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Urban vegetation classification with high-resolution PlanetScope and SkySat multispectral imagery
66-75Views:529In this study two high-resolution satellite imagery, the PlanetScope, and SkySat were compared based on their classification capabilities of urban vegetation. During the research, we applied Random Forest and Support Vector Machine classification methods at a study area, center of Rome, Italy. We performed the classifications based on the spectral bands, then we involved the NDVI index, too. We evaluated the classification performance of the classifiers using different sets of input data with ROC curves and AUC values. Additional statistical analyses were applied to reveal the correlation structure of the satellite bands and the NDVI and General Linear Modeling to evaluate the AUC of different models. Although different classification methods did not result in significantly differing outcomes (AUC values between 0.96 and 0.99), SVM’s performance was better. The contribution of NDVI resulted in significantly higher AUC values. SkySat’s bands provided slightly better input data related to PlanetScope but the difference was minimal (~3%); accordingly, both satellites ensured excellent classification results.
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Mapping aquatic vegetation of the Rakamaz-Tiszanagyfalui Nagy-Morotva using hyperspectral imagery
1-10Views:149Rapid development in remote sensing technologies provides more and more reliable methods for environmental assessment. For most wetlands, it is difficult to walk-in without disturbing the endangered species living there; therefore, application of opportunities provided by remote sensing has a great importance in population-mapping. One effective tool of vegetation pattern estimation is hyperspectral remote sensing, which can be used for association and species level mapping as well, due to high ground resolution. The Rakamaz-Tiszanagyfalui Nagy-morotva is an oxbow lake, located in the north-eastern part of Hungary. For this study, a wetland area of 1.17 km2 containing the original water bad and shoreline was selected. For the image analysis, images taken by an AISA DUAL system hyperspectral sensor were used. At the same time, 7 main vegetation classes were separated, which are typical for the sample plot designated on the test site. Classification was performed by the master areas signed by the most common associations of the Rakamaz-Tiszanagyfalui Nagy-morotva with determined spectrums. During the image analysis, SAM classification method was used, where radian values were optimized by the results of classification performed at the control area.
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Analysis of multitemporal aerial images for fenyőfő Forest change detection
89-100Views:223This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.
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Land cover analysis based on descriptive statistics of Sentinel-2 time series data
1-9Views:337In our paper we examined the opportunities of a classification based on descriptive statistics of NDVI throughout a year’s time series dataset. We used NDVI layers derived from cloud-free Sentinel-2 images in 2018. The NDVI layers were processed by object-based image analysis and classified into 5 classes, in accordance with Corine Land Cover (CLC) nomenclature. The result of classification had a 76.2% overall accuracy. We described the reasons for the disagreement in case of the most remarkable errors.
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Environmental objective analysis, ranking and clustering of Hungarian cities
91-108Views:34The aim of the study was to rank and classify Hungarian cities and counties according to their environmental quality and level of environmental awareness. Ranking of the Hungarian cities and counties are represented on their „Green Cities Index” and „Green Counties Index” values. According to the methodology shown in Part 1, cities and counties were grouped on different classification techniques and efficacy of the classification was analysed. However, they did not give acceptable results either for the cities, or for the counties. According to the parameters of the here mentioned three algorithms, reasonable structures were not found in any clustering. Clusters received applying algorithm fanny, though having weak structure, indicate large and definite regions in Hungary, which can be circumscribed by clear geographical objects.
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The developement of red mud flood environmental information system and the methodology for the spatial analysis of the degraded area
1-11Views:174The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database.
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Spatial distribution of vegetation cover in Erbil city districts using high-resolution Pléiades satellite image
10-22Views:190Green spaces are playing an essential role for ecological balance and for human health in the city as well. They play a fundamental role in providing opportunities for relaxation and enjoying the beauty of nature for the urban population. Therefore, it is important to produce detailed vegetation maps to assist planners in designing strategies for the optimisation of urban ecosystem services and to provide a suitable plan for climate change adaptation in one fast growing city. Hence, this research is an investigation using 0.5 m high-resolution multispectral Pléiades data integrated with GIS data and techniques to detect and evaluate the spatial distribution of vegetation cover in Erbil City. A supervised classification was used to classify different land cover types, and a normalised difference vegetation index (NDVI) was used to retrieve it for the city districts. Moreover, to evaluate the accessibility of green space based on their distance and size, a buffer zone criterion was used. The results indicate that the built-up land coverage is 69% and vegetation land cover is 14%. Regarding NDVI results, the spatial distribution of vegetation cover was various and, in general, the lowest NDVI values were found in the districts located in the city centre. On the other hand, the spatial distribution of vegetation land cover regarding the city districts was non-equal and non-concentric. The newly built districts and the districts far from the Central Business District (CBD) recorded the lowest vegetation cover compared with the older constructed districts. Furthermore, most of the districts have a lack of access to green spaces based on their distance and size. Distance and accessibility of green areas throughout the city are not equally distributed. The majority of the city districts have access to green areas within radius buffer of two kilometres, whereas the lowest accessibility observed for those districts located in the northeast of the city in particular (Xanzad, Brayate, Setaqan and Raperin). Our study is one of the first investigations of decision-making support of the spatial planning in a fast-growing city in Iraq and will have a utilitarian impact on development processes and local and regional planning for Erbil City in the future.
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Types and characteristics of the oxbow-lakes in Lower-Tisza-valley - classification from landscape planning perspective
19-25Views:54The study area is located in Hungary on the South of the Great Plane called Alföld in Hungarian. There are ten oxbow lakes are located in the region of the Lower Tisza Valley. The quality of the area’s oxbow lakes are rather different. There are protected, highly valuable sites in terms of landscape and nature conservation, yet degraded areas utilized for economic purposes can also be found. In the course of river-control in the Lower Tisza Valley was affected by the 84-90th cutoffs, therefore oxbows have been formed in the area. Four of these oxbows are on the part that is not effected by floods, and six of them are located in the active floodplain.The attributes or usage of oxbow lakes allow for a complex system of categorisation. The assessment and classification of oxbow lakes can establish the grounds for assessment, as well as for planning the interventions of landscape restoration.
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Time series analysis of major land resources using Landsat images in a part of district Jhansi, Uttar Pradesh, India
41-57Views:19Space born technology, with its repetitive nature, uses electromagnetic energy to capture digital data from the Earth's surface by remote sensing systems. The purpose of this research is to track changes in land resources with six time series (2003-09, 2003-15, 2003-21, 2009-15, 2009-21 and 2015-21) over a period of 18 years. Multi-date Landsat images of 2003, 2009, 2015 and 2021 have been used to monitor the changing pattern. Level – I classification scheme composed by NRSC/ ISRO and supervised Maximum Likelihood Classification (MLC) techniques were used to identify and classify land use/ land cover features located in Jhansi Tehsil. The findings show that there have been significant changes in land resources over the years. The area under agriculture land, built-up and waterbodies were increased by 48.83%, 53.53% and 106.73% while forest/ tree outside forest and wastelands were reduced by 59.74% and 38.68% respectively It is concluded that, the expansion of key land resources indicates the growth in population and socio-economic activities whereas the loss in some land resources might be due to human induced progressive activities.
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Studying floodplain roughness in an Upper Tisza study area
85-90Views:180Floods slowing down due to the significant decrease of the gradient have considerable sediment accumulation capacity in the floodplain. The grade of accumulation is further increased if the width of the floodplain is not uniform as water flowing out of the narrow sections diverge and its speed is decreased. Surface roughness in a study area of 492 hectares in the Upper Tisza region was analysed based on CIR (color-infrared) orthophotos from 2007. An NDVI index layer was created first on which object-based image segmentation and threshold-based image classification were performed. The study area is dominated by land cover / land use types (grassland-shrubs, forest) with high roughness values. It was concluded that vegetation activity based analyses on their own are not enough for determining floodplain roughness.
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Landuse/landcover change process in a tropical semi-arid zone: case of two rural communes (Chadakori and Saé-Saboua) in Maradi region, Republic of Niger
1-12Views:197The study aimed to analyze the process of Landuse/Landcover change of two rural communes (Saé Saboua and Chadakori) of Maradi region (Republic of Niger) over the past 28 years (1986 – 2014), through landscape structure analysis by diachronic cartographic approach and landscape indices. Mixed classification of temporal series of Landsat images led to identifying six Landuse/Landcover (LULC) classes, namely ”cultivated land under shrubs and trees”, ”cultivated land under trees”, “continuous cropland”, ”fallow/pasture land”, ”forest reserve”, and ”settlement”. The composition and structure of the studied landscapes have greatly changed from 1986 to 2014. The class ”cultivated land under trees” was the landscape matrix in 1986 with 38.65% of landscape total area but in 2001 and 2014 the class ”continuous cropland” became the landscape matrix. The changes also affected the ”forest reserve” which was transformed to smallholder agricultural land from 1986 to 2014. The area occupied by classes ”cultivated land under trees” changed from 38.65% in 1986 to 8.78% in 2014; and from 1986 to 2014, the area occupied by ”fallow/pasture land” has decreased of about 16%. The decrease in these classes was in favor of ¨continuous crop land¨, ¨settlement¨ and “cultivated land under shrubs and trees” which respectively gained 38%, 0.3% and 8.15% of their areas in 1986. The results of this study reflect the problem of access to land and even land saturation in semi-arid region, a consequence of strong population growth. They also contribute to a better rethinking of agricultural practices in order to initiate adaptation and resilience strategies for the population facing food insecurity and poverty.
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Geomorphologic analysis of drainage networks on Mars
15-30Views:46Altogether 327 valleys and their 314 cross-sectional profiles were analyzed on Mars, including width, depth, length, eroded volume, drainage and spatial density, as well as the network structure. According to this systematic analysis, five possible drainage network types were identified such as (a) small valleys, (b) integrated small valleys, (c) individual, medium-sized valleys, (d) unconfined, anastomosing outflow valleys, and (e) confined outflow valleys. Measuring their various morphometric parameters, these five networks differ from each other in terms of parameters of the eroded volume, drainage density and depth values. This classification is more detailed than those described in the literature previously and correlated to several numerical parameters for the first time. These different types were probably formed during different periods of the evolution of Mars, and sprung from differently localized water sources, and they could be correlated to similar fluvial network types from the Earth.
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Relation of meteorological elements and air pollutants to respiratory diseases
1-15Views:47This paper determines the characteristic weather types over the Carpathian Basin for the summer – early autumn period (July 15 – October 15) and the winter months (December, January, and February), with the levels of chemical (CO, NO, NO2 , NO2/NO, O3, O3max, SO2, PM10) and biological [Ambrosia (ragweed) pollen] air pollutants, and with their effect to the respiratory diseases. Based on the ECMWF data set, daily sea-level pressure fields analysed at 00 UTC (Coordinated Universal Time) were prepared for each weather type (cluster) in order to detect the relation between, on the one hand, the sea-level pressure patterns and, on the other, the levels of the chemical and biological air pollutants as well as the frequency of the respiratory diseases in Szeged. Objective definition of the characteristic weather types occurred by using the methods of Factor Analysis and Cluster Analysis. As a result, in the summer – early autumn period the total patient number is proportional to the mean monthly temperature, the maximum and minimum temperatures; however, respiratory diseases occur more frequently, when relative humidity is low. On the other hand, in the winter months there is no relation between the meteorological variables and the patient numbers.
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Preliminary analysis of red mud spill based on aerial imagery, Hungary
47-57Views:129One of the largest industrial spills in Europe occurred in the village of Kolontár (Hungary) on October 4, 2010. The primary objective of the hyperspectral remote sensing mission was to monitor that is necessary in order to estimate the environmental damage, the precise size of the polluted area, the rating of substance concentration in the mud, and the overall condition of the flooded district as soon as possible. The secondary objective was to provide geodetic data necessary for the high-resolution visual information from the data of an additional Lidar survey, and for the coherent modeling of the event. For quick assessment and remediation purposes, it was deemed important to estimate the thickness of the red mud, particularly the areas where it was deposited in a thick layer. The results showed that some of the existing tools can be easily modified and implemented to get the most out of the available advanced remote sensing data.
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Unsupervised classification of high resolution satellite imagery by self-organizing neural network
37-44Views:36The current paper discusses the importance of the modern high resolution satellite imagery. The acquired high amount of data must be processed by an efficient way, where the used Kohonen-type self-organizing map has been proven as a suitable tool. The paper gives an introduction to this interesting method. The tests have shown that the multispectral image information can be taken after a resampling step as neural network inputs, and then the derived network weights are able to evaluate the whole image with acceptable thematic accuracy.