TM Classification Research Articles

Effects and Prognostic Values of Circadian Genes CSNK1E/GNA11/KLF9/THRAP3 in Kidney Renal Clear Cell Carcinoma via a Comprehensive Analysis.

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent and deadly types of renal cancer in adults. Recent research has identified circadian genes as being involved in the development and progression of KIRC by altering their expression. This study aimed to identify circadian genes that are differentially expressed in KIRC and assess their role in KIRC progression. In KIRC, there were 553 differentially expressed rhythm genes (DERGs), with 300 up-regulated and 253 down-regulated DERGs. Functional enrichment analyses showed that DERGs were greatly enriched in the circadian rhythm and immune response pathways. Survival analyses indicated that higher expression levels of CSNK1E were related to shorter overall survival of KIRC patients, whereas lower expression levels of GNA11, KLF9, and THRAP3 were associated with shorter overall survival of KIRC patients. Through cell assay verification, the mRNA level of CSNK1E was significantly up-regulated, whereas the mRNA levels of GNA11, KLF9, and THRAP3 were dramatically down-regulated in KIRC cells, which were consistent with the bioinformatics analysis of KIRC patient samples. Age, grade, stage, TM classification, and CSNK1E expression were all shown to be high-risk variables, whereas GNA11, KLF9, and THRAP3 expression were found to be low-risk factors in univariate Cox analyses. Multivariate Cox analyses showed that CSNK1E and KLF9 were also independently related to overall survival. Immune infiltration analysis indicated that the proportion of immune cells varied greatly between KIRC tissues and normal tissue, whereas CSNK1E, GNA11, KLF9, and THRAP3 expression levels were substantially linked with the infiltration abundance of immune cells and immunological biomarkers. Moreover, interaction networks between CSNK1E/GNA11/KLF9/THRAP3 and immune genes were constructed to explore the stream connections. The findings could help us better understand the molecular mechanisms of KIRC progression, and CSNK1E/GNA11/KLF9/THRAP3 might be used as molecular targets for chronotherapy in KIRC patients in the near future.

An Exploratory Study of Trade Union Pluralism in Ghana

The practice of trade union pluralism at an enterprise level is seen as problematic for both the management of enterprises and the trade union movement. The problems arise from inter-union rivalries, competition and disputes over demarcations of privileges and rights. This article explores the practice of trade union pluralism at the enterprise level in Ghana with the aim of creating awareness of the effect of the practice on the general trade union movement. This qualitative study employed a cross-sectional design and used purposive and snowball sampling methods in selecting the participants. The data was analysed thematically. The findings from the study show that union pluralism is stimulating the decline in general union membership, the breakaway of local unions from the federations, and employers’ classification of workers based on their qualifications once they are employed by organisations, and their assignment to specific unions (automatic membership at enterprise level). It is suggested that employment laws encourage union breakaways, which weakens the unions especially at the enterprise level. It is recommended that the state, labour officials and policy-makers should enforce labour laws, especially regarding freedom of association, and consider revisiting or amending some labour laws to curb their abuse. The government and labour institutions need to work together to operationalise the implementation of legal provisions on freedom of association or consider amending the provisions to curb the existing abuse.

An Exploratory Study of Trade Union Pluralism in Ghana

The practice of trade union pluralism at an enterprise level is seen as problematic for both the management of enterprises and the trade union movement. The problems arise from inter-union rivalries, competition and disputes over demarcations of privileges and rights. This article explores the practice of trade union pluralism at the enterprise level in Ghana with the aim of creating awareness of the effect of the practice on the general trade union movement. This qualitative study employed a cross-sectional design and used purposive and snowball sampling methods in selecting the participants. The data was analysed thematically. The findings from the study show that union pluralism is stimulating the decline in general union membership, the breakaway of local unions from the federations, and employers’ classification of workers based on their qualifications once they are employed by organisations, and their assignment to specific unions (automatic membership at enterprise level). It is suggested that employment laws encourage union breakaways, which weakens the unions especially at the enterprise level. It is recommended that the state, labour officials and policy-makers should enforce labour laws, especially regarding freedom of association, and consider revisiting or amending some labour laws to curb their abuse. The government and labour institutions need to work together to operationalise the implementation of legal provisions on freedom of association or consider amending the provisions to curb the existing abuse.

Development of Internal Control Methodology by Using Statistical Methods of Variability Assessment of Material Flow Business Processes

Variability or instability is one of the key features of any process, including business processes of material flow internal control. Variability is a characteristic of all natural systems and technical processes. The objects which properties can be characterized via certain parameters arise at the output of any process.The article discloses the feasibility of using the statistical methods in the internal control system of business entities; in this case the focus is on the method of identifying the causes of variability using control charts of various types (Shewhart control charts) as a prime tool.The view points regarding variability of famous academic economists who researched the business process management issues are also considered. Authors’ classification of business process variation on types of material flow internal control with the allocation of controlled and uncontrolled variation is taken as the basis of the proposed application.The method of using control charts in estimating the efficiency of material flow internal control business processes is described in detail.

Discrimination of crown closure of forest ecosystems using different remotely sensed data: a case study of Kızılcasu planning unit

The objective of this study was to estimate crown closure using different satellite images, Landsat TM and QuickBird. As reference data, forest cover type map were used in the study, and two different methods were used to determine the crown closure. First, to classify crown closures from satellite images, a supervised classification method was used. Second, the linear mixture modeling (LMM) fuzzy classification method was used to determine the stand crown closure. Landsat TM and QuickBird data were used in this frame. The training dataset was derived from a fine spatial resolution land cover classification of QuickBird imagery. This classification was combined to estimate the percentage crown closure in Landsat TM spatial resolution. The research also focused on classifying and mapping the crown closure classes with the spatial analysis functions of geographical information systems (GIS). The results showed that the QuickBird image had the highest classification accuracies compared to the spatial analyses results of Landsat TM and fuzzy classification.

The importance of neck circumference to thyromental distance ratio (NC/TM) as a predictor of difficult intubation in obstructive sleep apnea (OSA) patients

BackgroundThe trial to find a bedside examination that is helpful for foreseeing difficult intubation is quite inspiring. It was reported that thyromental distance (TM), body mass index (BMI), neck circumference (NC) and a Mallampati score >3 were the only helpful bedside test predictors. By using magnetic resonance imaging, it was established that more fat was present in areas around the collapsible parts of the pharynx in OSA patients. So distribution of fat may provide a better suggestion of difficult intubation than neck circumference. The current work studied the neck circumference to thyromental distance ratio as a new predictor of difficult intubation in obstructive sleep apnea (OSA) patients and comparing it to the formally standard Mallampati score.Patients and methodsAfter approval of the ethical committee in Kasr Al Ainy University hospital and patients consent 50 ASA class 1 and II OSA patients, 18–60 years of both sexes, undergoing surgery under general anesthesia with tracheal intubation were enrolled in the study. It was a single group study. Body mass index, neck circumference (cm), thyromental distance (cm) and the ratio of the NC to TM (NC/TM) and Mallampati classification were recorded. Difficulty of intubation was assessed using the Intubation Difficulty Scale (IDS). Correlation between all variables and IDS, comparison between NC/TM ratio and Mallampati score as reliable tests for predicting difficult intubation and also measuring sensitivity and specificity of both.ResultsAmong the 50 patients, 11 patients experienced difficult intubation according to IDS scale. The Mallampati score and NC/TM were the only statistically significant variables that were associated with a difficult intubation. NC/TM ratio was strongly correlated to difficult intubation where P value = 0.01 odds ratio 37.5 with cut-off point is NC/TM ⩾5.15, but the correlation of Mallampati score was weaker P value = 0.05 and odds ratio was 14.5. Moreover, NC/TM ratio showed higher sensitivity (100%) and a negative predictive value (82%), than the Mallampati score sensitivity (90%) and specificity (61%).ConclusionDifficult intubation in OSA obese patients was independently associated with a Mallampati score of III or IV, and NC/TM ⩾5.15. Moreover, NC/TM yielded a high sensitivity, specificity and a negative predictive value.

Derivation of a Blueberry Ripeness Index with a View to a Low-Cost, Handheld Optical Sensing Device for Supporting Harvest Decisions

Abstract. Berry fruit farming and marketing have widely increased in recent years in marginal areas of Italy, especially in response to consumers’ growing interest in adhering to a bioactive and health-protecting diet. The ripening stage of berry fruits, on which their quality and nutraceutical attributes depend, is typically estimated by growers through visual inspection based on the growers’ experience. Low-cost, handheld, user-friendly devices could assist growers in the field in determining the optimal harvest date in accordance with the desired ripeness of berries. In order to explore the technical feasibility of such a system, this study focused on defining a simple ripeness index for blueberries by identifying the main spectral changes accompanying their ripening process, with special attention paid to the last and most relevant stages. With this aim, spectral measurements in the range of 445 to 970 nm were carried out on Vaccinium corymbosum (cv. Brigitta) during two different growing seasons. Spectra were acquired on 942 individual berries in the field at different dates. Measurements were accompanied by weekly samplings, with picked fruits divided into four ripeness grades according to commercial growers’ classification. A principal component analysis of fruit spectra highlighted that two main wavebands (680 and 740 nm) can maximize the differences between fully ripe samples and those close to ripeness or unripe. Hence, spectral values at 680, 740, and 850 nm (the latter being an additional normalization waveband) were used to create a blueberry ripeness index (BRI) as a linear combination of two spectral ratios: S1 = log(I680/I850) and S2 = (I740/I850). The definition of specific ripeness thresholds for the BRI according to more or less selective criteria was illustrated in an application example, and the ripeness classification capability was then assessed on a separate validation set of 471 berries. When applying a less selective threshold approach, the BRI correctly classified as ripe 85% of manually graded fully ripe berries, whereas 13% of close but not yet ripe validation samples were misclassified as fully ripe and ready to harvest. Comparatively, when a more demanding ripeness threshold was applied, the amount of nearly ripe berries misclassified as ripe decreased to 8%, but the amount of fully ripe berries not identified as ripe rose to 25%. In both cases, none of the unripe validation samples was erroneously classified as ripe fruit. These results, which were obtained with a BRI defined by spectral measurements at just three discrete wavelengths, point to the feasibility of a simple, microcontroller-based, handheld optical device able to implement the BRI to quickly assess the ripeness of sets of berries during the last and most delicate stages of the ripening process.

RESEARCH ON ESTIMATION CROP PLANTING AREA BY INTEGRATING THE OPTICAL AND MICROWAVE REMOTE SENSING DATA

Abstract. Considering the problem in monitoring agricultural condition in the semi-arid areas of Northwest of China, we propose a new method for estimation of crop planting area, using the single phase optical and microwave remote sensing data collaboratively, which have demonstrated their respective advantages in the extraction of surface features. In the model, the ASAR backscatter coefficient is normalized by the incident angle at first, then the classifier based on Bayesian network is developed, and the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. Moreover the crop planting areas can be extracted by the classification results. At last, the model is validated for the necessities of normalization by the incident angle and integration of TM and ASAR respectively. It results that the estimation accuracy of crop planting area of corn and other crops garden are 98.47% and 78.25% respectively using the proposed method, with an improvement of estimation accuracy of about 3.28% and 4.18% relative to single TM classification. These illustrate that synthesis of optical and microwave remote sensing data is efficient and potential in estimation crop planting area.

The distribution of lung cancer across sectors of society in the United Kingdom: a study using national primary care data

BackgroundThere is pressing need to diagnose lung cancer earlier in the United Kingdom (UK) and it is likely that research using computerised general practice records will help this process. Linkage of these records to area-level geo-demographic classifications may also facilitate case ascertainment for public health programmes, however, there have as yet been no extensive studies of data validity for such purposes.MethodsTo first address the need for validation, we assessed the completeness and representativeness of lung cancer data from The Health Improvement Network (THIN) national primary care database by comparing incidence and survival between 2000 and 2009 with the UK National Cancer Registry and the National Lung Cancer Audit Database. Secondly, we explored the potential of a geo-demographic social marketing tool to facilitate disease ascertainment by using Experian's Mosaic Public Sector ™ classification, to identify detailed profiles of the sectors of society where lung cancer incidence was highest.ResultsOverall incidence of lung cancer (41.4/100, 000 person-years, 95% confidence interval 40.6-42.1) and median survival (232 days) were similar to other national data; The incidence rate in THIN from 2003-2006 was found to be just over 93% of the national cancer registry rate. Incidence increased considerably with area-level deprivation measured by the Townsend Index and was highest in the North-West of England (65.1/100, 000 person-years). Wider variations in incidence were however identified using Mosaic classifications with the highest incidence in Mosaic Public Sector ™types 'Cared-for pensioners, ' 'Old people in flats' and 'Dignified dependency' (191.7, 174.2 and 117.1 per 100, 000 person-years respectively).ConclusionsRoutine electronic data in THIN are a valid source of lung cancer information. Mosaic ™ identified greater incidence differentials than standard area-level measures and as such could be used as a tool for public health programmes to ascertain future cases more effectively.

Decadal‐scale aspen changes: evidence in remote sensing and tree ring data

Abstract Question: (1) Which remote sensing classification most successfully identify aspen using multitemporal Landsat 5 TM images and airborne lidar data? (2) How has aspen distribution changed in southwestern Idaho? (3) Are topographic variables and conifer encroachment correlated with aspen changes? Location: Reynolds Creek Experimental Watershed in southwestern Idaho, USA. Methods: Multi‐temporal Landsat 5 TM and lidar data were used individually and fused together. The best classification model was compared with a 1965 aspen map and tree ring data. Conifer encroachment was examined via image‐based change detection and field mapping. Lidar‐derived topographic variables were correlated with aspen change patterns using quantile regression models. Results: The best Landsat 5 TM classification was a normalized difference vegetation index (NDVI)‐based approach with 92% overall accuracy. The lidar classification of tree presence/absence performed with 100% overall accuracy. Fusing the lidar classification with various Landsat 5 TM classifications improved overall accuracies 3 to 6%. Among the fusion models, the NDVI‐lidar fusion performed best with 96% overall accuracy. Change detection indicated 69% decline in aspen cover, but 179% increase in aspen cover in other areas of the watershed. Conifers have completely replaced 17% of the aspen, while 93% of the remaining aspen stands have young Douglas‐fir and western juniper trees underneath the aspen canopy. Aspen significantly decreased (P‐values <0.05) with increasing elevation (up to 2150 m) and decreasing slope. Conclusions: Landsat 5 TM data used with a NDVI‐based approach provide an accurate method to classify aspen distribution. Landsat 5 TM classifications can be further improved via fusion with lidar data. Aspen change patterns are spatially variable: while aspen is drastically declining in some parts of this watershed, aspen is increasing in other areas.

Techniques for developing land-use classification using moderate resolution imaging spectroradiometer imagery

Using NOAA AVHRR or MODIS imagery to create land-use classifications has been attempted for many years. Unfortunately, most of these classifications do not differentiate crop types. Crop models require that vegetation characteristics extracted from an image be the correct crop type. This study compares four techniques to create land-use classifications using MODIS data. These classifications were compared to the ground data that had been set aside, to a mask where each MODIS sized pixel were at least 80% of a single land-used based on a Landsat TM classification for the same year, and to the Landsat TM classification. Using a decision tree method and comparing the classification to an 80% mask resulted in an accuracy of 73% which was the highest accuracy obtained in this study. The study showed that accuracies could range from 37% to 73% depending on the classification process and if segment data, an 80% mask, or a Landsat TM classification were used for accuracy assessment.

Mapeamento de semeaduras de soja (Glycine max (L.)Merr.) mediante dados MODIS/Terra E TM/Landsat 5: um comparativo

O objetivo deste trabalho foi comparar mapeamentos de semeadura da cultura da soja na região oeste do Paraná, realizados com imagens MODIS/Terra e TM/Landsat 5. Primeiramente, construiu-se máscara de referência, considerando seis imagens TM ao longo do ciclo da cultura, utilizando-se dos algoritmos Paralelepípedo e MaxVer com posterior análise visual. As imagens MODIS foram classificadas com o algorítimo Paralelepípedo, em quatro passagens referentes ao pico vegetativo. O desempenho das classificações foi avaliado por meio de Matrizes de Erros, calculadas pela análise de 100 pontos amostrais (soja ou não-soja), aleatoriamente distribuídos em cada um dos oito municípios da área de estudo. Os principais resultados mostraram que a Exatidão Global (EG) e o Índice Kappa (IK), que variaram entre 0,55 e 0,80, em ambos os sensores, são considerados bons a muito bons. Quando EG e IK dos sensores TM e MODIS foram comparados, não se encontrou diferença significativa. O mapeamento da soja utilizando o sensor MODIS produziu 70% de confiabilidade sob o ponto de vista do usuário. A principal conclusão é a viabilidade de mapear a soja pelo sensor MODIS com as vantagens de que as imagens MODIS têm melhor resolução temporal e são disponibilizadas gratuitamente na Internet.

Creating a digital treeless peatland map using satellite image interpretation

In the satellite image-based estimation and classification of forest variables in Finland peatlands are usually processed separately from mineral soil forests, to improve the accuracy of the results. The division into peatlands and mineral soil forests is based on a mask provided by the National Land Survey. It would be advantageous, however, to update the mask with the satellite imagery used for estimating forest variables. The aim here was to compare methods for treeless peatland detection on a Landsat ETM+ satellite image. The area concerned was located within the southern aapa mire zone in Finland. The classification methods tested included sequential maximum a posteriori (SMAP), supervised maximum likelihood (ML) and unsupervised ML with Iso Cluster-based signatures. The unsupervised Iso Cluster ML method performed poorly, while the overall accuracies of SMAP and supervised ML were better and quite similar (88–94% and 89–90% on forestry land, respectively). SMAP produced more usable maps, by forming compact and unspeckled treeless peatland regions. The existing peatland mask was slightly more accurate than SMAP and ML, although it performed less well in the treeless peatland class. The updating of the existing mask by combining it with the best classification result did not succeed. The main conclusion is that a peatland mask can be based on Landsat TM classification, but in areas where a good topographic mask exists the latter is more useful, and cannot easily be updated with help of satellite image data.

500 heart beats for assessing diabetic autonomic neuropathy

The objective of the study was to investigate the usage of a new definition of autonomic dysfunction in assessing diabetic autonomic neuropathy (DAN), compared with the existing methods of evaluation, such as changes in heart rate variability (HRV) and autonomic scoring. In a prospective study, 21 diabetic patients and 9 non-diabetic volunteers were enrolled for assessment of DAN. Three methods were employed: scoring of the autonomic function involving 3 manoeuvres (more than 3000 heart beats), reduction in components of the power spectrum (PSD) of the HRV (Valsalva manoeuvre along less than 600 heart beats) and finally measurement of autonomic dysfunction as provided by the ANSiscope TM (supine position for 572 heart beats). All individual comparisons were taken between the three classifications given by the methods. Pathways leading from one classification to another were thoroughly represented. From 3 groups in the clinical classification (nondiabetic, diabetic without complications, diabetic with complications), autonomic scoring divided patients in 3 other groups with 15 healthy cases, 14 early cases and 1 case of advanced DAN. These 3 groups of scored patients were transformed in 2 ordered groups of equal size, by consideration of the amount of LF and/or HF component reduction (normal, abnormal). From this PSD distinction between absence and presence of DAN, the ANSiscope TM classified and ordered patients among 5 groups: 7 healthy cases, 7 early cases of DAN, 6 late cases, 7 advanced cases and 3 most advanced. Equivalence was found between the HRV and ANSiscope TM assessments as the latter classification was also brought to 2 groups, only distinguishing between absence and presence of DAN. The additional groups of the ANSiscope TM classification seem to provide evidence of early DAN for the first normal category and relativism in the severity of the neuropathy for the second abnormal category. Autonomic scoring did not convey the same diversity between groups as found with the groups formed by the other methods. These findings suggest that correct supine assessment of DAN with sole consideration of R-R time intervals is possible in a little more than 500 heart beats, i.e. with 5 to 8 minutes of ECG recording.

Landscape-scale characterization of cropland in China using Vegetation and Landsat TM images

In this landscape-scale study we explored the potential for multitemporal 10-day composite data from the Vegetation sensor to characterize land cover types, in combination with Landsat TM image and agricultural census data. The study area (175 km by 165 km) is located in eastern Jiangsu Province, China. The Normalized Difference Vegetation Index (NDVI ) and the Normalized Difference Water Index (NDWI ) were calculated for seven 10-day composite (VGT-S10) data from 11 March to 20 May 1999. Multi-temporal NDVI and NDWI were visually examined and used for unsupervised classification. The resultant VGT classification map at 1 km resolution was compared to the TM classification map derived from unsupervised classification of a Landsat 5 TM image acquired on 26 April 1996 at 30 m resolution to quantify percent fraction of cropland within a 1 km VGT pixel; resulting in a mean of 60% for pixels classified as cropland, and 47% for pixels classified as cropland/natural vegetation mosaic. The estimates of cropland area from VGT data and TM image were also aggregated to county-level, using an administrative county map, and then compared to the 1995 county-level agricultural census data. This landscape-scale analysis incorporated image classification (e.g. coarse-resolution VGT data, fineresolution TM data), statistical census data (e.g. county-level agricultural census data) and a geographical information system (e.g. an administrative county map), and demonstrated the potential of multi-temporal VGT data for mapping of croplands across various spatial scales from landscape to region. This analysis also illustrated some of the limitations of per-pixel classification at the 1 km resolution for a heterogeneous landscape.

Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes region (Ethiopia)

Early multidisciplinary surveys in the Lakes region of central/south Ethiopia show a highly variable land cover pattern characterised by complex interactions between environmental parameters and socio-economic dynamics. From an ecological point of view the area is highly sensitive and both food security and soil conservation are becoming serious problems for the rapidly growing population. The intensive land cover changes observed in this area during the last few decades beg accurate analysis. Land-cover change analysis over a long time-span was performed. Interpretation (API) of aerial photographs dated 1972 and classification of a 1994 Landsat TM image were used. Problems due to the heterogeneous nature of the data were overcome with a method for quantifying land cover on aerial photographs, thus producing data comparable to TM classification results. As land cover is linked, through land use, to social dynamics, in ground control use was made of the results of parallel socio-economic investigations. From the analysis, a general trend of increase in cultivated surfaces was noted. Unique strategies of land allocation according to physical settings were observed. A trend in the evolution of badlands was identified: rapid reactivation of previous erosion in newly cropped areas occurred; within a few decades this erosion reached quasi-equilibrium. The methods adopted showed some accuracy limitations, but allowed land-cover change analysis over a 22-year time-span, providing important insight into recent phenomena and present trends.

Bias in land cover change estimates due to misregistration

Land cover change may be overestimated due to positional error in multi-temporal images. To assess the potential magnitude of this bias, we introduced random positional error to identical classified images and then subtracted them. False land cover change ranged from less than 5% for a 5-class AVHRR classification, to more than 33% for a 20-class Landsat TM classification. The potential for false change was higher with more classes. However, false change could not be reliably estimated simply by number of classes, since false change varied significantly by simulation trial when class size remained constant. Registration model root mean squared (rms) error may underestimate the actual image co-registration asccuracy. In simulations with 5 to 50 ground control locations, the mean model rms error was always less than the actual population rms error. The model rms error was especially unreliable when small sample sizes were used to develop second order rectification models. We introduce a bootstrap resampling method to estimate false land cover change due to positional error. Although the bootstrap estimates were unbiased, the precision of the estimates may be too low to be of practical value in some land cover change applications.

Value of Ki-67 Immunolabelling as a Prognostic Factor in Prostate Cancer

The aim of the study was to analyze the results of Ki-67 immunostaining in prostatic adenocarcinoma and to assess its prognostic value. Clinical follow-up data was reviewed in 190 prostatic adenocarcinomas and the results of Ki-67 immunolabelling were correlated to standard prognostic factors and survival data of the patients. All stage and grade categories were included. Ki-67 expression correlated significantly with histological differentiation of tumors, indicators of cell proliferation, perineural growth, density of tumor-infiltrating lymphocytes and TM classification. In survival analysis, Ki-67 expression was able to discriminate patients into different prognostic groups (p = 0.0035). In a separate analysis including T1-2M0 tumors, Ki-67 immunolabelling was a significant predictor of survival (p = 0.0258). In Cox's multivariate analysis Ki-67 was an independent prognostic factor in the entire cohort. The results show that Ki-67 expression is a potentially useful prognostic factor in prostatic adenocarcinoma and it could be used as an additional criterion in defining a correct prognostic category in this malignancy.

Evaluation of airborne video data for land-cover classification accuracy assessment in an isolated Brazilian forest

This research was designed to evaluate the operational utility of airborne bispectral video data for reconnaissance assessment of land-cover variability and to document the viability of the video data for classification accuracy assessment. There are distinct logistical advantages utilizing airborne video data in isolated and environmentally sensitive regions where there is limited preexisting aerial photography and poor infrastructure and where ground accessibility is difficult and expensive. In a study of land-cover characteristic in Mato Grosso, Brazil, video data provided important insights into the variability and transitions in land-cover that could be used to identify targets for field work and training areas for subsequent satellite image (Landsat TM) classifications. Comparisons of Landsat TM classification accuracy assessments derived from the airborne video and standard color photography revealed that comparable results can be achieved at a high statistical level of significance (0.01). These results demonstrated that the video data can provide information for accuracy assessments equivalent to more standard photographic point-sample data acquisition missions with the added benefit of easily acquiringfar more data. Results of the supervised Landsat TM classification coupled with a topographic model produced an overall accuracy of 68% with a Kappa coefficient of 0.60, based upon a priori classes identified through evaluation of the airborne data and a site visit.

Maximum likelihood TM classification — Taking the effect of pixel to pixel correlation into account

Abstract To investigate the effect of a pixel to pixel correlation on classification performance for TM data, some experiments have been conducted. One of the results shows that the pixel to pixel correlation in homogeneous fields of TM data is larger than that of the simultaneously acquired MSS data. This implies that it is more important to take into account the pixel correlation for TM classification rather than MSS classification. To overcome the effect of the correlation, the following methods have been investigated. Divided the correlated image into several uncorrelated sub‐images and Based on the auto‐regressive model, modify the Gaussian statistical parameters for the correlated image to those for uncorrelated stochastic process. An example using agricultural TM data shows a slight improvement weighted mean percentage of correct classification. Through the investigation of the correlation structures, a more realistic model for TM data has been developed.