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1

Monitoring Land Use and Land Cover Changes Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Ait El Haj Fatiha, Ouadif Latifa, Akhssas Ahmed

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 1

272--286

EN

The study of land use and land cover change (LULC) is essential for the development of strategies, monitoring and control of the ecosystem. The present study aims to describe the dynamics of land cover and land use, and specially the impact of certain climatic parameters on the distribution of vegetation and land cover. For this study, multi-temporal remote sensing data are used to monitor land cover changes in Morocco, using a set of Landsat images, including Landsat 7 (ETM+), Landsat 5 (TM), and Landsat 8 (OLI), captured during the period 2000–2020, those changes were determined by adopting the maximum likelihood (ML) classification method. The classification results show good accuracy values in the range of 90% (2000), 80% (2007), 82% (2010), 93% (2020). The LU/LC change detection showed a decrease of agricultural and forest areas in the order of 5% between the year 2000 and 2020, and an increase of bare soil of 5% to 6%, and a notable change in urban area from 97.31 ha (0.03%) in 2000 to 2988.2637 ha (0.82%) in 2020. The overall results obtained from LULC show that the vegetation cover of the study area has undergone major changes during the study period. In order to monitor the vegetation status, an analysis of the precipitation-vegetation interaction is essential. The normalized difference vegetation index (NDVI) was determined from 2000 to 2020, to identify vegetation categories and quantify the vegetation density in the Lakhdar sub-basin. The obtained NDVI was analyzed using climatic index SPI (Normalized Precipitation Index) based on rainfall data from five stations. The correlation study between NDVI and SPI indices shows a strong linear relation between these two indicators especially while using an annual index SPI12 however, the use of NDVI index based on remote sensing provides a significant result while assessing vegetation. The results of our study can be used for vegetation monitoring and sustainable management of the area, since it is one of the largest basins in the country.

2

Monitoring spatial and temporal scales of shoreline changes in Lahou-Kpanda (Southern Ivory Coast) using landsat data series (TM, ETM+ and OLI)

Zonkouan Badjo Ruth Virginia, Bachri Imane, Beda Abaze Henri Joël, N’Guessan Kpangba Aristide Meniansou

Geomatics and Environmental Engineering

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2022

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Vol. 16, no. 1

145--158

EN

Shoreline changes are crucial for assessing human-ecosystem interactions in coastal environments. They are a valuable tool for determining the environmental costs of socioeconomic growth along coasts. In this research, we present an assessment of shoreline changes along the eastern coast of Lahou-Kpanda of the Ivory Coast during the period from 1980 to 2020 by applying Digital Shoreline Analysis System method using Landsat Data Series. The measurement of the shoreline dynamics of the Lahou-Kpanda coastline is mainly described in three parts: the west straight cordon, the dynamics at the mouth and the east straight cordon. The findings show a drastic reduction in natural shorelines. The greatest transition occurred along the mouth segment of the coast, where the average erosive velocity approaches 90 meters each year and the average distance has decreased by around 2 kilometers. The Ivory Coast lost more than 40% of its biological shorelines between 1980 and 2020, according to this report, a worrying development because these are regions that were once biologically abundant and highly rich. In general, human operations on the Ivory Coast’s shorelines have never had such an impact. The effects of these changes on habitats, as well as the vulnerability of new shoreline investments to increased human activity and sea-level rise, must be measured.

3

Green Space Assessment and Management in Biscay Province, Spain using Remote Sensing Technology

Makinde Esther O., Andonegui Cristina M., Vicario Ainhoa A.

Geomatics and Environmental Engineering

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2021

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Vol. 15, no. 4

21--43

EN

Our ecosystem, particularly forest lands, contains huge amounts of carbon storage in the world today. This study estimated the above ground biomass and carbon stock in the green space of Bilbao Spain using remote sensing technology. Landsat ETM+ and OLI satellite images for year 1999, 2009 and 2019 were used to assess its land use land cover (LULC), change detection, spectral indices and model biomass based on linear regression. The result of the LULC showed that there was an increase in forest vegetation by 12.5% from 1999 to 2009 and a further increase by 2.3% in 2019. However, plantation cover had decreased by 3.5% from 1999–2009; while wetlands had also decreased by 9% within the same period. There was, however, an increase in plantation cover from 2009 to 2019 by 2.1% but a further decrease in wetlands of 4.3%. Further results revealed a positive correlation across the three decades between the widely used Normalized Differential Vegetation Index (NDVI) with other spectral indices such as Enhance Vegetation Index (EVI) and Normalized Differential Moisture Index (NDMI) for biomass were: for 1999 EVI (R2 = 0.1826), NDMI (R2 = 0.0117), for 2009 EVI (R2 = 0.2192), NDMI (R2 = 0.3322), for 2019 EVI (R2 = 0.1258), NDMI (R2 = 0.8148). A reduction in the total carbon stock from 14,221.94 megatons in 1999 to 10,342.44 megatons 2019 was observed. This study concluded that there has been a reduction in the amount of carbon which the Biscay Forest can sequester.

4

Analysis of Spatial‑Temporal Changes of Agricultural Land Use During the Last Three Decades in the Araban District of Turkey Using Remote Sensing

Tunc Erdihan, Tsegai Awet Tekeste, Çelik Sevil

Geomatics and Environmental Engineering

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2021

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Vol. 15, no. 1

111--123

EN

Agricultural land use and land cover dynamics were investigated in the Araban district of Turkey during the periods 1984–2019 by the use of Remote Sensing and Geographic Information Systems (GIS). Landsat TM and Landsat TIRS / OLI satellite imageries were used to determine land use and land cover changes. Using unsupervised classification method of ERDAS 8.3 software, three main agricultural activities were identified namely irrigated farming, dry farming, and horticultural / garden farming. The analysis has revealed that during the last three decades dry farming has decreased significantly by 14.69% (3802.14 ha) whereas horticultural/garden crops and irrigated farming lands have increased by 11.32% (667.19 ha) and 2.51% (2929.41 ha) respectively. Araban has been under intensive agricultural use due to its fertile soil and preference for horticultural crops such as pistachio, grapes and olives that provide more profit over dry farming crops such as wheat and barley has changed land use. Decrease in dry farming in a semi arid climate where Araban is located, has a potential ecological consequence, including a rapid drop of groundwater level, drying of wetlands and the disappearance of the biodiversity, thus, a necessary measures should be taken to implement an environmentally friendly, sustainable agriculture and settlement plan.

5

Assessment of land surface temperature dynamics over the Bharathapuzha River Basin, India

John Jisha, Chithra N. R., Thampi Santosh G.

Acta Geophysica

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2021

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Vol. 69, no. 3

855--876

EN

Anthropogenic interventions have altered the natural environment and afected many of its physical, chemical, and biological characteristics. Changes in land use-land cover (LULC) are one of the main drivers that alter the hydrologic cycle and cause signifcant impacts on local, regional, and even the global climate system. It is now widely recognised and accepted that climate change is one of the gravest problems that our planet Earth is facing at present. This study analyses the impact of LULC dynamics on the spatial and temporal variation of land surface temperature (LST) in an inter-state river basin, which also happens to be the largest river basin in the state of Kerala, India, viz. the Bharathapuzha river basin, during the period 1990–2017. LST time-series analysis (derived from Landsat) revealed that 98% of the river basin experienced LST less than 298 K in January 1990. Over time, along with changes in LULC, LST also increased; in 2017, about 7.82% of the river basin experienced LST greater than 312 K. A notable change in LULC that occurred during this period was the drastic increase in areas with high albedo. The seasonal curves of LST derived from MODIS data are strong evidence of the devastating impacts of change in LULC on LST and, in turn, on climate change. The major spatial and temporal components of change in LST in the study region were identifed by principal component analysis (PCA). The results of this spatiotemporal analysis spread over a period of 28 years can be used for formulating sustainable development policies and mitigation strategies against extreme climatic events in the river basin.

6

Monitoring and forecasting spatio-temporal LULC for Akure rainforest habitat in Nigeria

Aliyu Yahaya A, Youngu Terwase T., Abubakar Aliyu Z., Bala Adamu, Jesulowo Christianah I.

Reports on Geodesy and Geoinformatics

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2020

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Vol. 110

29--38

EN

For several decades, Nigerian cities have been experiencing a decline in their biodiversity resulting from rapid land use land cover (LULC) changes. Anticipating short/long-term consequences, this study hypothesised the effects of LULC variables in Akure, a developing tropical rainforest city in south-west Nigeria. A differentiated trend of urban LULC was determined over a period covering 1999–2019. The study showed the net change for bare land, built-up area, cultivated land, forest cover and grassland over the two decades to be -292.68 km2, +325.79 km2, +88.65 km2, +8.62 km2 and -131.38 km2, respectively. With a projected population increase of about 46.85%, the study identified that the built-up land cover increased from 1.98% to 48.61%. The change detection analysis revealed an upsurge in built area class. The expansion indicated a significant inverse correlation with the bare land class (50.97% to 8.66%) and grassland class (36.33% to 17.94%) over the study period. The study observed that the land consumption rate (in hectares) steadily increased by 0.00505, 0.00362 and 0.0687, in the year 1999, 2009 and 2019, respectively. This rate of increase is higher than studies conducted in more populated cities. The Cellular Automata (CA) Markovian analysis predicted a 37.92% growth of the study area will be the built-up area in the next two decades (2039). The 20-year prediction for Akure built-up area is within range when compared to CA Markov prediction for other cities across the globe. The findings of this study will guide future planning for rational LULC

7

Geostatistical Methods as a Tool Supporting Revitalization of Industrially Degraded and Post-Mining Areas

Zawadzki Jarosław, Fabijańczyk Piotr, Przeździecki Karol

New Trends in Production Engineering

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2020

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Vol. 3, Iss. 1

30--40

EN

Post-industrial and post-mining areas have often been under strong anthropogenic pressure for a long time. As a result, such areas, after the ending of industrial activity require taking steps to revitalize them. It may cover many elements of the natural or urban environment, such as water, soil, vegetated areas, urban development etc. To carry out revitalization, it is necessary to determine the initial state of such areas, often using selected chemical, geophysical or ecological. After that it is also important to properly monitor the state of such areas to assess the progress of the revitalization process. For this purpose a variety of change detection technics were developed. Post-industrial areas are very often characterized by a large extent, are difficult to access, have complicated land cover. For this reason, it is particularly important to choose appropriate methods to assess the degree of pollution of such areas. Such methods should be as economical as possible and time-effective. A very desirable feature of such methods is that they should allow a quick assessment of the entire area. Geostatistics supplemented by modern remote sensing can be effective for this purpose. Nowadays, using remote sensing, it is possible to gather information simultaneously from the entire, even vast area, with high spatial, spectral and temporal resolution. Geostatistics in turn provides many tools that are able to enable rapid analysis and inference based on even very complicated often scarce spatial data sets obtained from ground measurement and satellite observations. The goal of the article was to present selected results obtained using geostatistical methods also related to remote sensing, which may be helpful for decision makers in revitalizing post-industrial and post-mining areas. The results described in this paper were based mostly on the previous studies, carried out by authors.

8

Changes in the built-up areas at the aeration wedges of City of Warsaw

Grzybowski Patryk, Gurdak Radoslaw

Geoinformation Issues

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2018

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Vol. 10, no. 1(10)

37--51

EN

The main objective of this paper is to present increasing share of built-up areas at the aeration wedges of City of Warsaw. The idea of Warsaw aeration corridors had been arisen in 1916 and was adapted to the present times in 1992, 2006 and 2018 in the planning’s documents which described Warsaw spatial development conditions. The goal for creation these corridors has been to establish the air exchange between areas around the city (especially green areas) and downtown. The analyses were carried out for years: 1992, 1995, 1998, 2001, 2004, 2006, 2009 – based on Landsat-5; 2013 – based on Landsat-8; 2015, 2018 based on Sentinel-2. As a result of research, it was found that aeration wedges had been constantly built-up. In 1992 built-up areas covered 14% (767 ha) of aeration corridors, in 1998 – 17% (918 ha), in 2006 – 24% (1245 ha), in 2013 – 26% (1341 ha), in 2018 – 27% (1383 ha). The largest loss of green areas was noticed as: arable lands and meadows – from 42% to 29%. In addition, during the research it was observed that new buildings have been situated in unfavorable way. New buildings are the walls and barriers to the air masses coming to the downtown.

PL

Głównym celem pracy było zaprezentowanie zmian w zabudowie na obszarach klinów napowietrzających miasta Warszawy. Idea korytarzy napowietrzających narodziła się w 1916, a następnie była zaadaptowana to potrzeb i warunków i obecnych czasów w latach 1992, 2006 i 2018. Opisana ona była w dokumentach dotyczących zagospodarowania przestrzennego Warszawy. Celem, dla którego wyznaczono kliny było zapewnienie wymiany powietrza pomiędzy centrum miasta a terenami podmiejskimi (szczególnie terenami zieleni). Analizy zostały przeprowadzone dla lat 1992, 1995, 1998, 2001, 2004, 2006, 2009 – wykorzystano zobrazowania Landsat 5; 2013 – wykorzystano zobrazowanie z Landsat 8, 2015 i 2018 – wykorzystano zobrazowanie z Sentinel-2. W wyniku badań, stwierdzono, że tereny korytarzy są stale zabudowywane. W roku 1992 obszary zabudowane wynosiły 14% całości powierzchni korytarzy (767 ha), w 1998 – 17% (918 ha), w 2006 – 24% (1245 ha), w 2013 – 26% (1341 ha), a w 2018 – 27% (1383 ha). Zmiany te w największym stopniu, spowodowały straty w obszarach rolniczych i łąkach. Ich powierzchnia w 1992 roku zajmowała 42%, w 2018 było to tylko 29%. Ponadto, podczas badań zaobserwowano, iż nowe budynki budowane są w niekorzystnym położeniu – są one przeszkodą dla swobodnych ruchów mas powietrza.

9

Vegetation changes and formation of small-scale urban heat islands in three populated districts of Kerala State, India

Veettil B. K., Grondona A. E. B.

Acta Geophysica

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2018

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Vol. 66, no. 5

1063--1072

EN

Currently, more than half of the world’s population is living in cities. Rapid and unplanned urbanization became a common scenario in rapidly developing countries such as those in Asia. Decline in vegetation coverage and increase in local air and land surface temperatures are among the adverse effects of unplanned urban growth. We used Landsat data for the period 1991–2017 to estimate the expansion of urban areas in terms of vegetation loss and the development of small-scale urban heat islands in developing cities in Kerala state of India. For the last 27 years, unplanned urbanization in Kerala state has increased and this resulted in the enhanced loss of vegetation and, possibly, resulted in the increase in land surface temperature (LST). Our results indicate that vegetation coverage, particularly near the urban areas, has been decreased by 5.8%, 10.4%, and 9.6% in Ernakulam, Trichur, and Kozhikode districts, respectively. The land surface temperatures also have been increased during the study period. It is interesting to note that higher increase in LST and higher reduction in vegetation coverage were observed in Trichur and Kozhikode districts compared with highly populated and urbanized Ernakulam district.

10

Analysis of multitemporal changes in the environment using GIS and remote sensing in the aspect of construcion projects

Głowienka E., Hejmanowska B., Michałowska K., Pękala A.

Geomatics, Landmanagement and Landscape

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2017

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no. 2

61--69

EN

Modern changes of environment are the result of many factors, of which anthropogenic activities and the development of infrastructure play the leading role in environmental, morphometric changes. The dynamics of expansion of construction lands, which until recently have changed only as a result of natural factors, makes it invariably important to analyse time changes and forecast potential effects of construction projects on the environment. A good source of information about changes, for example the course of rivers, hydrological conditions, diversity of vegetation in the areas of investment, are cartographic sources, in particular GIS techniques, satellite images, and aerial photographs. Proper assessing of the territory using GIS techniques may allow constructing roads not only with less damage to the environment and human health, but also avoiding technical problems, such as low bearing capacity of soils. The main objective of the study is to evaluate multitemporal changes of the environment in the course of the ongoing construction project, which is the construction of the A4 motorway in its Rzeszów Wschód – Jarosław Zachód section, in the area of the Wierzbna junction. The analysis was carried out on the basis of Landsat satellite images recorded in two different investment periods of the tested object: in 2006 – prior to the start of construction works, in 2015 – in the course of the ongoing construction works. In addition, the analysis of the obtained Landsat multitemporal satellite images made it possible to examine the morphology of the substrate conditions of river valleys of the San, Wislok, and Mleczka.

11

Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

Drzewiecki W.

Geodesy and Cartography

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2017

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Vol. 66, no. 2

171--209

EN

We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

12

Coastline change-detection method using remote sensing satellite observation data

Markiewicz Ł., Mazurek P., Chybicki A.

Hydroacoustics

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2016

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Vol. 19

277—284

EN

Coastal zones are not only the fundaments for local economics based on trade, shipping and transport services, but also a source of food, energy, and resources. Apart from offering diverse opportunities for recreation and tourism, coastal zones provide protection against storms and other meteorological disturbances. Environmental information is also essential because of the direct influence on a country’s maritime zones, which are territorial sea and exclusive economic zones. Keeping local communities and ecosystems healthy requires monitoring and assessing of all the vital changes of territorial sea and its baseline. The paper presents a method and a concept of a system that provides an efficient means of automatic analysis of spatial data provided by satellite observation systems (optical Landsat 8 and SAR Sentinel 1) in order to monitor, and detect, changes in the coastline. The proposed methodology is based on a set of algorithms that enable one to trace and detect changes in coastline shape, and eventual damage to marine infrastructure, such as breakwaters and harbours, relying on high resolution satellite observational products.

13

Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

Drzewiecki W.

Geodesy and Cartography

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2016

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Vol. 65, no. 2

193--218

EN

In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.

14

Earth observation and geospatial techniques for soil salinity and land capability assessment over Sundarban Bay of Bengal Coast, India

Das S., Choudhury M. R, Das S., Nagarajan M.

Geodesy and Cartography

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2016

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Vol. 65, no. 2

163--192

EN

To guarantee food security and job creation of small scale farmers to commercial farmers, unproductive farms in the South 24 PGS, West Bengal need land reform program to be restructured and evaluated for agricultural productivity. This study established a potential role of remote sensing and GIS for identification and mapping of salinity zone and spatial planning of agricultural land over the Basanti and Gosaba Islands(808.314sq. km) of South 24 PGS. District of West Bengal. The primary data i.e. soil pH, Electrical Conductivity (EC) and Sodium Absorption ratio (SAR) were obtained from soil samples of various GCP (Ground Control Points) locations collected at 50 mts. intervals by handheld GPS from 0–100 cm depths. The secondary information is acquired from the remotely sensed satellite data (LANDSAT ETM+) in different time scale and digital elevation model. The collected field samples were tested in the laboratory and were validated with Remote Sensing based digital indices analysisover the temporal satellite data to assess the potential changes due to over salinization. Soil physical properties such as texture, structure, depth and drainage condition is stored as attributes in a geographical soil database and linked with the soil map units. The thematic maps are integrated with climatic and terrain conditions of the area to produce land capability maps for paddy. Finally, The weighted overlay analysis was performed to assign theweights according to the importance of parameters taken into account for salineareaidentification and mapping to segregate higher, moderate, lower salinity zonesover the study area.

15

Semiautomatic land cover mapping according to the 2nd level of the CORINE Land Cover legend

Golenia M., Zagajewski B., Ochtyra A., Hościło A.

Polish Cartographical Review

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2015

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Vol. 47, No. 4

203--212

EN

Actual land cover maps are a very good source of information on present human activities. It increases value of actual spatial databases and it is a key element for decision makers. Therefore, it is important to develop fast and cheap algorithms and procedures of spatial data updating. Every day, satellite remote sensing deliver vast amount of new data, which can be semi-automatically classified. The paper presents a method of land cover classification based on a fuzzy artificial neural network simulator and Landsat TM satellite images. The latest CORINE Land Cover 2012 polygons were used as reference data. Three satellite images acquired 21 April 2011, 5 June 2010, 27 August 2011 over Warsaw and surrounding areas were processed. As an outcome of classification procedure, the maps, error matrices and a set of overall, producer and user accuracies and a kappa coefficient were achieved. The classification accuracy oscillates around 76% and confirms that artificial neural networks can be successfully used for forest, urban fabric, arable land, pastures, inland waters and permanent crops mapping. Low accuracies were obtained in case of heterogenic land cover units.

16

Mapa geomorfologiczna województw pomorskiego i warmińsko-mazurskiego z wykorzystaniem metod geoinformatycznych

Marcinkowska A., Ochtyra A., Olędzki J. R., Wołk-Musiał E., Zagajewski B.

Teledetekcja Środowiska

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2013

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T. 49

43--79

EN

The aim of this study was to prepare geomorphological maps of pomorskie and warminsko-mazurskie voivodeships in scale 1:300 000. Analysis primarily were based on the General Geomorphological Map of Poland 1:500 000 and Landsat 5 TM satellite images in RGB 453 composition, and alternatively with Geological Map of Poland 1:200 000, Topographic Map of Poland 1:100 000 and Digital Terrain Model from Shuttle Radar Topography Mission. These materials were processed into digital form and imported them PUWG 1992 coordinate system. Based on them was lead interpretation and vectorization of geomorphological forms. It was detailing the boundaries in accordance with the content of the General Geomorphological Map of Poland 1:500 000. Then polygons were coded according to the numbering of J. Borzuchowski (2010). Very important was process to design a legend and then editing maps. The last stage of this study was to prepare a composition for printing maps. The effect of studies are geomorphological maps of pomorskie and warminsko-mazurskie voivodeships in scale 1:300 000, and an interactive databases in ESRI shapefile format (*.shp).

17

Zastosowanie technik geomatycznych w opracowywaniu map pokrycia i użytkowania terenu dla obszarów zrekultywowanych

Szostak M., Nowicka M.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2013

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Vol. 25

203--216

EN

The aim of this study was to investigate the possible use of geotechniques and generally available geodata for mapping land cover on reclaimed areas . The choice of subject was dictated by the growing number of such areas and the related problem of restoring their value. The validity of the use of modern technology, including GIS, photogrammetry and remote sensing, was determined, especially for the land cover classes mapping that are relevant in assessing the effects of reclamation and analyzes of the changes taking place on such sites. The study was performed for dump site of the Sulphur Mine "Machów", which is an example of the reclaimed area, located in the Tarnobrzeski district. The research materials consisted of aerial orthophotos, which were the basis of on-screen vectorization of land cover classes; Landsat satellite images, which were used in the pixel based classification; and the CORINE Land Cover database as a general reference to the global maps of land cover and land use. The site was characterized by relatively large mosaic of landscape which is typical for reclaimed areas. Due to this fact, high resolution aerial photos were most suitable for the land cover mapping, allowing distinguishing highest number of land cover classes. The process was also successfully automated with the means of pixel-based image classification on the satellite images. This resulted also in the subjectivity of the operator and time costs. The efford made to develop land cover classes, supported with thorough knowledge of the operator, is important for the proper evaluation of the reclamation process.

PL

Celem pracy było zbadanie możliwości wykorzystania technik geoinformatycznych i ogólnie dostępnych geodanych dla opracowywania map pokrycia (użytkowania) terenu obszarów zrekultywowanych. Wybór tematu był podyktowany rosnącą liczbą takich obszarów i częstym problemem przywrócenia lub nadania gruntom poprzemysłowym wartości użytkowych (wykonanie rekultywacji). Określano zasadność wykorzystania nowoczesnych technologii GIS oraz materiałów geodezyjnych dla wyznaczenia granic klas pokrycia terenu, istotnych w ocenie efektów rekultywacji oraz analizach zmian zachodzących na tego rodzaju obiektach. Badania wykonano dla zwałowiska zewnętrznego Kopalni Siarki "Machów", zlokalizowanego na terenie powiatu tarnobrzeskiego, będącego przykładem obszaru zrekultywowanego. Podstawowymi materiałami badawczymi były ortofotomapy lotnicze, na postawie których wykonano wektoryzację ekranową klas pokrycia terenu; zobrazowania satelitarne Landsat, które posłużyły do przeprowadzenia klasyfikacji pikselowej oraz dane programu CORINE Land Cover, jako ogólne odniesienie do globalnych map pokrycia i użytkowania terenu. Zwałowisko Kopalni „Machów” charakteryzowała stosunkowo duża mozaikowatość krajobrazu (często występująca na terenach rekultywowanych), więc właściwą przydatnością do sporządzania map pokrycia terenu charakteryzowały się wysokorozdzielcze ortofotomapy lotnicze, umożliwiające wyodrębnienie największej liczby klas pokrycia terenu. Dla zautomatyzowania procesu wyznaczania granic pokrycia terenu testowano, metodę klasyfikacji nadzorowanej zobrazowań satelitarnych. (najlepsze efekty uzyskano z użyciem w klasyfikacji algorytmu największego prawdopodobieństwa). Pozwoliła ona na zmniejszenie subiektywizmu i czasu pracy operatora Staranie wykonane opracowanie kategorii pokrycia terenu, poparte gruntowną wiedzą fotointerpretatora na temat przyjętych kierunków rekultywacji oraz czasu jej rozpoczęcia i zakończenia, wykonane na materiałach geodezyjnych odpowiedniej rozdzielczości jest istotne, gdyż jest podstawą dla właściwej oceny przeprowadzonej rekultywacji.

18

Mapa zmian pokrycia terenu małopolski 1986-2011 wykonana w oparciu o klasyfikację obiektową obrazów satelitarnych Landsat oraz RapidEye

Wężyk P., Wójtowicz-Nowakowska A., Pierzchalski M., Mlost J., Szafrańska B.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2013

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Vol. 25

273--284

EN

Changes in land use / land cover are the result of interaction between natural processes and human activity. Using GIS analysis to estimate the dynamic of these changes we can detect former trends and their simulation in the future. Diagnosed directions of changes can be used e.g. to create local plans of spatial management or region growth policy. Main goal of this study was to diagnose main trends of changes in land use / land cover in Malopolska voivodeship in last 25 years (1986-2010). Results were shown as statistics and map compositions. Project was created based on RapidEye and LANDSAT 5 TM satellite data and aerial imagery from 2009-2010. The best way to process huge amount and various data was to use Object Based Image Analysis (OBIA). As the results of classification we received 10 classes of land use for both terms of analyses (1986-1987 and 2009-2010). Identified classes were: bare soil, grass-covered areas, urban areas, rivers and watercourses, coniferous forest, leaf forest, peatbog, and other areas. Results show, that especially 2 classes arisen much: forest (4.39%) and urban areas (2.40%), mostly at the expanse of agricultural (-3.60%) and grass-covered areas (-1.18%). Based on results we can say, that changes detected in past 25 years in Malopolska region, which we can also notice today, agree with general trends of landscape changes, that we can observe in Poland for the last 3 decades. These general changes are: renewed succession of forest on areas where agricultural production discontinued; also intense development of road infrastructure. Object Based Image Analysis allowed to realize these study for area of more than 15 000 km2 for only a few weeks.

PL

Zmiany pokrycia terenu i użytkowania ziemi są rezultatem wzajemnego oddziaływania na siebie złożonych procesów przyrodniczych oraz społeczno-ekonomicznych. Analizy przestrzenne GIS dynamiki tych zmian umożliwiają wykrycie występujących w przeszłości trendów i procesów oraz ich symulację dla nadchodzącego okresu. Zdiagnozowane kierunki przemian krajobrazu mogą zostać wykorzystane m.in. przy tworzeniu lokalnych planów zagospodarowania przestrzennego, czy generalnie kreowaniu polityki rozwoju regionów. Celem prezentowanego opracowania było zdiagnozowanie głównych trendów przemian pokrycia terenu województwa małopolskiego na przestrzeni ostatnich dwudziestu pięciu lat (19862011) oraz ich statystyczne i graficzne zaprezentowanie w postaci kompilacji map numerycznych. Projekt wykonano w oparciu o dane teledetekcyjne: zobrazowania satelitarne RapidEye i LANDSAT TM oraz lotnicze ortofotomapy (PZGiK) z lat 2009 - 2010. Duża ilość i różnorodność danych wymusiła zastosowanie obiektowego przetwarzania danych teledetekcyjnych, tj. klasyfikacji OBIA (ang. Object Based Image Analysis). W wyniku przeprowadzanej klasyfikacji otrzymano 10 klas pokrycia i użytkowania terenu dla dwóch terminów badawczych (1986-87 oraz 2010-11), tj.: grunty orne, użytki zielone, tereny zurbanizowane, rzeki i cieki, zbiorniki wodne, lasy iglaste, lasy liściaste, zadrzewienia i zakrzewienia, tereny różne oraz torfowiska. Wykazano, iż na obszarze Małopolski wystąpiło znaczne zwiększenie powierzchni lasów (wzrost o 4.4%) oraz terenów zurbanizowanych (wzrost o 2.4%), głównie kosztem powierzchni gruntów rolnych (ubytek o 3.6%) oraz trwałych użytków zielonych (ubytek o 1.2%). Otrzymane wyniki pozwoliły wysunąć wniosek, iż zmiany jakie zachodziły w przeciągu 25 lat oraz te, z którymi wciąż mamy do czynienia w województwie małopolskim, pokrywają się z ogólnymi kierunkami i trendami przemian krajobrazu obserwowanymi w Polsce w ostatnich trzech dekadach, tj. procesami sukcesji wtórnej zbiorowisk leśnych na gruntach, na których zaprzestano produkcji rolnej oraz związanych z inwestycjami infrastruktury drogowej i kolejowej. Zastosowanie automatycznej klasyfikacji obiektowej oraz analiz przestrzennych GIS pozwoliło na realizację opracowania dla obszaru ponad 15.000 km2 w ciągu zaledwie kilku tygodni.

19

Ocena możliwości identyfikacji łąk produkcyjnych i ekologicznych z wykorzystaniem pojedynczego zdjęcia satelity Landsat

Kosiński K., Hoffmann-Niedek A., Kozłowska T.

Woda-Środowisko-Obszary Wiejskie

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2012

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T. 12, z. 1

71-82

PL

W artykule przedstawiono możliwości identyfikacji produkcyjnych i ekologicznych siedlisk łąkowych na pojedynczym zdjęciu Landsat ETM+. Analizowano niezależnie dwa zdjęcia, pozyskane 10 września 1999 i 1 maja 2001 r. Podjęto próbę rozróżnienia siedlisk na podstawie par charakterystyk: kanałów spektralnych (ETM 3, 4, 5), kanału panchromatycznego (ETM8) i wskaźników różnicowych (NDVI - wskaźnik różnicowy obliczony z kanałów ETM4 i ETM3; ND(3,5) - wskaźnik różnicowy obliczony z kanałów ETM5 i ETM3), uzyskanych niezależnie z dwóch zdjęć. Z kategorią siedliskową związane są trzy pary charakterystyk obliczonych dla początku maja: ETM3 i NDVI, ETM4 i ETM5, jak również NDVI i ND(3,5). Jednak błędy klasyfikacji okazały się zbyt duże. Na zdjęciu wrześniowym nie stwierdzono różnic pomiędzy siedliskami w żadnej z par charakterystyk. Nie wyklucza to możliwości klasyfikacji siedlisk w trybie analizy wieloczynnikowej.

EN

The paper presents possibilities of identification of productive and ecological meadows on a single Landsat ETM+ image. Two images acquired on 10 September 1999 and 1 May 2001 were analyzed independently. Attempt was undertaken to distinguish habitats based on the following pairs of characteristics: spectral channels (ETM 3, 4, 5), panchromatic channel (ETM8) and differential indexes (NDVI, ND(3,5)) obtained from each of the images separately. Three pairs of characteristics are correlated with the habitat category obtained at the beginning of May: ETM3 vs NDVI, ETM4 vs ETM5 and NDVI vs ND(3.5). However, classification errors were far too high. In the image obtained in September, there were no differences between the habitats in any pair of characteristics. However, the possibility of classification of habitats in the multivariate analysis mode is still not excluded.

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Detekcja zmian pokrycia terenu na zdjęciach satelitarnych Landsat - porównanie trzech metod

Niedzielko J., Lewiński S.

Teledetekcja Środowiska

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2012

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T. 47

87--98

EN

Environmental changes are amongst the most important research subjects in geography. The changes may be natural, but also may be caused by human activity. Land cover is a significant component of the changing environment. Monitoring of its changes involves usage of satellite techniques. Landsat mission provides comparable data since forty years, very useful in land cover studies. Utilization of satellite techniques in such researches is developing quickly. This paper is an example of methods that enable quick and quite accurate assessment of range and spatial distribution of land cover changes. Practical application of image difference, principal component analysis and supervised classification to detect land cover changes is presented. Methods are applied to study area containing different land cover classes. Accuracy of methods was tested and compared. Combining methods presented in earlier researches, five new methods were developed: image difference, image difference with classification, classification, principal component analysis, principal component analysis with classification. Methods were applied to three different input datasets: pairs of images with different level of preprocessing. First dataset was a pair of georeferenced Landsat Thematic Mapper images. The second dataset was the same pair of images, atmospherically corrected using dark object subtraction method. Normalization of one image to the other provided the third dataset. Accuracy assessment was executed. Results were obtained from confusion matrices. Overall accuracy of methods was high, from 77% to 91%. Supervised classification was the most accurate method. Combining fully automatic methods with supervised classification has increased overall accuracy of automatic change detection, however not significantly. Studies on combining change detection methods should be continued. Future studies should concentrate on the automation of change detection process.