ID: 56391
Title: A study on comparison between fuzzy assignment problems using trapezoidal fuzzy numbers with average method
Author: S Manimaran and M Ananthanarayanan
Editor: Prof Natarajan Gajendran
Year: 2012
Publisher: Indian Society for Education and Environment, Vol 5, Issue 4, April 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Journal of Science and Technology
Keywords: Fuzzy sets, fuzzy numbers, fuzzy assignment problem, fuzzy ranking, hungerian method
Abstract: Assigment problem is very often used in solving problems of engineering and management science. In this paper, trapezoidal fuzzy numbers are considered which are more realistic and general in nature. The fuzzy assignment problem has been transformed into crisp assignment problem in the LPP form solved by using LINGO 9.0 and the results were compared with average method.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 56390
Title: Control algorithm for emission test simulation
Author: S B Ayati, H A Nozari, A Ordys and G Collier
Editor: Prof Natarajan Gajendran
Year: 2012
Publisher: Indian Society for Education and Environment, Vol 5, Issue 4, April 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Journal of Science and Technology
Keywords: Power train, emission tests, fuzzy, PID, automated test driving
Abstract: Automoibles are one of the main sources of global pollution. In order to prevent manufacturing of cars with high pollution, appropriate institutions are performing standard emission tests before the final product is released in the market. Recently, some robots and electronic devices are dedicated to perform such tests instead of human drivers. In this paper, simulation of the vehicle with the brake and the throttle as inputs, and the velocity, the position and the main components of exhaust gas as outputs in the emission test circumstances is discussed. The main components of exhaust gas are measured during the simulation. The performance of a nonlinear fuzzy controller and a conventional PID controller are compared to control the vehicle in such a test.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 56389
Title: Physiological characterization of rice under salinity stress during vegetative and reproductive stages
Author: Farshid Aref and Hassan Ebrahimi Rad
Editor: Prof Natarajan Gajendran
Year: 2012
Publisher: Indian Society for Education and Environment, Vol 5, Issue 4, April 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Journal of Science and Technology
Keywords: Saline water, salt tolerance, growth stages, yield components, panicle
Abstract: Salinity is one of the major environmental factors limiting crop productivity. For this reason, a greenhouse experiment was conducted in Rasht, North of Iran during 2010 growing season to evaluate the salinity levels of irrigation water at different growth stages on the same physiological characterization of rice. Treatments were arranged in a randomized complete block design with two factors and three replications. Factor one included four levels of saline water (2, 4, 6 and 8 dSm-1); factor two consisted of four growth stages (tillering, panicle initiation, panicle emergence and ripening). The results of this work showed that effect of different salinity levels on the all yield components except percentage of filled grains per panicle was not significant. Increase in salinity levels decreased this component. Effect of different growth stages on total number of empty grains per panicles, percentage of filled grains per panicle, number of unfilled panicles and percentage of ratio of number of unfilled panicles to tillers was significant but effect of different saline water on length of unfilled panicle and number of spikelets per unfilled panicle was insignificant. Resistance of final growth stages, i.e. panicle emergence and ripening stages against salinity was more than primary growth stages. i.e. tillering and panicle intiation. Therefore, in irrigation with saline water the final growth stages were important and irrigation with saline water should be applied at final growth stages.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 56388
Title: Soil physico-chemical characteristics of bryophytic vegetation residing kedarnath wildlife sanctuary (KWLS) Garhwal Himalaya, Uttarakhand, India
Author: Yateesh Mohan Bahuguna, Sumeet Gairola, D P Semwal, P L Uniyal and A B Bhatt
Editor: Prof Natarajan Gajendran
Year: 2012
Publisher: Indian Society for Education and Environment, Vol 5, Issue 4, April 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Journal of Science and Technology
Keywords: Liverworts, Hornworts, mosses, potassium, phosphorus, nitrogen, carbon, nutrient availability
Abstract: The present study was undertaken at eight different sites of Kedarnath Wildlife Sanctuary (KWLS) of Garhwal Himalaya, India to understand the physico-chemical properties of soils and influence of bryophytic communities on the status of nutrient availability. In the bryophytes dominated sites the values of organic carbon (0.21%) and nitrogen (0.04%) were found to be low as compared to values for forest soils dominated by higher plants which suggests that bryophytes prefer to occupy the barren sites with low organic matter. Mean available phosphorus content in soil of various sites varied between 13.02 Kgha-1 and 16.28 Kgha-1 with estimated mean exchangeable potassium content ranged between 145.60 Kgha-1 and 216.16 Kgha-1 . A significant negative correlation between soil temperature and moisture content was observed, whereas organic carbon and available phosphorus exhibited significantly positive correlation. Besides the characteristics of soil underneath the byrophytic vegetation, the study also highlights the kind of bryophytes communities found along altitudinal variation and soil types
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 56387
Title: Ecotoxicity of leaf extracts of Azadirachta indica on chironomids larvae
Author: J A Adakole and S Ogwu
Editor: Prof Natarajan Gajendran
Year: 2012
Publisher: Indian Society for Education and Environment, Vol 5, Issue 4, April 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Journal of Science and Technology
Keywords: Ecotoxicity, Azadirachta indica, Neem, Chironomus larvae, ecotoxicity
Abstract: The present study was designed to evaluate acute ectoxicity of aqueous and ethanolic leaf extracts of Azadirachta indica on Chironomus spp. Exposure of chironomd larvae to the crude aqueous extract (0.0 [control], 25.00, 50.00, 75.00, 150.00 & 200.00 mg/L) and ethanolic (0.0[control], 6.00, 12.00, 25.00, 50.00 & 100.00 mg/L) concentrations resulted in LC50 of 68.28 mg/L and of 6.65 mg/L respectively. Other toxic response by the larvae includes avoidance of sediment, impregnation of some segments with dark substances and bleaching/loss of respiratory pigments. Comparatively, mortality rate and other toxic responses was more in the ethanolic extract than in the aqueous extract test tanks. Impregnation of some larvae segments with dark substances suggests that feeding activity was going on during the toxicity test period and mortality of the larvae was partly due to contact with the polluted sediment and ingestion of contaminated particles of the sediment.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 56386
Title: Monitoring recent trends in the area of aeolian desertified land using Landsat images in China ' s Xinjiang region
Author: T Wang, C Z Yan, X Song, J L Xie
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, Xinjiang, Desertification, Trend analysis
Abstract: China ' s Xinjiang Uygur Autonomous Region is located in a region with an arid climate, and suffers from severe aeolian desertification. Aeolian desertified land (ADL) is widely distributed in the region and strongly constrains sustainable socioeconomic development. In this study, we used Landsat MSS, TM, and ETM images from 1975, 1990, 2000 and 2010 to classify the intensity of aeolin desertification in four categories (slight, moderate, severe, and extremely severe). Using these data, we developed an ADL database and use it to discuss the evolution of ADL during the study period, along with the desertification and restoration processes and the causes of the desertification. We found 47,833 km2 of ADL in 2010, most of which (more than 57%) was reated as extremely severe or severe. The area of ADL increased by 2228 km2 between 1975 and 1990 (by 4.67%). In constrast, some areas of ADL have been restored, so that the area of ADL has decreased since 1990: by 930 km2 from 1990 to 2000 (1.86%) and by 1223 Km2 from 2000 to 2010 (2.49%). Based on the analysis of effects of climate changes and human activities in the region, aeolian desertification was principally driven by human activities in this area; climatic variations had less effect on the area of severe desertification. And the driving force need for more detailed quantitative analysis with more frequent remotely sensed data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56385
Title: Multi-class predictive template for tree crown detection
Author: Calvin Hung, Mitch Bryson, Salah Sukkarieh
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Agriculture, forestry, vision, mapping, engineering, robotics
Abstract: This paper presents a novel approach for automatic segmentation and object detection of tree crowns in airborne images captured from a low-flying Unmanned Aerial Vehicle (UAV) in ecology monitoring applications. Cost effective monitoring in these applications necessitates the use of vision-band-only imaging on the UAV platform; the reduction in spectral resolution (compared to multi-or hyper-spectral imaging) is balanced by the high spatial resolution available (~20 cm / pixel) from the low-flying UAV, when compared to existing satellite or manned-aerial survey data. Our approach to object detection thus uses both geometry and appearance information (through the use of tree shape and shadow information) in addition to spectral information to help accurately distinguish tree crowns within our application. A predictive geometric template for tree detection is constructed using on-board UAV navigation data, sun lighting information and information about the geometry of the target crown. A two-stage detection algorithm is then used to segment tree crowns based on spectral (colour) information convolved with information from the predictive template. Results of our approach are presented using airborne image data collected from a fixed-wing UAV during a weed monitoring and mappign mission over farmland in West Queensland, Australia.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56384
Title: Deriving optical properties of Mahakam Delta coastal waters, Indonesia using in situ measurements and ocean color model inversion
Author: Syarif Budhiman, Mhd. Suhyb Salama, Zoltan Vekerdy, Wouter Verhoef
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Apparent optical properties, Inherent optical properties, Specific inherent optical properties, Total suspended matter, Chlorophyll a, Tropical waters
Abstract: The development of an operational water quality monitoring method based on remote sensing data requires information on the apparent and inherent optical properties of water (AOP and IOP respectively). This study was performed to detemine the apparent and inherent optical properties of coastal waters of teh Mahakam Delta, kalimantan, Indonesia, Inherent optical properties (IOPs) were derived from above-water radiometric measurements and ocean color model inversion. Retrieved IOPs and measured concentrations show good agreement both for total suspended matter (TSM) and chlorophyll a (Chl a) (R2 = 0.72 and 0.80 respectively). The linear relationship between the retrieved IOPs and the measured concentrations was then used to estimate the specific inherent optical properties (SIOPs) using the basic equation of the Lambert-Beer Law. The specific backscattering coefficient of TSM (bb.TSM(550)) was found to be 0.0087 m2g-1, and the specific absorption coefficient of Chl a (achl(440)) was found to be 0.023 m2g-1 in the Mahakam Delta. The estimated value of SIOP for TSM and Chl a could be considered spatially constant for the Mahakam Delta, and resulted in reliable estimates of TSM and Chl a concentrations (R2 = 0.84 and 0.85 respectively). The specific backscattering coefficient of TSM found in this study is similar to that of the Barito Estuary (in the southern part of Kalimantan) but lower than that of the Berau Estuary (in the northern part of Kalimantan), whereas the specific backscattering coefficient of Chl a is similar to that found in the Berau Estuary. This study contributes to the development of an operational method based on remote sensing data to map water constituent concentrations in the Mahakam Delta, as well as to enrich the information about the optical properties of Indonesia waters.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56383
Title: Discrepancy measures for selecting optimal combination of parameter values in object-based image analysis
Author: Yong Liu, Ling Bian, Yuhong Meng, Huanping Wang, Shifu Zhang, Yining Yang, Xiaomin Shao, Bo Wang
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Object-based image analysis, Image segmentation, discrepancy measures, Optimal parameter value combinations, under-segmentation, over-segmentation
Abstract: Most object-based image analysis use parameters to control the size, shape, and homogeneity of segments. Because each parameter may take a range of possible values, different combinations of value between parameters may produce different segmentation results. Assessment of segmentation quality, such as the discrepancy between reference polygons and corresponding image segments, can be used to identify the optimal combination of parameter values. In this research, we (1) evaluate four existing indices that describe the discrepancy between reference polygons and corresponding segments. (2) propose three new indices to evaluate both geometric and arithmetic discepancies, and (3) compare the effectiveness of the existing and porposed indices in identifying optimal combination of parameter values for image segmentation through a case study. A Landsat 5 Thematic Mapper (TM) image and an ALOS image of arid Northwestern China were used in the case study. The four existing indices include Quality Rate (QR), Over-segmentation Rate (OR), Under-segmentation Rate (UR), and Euclidean Distance 1 (ED1). The three proposed discrepancy indices include Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR), and Euclidean Distance 2 (ED2). The indices measure overlap, over-segmentation, and under-segmentation between reference polygons and corresponding image segments. Results show that the three proposed indices PSE, NSR, and ED2 are more effective than the four existing indices QR, OR, UR and ED1 in thier ability to identify optimal combinations of parameter values. ED2 that represents both geometric (PSE) and arithmetic (NSR) discrepancies is most effective.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56382
Title: Oil spill feature selection and classification using decision tree forest on SAR image data
Author: Konstantinos Topouzelis, Apostolos Pysllos
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Oil spill, decision forest, feature selection, SAR, classification, machine learning
Abstract: A novel oil spill feature selection and classification technique is presented, based on a forest of decision trees. The parameters of the two -class classification problem of oil spills and look -alikes are explored. The contribution to the final classification of the 25 most commonly used features in the scientific community was examined. The work is sought in the framework of a multi-objective problem, i.e. the minimization of the used input features and, at the same time, the maximization of the overall testing classification accuracy. Results showed that the optimum forest contains 70 trees and the three most important combination contain 4.6 and 9 features. The latter feature combination can be seen as the most appropriate solution of the decision forest study. Examination of the robustness of the above result showed that the proposed combination achieved higher classification accuracy than other well-known statistical separation indexes. Moreover, comparisons with previous findings converge on the classification accuracy (up to 84.5%) and to the number of selected features, but diverge on the actual features. This observation leads to the conclusion that there is not a single optimum feature combination; several sets of combinations exist which contain at least some critical features.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56381
Title: 3D terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology
Author: N Brodu, D Lague
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: LIDAR, classification, automation, algorithms, feature, scale
Abstract: 3D point clouds of natural enviornments relevant to problems in geomorphology (rivers, coastal environments, cliffs...) often require classification of the data into elementary relevant classes. A typical example is the separation of riparian vegetation from ground in fluvial environments, the distinction between fresh surfaces and rockfall in cliff environments, or more generally the classification of surfaces according to their morphology (e.g the presence of bedforms or by grain size). Natural surfaces are heterogeneous and their distinctive properties are seldom defined at a unique scale, prompting the use of multi-scale criteria to achieve a high degree of classfication success. We have thus defined a multi-scale measure of the point cloud dimensionality around each point. The dimensionality characterizes the local 3D orgnization of the point cloud within spheres centered on the measured points and varies from being 1D (points set along a line), 2D (points forming a plane) to the full 3D volume. By varying the diameter of the sphere, we can thus monitor how the local cloud geometry behaves across scales. We present the technique and illustrate its efficiency in separating riparian vegetation from ground and classifying a mountain stream as vegetation, rock, gravel or water surface. In these two cases, separating the vegetation from ground or other classes achieve accuracy larger than 98%. Comparison with a single scale approach shows the superiority of the multi-scale analysis in enhancing class separability and spatial resolution of the classification. Scenes between 10 and one hundred million points can be classified on a common laptop in a reasonable time. The technique is robust to missing data, shadow zones and changes in point density within the scene. The classification is fast and accurate and can account for some degree of intra-class morphological variability such as different vegetation types. A probabilistic confidence in the classification result is given at each point, allowing the user to remove the points for which the classification is uncertain. The process can be both fully automated (minimal user input once, all scenes treated in large computation batches), but also fully customized by the user including a graphial definition of the classifiers if so desired. Working classifiers can be exchanged between users independently of the instrument used to acquire the data avoiding the need to go through full training of the classifier. Although developed for fully 3D data, the method can be readily applied to 2.5 D airborne lidar data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56380
Title: Effect of canopy structure on sun-induced chlorophyll fluorescene
Author: A Fournier, F Daumard, S Champagne, A Ounis, Y Goulas, I Moya
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Canopy structure, chlorophyll fluorescene measurement, simulation, F687/F760 fluorescene ratio, Oxygen absorption band, band infilling
Abstract: We investigated the impact of canopy structure on chlorophyll fluorescene properties. For this purpose, we developed SpectroFLEX, an instrument for quantitative measurements of canopy fluorescence in O2 A and O2B atmospheric absorption bands. The fluorescene emission of a natural grass canopy was compared with the leaf level fluorescene spectrum acquired simultaneously. It was found that the red-to-far-red fluorescene ratio decreased by a factor of two from the leaf to canopy level. In addition, this ratio decreased under high light conditions. FluoSAIL simulations were conducted to study the impact of canopy density and geometry on this decrease. This effect has been attributed to a preferential re-absorption of red fluorescene emission during radiative transfer within the canopy compared to far-red emission.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56379
Title: Mathematical morphology-based generalization of complex 3D building models incorporating semantic relationships
Author: Junqiao Zhao, Qing Zhu, Zhiqiang Du, Tiantian Feng, Yeting Zhang
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Generalization, Complex 3D building, Mathematical morphology, Levels of detail sesimatic relationships
Abstract: A complex 3D building model contains a detailed description of both its appearance and internal structure with authentic architectural components. Because of its high complexity and huge data volumes, using a less detailed representation for the distant visual application of such a world is preferable. However, most mesh simplification algorithms cannot preserve manmade features of such models, and the existing 3D generalization algorithms are mainly proposed for regular-shaped buildings. More importantly, neither method can consistenly express geometry, topological relations, and sematics in multiple discrete Levels of Details (LoDs). This apper presents a novel mathematical morphology - based algorithm that generalizes the complex 3D building model in a unified manner using the following steps: (1) Semantic relationships between components, which reflect structural connectivity in the building at a certain LoD, are defined and extracted; (2) semantically connected components are merged and trivial geometric features of the components are eliminated simultaneously, with semantics associated with components then updated according to the merging; and (3) post-process is carried out to further reduce the redundancy of facets. The semantic relationships extracted ensure the proper generalization of topographical relations and semantics of building components, and mathematical morphologial operations implemented in the algorithm are capable of handling closed two-manifold components of various shapes. Experiments on both complex 3D building models in the classical Chinese style and prismatic 3D city models prove the effectiveness of the proposed method.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56378
Title: Spatio-temporal patterns in vegetation start of season across the island of Ireland using the MERIS Global Vegetation Index
Author: Brian O ' Connor, Edward Dwyer, Fiona Cawkwell, Lars Eklundh
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: CORINE, Landcover, MERIS Global Vegetation Index (MGVI), Start of season (SOS), Vegetation seasonality, Ireland
Abstract: Spring phenophases such as the beginning of leaf unfolding, measured in the Irish gardens of the International Phenological Garden (IPG) network, indicate an earlier spring occurrence hence a longer growing season. However, these measurements are limited to selected species of trees of a few point locations in the southern half of the country. The aim of this study was to develop a methodology, based on satellite remote sensing, to measure the vegetation start of season (SOS) across the whole island of Ireland on an annual basis, complementary to existing ground-based methods.
The SOS metric was extracted for each year in a 7-year time series of 10-day composited, 1.2 km reduced resolution MERIS Global Vegetation Indiex (MGVI) data from 2003 to 2009, based on curve fitting, using the time series analysis software. TIMESAT. Spatio-temporal variability in the SOS was detected across the island on an annual basis and highlighted in a series of anomaly images showing variation from the 7-year mean SOS. The 2006 SOS was late across the island while there were strong geographical gradients to the SOS anomalise in 2009 when it occurred later in the south and ealier in the north. There was a mix of early and late anomaly values throughout the country in the other years.
Qualitatively, the spatial patterns in the timing of the SOS were related to the distribution of landcover types as indicated by the CORINE Land Cover map (CLC). Three statistically separable groups of CLC classes were derived from differences in the SOS, namely agricultural and forest land cover types, peat bogs, and natural and semi-natural vegetation types. These groups demonstrated that vegetation in cultivated areas like pastures has a significantly earlier SOS than in areas os unmanaged vegetation such as peat bogs. An initial climate analysis indicated that an anomalously cold winter and spring in 2005/2006 delayed the 2006 SOS countrywide; while a cold winter followed by a mild spring in 2009 caused considerable spatial variability in the 2009 SOS across the country, ranging from late SOS in the south to early SOS in the north.
This study has demonstrated the utility of 10- day MGVI composites for derivation of an SOS metric which can be used as an indicator of spatial variability in vegetation seasonality and has highlighted how SOS varies accoding to landcover type. The availability of longer time series in the furture will allow more focused studies on the sensitivity of the SOS metric to changes in climate as well as short term weather events.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56377
Title: Relative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes
Author: Qing Xu, Zhengyang Hou, Timo Tokola
Editor: George Vosselman
Year: 2012
Publisher: Elsevier, Vol 68, March 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Multi-temporal images, pseudo-invariant features, multivariate alteration detection (MAD), transformation, Bi-temporal principle component analysis, Local radiometric correction, Estimation accuracy
Abstract: Relative radiometric correction methods have been widely used to correct ground illumination difference in multi-temporal satellite data. ALOS (Advanced Land Observing Satellite) data starts to play an important role in forest and carbon assessment, such as the REDD (Reducing Emissions from Deforestation and forest Degradation) program. The objective of the study was to compare three relative radiometric correction methods for five multi-temporal ALOS AVNIR -2 (Advanced Visible and Near Infrared Radiometer) images, and to examine the influence of each correction method on the estimation accuracy of forest attributes with auxillary field inventory plot data. Both spectral features and textual features were extracted before and after radiometric correction and used in estimation procedure. All the radiometric correction methods used improved the estimation accuracy of forest stem volume at plot level, and they were MAD (multivariate alteration detection) transformation -based normalization, PCA (principle component analysis) - based correction and local radiometric correction, among which MAD transformation based normalization exceeded others by reducing the relative RMSE by 5.75% with the ordinary least square fittign and 6.8% with the K-MSN (K-Most Similar Neighbour) method both after leave-one-out cross-validation. RMSE for only the corrected area is also calculated. In view of the small proportion of plots in that area. The result can be used to improve the visual effect of mosaics of multi-temporal ALOS scenes to retrieve more accurate forest estimates for national forest resources and biomass mapping.
Location: 231
Literature cited 1: None
Literature cited 2: None