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EN
The article presents an analysis of the accuracy of 3 popular machine learning (ML) methods: Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM), and Random Forest (RF) depending on the size of the training sample. The analysis involved performing the classification of the content of a Landsat 8 satellite image (divided into 6 basic land cover classes) in 10 different variants of the number of training samples (from 2664 to 34711 pixels), estimating individual results, and a comparative analysis of the obtained results. For each classification variant, an error matrix was developed and on their basis, accuracy metrics were calculated: f1-score, precision and recall (for individual classes) as well as overall accuracy and kappa index of agreement (generally for the entire classification). The analysis showed a stimulating effect of the size of the training sample on the accuracy of the obtained classification results in all analyzed cases, with the most sensitive to this factor being MLC, showing the best effectiveness with the largest training sample and the smallest - with the smallest, and the least SVM, characterized by the highest accuracy with the smallest training sample, comparing to other algorithms.
PL
Artykuł przedstawia analizę dokładności 3 popularnych metod uczenia maszynowego: Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) oraz Random Forest (RF) w zależności od liczebności próbki treningowej. Analiza polegała na wykonaniu klasyfikacji treści zdjęcia satelitarnego Landsat 8 (w podziale na 6 podstawowych klas pokrycia terenu) w 10 różnych wariantach liczebności próbek uczących (od 2664 do 34711 pikseli), oszacowaniu poszczególnych wyników oraz analizie porównawczej uzyskanych wyników. Dla każdego wariantu klasyfikacji opracowano macierz błędów, a na ich podstawie obliczono metryki dokładności: F1-score, precision and recall (dla pojedynczych klas) oraz ogólną dokładność i wskaźnik zgodności Kappa (ogólnie dla całej klasyfikacji). Analiza wykazała stymulujący wpływ rozmiaru próbki uczącej na dokładność uzyskiwanych wyników klasyfikacji we wszystkich analizowanych przypadkach, przy czym najbardziej wrażliwym na ten czynnik był MLC, wykazujący się najlepszą skutecznością przy największej próbce treningowej i najmniejszą - przy najmniejszej, a najmniej SVM, cechujący się największą dokładnością przy najmniejszej próbce treningowej, w porównaniu do pozostałych algorytmów.
EN
The remarkable feature of rapid urbanisation, which has fundamentally altered the distribution of land cover and land use (LULC), is what sets the contemporary era apart. The impact of these modifications on the resilience of Abuja’s metropolitan infrastructure from 2017 to 2022 is examined in this study. Our study examined the dynamic changes in LULC using information from remote sensing, geospatial analysis software, and land cover categorization techniques. The findings indicate major changes in Abuja’s topography, including a decrease in the number of water bodies, a decrease in the number of trees, the expansion of urban areas, changes in agricultural land use, and fluctuations in the amount of grazing land. The previously mentioned changes have significant consequences for urban infrastructure resilience, affecting various sectors such as water supply, transportation, housing, utilities, and food distribution systems. The infrastructure supporting water supply and sanitation may be severely stretched as the number of water bodies decreases, affecting the quantity and quality of accessible water supplies. As metropolitan areas expand, greater strain is placed on transportation infrastructure, exacerbating traffic congestion and complicating road maintenance difficulties. Changes in agricultural land use can have an impact on food production and distribution, hence affecting food security. Deforestation can cause ecological deterioration, affecting a variety of aspects such as temperature regulation, biological diversity, and atmospheric purity. Adaptive approaches, green infrastructure, and adopting sustainable urban design can all strengthen the resilience of urban infrastructure, according to this study. The significance of renewable energy adoption, community participation, green building laws, the establishment of public-private partnerships, integrated water resource management, and data-driven decision-making is emphasised. Improving legal frameworks that prioritise resilience and sustainability is critical. It is critical to have a complete grasp of the complicated links between changes in LULC, and the resilience of urban infrastructure in order to enable educated urban design and decision-making processes. Policymakers and urban planners may address and minimise the negative consequences of climate change while improving the overall quality of life in cities by using sustainable development practises. The findings of this study have the potential to dramatically improve Abuja’s people’s well-being and sustainability, especially given the variety of urban difficulties they encounter.
PL
Współczesną erę wyróżnia niezwykle szybka urbanizacja, która zasadniczo zmieniła rozkład pokrycia terenu i użytkowa- nia gruntów (LULC). W niniejszym badaniu przeanalizowano wpływ tych zmian na odporność infrastruktury metropo- litalnej Abudży w latach 2017-2022. Dynamiczne zmiany LULC zbadano przy użyciu informacji z teledetekcji, oprogra- mowania do analizy geoprzestrzennej oraz technik kategoryzacji pokrycia terenu. Wyniki wskazują na poważne zmiany w topografii Abudży, w tym spadek liczby zbiorników wodnych, spadek liczby drzew, ekspansję obszarów miejskich, zmiany w użytkowaniu gruntów rolnych i wahania w ilości pastwisk. Zmiany te mają znaczące konsekwencje dla od- porności infrastruktury miejskiej, wpływając na różne sektory, takie jak zaopatrzenie w wodę, transport, mieszkalnic- two, usługi komunalne i systemy dystrybucji żywności. Infrastruktura wspierająca zaopatrzenie w wodę i urządzenia sanitarne może być poważnie obciążona, ponieważ malejąca liczba zbiorników wodnych odbija się na ilości i jakości dostępnych zasobów wody. Wraz z rozwojem obszarów metropolitalnych rośnie obciążenie infrastruktury transportowej, co zwiększa natężenie ruchu i komplikuje utrzymanie dróg. Zmiany w użytkowaniu gruntów rolnych wpływają na pro- dukcję i dystrybucję żywności, a tym samym na bezpieczeństwo żywnościowe. Wylesianie może powodować pogorszenie stanu środowiska, wpływając na regulację temperatury, różnorodność biologiczną i czystość atmosfery. Według naszych badań podejście adaptacyjne, zielona infrastruktura i przyjęcie zrównoważonego projektowania urbanistycznego mogą wzmocnić odporność infrastruktury miejskiej. Podkreśla się znaczenie energii odnawialnej, udziału społeczności, przepi- sów dotyczących zielonego budownictwa, ustanowienia partnerstw publiczno-prywatnych, zintegrowanego zarządzania zasobami wodnymi i podejmowania decyzji w oparciu o dane. Kluczowe znaczenie ma poprawa ram prawnych, które powinny priorytetowo traktować kwestie odporności miejskiej oraz zrównoważonego rozwoju. Świadome projektowanie urbanistyczne i procesy decyzyjne możliwe są jedynie przy zrozumieniu skomplikowanych powiązań między zmianami w LULC a odpornością infrastruktury miejskiej. Zastosowanie praktyk zrównoważonego rozwoju umożliwi decydentom i urbanistom zminimalizowanie negatywnych konsekwencji zmian klimatycznych oraz podniesienie ogólnej jakości życia w miastach. Wyniki tego badania mogą potencjalnie znacznie poprawić dobrobyt i zrównoważony rozwój mieszkańców Abudży, zwłaszcza biorąc pod uwagę różnorodność napotykanych przez nich trudności miejskich.
EN
Hydrogeological risks that are associated with rivers have emerged as a significant concern worldwide, impacting both natural ecosystems and human settlements. This contribution presents an interdisciplinary project that leverages many technologies for data-acquisition and modeling to comprehensively analyze and manage risks in riverine environments. The project integrates geomatics, geological, and hydrological techniques to provide a holistic understanding of river dynamics and their associated hazards. As a central component of this project, geomatics plays a pivotal role in instrumental field surveying through the deployment of photogrammetry and LiDAR instruments. Remote-sensing data from satellite imagery further enriches the project’s temporal analysis capabilities. By analyzing this data over time, researchers can monitor changes in river patterns, land use, and climate-related variables; this helps identify trends and potential triggers for hydrological events. To manage and integrate the vast amount of geospatial information that is generated, a geodatabase within a geographic information system (GIS) has been established. It enables efficient data storage, retrieval, and analysis, fostering collaboration among multidisciplinary researcher teams. This system offers tools for risk-assessment, modeling, and scenario planning; these allow for proactive measures for mitigating hydrological risks.
EN
In the Ferkla Oasis, much like in numerous other oases across the southeastern region of Morocco, a range of socioeconomic and environmental challenges are intricately linked to the inadequate management of water resources. One proposed remedy to address these concerns is the implementation of artificial aquifer recharge, which stands as an alternative strategy to safeguard the crucial oasis ecosystems. Thus, to evaluate the viability of this method in promoting sustainable water resource usage, it becomes imperative to delineate groundwater recharge potential zones (GRPZs). This study aims to achieve this objective by mapping GRPZs within the Ferkla Oasis, employing a fusion of the analytical hierarchy process (AHP), geospatial information derived from remote sensing (RS), and geographic information system (GIS) technologies. In pursuit of this goal, an array of geological, topographical, pedological, hydrological, and climatic criteria have been meticulously selected, classified, and assigned weights following their relevance to water infiltration suitability. This comprehensive approach culminates in the generation of seven thematic maps: slope, lineament density, lithology, soil type, drainage density, land use/land cover, and rainfall distribution. Through the integration of these aforementioned maps, a tripartite classification of potential GRPZs emerges, comprising low, medium, and high categories. The findings underscore the distribution: 30% of the total study area exhibits a low potential for GRPZs, 50% of the total land area is characterized as having medium potential GRPZs, while the remaining 20% is designated as high potential GRPZs. These outcomes have been substantiated through validation against piezometric levels, which have been ascertained through recent field surveys. Consequently, these results stand as a testament to the efficacy of the presented approach as a robust decision-making tool. The approach effectively facilitates the establishment of conditions conducive to viable artificial recharge, thereby offering a means to safeguard the groundwater reservoirs that sustain the fragile oasis environments.
EN
One of today's most important environmental problems is air pollution augmentation. Air pollution is getting worse over time and hurts human health. For the current study, various polar orbiting satellites were utilized to collect data on PM2.5, SO2, AOD, CO, and ozone over Pakistan between January 2005 and December 2021. According to the spatial distribution results, these characteristics have high values throughout central Punjab, western Baluchistan, central Sindh, and Khyber Pakhtunkhwa. The seasonal variation in PM2.5, SO2, AOD, CO, and ozone was calculated using monthly data. The greatest value for PM2 5 is 8.7 X 10-8 kg/m3 during the monsoon season, while the highest value for SO2 is 1.4 X 10-5 kg/m2 during the winter. Over Punjab, Sindh, Baluchistan, KPK, and Gilgit, AOD was between 0.7 and > 1.0, CO was 127.2 ppb, and ozone was 330.7 DU. Furthermore, we create correlation maps of AOD, CO, SO2, PM2.5, and ozone and evaluate their relationship of high and low values across Pakistan. We looked into the 0.99 correlation between AOD and PM2.5, the strongest ever recorded. Despite this, we look at time series graphs to show the rising and falling pattern of these parameters from January 2005 to December 2021. We also used tables to determine the relative change in Multan, Lahore, Karachi, Peshawar, Quetta, Rawalpindi, Faisalabad, Hyderabad, Gujranwala, and Abbottabad in Pakistan from January 2005 to December 2021.
EN
The study aims to assess variations in spatio-temporal characteristics of water quality parameters from three tropical estuaries, namely Muri-Ganga, Saptamukhi, and Hooghly, in the western portion of the Indian Sundarbans. Reliable retrieval of near-surface concentration of water quality parameters such as Chlorophyll-a, SST & TSM from diverse aquatic ecosystems with broad ranges of tropical requirements has always remained a complex issue. In this study, application of Case 2 Regional Colour Correction (C2RCC) processor has been tested for its accuracy across different bio-optical regimes in both inland and coastal waters. Satellite images for the same period were also collected and analysed using the C2RCC processing sequence to retrieve parameters like the depth of water, surface reflectance, water temperature, inherent optical properties (IOPs), chlorophyll-a, salinity, total suspended matter (TSM), etc., using the SNAP software. In situ sampling from specific locations within these estuaries and water quality analysis were conducted for the period 2017-2019. The OLCI retrieved datasets were compared and corroborated with field survey datasets. It was observed that the highest amount of TSM was recorded at Diamond Harbour during the 2018 pre-monsoon season (301.40 mg/L field-based value and 308.54 mg/L estimated value). Similarly, chlorophyll-a had higher concentrations throughout the monsoon season (3.03 mg m-3, (field survey), and 2.96 mg m-3, (estimated) at Fraserganj and Sagar south points. A very good correlation was observed for all seasons for Chl-a (r = 0.829) and TSM (r = 0.924) between the OLCI data and in situ measurements. Higher correlation and significant ‘r’ values highlight the importance of having both field-based as well as remotely-sensed information in understanding any dynamic system in a sustained manner. Results also confirm that the water quality model using OLCI Chl-a and TSM products outperforms conventional techniques. The study demonstrates the efficacy of using Sentinel 3 OCLI data for shallow marine and estuarine remote sensing applications, especially for monitoring TSM and Chl-a concentrations.
PL
Jak rozpoznać zasoby i stan zachowania miast? Jeszcze niedawno byłoby to niemożliwe bez rzeszy naukowców. Na szczęście dziś standardem powoli staje się teledetekcja, pozwalająca na szybkie udokumentowanie stanu środowiska przyrodniczego miasta.
EN
Radiometric correction is a process that is often neglected when developing unmanned aerial vehicle (UAV) images. The aim of the work was to test the radiometric correction of images taken from a Parrot Sequoia+ camera mounted on UAV. Therefore, a script was written in Matlab environment to enable radiometric correction of the obtained images. The images were subjected to the correction process using the Matlab script and the commercial software Pix4D. The results were compared, and the study found a significant improvement in the radiometry in both cases. The computational process eliminated the influence of variable in-flight insolation caused by cloud cover. The software developed for the article was found to be as good as the commercial one.
EN
Ice phenomena in watercourses and channels pose a threat to flow continuity and hydrotechnical devices. The organoleptic method, relying on human observation, has limitations such as a narrow range, subjective assessment, and high effort, leading to its decline in use. This article presents a number of modern techniques, i.e., the interpretation of RGB images, using unmanned aerial vehicles. Drone imagery offers a bird’s-eye view of areas that would otherwise be difficult to survey. It can improve the detection of frazil ice jams and, thus, contribute to the monitoring and spread of frazil ice. The authors performed research in the area of the Wrocław Water Junction on the Odra River in the area of the inlet near the fish pass at the Opatowice Weir during the flow of frazil ice on the water surface. To observe the phenomenon, a UAV with an RGB camera was used to record video in an orthogonal perspective in order to reduce geometric distortions of the optical system. The center of the frame was used for the analysis. The presented research results and the recognition of the literature indicate the possibility of using the presented technique for early detection of a potential threat from emerging ice phenomena. The results of the conducted analyses are objectively compared to the observational technique used at observation stations and allow for a reliable comparison of the intensity of ice phenomena in selected periods.
EN
Turbidity is an important indicator of water quality in rivers, lakes, and coastal areas. Research on turbidity issues in these areas is significant not only for the development and utilization of water resources for aquaculture, tourism, and other purposes but also for assessing the level of silt (sand) in the river, allowing sediment alluvial to build up a bank of the river, and monitoring the degree of water corrosion in the bridge substructure. This allows for the building of an effective maintenance and conservation program for the bridge in response to climate change. Traditional methods have defined the turbidity of water in a local area, on a small scale. Interpolation errors of traditional methods for large areas may exceed over 20%. The use of remote sensing technology as Landsat-8 satellite images with a high geometric resolution of 30-meter multispectral channels allows us to estimate and distribute the water turbidity in a 30 × 30 m grid in detail. Using multi-temporal Landsat-8 data in 2014 and 2015 for modeling water turbidity of Tien and Hau rivers and coastal areas in South Vietnam, the obtained mean absolute error is approximately 20%, the Root Mean Square Error (RMSE) does not exceed 10 NTU. The models have a high coefficient of efficiency ME, approximately 90% (ME = 0.862), and the correlation coefficient R stronger than 90%. This allows an overall assessment of changes in water flow velocity concerning the amount of sediment in the river.
PL
Mętność jest ważnym wskaźnikiem jakości wody w rzekach, jeziorach i obszarach przybrzeżnych. Badania nad tą kwestią są istotne nie tylko dla rozwoju i wykorzystania zasobów wodnych na potrzeby akwakultury, turystyki i innych celów, ale także dla oceny poziomu mułu (piasku) w rzece, pozwalającego osadom aluwialnym budowanie brzegu rzeki oraz monitorowanie stopnia korozji w podporach mostu. Umożliwi to opracowanie skutecznego programu konserwacji i utrzymania mostu w odpowiedzi na zmiany klimatyczne. Tradycyjne metody pozwalają określić mętność wody w obszarze lokalnym, w małej skali. Błędy interpolacji tradycyjnych metod do dużych obszarów mogą przekraczać 20%. Zastosowanie technologii teledetekcji w postaci zdjęć satelitarnych Landsat-8 o wysokiej rozdzielczości geometrycznej 30-metrowych kanałów wielospektralnych pozwala na szczegółowe oszacowanie i rozmieszczenie zmętnienia wody w siatce 30 × 30 m. Wykorzystując wieloczasowe dane Landsat-8 z lat 2014 i 2015 do modelowania zmętnienia wody rzek Tien i Hau oraz obszarów przybrzeżnych w południowym Wietnamie, uzyskany średni błąd bezwzględny wynosi około 20%, a średni błąd kwadratowy (RMSE) nie przekracza 10 NTU. Modele mają wysoki współczynnik efektywności ME, około 90% (ME = 0,862), a współczynnik korelacji R jest wyższy niż 90%, co stwarza możliwość dokonania ogólnej oceny zmian prędkości przepływu wody w odniesieniu do ilości osadów w rzece.
EN
The documentation of cultural heritage objects requires a special approach, as does the collection of materials describing a monument over a period of time. With the development of measurement and information technologies, such documentation can be supplemented by a digital model of the object, a 3D visualization in a computer environment, or a miniature, scaled 3D printout. This paper presents a methodology for developing the 3D documentation of the Monument to the Polish Diaspora Bond with the Homeland, a sculpture located in Koszalin, Poland. In the study, terrestrial laser scanning supplemented with photos was used for non-invasive measurements, and existing free software was used to generate a 3D model. The results of the study can supplement the technical documentation of an object so as to preserve its characteristic features and ease the conservation of monuments. The proposed approach to modelling 3D monuments can be used to create HBIM documentation.
EN
The purpose of the described research was an attempt to estimate the leaf area index (LAI) parameter describing the structure of the vegetation based on the Landsat 5TM satellite imagery and field measurements made with the use of an optical plant canopy analyzer. The study was carried out in north-eastern Poland in the Biebrza river valley within the boundaries of the Biebrza National Park during the growing season of the year 2007. There were 13 spectral indices given in the literature known to be correlated with the LAI. The highest coefficient of determination and the highest correlation coefficient were obtained for the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI) indices for the wetland areas in the Biebrza river valley. The field measurements of the leaf area index and its spatial representation on satellite image show that the vegetation of natural river valleys is characterized by high spatial and seasonal variability. The study of the LAI on such large natural areas that are extensively used also requires knowledge of the methods of land use and the application of individual agrotechnical measures.
PL
W artykule przedstawiono wyniki obserwacji wykonanych z powietrza za pomocą BSP w podczerwieni. Warunki obserwacji były zbliżone do rzeczywistych warunków pola walki. Wyniki obserwacji porównano z badaniami laboratoryjnymi, w których użyto wzorca ciała czarnego do pomiaru transmisji radiacyjnej 11 różnych materiałów siatek maskujących. W badaniach odniesiono się do zmierzonej procentowej przepuszczalności promieniowania badanych materiałów, oznaczonych dalej w artykule współczynnikiem transparentności. Z przeprowadzonych badań wynika, że korelacja między transparentnością w świetle widzialnym i promieniowaniem podczerwonym przechodzącym przez materiał maskujący dla przebadanych materiałów nie jest zbieżna. Biorąc pod uwagę fakt, że siatki maskujące i materiały, z których są one wykonywane, stały się wyposażeniem bardzo pożądanym na współczesnym polu walki i wiele podmiotów rozpoczęło ich produkcję, powstała silna potrzeba opracowania szybkiej metody oceny przydatności takich materiałów w aspekcie kamuflażu termicznego. W pracy zaproponowano zastosowanie prostego wskaźnika oceny kamuflażu wyznaczanego na podstawie transparentności w dwóch zakresach spektralnych.
EN
This article presents the results of aerial observations conducted using infrared airborne surveillance platforms. The observation conditions closely resembled real battlefield conditions. The observation results were compared with laboratory studies that utilized a black body reference to measure the radiative transmission of 11 different masking nets materials. The research referred to the measured transparency coefficient of the tested materials. The conducted research indicates that there is no consistent correlation between transparency in visible light and infrared radiation passing through the masking material for the tested materials. Considering that camouflage meshes and the materials from which they are made have become highly sought-after equipment on the modern battlefield, with many entities initiating their production, there is a strong need to develop a rapid method for assessing the suitability of such materials in terms of thermal camouflage. The study proposes the utilization of a simple camouflage evaluation index based on transparency in two spectral ranges.
EN
Water erosion is a critical issue for Morocco, especially in its semi-arid regions, where climatic and edaphic conditions only allow erratic soil formation and vegetation growth. Therefore, water erosion endangers human activity both directly (loss of arable land, landslides, mudflows) and indirectly (siltation of dams, river pollution). This study is part of the Kingdom’s effort to assess the risk of water erosion in its territory. It is dedicated to the Bin El-Ouidane dam water catchment, one of the biggest water storage facilities in the country, located in the High Atlas Mountains. The poorly developed soils are very sensitive to erosion in this mountainous area that combines steep slopes and sparse vegetation cover. The calculation of soil losses is carried out with the RUSLE model and corrected by estimating areas of deposition based on the unit stream power theory. This method produces a mean erosion rate of around 6.3 t·ha-1·y-1, or an overall annual loss of 4.1 mln t, consistently with the siltation rate of the dam. Primary risk areas (erosion rates > 40 t·ha-1·y-1) account for 54% of the total losses, while they cover only 7% of the catchment. This distribution of the soil losses also shows that the erosion risk is mainly correlated to slope, directing the means of control toward mechanical interventions.
EN
The objective of this study is to map through multisource data, the change in land use structure and quantify its evolution around the semi-arid watershed of Wadi Sarno of Sidi Bel Abbès between 2000 and 2021. To this end, satellite images of 2000 and 2021 have been exploited by remote sensing and GIS, as well as field surveys for verification and validation of the results obtained. The methodology is based on supervised classification by maximum likelihood from the processing of satellite images. The analysis of the dynamics of land use shows that the areas of natural formations (dense forest and bare land) have decreased from 17,560 ha to 15,516 ha, that is to say, a regression of 8.04%, while the anthropised formations (Agriculture, open forest and rangeland, built-up areas, water bodies) have experienced an increase in their surface area, they have gone from 7901 ha to 9945 ha, that is to say, 10.4% of the total surface area of the basin. In the light of these results, it is possible to define priority areas for restoring degraded zones and enhancing natural formations. by giving priority to perennial crops to fix the soil in place and benefit from additional income for the region's farmers. By planting hardy species such as olives, figs, almonds, carob trees and so on. These species have proven their effectiveness and adaptation to local soil and climate conditions.
EN
The aboveground net primary productivity (ANPP) of bofedales is one of the most important indicators for the provision of ecosystem services in the high Andean areas. In the case of bofedales, the evaluation of the ANPP supply capacity as a service on a spatial and temporal scale through remote sensing has been little addressed. The capacity, intra and interannual, to provide the ANPP of the high Andean wetlands was quantified at a spatial and temporal level through remote sensing. The normalized difference vegetation index (NDVI) of the MODIS sensor was used according to the Monteith model (1972), product of the incident photosynthetically active radiation, fraction of the absorbed radiation, and the efficiency of using the radiation of the calibrated vegetation with dry matter sampling in the field. Results show an ANPP prediction R 2 of 0.52 (p < 0.05), with no significant spatial difference between field samples. When applying the model, the intra-annual temporary ANPP supply capacity presents a maximum average of 160.54 kg DM·ha -1·month -1 in the rainy season (December-May) and a maximum average of 81.17 kg DM·ha -1·month in the dry season (June-October). In 2003-2020, the interannual temporary capacity presented values of 1100-1700 kg DM·ha -1·year -1. This makes it possible not to affect the sustainability of the wetlands and prevent their depletion and degradation. Understanding the ANPP supply capacity of bofedales can favour the efficient use of the resource and indirectly benefit its conservation.
EN
The cartography and quantification of irrigated fields in the context of decreasing rainfall constitute a key element for water resources management. Therefore, in this context, the use of remote sensing methods applied to Landsat-type images with a high spatial resolution for monitoring the changes in land use in general and irrigated crops, in particular, is highly relevant. This paper aims to present a method for mapping spatial and temporal changes in irrigated parcels in the Guigou Plain, located in the central Middle Atlas, based on Landsat images and fieldwork. For the years 1985, 1998, 2010 and 2018, the use of a supervised classification method based on the principle of machine learning, fed by precise field surveys, has made it possible to highlight a significant extension of irrigated areas to the expense of pastureland and rainfed crops. Over the entire period under consideration, the results obtained with good precision (98.5% overall accuracy) showed that the area under irrigated crops has increased from approximately 699 ha to 3988 ha, i.e. an increase of 570%. The corollary of this increase is strong pressure on the water resource, especially groundwater. This information on the total extension of irrigated plots can be taken as a reference in the perspective of reasoned management of water resources in the sector.
EN
The land is one of the most treasures to support life, like food, fibre, medicine, and minerals, etc. Stone quarrying is one of the key elements which supports socio-economic development and industrial expansion. RS and GIS play an important role in environmental assessment to monitor the stone quarries and related activities for time to time. The present study was carried out to evaluate the impact of stone quarrying and crushing activities (SQCA) on land resources. Therefore, matrix change analysis of 2021, 2015, 2008 and 2003 were used for change detection. High-resolution Google Earth Pro images were used for the assessment of spatial as well as temporal changes caused by stone quarries and associated activities, which result in land use/land cover changes. The results show that the temporal changes in and around the quarrying sites over 18 years have contributed to dynamic changes in land use/land cover. According to the study, damaging mining operations have grown in the area. SQCA are mostly carried out on agricultural land as well as wasteland, which decreases about 18.44% and 59.89% during the study period. Abandoned pits left without reclamation converted to derelict ponds degrading the landscape and becoming dangerous for humans and the ecosystem.
EN
This study aimed to understand the new management challenges related to the impact of climate change on biodiversity, deterioration of agricultural productivity, food security, and increasing rates of desertification. This constitutes an important indicator for studying Land Degradation Neutrality (SDGs Target 15.3), which is considered a significant target in achieving the Sustainable Development Goals 2030. The present study is concerned with assessing and monitoring land management and land degradation in Wadi El Farigh from 2000 to 2019. Soil quality is a major part of the chain that leads to understanding sustainable land management of natural resources (land, groundwater, and natural vegetation). A geopedological approach produced the studied area’s physiographic and soil map. The study of changes in land degradation level in Wadi El Farigh over 20 years with a period of every five years shows a very high improvement in the study area from the year 2000 up to 2014. From 2015 to 2019, this class was reduced due to the effects of land degradation reflected by the use of saline water for irrigating crops. Using remote sensing and geostatistical analyses within the GIS environment illustrated that the soils were classified as Entisols, representing 79.45 of the total studied area, and Aridisols representing 20.55% of the total studied area.
EN
The purpose of the study was to establish dependence of sunflower productivity on hybrid plasticity under the climatic conditions of the Steppe zone and effectiveness of growth-regulators on the basis of the analysis of differentiation of a vegetation index. The research on the development and productivity of different sunflower hybrids under the natural-climatic conditions of the Steppe zone of Ukraine was conducted in the years of 2019 (medium-wet), 2020 (dry) and 2021 (wet). Spatio-temporal differentiation of the vegetation of sunflower hybrids was established on the basis of calculation of a normalized difference vegetation index (NDVI) using the data of the decoded space images of Sentinel 2. Cartographic and grapho-analytical materials reflecting the reaction of plants to natural-climatic conditions and multifunctional growth-regulators were obtained. The dependence of the reaction of sunflower hybrids to multifunctional growth-regulators on their plasticity in response to the natural-climatic conditions of the Steppe zone was established. There was a weak reaction to application of growth-regulators of the sunflower hybrids Oplot and P64HE133 which are characterized by a high level of plasticity in response to the natural-climatic conditions of the Steppe zone. It was proven that the application of the biological preparation Helafit Combi exceeded the level of agrocenoses productivity in comparison with the chemical preparation ArchitectТМ by 1.1-5.4%. It was established that foliar treatment with growth-regulators led to a decline in water uptake by the sunflower hybrids by 1.2–10.0% in the dry year, by 3.8–8.6% in the medium-wet year and by 3.7%–21.9% in the wet year. There was a significant reduction in the level of water uptake by the hybrid Hector – by 7.7–10.0% and the hybrid 8KH477KL – by 1.2–21.9%. The research results are the basis for forecasting the development of sunflower hybrid crops with further measurement of the crop productivity that allows establishing a probable level of efficiency of sunflower hybrid production by agricultural producers under the climatic conditions of the Steppe zone.
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