Seasonal effects of Land cover changes on ecological of migratory birds in Al-Hammar Marsh, southern Iraq

Author(s):  
Ali K. Mohammed Ali ◽  
Fouad K. Al Ramahi

Abstract Al-Hammar Marsh in Iraq stands out for hosting the largest concentrations of coastal migratory birds along the migration path between the Arabian Gulf and the Mediterranean Sea. Despite this importance, there is no complete review of the dynamics of these birds. In this study, we collected and analyzed the results of six species of migratory birds (Mallard duck, Graylag goose, White pelican, Barn swallow, Common gull, White stork) in the Region, in addition to the results of the land cover in October of 2000 to 2020, The results show the presence across the past two decades of a change in the population makeup of migratory birds. Complete numbers of migratory birds indicated a decline in the residual types between 2000 and 2020. The disproportion among numbers was also too large for trends to be observed. The region also showed a decrease in the areas of vegetation cover during the study period was equal to 5.0%, 3.5%, and 15.6%, And an increase in the areas of water bodies during the study period was equal to 7.8%, 21.0%, and 62.6%, respectively, Finally, A multivariate analysis suggests a general decline in types that depend on the Wetland for feeding and breeding an in the sublittoral and the offshore zones. Use satellite data can be used for monitoring several variables such as water bodies, vegetation cover, Climate factors that influence the activity of Migratory birds.

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110261
Author(s):  
Hamza Islam ◽  
Habibuulah Abbasi ◽  
Ahmed Karam ◽  
Ali Hassan Chughtai ◽  
Mansoor Ahmed Jiskani

In this study, the Land Use/Land Cover (LULC) change has been observed in wetlands comprises of Manchar Lake, Keenjhar Lake, and Chotiari Reservoir in Pakistan over the last four decades from 1972 to 2020. Each wetland has been categorized into four LULC classes; water, natural vegetation, agriculture land, and dry land. Multitemporal Landsat satellite data including; Multi-Spectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager (OLI) images were used for LULC changes evaluation. The Supervised Maximum-likelihood classifier method is used to acquire satellite imagery for detecting the LULC changes during the whole study period. Soil adjusted vegetation index technique (SAVI) was also used to reduce the effects of soil brightness values for estimating the actual vegetation cover of each study site. Results have shown the significant impact of human activities on freshwater resources by changing the natural ecosystem of wetlands. Change detection analysis showed that the impacts on the land cover affect the landscape of the study area by about 40% from 1972 to 2020. The vegetation cover of Manchar Lake and Keenjhar Lake has been decreased by 6,337.17 and 558.18 ha, respectively. SAVI analysis showed that soil profile is continuously degrading which vigorously affects vegetation cover within the study area. The overall classification accuracy and Kappa statistics showed an accuracy of >90% for all LULC mapping studies. This work demonstrates the LULC changes as a critical monitoring basis for ongoing analyses of changes in land management to enable decision-makers to establish strategies for effectively using land resources.


2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiros Tsegay Deribew

AbstractThe main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986–2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~ 5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.


Author(s):  
Qijiao Xie ◽  
Qi Sun

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.


2021 ◽  
Vol 13 (12) ◽  
pp. 6565
Author(s):  
Shama E. Haque

Phosphorus is an essential component of modern agriculture. Long-term land application of phosphorous-enriched fertilizers and animal manure leads to phosphorus accumulation in soil that may become susceptible to mobilization via erosion, surface runoff and subsurface leaching. Globally, highly water-soluble phosphorus fertilizers used in agriculture have contributed to eutrophication and hypoxia in surface waters. This paper provides an overview of the literature relevant to the advances in phosphorous management strategies and surface water quality problems in the U.S. Over the past several decades, significant advances have been made to control phosphorus discharge into surface water bodies of the U.S. However, the current use of phosphorus remains inefficient at various stages of its life cycle, and phosphorus continues to remain a widespread problem in many water bodies, including the Gulf of Mexico and Lake Erie. In particular, the Midwestern Corn Belt region of the U.S. is a hotspot of phosphorous fertilization that has resulted in a net positive soil phosphorous balance. The runoff of phosphorous has resulted in dense blooms of toxic, odor-causing phytoplankton that deteriorate water quality. In the past, considerable attention was focused on improving the water quality of freshwater bodies and estuaries by reducing inputs of phosphorus alone. However, new research suggests that strategies controlling the two main nutrients, phosphorus and nitrogen, are more effective in the management of eutrophication. There is no specific solution to solving phosphorus pollution of water resources; however, sustainable management of phosphorus requires an integrated approach combining at least a reduction in consumption levels, source management, more specific regime-based nutrient criteria, routine soil fertility evaluation and recommendations, transport management, as well as the development of extensive phosphorus recovery and recycling programs.


2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.


Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.


Author(s):  
Alexey Osipov ◽  
Georgy Osipov ◽  
Vasily Kovyazin

Biogenic pollution of water bodies and their eutrophication is one of the most serious environmental problems of our time. One of the sources of water pollution with biogenic substances is forests, which belong to the background sources of biogenic load. Currently available methods for assessing the removal of nutrients from the forest vegetation cover do not provide the desired results, which causes an urgent need for their improvement. This article describes the method developed by the authors of geoinformation modeling of removal of biogenic substances from the forest vegetation cover to water bodies, taking into account the spatial distribution of vegetation in the catchment area, its species composition and absorption of biogenic substances during their migration. The Eastern part of the Gulf of Finland was adopted as the object of testing of the developed method. this is due to the fact that eutrophication processes are actively manifested within its water area. The volume of the background biogenic load on the Gulf of Finland, formed during the decomposition of the fall of the natural vegetation cover in the catchment area, was determined based on the specific removal of biogenic substances from plant communities and their absorption during migration “plant community — water object”. The total background biogenic load on the eastern part of the Gulf of Finland, formed as a result of decomposition of natural vegetation cover, was 170.21 t/year for the northern catchment for nitrogen, 12.14 t/year for phosphorus, and 207.31 t/year for the southern catchment for nitrogen , and 15.68 t/year for phosphorus. The data obtained do not contradict the results of other authors who study the background biogenic load on the Gulf of Finland. The method can be effectively used in the development of measures to reduce the nutrient load on water bodies and planning of economic activities in catchments.


Urbanization plays a key role in the health of the water bodies in any region. In a rapidly growing country like India, especially Bangalore district, rapid urbanization has seen a steep decline in the number of water bodies the region is famous for. In this paper, Land Use and Land Cover change is analysed for the remotely sensed images of Bangalore District using Spectral Angle Mapper Algorithm. Data for the purpose of analysis was obtained from BHUVAN (NRSC, ISRO). The study area is Bangalore District and data was collected from the time period 2008-2016. The major classes used in the classification are Land(Built-up), water bodies (Lakes), Vegetation (Gardens), Soil (Barren and fertile). The satellite images and the accompanying classification algorithms indicate that the percentage of water bodies have drastically shrunk (from 2.9% in 2008to1.8% in 2016) in the area of study. The results of this study can be used by the civic authorities to implement decisions to conserve the water bodies in the area.


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