment seemed to lower the antibody production by one log2 unit after priming and first booster and two log2 unit after second booster without affecting the kinetics of antibody production. The antibody titres in immunised control group were 64, 128 and 512 after priming, first booster and second booster on peak titre day while the corresponding titres in hostacycline treated group were 32, 64 and 128 respectively when immunised by injection. Immunised fish showed antibody peak on day 15 after priming and first booster and on day 7 after second booster both in control and hostacycline treated fish.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 51936
Title: Effect of water stress on morphological and biochemical attributes of Brunfelsia latifolia
Author: Akhila S Nair, Athira S Nair, T. K. Abraham and D. S.Jaya
Editor: Dr. S. Palanichamy
Year: 2008
Publisher: Palani Paramount Publications, Vol 23, No 4 , December 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Journal of Ecobiology-An International Journal for Scientific Research on Environmental Biology, Toxicology and Inter Relations
Keywords: Biomolecules, Membrane stability index, Pigments, Water stress, Brunfelsia latifolia
Abstract: Membrane Stability Index or Percentage of injury is considered as a key factor to detect the tissue damages caused by water deficit stress. The water scarcity stress induced changes in specific leaf area; pigments like chlorophyll, carotenoids, phaeophytin; and biomolecules like protein, carbohydrate and starch of Brunfelsia latifolia were detected. The percentage of injury increased with increased stress in both mature and tender leaves. The tender leaves suffered up to 80% of injury and the mature leaves up to 75% of injury during severe water stress. The tender leaves suffered more tissue damage than mature leaves. The percentage of injury is inversely proportional to the total chlorophyll, carotenoids, and phaeophtin content. As the stress progresses, all the pigment contents got depleted significantly. The carbohydrate and starch content decreased with progressed stress, while the protein content got augmented with increased stress. In the tender leaves of severely stressed plants, the protein content increased twice (7.38 mg/g/ F. wt.) compared to that of the control plants (3.55 mg/g F.wt). The increase in protein content with increased stress should need a special attention, because it may be due to the stress induced proteins formed as a response to water stress in order to overcome the tissue damages formed.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 51935
Title: Validation and comparison of advanced differential interferometry techniques: Murcia metropolitan area case study
Author: G. Herrera, R. Tomas, J.M.Lopez-Sanchez, J.Delgado, F.Vicente, J. Mulas, G.Cooksley, M.Sanchez, J.Duro, A. Arnaud, P.Blanco, S.Duque, J.J.Mallorqui, R. De la Vega-Panizo, O. Monserrat
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Advanced DInSAR, Ground surface deformation, Subsidence, Monitoring, Validation
Abstract: This paper is focused on the analysis of the performance of Stable Point Network (SPN) and Coherent Pixel Technique (CPT), which are Advanced Differential Interferometry Techniques (A-DInSAR) that estimate, among other results, mean deformation velocity maps of the ground surface and displacement time series from a SAR dataset. The test site is the metropolitan area of the city of Murcia (Spain) where a moderate slow subsidence induced by the overexploitation of aquifers in present. SAR data acquired between July 1995 and August 2005 from ERS and ENVISAT sensors have been processed by the SPN and CPT techniques and compared with in situ instrumental measurements assumed as reference. Experimental results have shown that both SPN and CPT techniques provide estimates of the deformation evolution in time with an absolute difference below 6 mm consistently in all companies. SPN vs extensometer, CPT vs extensometer and SPN vs CPT. The proposed validation and comparison experiment between both A-DInSAR techniques has been useful to observe their differences and complementarities.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51934
Title: Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions
Author: Uwe Soergel, Eckart Michaelsen, Antje Thiele, Erich Cadario, Ulrich Thoennessen
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: SAR images, Stereo, Building extraction, Production system, Perceptual grouping
Abstract: SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of air borne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge -based approach is applied, which is realized by a production system that codes a set suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach is tested using real SAR data of an urban scene.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51933
Title: Rapid mapping of high resolution SAR scenes
Author: F.Dell ' Acqua, P.Gamba, G.Lisini
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: SAR, Scene interpretation, Textural features, Road extraction
Abstract: This paper describes a semi-automatic procedure for cartographic mapping using high resolution SAR and interferometric SAR data. Various two-dimensional features are extracted and combined in order to achieve a basic yet effective recognition of the elements in the scene. Many relevant elements of the landscape are automatically extracted without requiring any deep interaction with the operator. Being based on geometric models assuming regularity of shapes and patterns, the procedure is well suited for detecting man-made features, such as the road network (outside and inside human settlements) and built-up areas. It can be used, however, to extract natural features, focussing on different geometric models. Moreover, extracted elements of the scene can be grouped into higher level ones, such as crossroads, bridges and overpasses, through data fusion at the feature level, because the procedure is characterized by a multi-scale, object-based approach.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51932
Title: Interferometric SAR for characterization fo ravines as a function of their density, depth and surface cover
Author: R.S.Chatterjee, S.K.Saha, Suresh Kumar, Sharika Mathew, R.C.Lakhera, V.K.Dadhwal
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Ravines, InSAR, Characterization, Chambal, India
Abstract: In recent years, the problem of ravine erosion with consequent loss of usable land has received much attention worldwide. The Chambal ravine zone in India is well known for being an extremely intricate, deeply incised network of ravines in a 10 km wide zone on the flanks of the Chambal River.lt occupies an area of ~0.5 million hectares at the expense of fertile agriculturral land of the Chambal Valley. The broad grouping of the ravines considering their reclamaiton potential, as carried out by previous workers based on visual interpretation of optical remote sensing data, in mostly descriptive in nature. In the present study, characterization of the ravines as a function of their erosion potential expressed through ravine density, ravine depth, and ravine surface cover was made in quantitative terms exploiting the preferential characteristics of side-looking, long-wavelength, coherent SAR signal and precision measurements associated with the InSAR technique.The outlines of ravines appear remarkably prominent in SAR backscattered amplitude images due to the high sensitivity of the SAR signal to terrain reggedness. Using local statistics-based meso and macro textural information of SAR backscattered amplitude images in 7 x 7 pixel windows (the pixel size being 20m x 20m), the ravine-affected area has been classified into three density classes, namely low, moderate, and high density ravine classes. C-band InSAR digital elevation models (DEMs) of sparsely vegetaed ravine areas essentially give the terrain height. From the pixel-by-pixel terrain height, the ravine depth was calculated by differencing the maximum and minimum terrain heights of the pixels in a 100m distance range. Considering the vertical precision of the ERS InSAR DEMs of ~5m and ravine depth classification by previous workers [Sharma H.S., 1968. Genesis and pattern of ravines of the Lower Chambal Valley, India. Special Issue. 21st International Geographical Union Congress 30(4), 14-24; Seth S.P., Bhatnagar, R.K., Chauhan, S.S., 1969. Reclamability classification and nature of ravines of Chambal Command Areas. Journal of soil and Water Conservation in India 17 (3-4), 39-44], three depth classes, namely shallow (<5m), moderately deep (5-20m), and deep (>20m) ravines, were made. Using temporal decorrelation property of the close time interval InSAR data pair, namely the ERS SAR tandem pair, four ravine surface cover classes, namely barren land, grass/scrub/crop land, sparse vegetation, and wet land/dense vegetation, could be delineated, which was corroborated by the spectral signatures in the optical range and selective ground truths.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51931
Title: Classification comparisons between dual-pol, compact polarimetric and quad-pol SAR imagery
Author: T.L. Ainsworth, J.P. Kelly, J.S.Lee
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, SAR, Classification
Abstract: We present a study of the polarimetric information content of dual-pol imaging modes and dual-pol imaging extended by polarimetric scattering models. We compare Wishart classifications both among the partial polarimetric datasets and against the full quad-pol dataset. Our emphasis is the inter-comparisons between the classification results based on dual -pol modes, compact polarimetric modes and scattering model extensions of the compact polarimetric modes. We primarily consider novel dual-pol modes, e.g. transmitting a circular polarization and receiving horizontal and vertical polarizations, and the pseudo-quad-pol data derived from polarimetric scattering models based on dual -pol data. We show that the overall classification accuracy of the Pseudo-quad-pol data is essential the same as the classification accuracy obtained directly employing the underlying dual -pol imagery.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51930
Title: Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data
Author: Wagner F. Silva, Bernardo F.T.Rudoff, Antonio R. Formaggio, Waldir R. Paradella, Jose C. Mura
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, Classification, Multi-polarization, Contextual classifier, imae classification
Abstract: Recent articles are indicating that polarimetric data provide significantly more information than conventional or multi-polarized images, particularly due to the additional phase information. The objective of this paper is to evaluate the multi-polarized and fully polarimetric L-band airborne SAR-R99B data, in terms of their capability to distinguish among different agricultural crops in the western part of Bahia State, Brazil. Emphasis was given to coffee, cotton and pasture crops which were at well developed growing stages. Discrimination amon gcrops was carried out using graphical analysis of mean backscatter values. Crop classification was performed for single and multiple polarizations, and fully polarimetric images with a classifier that uses the contextual Iterated Conditional Modes-ICM algorithm. The investigation confirmed the potential of L-band multi-polarized and polarimetric airborne SAR- R99B data to distinguish and classify agricultural crops in the tropical condition of the test-site. In addition, it clearly indicated the gradual and considerable improvement that was achieved going from single to three polarizations and from multi-polarized to fully polarimetric images.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51929
Title: Classifier ensembles for land cover mapping using multitemporal SAR imagery
Author: Bjorn Waske, Matthias Braun
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Decision tree, Random forests, Boosting, Multitemporal SAR data, Land cover classification
Abstract: SAR data are almost independent form weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e boosted decision tree and random forests) are applied to multi-temporal c-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forces are computationally highly efficient and are hence considered very well suited form land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51928
Title: Integration of optical and Synthetic Aperture Radar (SAR) imagery for delivering operational annual crop inventories
Author: Heather McNairn, Catherine Champagne, Jiali Shang, Delmar Holmstrom, Gordon Reichert
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 5 , September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Crops, classification, SAR, optical, Multi-polarization
Abstract: Agriculture plays a critical role within Canada ' s ecnomy and, as such, sustainability of this sector is of high importance. Targeting and monitoring programs designed to promote economic and enviornmental sustainability are a vital component within Canda ' s agricultural policy. A hierarchy of land information, including up to date information on cropping practices, is needed to measure the impacts of programs on land use decision-making and to gauge the environmental and economic benefits of these investments. A multi-year, multi-site research activity was completed to develop a robust methodology to inventory crops across Canada ' s large and diverse agricultural landscapes. To move towards operational implementation the methodology must deliver accurate crop inventories, with consistency and reliability. In order to meet these operational requirements and to mitigate risk associated with reliance on a single data sourcee , the methodology integrated both optical and synthetic Aperture Radar (SAR) imagery. The results clearly demonstrated that multi-temporal satellite data can successfully classify crops for a variety of cropping systems present across Canada. Overall accuracies of at least 85% were achieved, and most major crops were also classified to this level of accuracy. Although multi-temporal optical data would be the preferred data source for crop classification, a SAR-optical dataset (two Envisat ASAR images and one optical image) provided acceptable accuracies and will mitigate risk associated with operational implementation. The preferred dual-polarization mode would be VV-VH. Not only were these promising classification results repeated year after year, but the target accuracies were met consistently for multiple sites across Canada, all with varying cropping systems.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51927
Title: Synchronicity between satellite-measured leaf phenology and rainfall regimes in tropical forests
Author: Sunyurp Park
Editor: Russell G.Congalton
Year: 2009
Publisher: ASPRS, Vol 75, No 10 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: MODIS VI data, NDVI, mean annual precipitaton (MAP), enhanced vegetation index (EVI)
Abstract: The seasonal and interannual cycles of the canopy phenology of Hawaiian tropical ecosystems were extracted from seven -year MODIS VI data. NDVI responded sensitively to surface greenness of dry-to-mesic ecosystems, but it showed little change as mean annual precipitaton (MAP) surpassed 2,000 mm. Canopy greenness seasonality was strongest in dry areas, and its strength had and inverse relatioship with MAP (r = -0.75, P<0.0001). Study results report that the photosynthetic activity of dry biomes responded synchronously to annual rainfall patterns. As MAP increased, the enhanced vegetation index (EVI) had significant variations among wet biomes, and its canopy greenness cycles lagged behind seasonal rainfall cycles. As a result, greenness peaks of dry-to-mesic environments occurred in the west season, whereas those of wet enviornments (MAP>2,000 mm) occurred in the dry season. This result leads to a conclusion that forest productivity of perhumid environments may be limited by reduced solar hours.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51926
Title: Spectral distance decay: Assessing species beta-diversity by quantile regression
Author: Duccio Rocchini, Harini Nagendra, Rucha Ghate, and Brian S. Cade
Editor: Russell G.Congalton
Year: 2009
Publisher: ASPRS, Vol 75, No 10 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Regression analysis, species, beta-diversity,ordinary least square (OLS), quantile regression
Abstract: Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (OLS) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p<0.05) considering both OLS and quantile regression. Nonetheless, OLS regression estimate of mean decay rate was only half the decay rate indicated by the upper quantles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51925
Title: A wavelet and IHS Integration method to fuse high resolution SAR with moderate resolution multispectral images
Author: Gang Hong, Yun Zhang, and Bryan Mercer
Editor: Russell G.Congalton
Year: 2009
Publisher: ASPRS, Vol 75, No 10 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Synthetic aperture radar (SAR), multispectral (MS) images, IHS (Intensity, Hue and Saturation), Radarsat image, Landsat TM image
Abstract: Synthetic aperture radar (SAR) imaging can be a feasible alternative or a complement to traditional optical remote sensing techniques because it does not depend on solar illumination and weather conditions. The high spatial resolution of SAR, such as the Intermap STAR-3i airborne SAR image with 1.25 m spatial resolution, makes it applicable for high spatial resolution mapping purposes. However, difficulties sometimes exis in the interpretation of SAR images. Image fusion presents and alternative to improve the interpretability of SAR images by fusing the color information from moderate spatial resolution multispectral (MS) images. In this paper, a new fusion method based on the integration of wavelet transform and IHS (Intensity, Hue and Saturation) transform is porposed for SAR and MS fusion ot maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. Three data sets are used to evaluate the proposed fusion method: two sets are airborne SAR images with MS images at different spatial resolutions; the other set is a Radarsat image with a Landsat TM image. The fusion results are evaluated visually and statistically. The evaluation shows that successful results are achieved in the fusion of all SAR and MS images from a variety of sensors with significant spatial and spectral variations by using the proposed image fusion method.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51924
Title: Tree crown detection on multispectral VHR satellite imagery
Author: Ioannis N. Daliakopoulos, Emmanouil G. Grillakis, Aristeidis G. Koutroulis, and Ioannis K. Tsanis
Editor: Russell G.Congalton
Year: 2009
Publisher: ASPRS, Vol 75, No 10 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Arbor Crown Enumerator (ACE), Normalized Difference Vegetation Index (NDVI), Laplacian of the Gaussian (LOG), Keritis watershed, Island of Crete, environmental applications
Abstract: A new method called Arbor Crown Enumerator (ACE) was developed for tree crown detection from multispectral Very High-resolution (VHR) satellite imagery. ACE uses a combination of the Red band and Normalized Difference Vegetation Index (NDVI) thresholding, and the Laplacian of the Gaussian (LOG) blob detection method. This method minimizes the detection shortcomings of its individual components and provides a more accurate estimation of the number of tree crowns captures in an image sample. The ACE was applied successfully to sample images taken from a four-band QuickBird (0.7m x 0.7m) scene of Keritis watershed, in the Island of Crete. The method performs very well for different tree types, sizes and densities that may include non vegetation features such as roads and houses. Statistical analysis on the tree crown detection results from the sample images supports the agreement between the measurements and the simulations. The new method reduces considerably the effort of manual tree counting and can be used for environmental applications of fruit orchard, plantation and open forest population monitoring.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 51923
Title: Examination of the land surface temperature response for Santiago, Chile
Author: Marco A Pena
Editor: Russell G.Congalton
Year: 2009
Publisher: ASPRS, Vol 75, No 10 , October 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: land surface temperature(LST), surface urban heat island (SUHI), Landsat images, ASTER images
Abstract: The causes associated with the land surface temperature(LST) response of Santiago city and its rural surroundings are examined in an attempt to assess the surface urban heat island (SUHI). Seven Landsat and ASTER images acquired on summer mornings between 1998 and 2005 were processed. For each image LST was examined for urban and rural areas, and the main land-cover types, and then correlated with vegetation cover, soil moisture content, and albedo. At the time of data acquisition, the warmer conditions of the dry and poorly vegetated land-covers of the northern rural valley result in a negative SUHI intensity. Meanwhile, the colder conditions of the moist and well vegetated land-covers of the southern rural valley result in a positive SUHI intensity. The strong correlation coefficients retrieved between the above mentioned parameters for the rural area, support the wide thermal range associated with it, which is influenced by the high warming rate of its dry and poorly vegetated landcovers.
Location: 231
Literature cited 1: None
Literature cited 2: None