Landsat Images For Years Research Articles

Illustration of Rapid Urban Growth in Surkhet Valley of Nepal via Land Use and Land Cover Dynamics

Surkhet Valley hosts Birendranagar City which is the capital of Karnali Province of Nepal and there is a rapid change in the landscape of this valley. This change can be attributed to its designation as an administrative capital and the leading economic center of the province. Thus, this study aimed to observe the changing land use and land cover (LULC) patterns of Surkhet Valley. Object-based image analysis was carried out for image classification for Landsat images of years 1989, 1999, 2009, and 2019. Key findings, for the area of 103.15 km2 Surkhet Valley, showed decreasing area of cultivated lands and increasing spatial coverage of built-up areas. The cultivated lands that measured 42 km2 for the year 1989 had plummeted to just 28.23 km2 in 2019. On the other side, the area covered by built-up class was only 1.16 km2 in 1989 which rose to 15.41 km2 in 2019. The changes in LULC coverage of other classes such as forests, shrub/grassland, sand, and water were negligible. The rate of change in the area of LULC classes built-up and cultivation was near but in the opposite direction. Built-up had an increasing rate of 0.49 km2year-1 while cultivation area had a decreasing rate of -0.46 km2year-1. When the built-up area of 2019 was compared to the base area of 1989 it had a gain of 1270.46% indicating its rapid growth in the past three decades. These reflected an increasing trend in spatial coverage of built-up areas indicating rapid urban growth.

Riverbank Erosion & Consequent Land Settlement Issues: A Case of River Chenab, District Hafizabad

When calamity strikes, it causes damage but it also provides opportunities for newer learnings opportunities and better preparedness to combat menace. Pakistan is agrarian economy and comprises fertile plains. According to Pakistan Bureau of Statistics, agriculture contributes to 24 percent of national Gross Domestic Product. Agriculture is dependent on water needs, met through water channels fed by rivers originating mostly from glacial sources existing in northern part of the country. The country hosts five major rivers, namely Indus Jhelum, Chenab, Ravi, and Sutlej. The dendritic river patterns follow gravity flow causing frequent morphological changes and riverbank erosion is the most significant phenomenon which acts as hazard for farming communities in terms of loss of shelter, livelihood, and landholdings. An in-time identification of the issue is the real concern nowadays. Presently, different tools are available for instant interpretation of riverbank erosion like Remote Sensing (RS) and Geographical Information System (GIS), which are not only good for instant identification but also helpful for precise estimation of historical losses. Landsat images for years 2009, 2013, and 2017 have used to make an initial assessment of erosion hotspots. High-resolution satellite imagery from Google Earth is also used for meticulous analysis. The analysis shows that beyond other factors, average riverbank displacement rate due to erosion directly depends on rise in water levels. The study provides systematic bases to estimate the losses precisely. The study is useful for damages assessment of land and livelihood to device relief packages for the affected communities. The study also builds the capacity in resolving land settlement issues consequent to the riverbank erosion phenomenon.

Impact of land use and land cover change on the magnitude of surface runoff in the endorheic Hayk Lake basin, Ethiopia

This study focused to analyze the main human-induced land use and/or cover changes and their impact on the response to surface runoff from the Hayk Lake endorheic basin between 1989 and 2015. The investigation of Landsat images of years 1989, 2000 and 2015 with the aid of ArcGIS 10.1 indicated an increase in cultivation land by 137.74% at the disbursement of a decrease of 1.34% in lake water, 49.48% in shrubland, 55.84% in plantation, and 17.32% in grassland. Overall accuracy (92%–96%) and kappa values (0.90–0.95) proved that the image classifications were accurate. The impact of the changed land use and/or cover on surface runoff was investigated by simulating the surface runoff for the years 1989, 2000 and 2015, and then quantifying the individual rate of contribution of land use and/or cover change on the magnitude of simulated surface runoff using HEC-HMS modeling tool. The analysis found that land use and cover change alone increased surface runoff by 20.18% and that climate change reduced surface runoff by 120.18%. The combined effect reduced surface runoff and caused a continued decline in water level at Hayk Lake. Therefore, this study advocated basin-based lake water management strategies linked to the negative impacts of land use and land cover, and climate change on the water balance of Hayk Lake for its sustainability.

A novel hybrid approach using SVM and spectral indices for enhanced land use land cover mapping of coastal urban plains

In present study, Landsat images of years 2001, 2009 and 2018 are used for LUC mapping of a coastal-urban-floodplain wherein built-up and coastal-barren classes have been identified to be the most confusing classes for interpretation. Otsu’s thresholding techniques have been used for mapping of waterbodies, built-up, and coastal-barren lands. The performance of most commonly used built-up indices have been assessed, among which BCI performed best for the study area. A new index, called Coastal-Barren-Index (CBI), has been developed using the spectral characteristics of SWIR1 and green spectral reflectance bands. A critical comparison of SVM and RFC classifiers are reported, and, finally, a hybrid approach is proposed as a combination MNDWI-CBI-SVM for mapping of the study area with Overall Accuracy 90.5% and Kappa value 0.87. The proposed approach is validated for an independent site, and, can be considered as generic in nature for LUC mapping of coastal urban plains.

Applicability of the CA-Markov Model in Land-use/Land cover Change Prediction for Urban Sprawling in Batticaloa Municipal Council, Sri Lanka

Rapid urbanization is leading to sprawling development around the world today, which is becoming a concerning issue for researchers and planners. Urban sprawl depends on the dynamics of land use, mainly on the built-up growth in this area. The study aims to apply and test the applicability of the CA-Markov model in the land use/land cover change prediction for urban sprawling in Batticaloa Municipal Council, Sri Lanka. The secondary data were used, which are Landsat images for years 1990, 2000, 2010, and 2020. The Supervised Maximum Likelihood classification, the Markovian transition estimate, and the CA-Markov chain analysis were employed with ArcGIS 10.6.1, IDRISI 17.0, and MS-Excel 2013. The result revealed that the existing and simulated maps for the years 2000, 2010, and 2020 showed an almost equal probability of changes. The simulation for 2030 is credible for the future prediction, which showed that a significant estimate occurs. Therefore, the CA-Markov model is appropriate for land use/land cover predictions.

Application of modified cellular automata Markov chain model: forecasting land use pattern in Lebanon

This article modifies the use of the Cellular Automata Markov Chain Model to predict future land use pattern in Lebanon, and compares it to the current developed model. LandSat images of years 2000, 2009 and 2018 are used to generate land use maps within the geographic information system. Current developed model was generated by integrating Population density data with land use classification maps to decompose the built-up development to three sub-classes: High, Medium and Low-density built-up land uses. Simulations of future land use pattern over the year 2018 based on these two prediction models reveal that the Modified Cellular Automata Markov Chain Modelling technique is more accurate than the Extended Markov Chain model. Spatial effects of built-up densities are validated in this study. Consequently, the extension of the Cellular Automata Markov Chain Model represents an innovative tool for regional and urban planning to forecast potential locative distribution of old and new urban agglomeration. The sequential shift of the urban areas among different density classes in addition to the interactions of urban agglomerations should be employed as a guiding tool for decision-makers and planners during the phase of developing new population and economic strategies, new urban Masterplan and during the process of enacting/developing new land-use policies. In the final part of the study, a simulation of land use pattern for the year 2036 is generated using TerrSet v.18 software and an analysis of the outcome for the forecasted map is discussed.

Mapping the Effects of Anthropogenic Activities in the Catchment of Weija Reservoir using Remote Sensing Techniques

Man has contributed to land cover alteration since time-immemorial through clearing of land for residential, agriculture, recreational and industrial purposes. The emergence of adapting wild plants and animals for human use as well as industrialisation have also contributed to the alteration of land cover. Over the years, anthropogenic activities have had great impact on the Weija catchment. This study seeks to map the catchment and determine the impact of anthropogenic activities using Remote Sensing techniques. Observations and measurements were made on the field as well as classification of land cover using Landsat images of years 1991, 2003 and 2017. Results showed an increase in built-up areas by 18% from 1991 to 2017. Other classes such as shrubs increased due to decrease in dense vegetation. This study confirms the use of Remote Sensing as a valuable tool for detecting change in land cover and determining the impact of anthropogenic activities in the Weija Catchment. Keywords: Land Cover, GIS, Remote Sensing, Weija Catchment, Anthropogenic Activities

Water Resources Dynamics and Vulnerability in Rusizi National Park (Burundi) from 1984 to 2015, in the Context of Climate Change and Global Warming

The study of water resources’ dynamics and vulnerability in Rusizi national Park aimed to achieve the following objectives: (1) to identify, characterize and map water bodies, (2) to analyze and explain their periodical evolutions and (3) to analyze the spatial transformation processes affecting them. It is a contribution to the knowledge of the Park’s water resources for the development of monitoring systems and the sustainability of their functions as strategic ecosystems. It is based on the diachronic analysis of land cover from multi-date Landsat images of years 1984, 1990 and 2011 (TM), 2000 (ETM+) and 2015 (OLI-TIRS), landscape ecology tools and socio-economic and climate data. Supervised classification of images allowed the identification of 9 to 10 land cover classes including water bodies, according to years. A total number of 17 water bodies were detected from 1984 to 2015. During this period, regularly detected and dried up water bodies represent 18.2% and 54.6% respectively. The rates of water bodies’ drying up were 69.2% in 2000 and 64.2% in 2015. Water bodies are experiencing a great deterioration in number, size and stability. The Park's water coverage has decreased from 3.56% in 1984 to 2.43% in 2015. This corresponds to a decline of 31.2%. The water bodies’ stability, which was 75.70% between 1984 and 1990, represents only 42.78% between 1984 and 2015. The stability of individual water bodies is decreasing as well while low spatial connectivities are being observed between some close water bodies. The spatial transformation processes carrying these dynamics are patch enlargement, patch creation, patch attrition and patch dissection, depending on the period. Global warming, rainfall variability and farming activities like land drainage and irrigation are the most important threats to water resources.

Prediction of spatial land use changes based on LCM in a GIS environment for Desert Wetlands – A case study: Meighan Wetland, Iran

Meighan Wetland and its surroundings have undergone many changes in recent years. This study aims to monitor and predict land use changes using the land change model (LCM) module in the Meighan wetland. Land Sat images of years 2000, 2007 and 2015 were used to produce digital land use maps. The images were classified into seven classes including; Salt lake, Agriculture, Rangeland, Manmade, Wastewater, Wetland and Mine areas. The LCM module in Idrisi GIS software was used to analyze the land use changes for predicting the land uses status in 2015, based on artificial neural network (ANN) and Markov Chain analysis. The ANN was trained with various influencing factors including; distance from road, distance from manmade areas, distance from land changed edge, distance from stream, elevation and slope. The results indicated that 1663.88 ha of the rangeland cover and 715.68 ha of the salt lake cover have been degraded during the 2000–2015 period. Furthermore, the wetland, mine, wastewater and manmade degradation are increased to 724 ha, 335 ha, 37 ha and 270 ha in comparison to initial land conditions. Also, the result shows that rangeland and salt lake areas will decrease in the year 2030 compare to 2015, while, wetland, mine and manmade land changes may increase.

The use of remote sensing to estimate changes of seagrass extent and biomass in Cockburn Sound, Western Australia

The extent of seagrasses in Cockburn Sound was examined using Nearmap images of year 2010, 2012, 2014, and 2016 to be compared to the last assessment in 1999. It was identified that the seagrass coverage has increased by 231 Ha since 1999, with most of the growth occurred in the southern part. While the water quality in Cockburn Sound has improved, it is believed that there are other pressures affecting the slow growth rate of the seagrasses. Seagrass biomass was also evaluated using Landsat images of year 1994, 1999, 2010, 2012, 2014, and 2016 in addition to a field survey data of leaf biomass in 2016. Despite its increasing extent, seagrass in Cockburn Sound indicated a declining biomass since 1994, which is believed due to the changing nutrient content.

Glacier area and volume changes of Hidden Valley, Mustang, Nepal from ~1980s to 2010 based on remote sensing

Abstract. Glaciers are one of the important natural resources of freshwater and sources of water for hydropower, agriculture and drinking whenever the water is scarce. This mapping and change analysis helps to understand the status and decadal changes of glaciers in Hidden Valley, Mustang district, Nepal. The investigation is carried out using Landsat images of the years 1977 (~1980s), 1990, 2000 and 2010. We mapped 10 glaciers of the Hidden Valley covering an area of 19.79 km2 based on the object-based image classification method using an automatic method and manual delineation by a Geographic Information System (GIS), separately. The glacier outlines for 2010, 2000, 1990 and 1980s in both methods are delineated from the multispectral Landsat images of the respective years. The total area losses of the glaciers from the automatic method are 1.713 and 0.625 km2 between 1990−2000 and 2000−2010 and from manual delineation are 2.021, 1.264, 1.041 km2 between ~1980s−1990, 1990−2000 and 2000−2010. The amount of average estimated glacier ice reserves lost is 0.326 km3 (26.26 %) and the total glacier area loss is 4.33 km2 (21.87 %) from the 1980s to 2010 based on manual delineation. The glaciers of Hidden Valley are shrinking and fragmented due to decrease in glacier area and ice reserves.

Dynamics of Land Cover and Impact on Stream flow in the Modder River Basin of South Africa: Case Study of a Quaternary Catchment

Understanding how dynamics in individual land use types influence changes in streamflow is vital. Most hydrological studies are based on paired catchment and modelling approaches. These are data intensive and require a long period of monitoring. To determine the hydrological effects of tropical vegetation conversion over large areas, it is manageable to study the same basin over different time periods. The study analysed changes in historical stream flow patterns with reference to dynamics in land cover in C52A quaternary catchment of South Africa. Landsat images for years 1993, 2004 and 2013 were used for the development of land cover maps. Subsequently, step-change (median point change, Mann-Whitney and Kruskall Willis) and trend detection tests (Spearman’s rho and Kindall’s tau) were applied to average annual discharge and rainfall data for the catchment between 1984 and 2013.Tukey’s honestly significant difference (HSD) test was also used to compare the means. Results revealed that huge land cover changes coincided with significant (p<0.05) changes in streamflow although rainfall remained homogenous over the same period. This suggests that land cover change is intricately coupled to increases in streamflow. In addition, increased runoff is usually accompanied by increased rates of erosion and siltation. To ensure sustainable management of the catchment, therefore, soil and water conservation measures are critical within the broader context of integrated water resources management.