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Historical and projected land-use / land cover changes of the Welmel River Watershed, Genale Dawa Basin, Ethiopia

Ayalew Solomon E., Nigussie Tewodros A.

Journal of Water and Land Development

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2023

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no. 58

89--98

EN

Human activities on land have grown significantly changing the entire landscape, while most of the changes have occurred in the tropics. The change has become a serious environmental concern at the local, regional and global scales. The intensity, speed, and degree of land use / land cover (LULC) changes are nowadays quicker compared to the past because of the development of society. Moreover, the rapid increase in population resulted in disturbing a large number of landscapes on the Earth. The main objective of this study was to detect historical (1990-2020) and predicted (2020-2050) LULC changes in the Welmel River Watershed, which is located in the Genale-Dawa Basin, South Eastern Ethiopia. The dataset of 1990, 2005, and 2020 was generated from Landsat 5, Landsat 7 and Landsat 8 respectively to determine the historical LULC map. The result of this study revealed that agriculture/ settlement increased by 6.85 km2 ∙y-1, while forestland declined by 9.16 km2 ∙y-1 over the last 31 years between 1990 and 2020. In the coming 31 years (by 2050), if the existing trend of the LULC change continues, agriculture/settlement land is expected to increase from 290.64 km2 in 2020 to 492.51 km 2 in 2050 at the rate of 6.73 km2 ∙y-1, while forestland is expected to shrink from 690.48 km2 in 2020 to 427.01 km2 in 2050 by a rate of 8.78 km2 ∙y-1.

2

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.

3

Influence of land use changes on road network and channel level in Uszwica catchment in 1975–2015 (Polish Western Carpathians)

Bucała-Hrabia Anna

Studia Geomorphologica Carpatho-Balcanica

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2021

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Vol. 55

71--88

EN

The impact of land use changes (LULC) on road network and channel level on the period 1975–2015 were studied in the Uszwica catchment (22.7 km2 ) in the Polish Western Carpathians. This period covers the transformation of the Polish economy from a communist system to a free-market economy after 1989. The analysis of aerial photos using GIS technics indicates that during the investigated period the forest area increased by 25 % and the cultivated land area decreased by 88 % in the Uszwica catchment. The population density increased from 90 to 116 people · km–2, while employment in agriculture decreased from 51.6 % to 4.2 %. As a result of forest succession and cultivated land abandonment the density of used roads and the roads that have connection with stream decreased by 27 % and 8 %, respectively in the Uszwica catchment. The fluvial system of Uszwica channel was strongly influenced by LULC changes. This has led to initiated channel incision by about 1 cm · year–1 after 1989.

4

Forest cover change detection in relation to climate variability and LULC changes using GIS and RS techniques. A case of the Kafa zone, southwest Ethiopia

Lemma Dejene Beyene, Gebretsadik Kinde Teshome, Debela Seifu Kebede

Journal of Water and Land Development

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2021

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no. 51

152--162

EN

Ethiopia has lost sizable forest resources due to rapid population growth and subsequent increase in the demand for agricultural land and fuel woods. In this study, GIS and remote sensing techniques were used to detect forest cover changes in relation to climate variability in the Kafa zone, southwest Ethiopia. Landsat Thematic Mapper (TM) images of 1986 and 1990, Enhanced Thematic Mapper plus (ETM+) image of 2010 and Landsat-8 Operational Land Imager (OLI-8) image of 2018 were acquired at a resolution of 30 m to investigate spatial-temporal forest cover and land use changes. A supervised image classification was made using a maximum likelihood method in ERDAS imagine V9.2 to identify the various land use and land cover classes. Both spectral (normalised difference vegetation index – NDVI) and post classification change detection methods were used to determine the forest cover changes. To examine the extent and rate of forest cover changes, post classification comparisons were made using ArcGIS V 10.4.1. A net forest cover change of 1168.65 ha (12%) was detected during the study period from 1986 to 2018. The drop in the NDVI from 0.06–0.64 in 1986 to (–0.08)–0.12 in 2018 indicated a marked forest cover change in the study area. The correlation of NDVI values with climate data indicated the forest was not in a stable condition. The declining of the forest cover was most likely caused by climate variability in the study area.

5

Analyzing the decadal transformation of the LULC from tillage to a townified area in the Lower Himalayan Region, Pakistan

Anwar Zartashia, Alam Arif, Elahi Noor

Journal of Water and Land Development

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2021

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no. 50

48--55

EN

Land use land cover change (LULC) has become part of the global science agenda and the understanding of LULC change is vital for planning sustainable management of natural resources. The study has employed multi- temporal satellite imagery to examine the LULC change in the Abbottabad District from 1989 to 2019. Images from Landsat-5, Landsat-7, and Landsat-8 Thematic Mapper (TM) for the same season were acquired from the USGS for the years of 1989, 1999, 2009 and 2019. The images were pre-processed by atmospheric correction, extraction of the study area and band composite. The supervised image classification using Maximum Likelihood Classifier and accuracy assessment were applied to prepare LULC maps of the Abbottabad District. In the last three decades, the study area witnessed number of changes in the pattern of LULC due to population growth, rapid urbanization and increased development of infrastructure, which cumulatively led to the emergence of new patterns being employed for land use. Results of the analysis involving the classified maps show that agricultural land and bare land have decreased, respectively 15.73% and 3.81%, whereas water resources have decreased significantly by 0.58%. This study reveals that GIS can be used as an informative tool to detect LULC changes. However, for planning and management, as well as to gain better insight into the human dynamics of environmental variations on the regional scale, it is crucial to have information about temporal LULC transformation patterns in the study area.

6

Mapping food extend and its impact on land use/land cover and settlements variations: a case study of Layyah District, Punjab, Pakistan

Soomro Shan-e-hyder, Hu Caihong, Boota Muhammad Waseem, Soomro Mairaj Hyder Alias Aamir, Jian Shengqi, Zafar Zeeshan, Li Xiaoping

Acta Geophysica

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2021

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Vol. 69, no. 6

2291--2304

EN

Floods are the most frequent and most distractive natural disaster around the globe. Pakistan is facing frequent flooding since 1929 and foods in the Indus river basin cost more than 7000 lives and caused mighty changes in land use and land covers (LULC) since 1947. District Layyah hit by food on August 1, 2010. Landsat ETM+ with 30 m spatial resolution was utilized to investigate the LULC changes in district Layyah for the 2010 food. It was revealed water area increased 8.05% from July 3 (379.13 km2 ) to August 20 (656.02 km2 ) in district Layyah. Vegetation cover increased from 1149.62 km2 on July 3 to 1842.23 km2 on August 20 in district Layyah and showed a 20.13% increment. Barren/built-up area showed a decrement of 28.18% from 1911.72 km2 in pre-food analysis to 941.90 km2 in the post-food analysis. Total 15 union councils (UC) of district Layyah were affected by food from which 10 lies in tehsil Layyah and 5 belongs to tehsil Karor Lal Esan. Flood affects 177 settlements in district Layyah from which 156 belong to tehsil Layyah and 21 were from tehsil Karor Lal Esan. These results suggest that the impacts of the food on LULC need more attention to cope with the challenge of frequent flooding and impacts in Pakistan.

7

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

8

When the heat is on: urbanization and land surface temperature in Guwahati, India

Chetia Sourav, Saikia Anup, Basumatary Manjil, Sahariah Dhrubajyoti

Acta Geophysica

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2020

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Vol. 68, no. 3

891--901

EN

The study examines the efects of urbanization on land surface temperature (LST) in Guwahati, a city in India using satellite data. Landsat images were utilized for LST retrieval, land-use land-cover (LULC) classifcation and the normalized diference built-up index mapping. Surface Energy Balance Algorithms for Land and support vector machine methods were used in the study. Results showed that the city has gone through massive changes in its LULC pattern with a high degree of urbanization during the period 1992–2015. The built-up area (BUA) increased to 87.8 km2 in 2015 from 11.6 km2 in 1992 while vegetation decreased from 143.3 to 76.6 km2 . Open spaces and water bodies decreased from 14.5 to 5 km2 and to 6.6 km2 from 6.7 km2 , respectively. Conversely, an increasing trend of LST was observed. The mean LST which was 18.5 °C in 1992 rose to 29.03 °C in 2015. Linear regression used in quantifying the relationship between urbanization and LST showed a positive relationship between LST and BUAs in the city.

9

Spatiotemporal variability in spate irrigation systems in Khirthar National Range, Sindh, Pakistan (case study)

Soomro Abdul Ghani, Babar Muhammad Munir, Arshad Muhammad, Memon Anila, Naeem Babar, Ashraf Arshad

Acta Geophysica

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2020

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Vol. 68, no. 1

219--228

EN

Satellite remote sensing and geographical information system (GIS) have been used successfully to monitor and assess the land use and land cover (LULC) dynamics and their impacts on people and the environment. LULC change detection is essential for studying spatiotemporal conditions and for proposing better future planning and development options. The current research analyzes the detection of spatiotemporal variability of spate irrigation systems using remote sensing and GIS in the Khirthar National Range, Sindh Province of Pakistan. We use Landsat images to study the dynamics of LULC using ArcGIS software and categorize fve major LULC types. We obtain secondary data related to precipitation and crop yield from the provincial department of revenue. The maximum likelihood supervised classifcation (MLSC) procedure, augmented with secondary data, reveals a signifcant increase of 86.25% in settlements, 83.85% in spate irrigation systems, and 65% in vegetation, and a substantial negative trend of 39.50% in water bodies and 20% in barren land during the period from 2013 to 2018. Our study highlights an increase in settlements due to the infow of local population for better means of living and an increase in spate irrigation systems, which indicates the water conservation practices for land cultivation and human purpose lead to the shrinkage of water bodies. The confusion matrix using Google Earth data to rectify modeled (classifed) data, which showed an overall accuracy of 82.8%–92%, and the Kappa coefcient estimated at 0.80–0.90 shows the satisfactory results of the LULC classifcation. The study suggests the need to increase water storage potential with the appropriate water conservation techniques to enhance the spate irrigation system in the hilly tracts for sustainable develop‑ ments, which mitigates drought impact and reduces migration rate by providing more opportunities through agricultural activities in the study area.

10

Analysis of the usefulness land use and land cover maps for estimating the population of urban areas – valorisation of multi-variant population maps based on the GUS kilometre network

Pirowski Tomasz, Timek Małgorzata

Geoinformatica Polonica

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2019

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T. 18

57--69

EN

The paper is a continuation and summary of a series of publications related to the dasymetric estimation of the distribution of the population of Krakow. The conversion of the population from the original census units is based on the development data from three sources, the Corine Land Cover project (CLC), the Urban Atlas project (UA) and the object classification (OBIA) of the RapidEye data. The experiment was conducted using archival statistical data from 2009 from 141 urban units (u.u.) of the city. In the first two parts of the cycle (Pirowski and Timek, 2018; Pirowski et al., 2018) population conversion was presented on the basis of CLC, UA and OBIA maps, obtaining a total of 12 maps of Krakow’s population. The obtained error distributions were presented and the calculated weights of population density for each category of residential buildings were discussed. In the third part of the cycle (Pirowski and Berka, 2019) the results were analyzed in detail by reference to the reference, high-resolution population map of the Bronowice district (north-western part of the city). In this publication, ending the cycle, population maps were verified on the basis of a kilometre grid of the Central Statistical Office (GUS), which is an aggregation of data from the National Census of Population and Housing 2011, made available by the Office in 2017. The results of high-resolution verification carried out in the Bronowice district were compared with the data of the CSO (GUS). In the GUS grid the best results were obtained for surface and weight UA methods (RMSE 908–917 people; MAPE 42-46%). The estimation of population distribution using OBIA data (RMSE 1115–2073 people; MAPE 121–184%) was found to be incorrect. After the correction of OBIA by UA data, a significant improvement in the results for surface-weighted methods was obtained (RMSE 930–1067 people; MAPE 53–68%), however, the error rate was still higher than for UA itself, which eliminates the OBIA method from practical applications in this area. A correlation was found between the RMSE and MAPE errors recorded in UC at the stage of weight selection and the RMSE and MAPE errors recorded in the GUS grid, respectively R2(RMSE)=91%, R2(MAPE)=65%. Therefore, the correlation detected indicates that the low errors obtained at the selection stage translate into reliable population estimates. The proposed weighting methodology limits the subjectivity of the method, based on the minimisation of RMSE and MAPE in the original census units. The disadvantage of the method is that it is necessary to define the boundary conditions for the selection of weights, in case of obtaining unreal weights and the possibility of occurrence of equifinality phenomenon, difficult to detect in the absence of additional reference data.

PL

Artykuł jest kontynuacją i podsumowaniem cyklu publikacji związanych z dazymetrycznym szacowaniem rozmieszczenia ludności Krakowa. Przeliczanie ludności z pierwotnych jednostek spisowych oparto na danych o zabudowie z trzech źródeł, z projektu Corine Land Cover (CLC), z projektu Urban Atlas (UA) oraz z klasyfikacji obiektowej (OBIA) danych RapidEye. Eksperyment przeprowadzono wykorzystując archiwalne dane statystyczne z roku 2009 ze 141 jednostek urbanistycznych (j.u.) miasta. W pierwszych dwóch częściach cyklu (Pirowski i Timek, 2018; Pirowski i in., 2018) zaprezentowano przeliczanie populacji na bazie map CLC, UA oraz OBIA, łącznie uzyskując 12 map zaludnienia Krakowa. Przedstawiono uzyskane rozkłady błędów, poddano dyskusji obliczone wagi zagęszczenia ludności dla każdej kategorii zabudowy mieszkalnej. W trzeciej części cyklu (Pirowski i Berka, 2019) opracowane wyniki poddane zostały szczegółowej analizie poprzez odniesienie się do referencyjnej, wysokorozdzielczej mapy zaludnienia dzielnicy Bronowice (północno-zachodni obszar miasta). W niniejszej publikacji, kończącej cykl, zweryfikowano mapy zaludnienia w oparciu o siatkę kilometrową GUS, będącą agregacją danych Narodowego Spisu Powszechnego Ludności i Mieszkań z 2011, udostępnioną przez Urząd w 2017 roku. Porównano wyniki weryfikacji wysokorozdzielczej prowadzonej na dzielnicy Bronowice z weryfikacją na danych GUS. W siatce GUS uzyskano najlepsze wyniki dla metod powierzchniowo-wagowych UA (RMSE 908–917 osób; MAPE 42–46%). Za błędne uznano szacowanie rozmieszczenia ludności przy użyciu danych OBIA (RMSE 1115–2073 os.; MAPE 121–184%). Po korek¬cie OBIA poprzez dane UA uzyskano znaczącą poprawę wyników dla metod powierzchniowo-wagowych (RMSE 930–1067 osób; MAPE 53–68%), jednak poziom błędów był nadal wyższy niż dla samej UA, co eliminuje metodę OBIA z zastosowań praktycznych w tym obszarze. Stwierdzono zależność pomiędzy notowanymi błędami RMSE i MAPE w j.u. na etapie doboru wag a notowanymi błędami RMSE i MAPE w siatce GUS, odpowiednio R2(RMSE) = 91%, R2(MAPE) = 65%. Zatem wykryta korelacja wskazuje, że niskie błędy uzyskane na etapie doboru wag przekładają się na wiarygodne szacowanie liczby ludności. Proponowana metodyka doboru wag ogranicza subiektywizm metody, opierając się na minimalizacji RMSE i MAPE w pierwotnych jednostkach spisowych. Wadą metody jest konieczność definiowania warunków brzegowych doboru wag, w przypadku uzyskiwania nierzeczywistych wag oraz możliwość wystąpienia ekwifinalności, trudnej do wykrycia przy braku dodatkowych danych referencyjnych.

11

Analysis of land use and land cover maps suitability for estimating population density in urban areas - exclusion of the equifinality phenomenon on population maps developed from CLC, UA and OBIA data

Pirowski Tomasz, Berka Katarzyna

Geoinformatica Polonica

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2019

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T. 18

45--55

EN

The series of articles contains a comparison of the possibilities of using for dasymetric estimation of population distribution of spatial information about buildings. The buildings come from three sources characterized by different spatial, thematic and temporal accuracy. These are data from Corine Land Cover (CLC) and Urban Atlas (UA) projects and the result of object classification (OBIA) of RapidEye data. The experiment was carried out in the area of Krakow. Statistical data from 141 city urban units (u. u.) were used. In the first two parts of the cycle, population conversions based on CLC, UA, OBIA and OBIA in combination with UA were presented (Pirowski and Timek, 2018; Pirowski et al., 2018). In total, 12 maps of Kraków’s population were obtained. RMSE and MAPE mean errors were calculated as well as population density for each category of residential development. The results were discussed. In the third part of the cycle, the obtained population maps were analyzed in detail, referring to the Bronowice district (the north-western area of the city) prepared especially by the population. The reference map has been made in high resolution. The methodology of its elaboration has been described in detail. Complementary use of orthophotomap from aerial photographs together with public databases (Geoportal, OpenStreetMap, GoogleStreetView) was presented. The proprietary MMAPE parameter has been proposed. The parameter analyzes the similarity of the reference map of Bronowice with the dasymetric maps. It allows you to statistically describe their credibility and exclude the phenomenon of equivalence. As a result of the conducted research, an erroneous population distribution was detected for the variant OBIA, in which the weights were determined by minimizing the MAPE error. From the remaining experiments, the three best results were obtained by maps using information about urban development from Urban Atlas (MMAPE100m = 19.3–22.1%). Complementary use of OBIA and UA did not bring any synergy effect – the results were worse than for UA (21.6–24.3%). High errors were noted for OBIA – it is only worth to notice a better result from the binary OBIA method (MMAPE100m = 22.8%) than the result from the binary CLC method (MMAPE100m = 24.3%). At this stage of the research, UA data is recommended for the conversion of population. The object classification methods are not a reliable source of data on building types, and such information is necessary for the use of surface-by-weight methods. The use of OBIA is possible only in the binary method and gives results similar to the use of data from CLC. In the fourth part, it is planned to verify the population maps using the Central Statistical Offic (CSO) kilometer network for the whole of Poland, which was made available in 2017. On the basis of multivariate tests and two-stage verification, the authors plan to provide the advantages and disadvantages of the described methods of population conversion and to develop a ranking of the obtained Krakow population maps.

PL

Cykl artykułów zawiera porównanie możliwości wykorzystania do dazymetrycznego szacowania rozmieszczenia ludności informacji przestrzennej o zabudowie z trzech źródeł, charakteryzujących się różną dokładnością przestrzenną, tematyczną i czasową: dane z projektów Corine Land Cover (CLC) i Urban Atlas (UA) oraz klasyfikacji obiektowej (OBIA) danych RapidEye. Eksperyment przeprowadzono na obszarze Krakowa, wykorzystując dane statystyczne ze 141 jednostek urbanistycznych miasta. W pierwszych dwóch częściach cyklu zaprezentowano przeliczanie populacji w oparciu o CLC, UA (Pirowski i Timek, 2018) oraz OBIA, w tym jej skorygowany wynik poprzez połączenie z UA (Pirowski i in., 2018). Łącznie uzyskano 12 map zaludnienia Krakowa. Poddano dyskusji obliczone błędy średnie RMSE i MAPE oraz wagi zagęszczenia ludności dla każdej kategorii zabudowy mieszkalnej. W trzeciej części cyklu uzyskane wyniki poddane zostały szczegółowej analizie dzięki specjalnie przygotowanej przez autorów, wysokorozdzielczej referencyjnej mapie ludności dzielnicy Bronowice (północno-zachodni obszar miasta). Szczegółowo opisano przyjętą metodykę jej opracowania, w tym komplementarne wykorzystanie interpretacji ortofotomapy ze zdjęć lotniczych oraz ogólnodostępnych baz danych (Geoportal, OpenStreetMap, GoogleStreetView). Zaproponowano autorski parametr MMAPE, analizujący podobieństwo mapy referencyjnej Bronowic z mapami dazymetrycznymi, pozwalający statystycznie opisać ich wiarygodność i wykluczyć zjawisko ekwifinalności. W wyniku przeprowadzonych badań wykryto błędny rozkład ludności dla wariantu opartego o klasyfikację obiektową z ustalaniem wag na drodze minimalizacji błędu MAPE. Spośród pozostałych eksperymentów trzy najlepsze wyniki uzyskały mapy wykorzystujące informacje o zabudowie z Urban Atlas (MMAPE100m = 19,3–22,1%). Komplementarne wykorzystanie OBIA i UA nie przyniosło efektu synergii – wyniki są gorsze niż dla UA (21,6–24,3%). Wysokie błędy odnotowano dla OBIA – warto jedynie odnotować lepszy wynik dla metody binarnej OBIA (MMAPE100m = 22,8%) niż dla metody binarnej CLC (MMAPE100m = 24,3%).Na tym etapie badań rekomenduje się do przeliczania ludności stosować dane UA. Metody klasyfikacji obiektowej nie są wiarygodnym źródłem danych o rodzajach zabudowy, niezbędnym dla metod powierzchniowo-wagowych. Stosowanie OBIA jest możliwe w metodzie binarnej i daje rezultaty zbliżone do korzystania z CLC. W czwartej części planuje się weryfikację map zaludnienia wykorzystując siatkę kilometrową GUS, udostępnioną przez urząd w 2017 roku, dla całej Polski. Na bazie wielowariantowych testów i dwuetapowej weryfikacji autorzy planują podać ograniczenia proponowanej metody przeliczania ludności oraz opracować ranking map.

12

Analysis of land use and land cover maps suitability for modeling population density of urban areas – redistribution to new spatial units based on CLC and UA databases

Pirowski T, Timek M.

Geoinformatica Polonica

|

2018

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T. 17

53--64

EN

The series of articles contains a comparison of the possibilities of using data from three sources for mapping people, with diff erent spatial, thematic and time accuracy. These are data from Corine Land Cover (CLC) and Urban Atlas (UA) projects and the result of object classifi cation (OBIA) of RapidEye data. The information on the existence of building zone included on the land use and land cover maps (LULC) constituted a limiting variable in the dasymetric method of population mapping. Categories related to building types allowed for the introduction of variable relationships, diversifying population density. These treatments enabled multi-variant development of maps of spatial population occurrence at a higher level than the original census units. The experiment was carried out in the area of Krakow. Statistical data from 141 urban units (u.u.) of the city were used. Generation of population maps was carried out in several variants. Divisions of buildings were made depending on its characteristics and functions. The results of population conversion were analyzed on Central Statistical Offi ce (hereafter referred as CSO, in Polish: GUS) data in a kilometer grid and on a specially prepared map of the population including a part of Krakow. The applied double verifi cation allowed to rank the obtained population maps and provide border spatial accuracy of their cellular representation. The fi rst part of the cycle presents the state of knowledge about population mapping and population conversion using the dasymetric method. The area of research is described. Spatial and statistical data used in the research were characterized. Works related to population conversion based on CLC and UA were presented. Six maps of the population distribution of Krakow were obtained. A multi-variant process of recalculating and setting weights for various types of buildings is described by providing for urban units the values of RMSE and MAPE. Population using the surface-weight method based on UA data was considered the best (MAPE 66%, RMSE 3442 people/u.u.). On CLC data, these errors were: MAPE 168%, RMSE 5690 people/u.u. In the subsequent parts of the cycle, the population conversion will be presented using object-oriented classifi cation. The methodology for the verifi cation of results will be described based on a photointepretation map of the population and the GUS perimeter grid. A discussion will be conducted related to the use of RMSE and MAPE measures. The ranking of methods and recommendations improving the results of population redistribution based on CLC, UA and OBIA will be given.

PL

Cykl artykułów zawiera porównanie możliwości wykorzystania do kartowania ludności danych z trzech źródeł, o różnej dokładności przestrzennej, tematycznej i czasowej: dane z projektów Corine Land Cover (CLC) i Urban Atlas (UA) oraz wynik klasyfikacji obiektowej (OBIA) danych RapidEye. Zawarta na mapach pokrycia i użytkowania terenu informacja o występowaniu zabudowy stanowiła zmienną ograniczającą w dazymetrycznej metodzie kartowania ludności. Kategorie związane z typami zabudowy pozwoliły na wprowadzenie zmiennych powiązań, różnicujących zagęszczenie ludności. Te zabiegi umożliwiły wielowariantowe opracowanie map przestrzennego występowania ludności na poziomie wyższym niż pierwotne jednostki spisowe. Eksperyment przeprowadzono na obszarze Krakowa, wykorzystując dane statystyczne ze 141 jednostek urbanistycznych (j.u.) miasta. Generowanie map ludności przeprowadzono w kilku wariantach, dokonując podziałów zabudowy w zależności od jej charakterystyki i funkcji. Wyniki przeliczania ludności na nowe jednostki przestrzenne odniesiono na etapie weryfikacji do danych o ludności podanych przez GUS w siatce kilometrowej oraz do specjalnie przygotowanej przez autorów szczegółowej mapy ludności obejmującej fragment Krakowa. Zastosowana podwójna weryfikacja pozwoliła na uszeregowanie według jakości uzyskanych map populacji oraz podanie granicznych dokładności przestrzennych ich komórkowej reprezentacji. W pierwszej części cyklu zaprezentowano zarys stanu wiedzy o kartowaniu ludności i zasadach przeliczania populacji metodą dazymetryczną. Opisano obszar badań, scharakteryzowano wykorzystane w badaniach dane przestrzenne i statystyczne. Przedstawiono prace związane z przeliczeniem populacji w oparciu o CLC i UA, uzyskując łącznie 6 map rozkładu ludności Krakowa. Wielowariantowy proces przeliczania i ustalania poprawnych wag dla różnych typów zabudowy scharakteryzowano poprzez podanie dla jednostek urbanistycznych, sprzed realizacji warunku Toblera, wartości średniego błędu kwadratowego (RMSE) oraz średniego absolutnego błędu procentowego (MAPE). W oparciu o te parametry kartowanie ludności metodą powierzchniowo-wagową, bazującą na danych UA, uznano za najlepszą (MAPE 66%, RMSE 3442os./j.u.), podczas gdy na danych CLC błędy te wyniosły: MAPE 168%, RMSE 5690 os./j.u. W kolejnych częściach cyklu przedstawione zostanie przeliczanie populacji z zastosowaniem klasyfikacji obiektowej. Opisana zostanie metodyka weryfikacji wyników w oparciu o fotointepretacyjną mapę ludności oraz siatkę kilometrową GUS. Przeprowadzona będzie dyskusja nad zasadnością stosowania miar optymalizacyjnych RMSE i MAPE. Podany zostanie ranking metod oraz rekomendacje poprawiające wyniki redystrybucji ludności w oparciu o CLC, UA i OBIA.

13

Assessment of Shoreline and Associated Landuse/Land cover Changes along Part of Lagos Coastline, Nigeria

Akinluyi F. O., Adebola A. O., Adeseko A. A.

Contemporary Trends in Geoscience

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2018

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Vol. 7, iss. 1

59--71

EN

The city of Lagos, Nigeria has undergone rapid increase in population due to economic and commercial activities. As a result of this, there has been a persistent change in Land use/Land cover (LULC) of the city and shoreline through the years. This observation necessitated the use of multi-temporal satellite data to characterize shoreline changes between 1984 and 2016. Therefore, the study attempts to determine the shoreline change during the study period and the coastal land use and land cover (LULC) of the study area. Satellite data was acquired and subjected to some image processing techniques such as image enhancement, supervised classification, and shoreline extraction. The digital shoreline analysis system (DSAS) in ArcGIS environment was utilized to cast transects and calculate statistical parameters for the shoreline and spatial data used was Landsat TM, ETM and OLI for the years 1984, 1990, 2000, 2004 and 2016 respectively. The results indicate that LULC changes in built-up areas increases rapidly during the years (1984-2015) from 12.2 -36.2%, water bodies increased from (1984-1990-2000) from 52%, 54%, 52% and reduces to 47.4% in the year 2015 while vegetation cover reduces drastically through the year range from 36%, 33%, 29%, 24% and 16%. A total of 1034 transects were generated with 100m spacing and the average rate of change was calculated for the 32 year period (1984-2016). The linear regression rate (LRR) shoreline result shows a mean of -0.59m/year where 73.1% of transect fall under erosion and 61.8% accretion respectively. The end point rate (EPR) and net shoreline movement (NSM) analysis revealed mean shoreline change of -0.57m/year and -18.1m/period respectively from 1984-2016. The EPR and NSM results both revealed that 231 transect or 22.3% experienced erosion, and 805 transect or 77.9% with accretion. It was observed that significant accretion rate recorded along most sections of the shorelines is attributed to beach nourishment activities.

14

Wpływ algorytmów scalania danych na wyniki kartowania pokrycia terenu - wybrane aspekty

Pirowski T., Garlewicz B., Gryboś K.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2018

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vol. 30

67--82

PL

W artykule dokonano waloryzacji wybranych metod scalania danych teledetekcyjnych o różnej rozdzielczości pod kątem ich przydatności do kartowania pokrycia i użytkowania terenu. Analizie poddano oryginalne dane Landsat ETM+ (30m), dane Landsat przeliczone do 5m z dodanym do zestawu kanałem IRS PAN 1D (5m) oraz dane Landsat i IRS PAN scalone czterema metodami: IHS, PCA, WMK i PL, charakteryzującymi się wyraźnie odmiennymi algorytmami integracji. Opracowanych w ten sposób sześć zestawów danych poddano klasyfikacji spektralnej metodami maksymalnego prawdopodobieństwa, drzew decyzyjnych i sieci neuronowych. Wyniki uzyskane na danych sprzed i po integracji zestawiono dodatkowo z analizami fotointerpretacyjnymi, wykonanymi równolegle do analiz klasyfikacyjnych. Testy potwierdziły przewagę metody fotointepretacyjnej nad wynikami klasyfikacji spektralnej, w zależności od zestawu danych, o 6-11% wartości dokładności całkowitej mapy pokrycia i użytkowania terenu. Scalenie danych poprawia ogólną dokładność klasyfikacji o 9% pomiędzy pracą na oryginalnym obrazie Landsat (30m) a zintegrowanym Landsat z IRS (5m), pozwalając uzyskać dokładność 64%. Dla metody fotointerpretacyjnej wzrost dokładności wynosi 6%, osiągając 71%. Wybór metody integracji jest drugorzędny - zróżnicowanie wyników w metodzie fotointerpretacyjnej wynosi 1%, dla metod klasyfikacyjnych około 5% (najlepsza - PL; najgorsza - IHS). Znaczenie dla wyników klasyfikacji ma wybór algorytmu: z wszystkich testowanych zestawów danych najlepsze wyniki uzyskano dla sieci neuronowych (64%), następnie dla drzew decyzyjnych (62%) i metody największego prawdopodobieństwa (59%).

EN

The article valorises selected methods of merging remote sensing data of different resolution in terms of their suitability for mapping land use and land cover. The original Landsat data (30m) was analyzed, Landsat data converted to 5m with IRS PAN 1D (5m) added to the set and Landsat and IRS PAN data merged with four methods: IHS (transformation into space intensity, hue, saturation), PCA (principal components analysis), WMK (Wiemker's method) and PL (laplace pyramid), characterized by distinctly different integration algorithms . Six sets of data developed in this way were subjected to spectral classification by maximum probability methods, decision trees and neural networks. The results obtained on the data from before and after the integration were additionally compiled with photointerpretation analyzes, made in parallel to the classification analyzes. The research area was the city of Kraków with adjacent suburban areas, 10x20 km in size. For the research objective being pursued, 5 reference squares 500m x 500m were prepared, ensuring diversity and representativeness for the entire analysis area. The reference data was based on a photo interpretation aerial photographs with a field pixel size of 0.75m. The tests confirmed the predominance of the photo interpretation method over the results of spectral classification, depending on the data set, by 6-11% of the accuracy value of the total land use and land cover maps. Merging data improves the overall accuracy of the 9% classification between work on the original Landsat image (30m) and the integrated Landsat with IRS (5m), allowing for an accuracy of 64%. For the photointerpretation method, the increase is 6%, reaching the accuracy of 71%. The choice of the method of integration is secondary - the variation in results in the photointerpretation method is 1%, for classification methods about 5% (best - PL, worst - IHS). The choice of the algorithm is important for classification results: of all the tested data sets, the best results were obtained for neural networks (64%), then for decision trees (62%) and the maximum probability method (59%).

15

Improved vegetation parameterization for hydrological model and assessment of land cover change impacts on flow regime of the Upper Bhima basin, India

Mohaideen M. M. D., Varija K.

Acta Geophysica

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2018

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Vol. 66, no. 4

697--715

EN

This study investigates the potential and applicability of variable infiltration capacity (VIC) hydrological model to simulate different hydrological components of the Upper Bhima basin under two different Land Use Land Cover (LULC) (the year 2000 and 2010) conditions. The total drainage area of the basin was discretized into 1694 grids of about 5.5 km by 5.5 km: accordingly the model parameters were calibrated at each grid level. Vegetation parameters for the model were prepared using temporal profile of Leaf Area Index (LAI) from Moderate-Resolution Imaging Spectroradiometer and LULC. This practice provides a methodological framework for the improved vegetation parameterization along with region-specific condition for the model simulation. The calibrated and validated model was run using the two LULC conditions separately with the same observed meteorological forcing (1996–2001) and soil data. The change in LULC has resulted to an increase in the average annual evapotranspiration over the basin by 7.8%, while the average annual surface runoff and baseflow decreased by 18.86 and 5.83%, respectively. The variability in hydrological components and the spatial variation of each component attributed to LULC were assessed at the basin grid level. It was observed that 80% of the basin grids showed an increase in evapotranspiration (ET) (maximum of 292 mm). While the majority of the grids showed a decrease in surface runoff and baseflow, some of the grids showed an increase (i.e. 21 and 15% of total grids— surface runoff and baseflow, respectively).

16

Determination of the spatial structure of vegetation on the repository of the mine "Fryderyk" in Tarnowskie Góry, based on airborne laser scanning from the ISOK project and digital orthophotomaps

Szostak M., Wężyk P., Pająk M., Hawryło P., Lisańczuk M.

Geodesy and Cartography

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2015

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Vol. 64, no. 1

87--99

EN

The purpose of this study was to determine the spatial structure of vegetation on the repository of the mine “Fryderyk” in Tarnowskie Góry. Tested area was located in the Upper Silesian Industrial Region (a large industrial region in Poland). It was a unique refuge habitat – Natura2000; PLH240008. The main aspect of this elaboration was to investigate the possible use of geotechniques and generally available geodata for mapping LULC changes and determining the spatial structure of vegetation. The presented study focuses on the analysis of a spatial structure of vegetation in the research area. This exploration was based on aerial images and orthophotomaps from 1947, 1998, 2003, 2009, 2011 and airborne laser scanning data (2011, ISOK project). Forest succession changes which occurred between 1947 and 2011 were analysed. The selected features of vegetation overgrowing spoil heap “Fryderyk” was determined. The results demonstrated a gradual succession of greenery on soil heap. In 1947, 84% of this area was covered by low vegetation. Tree expansion was proceeding in the westerly and northwest direction. In 2011 this canopy layer covered almost 50% of the research area. Parameters such as height of vegetation, crowns length and cover density were calculated by an airborne laser scanning data. These analyses indicated significant diversity in vertical and horizontal structures of vegetation. The study presents some capacities to use airborne laser scanning for an impartial evaluation of the structure of vegetation.

PL

Celem badań była ocena struktury przestrzennej roślinności porastającej zwałowisko odpadów kopalni ”Fryderyk” w Tarnowskich Górach, położone na północnym skraju Górnośląskiego Okręgu Przemysłowego. Teren, na którym znajduje się zwałowisko należy do sieci Natura 2000 (PLH 240008). Głównym aspektem poruszanym w opracowaniu było określenie możliwości wykorzystania ogólnie dostępnych geodanych dla opracowywania map pokrycia i użytkowania terenu zwałowiska oraz określenia struktury roślinności na tym obszarze. Analizowane materiały to zdjęcia i ortofotomapy lotnicze z lat: 1947, 1998, 2003, 2009, 2011 oraz dane z lotniczego skanowania laserowego (z projektu ISOK, 2011). Efektem opracowania było określenie charakterystyki przestrzennej roślinności na zwałowisku kopalni ”Fryderyk”. Analizy wykazały stopniową ekspansję roślinności na powierzchni hałdy. W 1947 roku 84% powierzchni terenu badań pokryta była przez roślinność niską a w roku 2011 roślinność wysoka zajmowała już około 50% obszaru zwałowiska. Analizy wykazały znaczne zróżnicowanie w poziomej i pionowej strukturze roślinności. W opracowaniu przedstawiono możliwości wykorzystania danych z lotniczego skanowania laserowego dla obiektywnej oceny struktury roślinności.