scholarly journals Remote sensing of land use/cover changes and its effect on wind erosion potential in southern Iran

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1948 ◽  
Author(s):  
Mahrooz Rezaei ◽  
Abdolmajid Sameni ◽  
Seyed Rashid Fallah Shamsi ◽  
Harm Bartholomeus
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Land Management ◽  
Sediment Yield ◽  
Wind Erosion ◽  
Agricultural Practices ◽  
Yield Potential ◽  
Landsat 8 ◽  
High Sediment

Wind erosion is a complex process influenced by different factors. Most of these factors are stable over time, but land use/cover and land management practices are changing gradually. Therefore, this research investigates the impact of changing land use/cover and land management on wind erosion potential in southern Iran. We used remote sensing data (Landsat ETM+ and Landsat 8 imagery of 2004 and 2013) for land use/cover mapping and employed the Iran Research Institute of Forest and Rangeland (IRIFR) method to estimate changes in wind erosion potential. For an optimal mapping, the performance of different classification algorithms and input layers was tested. The amount of changes in wind erosion and land use/cover were quantified using cross-tabulation between the two years. To discriminate land use/cover related to wind erosion, the best results were obtained by combining the original spectral bands with synthetic bands and using Maximum Likelihood classification algorithm (Kappa Coefficient of 0.8 and 0.9 for Landsat ETM+ and Landsat 8, respectively). The IRIFR modelling results indicate that the wind erosion potential has increased over the last decade. The areas with a very high sediment yield potential have increased, whereas the areas with a low, medium, and high sediment yield potential decreased. The area with a very low sediment yield potential have remained constant. When comparing the change in erosion potential with land use/cover change, it is evident that soil erosion potential has increased mostly in accordance with the increase of the area of agricultural practices. The conversion of rangeland to agricultural land was a major land-use change which lead to more agricultural practices and associated soil loss. Moreover, results indicate an increase in sandification in the study area which is also a clear evidence of increasing in soil erosion.

Influence of changing land use/cover and land management on wind erosion potential in southwestern Iran

2020 ◽  
Author(s):  
Fahime Nikseresht ◽  
Schulin Rainer
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Soil Erosion ◽  
Land Management ◽  
Sediment Yield ◽  
Wind Erosion ◽  
Dust Storms ◽  
Yield Potential ◽  
Southwestern Iran ◽  
High Sediment

<p>Wind erosion is one of the main factors of soil degradation and air pollution in arid and semiarid regions. In recent years, dust storms have become ever more important sources of air pollution in large areas of Iran. Dust storms previously were confined to the summer season and to western Iran. Nowadays, dust storms occur during eight months of the year and extend to the central regions and the entire south of Iran. This is causing increasing problems for the residents of the affected areas, threatening their health and impairing social, economic and agricultural activities. Ahvaz, the capital of Khuzestan Province, is the city that is most seriously affected by these problems in Iran.</p><p>Wind erosion is a multifaceted phenomenon influenced by a variety of factors. One of these factors that has changed considerably in recent time in Iran is land use/cover and land management. To investigate the impact of these changes on wind erosion potential in southwestern Iran we applied an empirical model of the Iran Research Institute of Forest and Rangeland (IRIFR) to remote sensing data extracted from Landsat ETM+ and Landsat 8 imagery of 2010 and 2019. Relationships between changes in wind erosion and land use/cover were determined by cross-tabulation, combining the original spectral bands with synthetic bands and using Maximum Likelihood classification.</p><p>The results indicate major changes in wind erosion potential over the last decade in the study area. Interestingly, while areas with a low, medium, and high sediment yield potential decreased, areas with a very high sediment yield potential have increased. Increasing soil erosion potential was primarily related to the conversion of rangeland to agricultural cropland Moreover, the results indicate an increase in desertification in the study area which is also a clear evidence of increasing in soil erosion.</p>

scholarly journals Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

2014 ◽  
Vol 18 (9) ◽  
pp. 3763-3775 ◽  
Author(s):  
K. Meusburger ◽  
G. Leitinger ◽  
L. Mabit ◽  
M. H. Mueller ◽  
A. Walter ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Sediment Yield ◽  
Soil Loss ◽  
Water Erosion ◽  
Erosion Rates ◽  
The Difference ◽  
Snow Gliding

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

Agricultural Land Management Options Following Large-Scale Environmental Contamination: Evaluation for Fukushima Affected Agricultural Land

2013 ◽  
Author(s):  
Hildegarde Vandenhove
Keyword(s):  
Land Use ◽  
Land Management ◽  
Nuclear Power ◽  
Large Scale ◽  
Agricultural Land ◽  
Agricultural Practices ◽  
Management Option ◽  
Management Options ◽  
Fukushima Daiichi ◽  
Agricultural Land Management

The accident at the Fukushima Daiichi Nuclear Power Plant has raised questions about the accumulation of radionuclides in soils, the transfer in the foodchain and the possibility of continued restricted future land use. This paper summarizes what is generally understood about the application of agricultural countermeasures as a land management option to reduce the radionuclides transfer in the food chain and to facilitate the return of potentially affected soils to agricultural practices in areas impacted by a nuclear accident.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

Penentuan Luas Area Sawah Kabupaten Sleman Pada Citra Landsat 8 Operational Land Imager (OLI)

Respati ◽  
2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Sulidar Fitri ◽  
Novi Nurjanah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Support Vector Machine ◽  
Rice Field ◽  
Image Data ◽  
Rice Fields ◽  
Support Vector ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Learning Machine

INTISARITeknologi penginderaan jauh sangat baik dijadikan data pembuatan peta penggunaan lahan, karena kebutuhan pemetaan semakin tinggi terutama untuk mendeteksi perubahan penggunaan lahan terutama untuk penentuan luas area khususnya sawah di kabupaten Sleman. Untuk mendapatkan informasi luasan area sawah dari interpretasi citra landsat-8 OLI (Operational Land Imager) diperlukan metode khusus, terutama untuk pengolahan data citra penginderaan jauh secara digital. Salah satu metode pengolahan citra penginderaan jauh adalah metode Support Vector Machine (SVM). Metode SVM merupakan metode learning machine (Pembelajaran mesin) yang dapat mengklasifikasikan pola serta mengenali pola dari inputan atau contoh data yang diberikan dan juga termasuk ke dalam supervised learning. Hasil area sawah yang didapati dari citra Landsat 8 OLI dengan pengolahan metode SVM didapati berada di 18 kecamatan dala Kabupaten Sleman. Luasan tertinggi ada di kecamatan Ngaglik dengan 19,78 KM2 dan terendah di kecamatan Turi seluas 2,14 KM2. Nilai keseluruhan akurasi yang didapat untuk kelas lahan sawah dan area non sawah adalah adalah 53%.Kata kunci— Landsat-8 OLI, SVM, Data Citra, Geospasial, Luas Area Sawah ABSTRACTRemote sensing technology is very well used as a data for making land use maps, because mapping needs are increasingly high especially for detecting land use changes, especially for determining the area, especially rice fields in Sleman district. To get information about the area of the rice fields from the interpretation of Landsat-8 OLI (Operational Land Imager), special methods are needed, especially for processing remote sensing image data digitally. One method of processing remote sensing images is the Support Vector Machine (SVM) method. The SVM method is a learning machine method that can classify patterns and recognize patterns from input or sample data provided and also includes supervised learning. The results of the rice field that were found from the Landsat 8 OLI image by processing the SVM method were found in 18 sub-districts in Sleman Regency. The highest area is in Ngaglik sub-district with 19.78 KM2 and the lowest in Turi sub-district is 2.14 KM2. The overall value of the accuracy obtained for the class of rice field and non-rice field is 53%.Kata kunci—  Landsat-8 OLI, SVM, Image Data, Geospatial, Area of Rice Fields

scholarly journals On-Site Water and Wind Erosion Experiments Reveal Relative Impact on Total Soil Erosion

Geosciences ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 478 ◽  
Author(s):  
Miriam Marzen ◽  
Thomas Iserloh ◽  
Wolfgang Fister ◽  
Manuel Seeger ◽  
Jesus Rodrigo-Comino ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Wind Erosion ◽  
Soil Surface ◽  
Water Erosion ◽  
Relative Impact ◽  
Wheat Field ◽  
Total Soil ◽  
Potential Impact

The relative impact of water and wind on total erosion was investigated by means of an experimental-empirical study. Wind erosion and water erosion were measured at five different sites: (1) Mediterranean fallow, (2) Mediterranean orchard, (3) wheat field, (4) vineyard and (5) sand substrate. Mean erosion rates ranged from 1.55 to 618 g·m−2·h−1 for wind and from 0.09 to 133.90 g·m−2·h−1 for rain eroded material over all tested sites. Percentages (%) of eroded sediment for wind and rain, respectively, were found to be 2:98 on Mediterranean fallow, 11:89 on Mediterranean orchard, 3:97 on wheat field, 98:2 on vineyard and 99:1 on sand substrate. For the special case of soil surface crust destroyed by goat trampling, the measured values emphasize a strong potential impact of herding on total soil erosion. All sites produced erosion by wind and rain, and relations show that both erosive forces may have an impact on total soil erosion depending on site characteristics. The results indicate a strong need to focus on both wind and water erosion particularly concerning soils and substrates in vulnerable environments. Measured rates show a general potential erosion depending on recent developments of land use and climate change and may raise awareness of scientist, farmers and decision makers about potential impact of both erosive forces. Knowledge about exact relationship is key for an adapted land use management, which has great potential to mitigate degradation processes related to climate change.

scholarly journals A Remote Sensing Based Method to Detect Soil Erosion in Forests

2019 ◽  
Vol 11 (5) ◽  
pp. 513 ◽  
Author(s):  
Hanqiu Xu ◽  
Xiujuan Hu ◽  
Huade Guan ◽  
Bobo Zhang ◽  
Meiya Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Southern China ◽  
Red Soil ◽  
Forest Area ◽  
Landsat 8 ◽  
Large Spatial Scale ◽  
Five Factors

Rainwater-induced soil erosion occurring in the forest is a special phenomenon of soil erosion in many red soil areas. Detection of such soil erosion is essential for developing land management to reduce soil loss in areas including southern China and other red soil regions of the world. Remotely sensed canopy cover is often used to determine the potential of soil erosion over a large spatial scale, which, however, becomes less useful in forest areas. This study proposes a new remote sensing method to detect soil erosion under forest canopy and presents a case study in a forest area in southern China. Five factors that are closely related to soil erosion in forest were used as discriminators to develop the model. These factors include fractional vegetation coverage, nitrogen reflectance index, yellow leaf index, bare soil index and slope. They quantitatively represent vegetation density, vegetation health status, soil exposure intensity and terrain steepness that are considered relevant to forest soil erosion. These five factors can all be derived from remote sensing imagery based on related thematic indices or algorithms. The five factors were integrated to create the soil erosion under forest model (SEUFM) through Principal Components Analysis (PCA) or a multiplication method. The case study in the forest area in Changting County of southern China with a Landsat 8 image shows that the first principal component-based SEUFM achieves an overall accuracy close to 90%, while the multiplication-based model reaches 81%. The detected locations of soil erosion in forest provide the target areas to be managed from further soil loss. The proposed method provides a tool to understand more about soil erosion in forested areas where soil erosion is usually not considered an issue. Therefore, the method is useful for soil conservation in forest.

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