Landsat TM Research Articles

The impact of land use and cover changes on river flows in Wundanyi Catchment of Taita Hills, Kenya (1970–2030)

<p>Taita Hills are one of the most important biodiversity hotspots of Kenya but are experiencing a high rate of deforestation due to the to the conversion of its original forestland to agriculture and settlement during the last century. These landscape dynamics, coupled with rainfall fluctuations in these critical ecosystems, may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of land use/cover change (LUCC) in the Wundanyi catchment from 1970 to 2030 and predict their specific and combined effects on surface runoff and stream flow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modeling using both historical and primary data from the Wundanyi catchment and Landsat TM and ETM+ imagery of Taita Hills for 1990, 2000, and 2010. Results show highly variable mean seasonal and annual values of discharge in Wundanyi catchment, probably attributed to environmental changes affecting Taita Hills in general and Wundanyi catchment in particular. Compared to 1990, major land use/cover changes in 2010 were featured by the expansion of built-up area (250%), plantation forest (23.7%), broadleaved forest (17.4%), and thicket (15.9%). It was also notable the decrease in woodland (−30.3%), cropland (−21.6%), and shrubland (−0.8%). Dynamic spatial trends by the year 2030 will be evidenced by increased thicket by 0.41% per annum (<em>R</em><sup>2</sup> = 81.6%) and by decreased plantation forests (−0.13%; <em>R</em><sup>2</sup> = 91.3%), woodland (−0.10%; <em>R</em><sup>2</sup> = 77.6%), shrubland (−0.11%; <em>R</em><sup>2</sup> = 85.2%), broadleaved forests (−0.03%; <em>R</em><sup>2</sup> = 56.6%) and cropland (−0.09%; <em>R</em><sup>2</sup> of 84.4). These changes will shape the catchment landscape and influence its hydrology, unless the existing forest and agricultural policy interventions are enforced. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in the Wundanyi catchment.</p>

Variation of groundwater level due to land use, precipitation, and earthquake in Yogyakarta City from 2005 to 2020

Yogyakarta City not only experiences rapid land use conversion and precipitation decline but also experiences frequent earthquake events. These factors can have a significant impact on groundwater variation dynamics in this city. Therefore, the aim of this research is to analyze the factors that can influence groundwater oscillation based on precipitation, land use, earthquake, and river discharge changes. The method used to analyze spatio-temporal groundwater level and precipitation are by applying space-time Bayesian statistics since Bayesian has lower root mean square error compared to the space-time variogram and inverse distance methods. Land use is classified with false color composite for Landsat ETM and infrared color composite for Landsat 8 since these color composites well classify built-up and non-built-up areas. River discharge is analyzed as a primary indication of earthquake event impact on groundwater level variation.There is no significant variation of groundwater level from 2005 to 2020. Groundwater fluctuation is classified as stable since the magnitude of change is approximately less than 1.5 m from dry to wet period. It is also probably because there is abundances of groundwater resources in Yogyakarta City that shallow aquifer have very high hydraulic conductivity. The conversion speed from non-built-up area into built-up area is 26% from 2005 to 2015, while 8% from 2015 to 2020. At least 78% of Yogyakarta City is built-up areas in 2020. Abrupt changes in groundwater level is due to: a) declining trends of precipitation on May 2009 to July 2016 with average accumulative monthly residual rainfall ranging from 500 mm month−1 to 1300 mm month−1, and b) high magnitude earthquake occurrences on May 2006, November 2010 and 2015 when groundwater patterns and levels including discharge rivers showed distinct behavior. This study shows that precipitation and earthquake are the major contribution to groundwater level variation compared to land use.

Soil Salinity Inversion in Yellow River Delta by Regularized Extreme Learning Machine Based on ICOA

Soil salinization has seriously affected agricultural production and ecological balance in the Yellow River Delta region. Rapid and accurate monitoring of soil salinity has become an urgent need. Traditional machine learning models tend to fall into local optimal values during the learning process, which reduces their accuracy. This paper introduces Circle map to enhance the crayfish optimization algorithm (COA), which is then integrated with the regularized extreme learning machine (RELM) model, aiming to improve the accuracy of soil salinity content (SSC) inversion in the Yellow River Delta region. We employed Landsat5 TM remote sensing images and measured salinity data to develop spectral indices, such as the band index, salinity index, vegetation index, and comprehensive index, selecting the optimal modeling variable group through Pearson correlation analysis and variable projection importance analysis. The back propagation neural network (BPNN), RELM, and improved crayfish optimization algorithm–regularized extreme learning machine (ICOA-RELM) models were constructed using measured data and selected variable groups for SSC inversion. The results indicate that the ICOA-RELM model enhances the R2 value by an average of about 0.1 compared to other models, particularly those using groups of variables filtered by variable projection importance analysis as input variables, which showed the best inversion effect (test set R2 value of 0.75, MAE of 0.198, RMSE of 0.249). The SSC inversion results indicate a higher salinization degree in the coastal regions of the Yellow River Delta and a lower degree in the inland areas, with moderate saline soil and severe saline soil comprising 48.69% of the total area. These results are consistent with the actual sampling results, which verify the practicability of the model. This paper’s methods and findings introduce an innovative and practical tool for monitoring and managing salinized soils in the Yellow River Delta, offering significant theoretical and practical benefits.

An Investigation of the Impact of Spatiotemporal Changes of Land Use and Land Cover and Land Surface Temperature Using RS Techniques for Selected Cities in Sri Lanka

Changes in land use and land cover (LULC) have an impact on land surface temperature (LST) locally, regionally, and globally. This research focused on the spatiotemporal dynamics of LULC and LST between 2000 and 2021 at six selected meteorological stations, belonging to the different climatic zones of Sri Lanka. The LULC were classified from Landsat ETM+ and OLI/TIRS data using the maximum likelihood classification approach, while LST was retrieved using the thermal band of both Landsat images. Resultsreveal that the built-up areas have increased in all selected locations and bare land, vegetation cover, and agricultural land have all declined in the last 20 years. In Galle and Batticaloa areas, built-up areas have grown significantly by 11.9% and 11.14% respectively, by 2021. The thermal environment spatiotemporal alterations were consistent with the urbanization trend. Since many other land use types have been converted into urban areas, the average LST in Vavuniya, Anuradhapura, Batticaloa, and Galle has been rising steadily. This showed that increasing built-up area density has played a significant role in raising LST in the study areas. The vegetation cover, agricultural land, and water bodies showed the least LST change. By examining the correlation analysis between the Normalized Difference Vegetation Index (NDVI) and LST, a somewhat positive relationship was revealed only in the areas of Galle, Batticaloa, and Hambantota. Nevertheless, the findings of this study will serve as a helpful benchmark for future landscape and urban design initiatives aimed at reducing the detrimental effects of LST on urban sustainability.

Environmental risk analysis of a Ramsar site: a case study of east Kolkata wetlands with PSR framework.

The East Kolkata Wetlands (EKWT), designated as a Ramsar Site for its crucial role in sewage water purification, agriculture and pisciculture, faces escalating environmental threats due to rapid urbanisation. Employing the pressure-state-response (PSR) framework and Environmental Risk Assessment (ERA), this study spans three decades to elucidate the evolving dynamics of EKWT. Using Landsat TM and OLI images from 1991, 2001, 2011 and 2021, the research identifies key parameters within the PSR framework. Principal component analysis generates environmental risk maps, revealing a 46% increase in urbanisation, leading to reduced vegetation cover and altered land surface conditions. The spatial analysis, utilizing Getis-Ord Gi* statistics, pinpoints risk hotspots and coldspots in the EKWT region. Correlation analysis underscores a robust relationship between urbanisation, climatic response and environmental risk. Decadal ERA exposes a noteworthy surge in high-risk areas, indicating a deteriorating trend. Quantitative assessments pinpoint environmental risk hotspots, emphasizing the imperative for targeted conservation measures. The study establishes a direct correlation between environmental risk and air quality, underscoring the broader implications of EKWT's degradation. While acknowledging the East Kolkata administration's efforts, the research recognises its limitations and advocates a holistic, multidisciplinary approach for future investigations. Recommendations encompass the establishment of effective institutions, real-time monitoring, public engagement and robust anti-pollution measures. In offering quantitative insights, this study provides an evidence-based foundation for conservation strategies and sustainable management practices essential to safeguard the East Kolkata Wetlands.

Land Use Land Cover (LULC) Change Dynamics Associated with Mining Activities in Kitwe District and Adequacy of the Legal Framework on Mine Closure in Zambia

Land use land cover (LULC) changes resulting from copper exploration in Kitwe District, Copperbelt Province has adversely impacted the environment. To understand LULC change dynamics associated with mining activities, this study mapped LULC changes using the Google Earth Engine (GEE) from 1990 to 2020. In addition, the Zambian legal framework for mine closure was assessed in terms of adequacy and comprehensiveness. A remote sensing analysis using Landsat TM (1990, 2000, and 2010) and OLI (2020) images was performed and the GEE Random Forest classifier algorithm was employed to detect LULC changes. Then, transition matrices and overall changes were calculated for each LULC class. The LULC classification had an overall accuracy and kappa coefficient of 82.47% and 0.78, respectively. In total, 45.2% of the district area (360.92 km2) experienced LULC changes from 1990 to 2020. The overall change indicates that the areas of built-up area, bare land, and grassland/pasture/agricultural land gained 35.84, 14.67, and 43.53 km2, respectively, while forest lost 95.30 km2, with the major driver being the privatization of mining companies. Several concerns regarding the mine closure process practiced in Zambia have principally been raised to the government. Although the legislation generally conformed to international best practices, a gap involving various pieces of legislation, overlapping requirements, and different interpretations of the laws by different governmental departments makes the system complex and unmanageable. An area of concern is the government’s capability and competence to implement legislation. Ineffective law enforcement, that is, the inadequacy of the legislation, is to blame for LULC changes in mining areas, resulting in mining corporations not paying attention to the changes made, particularly regarding mine closures. This study provides decision-makers and land use planners with baseline knowledge on LULC changes that can be valuable for future mining legislation and how these legislations can be effectively executed to ensure sustainable mine closure.

Оценка состояния почвенно-растительного покрова бассейна реки на основе данных дистанционного зондирования

The aim of this work was to summarize the studies devoted to the soil and vegetation cover assessment of the river basin on the example of the Klyazma River catchment using remote data for a 17-year period. The remote data from the MODIS/Terra+Aqua Land Cover Land Cover, Landsat ETM+ and Meteor with different spatial resolutions were used in the work. The assessment of land use structure dynamics was carried out for the Klyazma River basin as a whole, as well as for individual landscapes. According to MODIS data there is a common trend towards an increase (about 9%) in the area of forest vegetation and a decrease in arable land and pastures for most of the basin. The exception is the interfluve of the Lukh River, where there is a decrease in forest lands and their transition to wetlands. Different landscapes of the Klyazma Rivers basin vary in both the rate and intensity of organic matter accumulation in the form of gross and net primary production as well as respond differently to climatic changes and land use change. However, the unified ecosystem of an entire river basin is more stable compared to its constituent landscapes. The remote sensing data allowed us to establish that the deep valley of the Rpen River (a tributary of the Klyazma River) forms an air flow that carries atmospheric pollution out of the Vladimir industrial zone.

Spatio-Temporal Analysis of Land Use/Land Cover Change and the Implications on Sustainable Development Goals in the Vea Catchment of Ghana

Globally, land use and land cover change (LULCC) is recognized as posing a substantial environmental challenge with lasting and severe consequences. This study quantified LULCC within the Vea catchment area spanning 24 years, from 1998 to 2022. Landsat TM imagery from 1998, ETM+ imagery from 2006, and Landsat 8 OLI imagery from 2014 to 2022 were used. A supervised classification algorithm was employed to classify the LULC classes. The findings reveal a notable transformation in the Vea catchment area from 1998 to 2022, primarily by converting grassland to cropland. Agricultural activities emerged as a significant contributor to the observed LULCC trend. Notably, cropland expanded from 10.9% to 51.98% between 1998 and 2022, while grassland and mixed vegetation/forest areas decreased from 54.8% to 18.14% and 31.7% to 22.73%, respectively. These results, it is argued, underscore the potential implications for achieving the targets set by the UN's Sustainable Development Goals.

Assessing lake shoreline change and prediction for 2030 by physical drivers: A Case Study from Lake Batur, Batur UNESCO Global Geopark, Bali

Over ten years, the water level of Lake Batur has increased. Agriculture area and settlements around Lake Batur are threatened by rising water level. This study aims to analyze the shoreline change of Lake Batur, located in the Batur UNESCO Global Geopark (BUGG), during the period of 2007 – 2018 and design a prediction for 2030. Understanding the shoreline change is very important for lake management and planning. Shoreline changes were analyzed in Geographic Information System (GIS) application. The data were obtained based on Remote Sensing (RS) data, Landsat ETM+ imagery on September 24, 2007, and Landsat OLI imagery on October 24th, 2018. Predictions of lake shoreline in 2030 result from modelling by integrating ASTER-GDEM V2 data, lake water level data for 2007–2018, annual average rainfall data for 2007–2018, and bathymetry data for 2013 and 2015. The results of the satellite imagery analysis show that there has been a change in the length of the shoreline, which has increased from 20.47 km in 2007 to 21.28 km (3.96%) in 2018. The lake surface area changed from 15.34 km2 in 2007 to 16.16 km2 in 2018 (5.35%). The prediction of lake shoreline changes in 2030 showed that Lake Batur will increase to 26.90 km (26.41%), and lake surface area is predicted to increase by 17.67 km2 (9.34%) from 2018. This is because of the morphological change of Lake Bottom.

Association mining of coastline change and land use patterns to enhance conservation

Coastal zones, as interfaces between marine and terrestrial ecosystems, possess great ecological and economic value but are environmentally fragile. This research provides a new perspective for studying development and change patterns in coastal zones, offering insights for land planning and contributing to the ecological preservation and sustainable development of coastal areas. We utilized Landsat TM and OLI sensor imagery (from the years 1990, 2000, 2010, and 2020) to extract coastline and land use information from the coastal zone of Shandong Province. Through the establishment of association mining models between coastline changes and land use patterns, the relationships between spatial layout changes and development processes in different geographical locations are revealed. In the initial stage, weak expansion and moderate changes in the coastline corresponded to units with lower land development intensity sequences. In the intermediate stage, with increasing coastline expansion and intense changes, the sequence of land development intensity was extremely strong > strong > moderate > weak from the sea to the land. This type of association was mostly distributed in the Laizhou Bay salt field and coastal port areas and was mostly focused on aquaculture and port trade, causing “strong” and “extremely strong” units of regional land development intensity. In the later stage, as coastline expansion slowed, the use of ports and docks caused the development intensity of the surrounding land to fluctuate. Farming, fishing, salt field and port construction in the coastal zone of Shandong Province were the major forms of land expansion and change. The association rules between coastline expansion or erosion and coastal development intensity revealed the impact of coastline changes on the spatial pattern from sea to land, which is important for planning layouts, optimizing industrial structures, and maximizing socioeconomic and environmental benefits in coastal areas.

Trends in Concentration and Flux of Total Suspended Matter in the Irrawaddy River

Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, based on the existing measured the total suspended matter flux (FTSM) and discharge data for the Irrawaddy River, an inversion model of the total suspended matter concentration (CTSM) is constructed for the Irrawaddy River, and the CTSM and FTSM from 1990 to 2020 are estimated using the L1 products of Landsat-8 OLI/TIRS and Landsat-5 TM. The results show that over the last 30 years, the FTSM of the Irrawaddy River decreased at a rate of 3.9 Mt/yr, which is significant at the 99% confidence interval. An increase in the vegetation density of the Irrawaddy Delta has increased the land conservation capacity of the region and reduced the inflow of land-based total suspended matter (TSM). The FTSM of the Irrawaddy River was estimated by fusing satellite data and data measured at hydrological stations. The research method employed in this paper provides a new supplement to the existing hydrological data for large rivers.

Study of The Impact of Coastline Changes on Coastal Settlement Areas Along th East Coast of Minahasa

The natural phenomenon of abrasion on the east coast of Minahasa which occurred from 1980 to 2020 has brought about changes in the coastline which then threatens the existence of coastal residential areas. Land function data in this study uses data sourced from the USGS (United States Geological Survey) Landsat-5 TM Imagery web and also Google Earth Pro Data, the data is in the form of historical image data with 10-year intervals and starting from 2003 to 2023. In 20 years there has been an increase in the area of built-up land for settlement functions in each village. The function of plantation land has been reduced in area as a result of settlement development. Meanwhile, sandy coastal land has also experienced a reduction in area as a result of sea waves and abrasion. The results showed that Atep Oki Village had experienced the farthest coastal setback of 42.28 m, while Kamenti Village and Parentek Village, respectively as far as 27.27 m and 23.33 m. These findings have confirmed the impact of waves that damaged the coast of Atep Oki village in 2013. It also shows that the abrasion process will be continue on the coast of Atep Oki village and its surroundings. The measured coastline setback distance is around 23 - 43 meters which causes a reduction in the area of residential land as well as damage to house buildings, road infrastructure and boundary embankments. Residents must move their residence to an area that is safer from the threat of waves and abrasion processes. Damaged house buildings especially those made of wood and plywood require repair costs while most residents have limited income as farmers, cultivators and fishermen. This condition causes the threat of loss of living environment and increased spending due to abrasion disaster adaptation efforts.

Spatio-temporal analysis of urban expansion using remote sensing data and GIS for the sustainable management of urban land: the case of Burayu, Ethiopia

PurposeThe purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.Design/methodology/approachLandsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.FindingsThe study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.Research limitations/implicationsAs a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.Practical implicationsData on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.Originality/valueThe use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

Changes in water surface area of the Middle Atlas-Morocco lakes: A response to climate and human effects

The lakes represent crucial surface water resources and an integral part of wetlands. The most concerning aspect of the degradation of these areas is the complete drying up of the lakes. In the Mediterranean region, successive changes in land use practices in the context of climate change have strongly influenced wetland areas. In this study, we used Landsat TM, OLI, and OLI-2 satellite images to monitor the water surface area in two representative lakes (Aoua and Ifrah) of the Tabular Middle Atlas and to map land use across the entire study area. To extract information related to lakes and land use, we employed the Support Vector Machine machine learning algorithm, widely used in remote sensing studies. However, we identified drought periods from precipitation data using the Standardized Precipitation Index (SPI) recommended by the World Meteorological Organization (WMO). The results obtained from the processing of Landsat satellite images indicate a significant reduction in the surface area of the lakes, with periods of drying for Aoua lake, endangering their fragile ecosystems and biodiversity. The critical situation of the two lakes is attributed to a combination of natural and anthropogenic factors. The analysis of climatic data shows a significant climate change from the 1980s, with long periods of drought. In parallel, the study area has undergone remarkable modifications in land use patterns, mainly characterized by a significant extension of irrigated agricultural surfaces to the detriment of grazing and rainfed lands. In three decades, the area of irrigated crops has increased from approximately 1300 hectares in 1985 to 7070 hectares in 2022, representing an increase of 542%. The findings presented in this study reveal the extent of lake degradation in the TMA and reflect the alarming decline in groundwater levels. This situation indicates the necessity of formulating a strategy to protect water resources and wetlands in the Middle Atlas.

Study on shoreline migration and island dynamics over the last five decades in the Muriganga River using multi-temporal satellite images.

The Muriganga River, also known as channel creek, underwent morphological changes often since it is an alluvial as well as a tidal river. The present study analyses the morphological changes in the Muriganga River and its islands with the help of the Remote Sensing and Geographical Information System (GIS) and digital shoreline analysis tool (DSAS 5.0). Moreover, the computation of morphological changes was also performed on two islands, i.e. Sagar and Ghoramara, which are situated just outside the river reach. Eight cloud-free satellite images of Landsat MSS (1972-1980), Landsat TM (1988-2011) and Landsat OLI (2017-2021) have been used to investigate the river shoreline shifting and island dynamics of the Muriganga River resulted from the erosion-accretion process during the last 49 years. For the short-term study, the erosion-accretion rates are derived from one Landsat image to the next, whereas for long-term analysis, the erosion-accretion rates are estimated based on the difference between 1972 as the reference image and the succeeding images. Short-term and long-term analysis shows that the average rate of erosion is more than that of accretion in Muriganga River. It is also found that the areas of Sagar, Ghoramara, Mousuni and Pushpa islands are shrinking continuously, whereas the Niogi and Basit islands are expanding enormously. These may indicate that the shoreline erosion results in widening the river and the eroded materials are accumulated in Niogi and Basit islands. The results suggest that there is an urge for a better coastal management strategy for the erosion control scheme. This study also helps in gaining knowledge of maintaining the navigability in the Muriganga River.

Spatial and temporal patterns of forest fires in the Central Monte: relationships with regional climate

BackgroundNatural and anthropogenic wildfires burn large areas of arid and semi-arid forests with significant socio-economic and environmental impacts. Fire regimes are controlled by climate, vegetation type, and anthropogenic factors such as ignition sources and human-induced disturbances. Projections of climate and land-use change suggest that these controlling factors will change, altering fire regimes in the near future. In the southern Central Monte, Mendoza, Argentina, the factors that modulate the fire temporal and spatial variability are poorly understood. We reconstructed the fire history of southeast of Mendoza from 1984 to 2023 and investigated the relationships between fire extent and climate variability at seasonal and interannual scales. Burned areas were determined using Google Earth Engine by processing Landsat 5-TM, Landsat 7-ETM+ , and Landsat 8-OLI-TIRS sensor imagery.ResultsThe region exhibited high spatial and temporal variability in fire occurrence, being a mosaic of areas with different fire histories and recovery times. Between 1985 and 2023, fire recurrence ranged from sites unburned to sites with up to 14 fires. The occurrence of large fires was strongly favored by a combination of a year with abundant spring–early summer precipitation, which favors fuel accumulation, followed by a year of low spring–early summer precipitation. Precipitation and burnt area showed a very pronounced 6–7 year cycle, suggesting a dominant climatic control on fire occurrence.ConclusionsFire distribution in southeastern Mendoza forests is not homogeneous, resulting in a mosaic of patches with different fire histories. This heterogeneity may be related to vegetation patterns and land use. The temporal variability of fires is strongly influenced by climate variability, which would promote fuel production and subsequent drying. Large fires are concentrated in periods of high interannual precipitation variability. Climate change scenarios predict an increase in temperature and precipitation variability in the region, suggesting future changes in fire dynamics. Our results contribute to the development of fire guidelines for southeastern Mendoza forests, focusing on periods of wet years followed by dry years that favor fire occurrence and spread.

Lineaments Characterization and their Tectonic Significance in Mineralization using Landsat TM Data and Field Studies along Mambilla Plateau, Northeast, Nigeria

Lineament characterization and their tectonic significance in mineralization using Landsat TM data and field studies Along the Mambilla Plateau and environs, northeast Nigeria .The area forms part of the mineralized shear zone of the Northeastern, part of the Basement Complex. The Basement Complex rocks underlie more than two-thirds of the plateau and date back to the Precambrian to early Paleozoic eras. While the remaining part of the plateau and its surroundings are made up of volcanic rocks of the upper Cenozoic to Tertiary and Quaternary ages. Remote sensing imagery data and field measurements were integrated for mapping the structural elements and hydrothermal alteration zones related to mineralization. Tectonically the lineaments trends NE-SW, NNW-SSE, NW-SE, and NS, are the main trends controlling mineralization in the area based on data from remote sensing and field measurements. On the other hand, applying band ratios and the constrained energy minimization (CEM) technique to Landsat-8 data pointed out alteration minerals associated with the hydrothermal fluids. Silica, sericite, and chlorite are the common alteration minerals detected, while goethite and epidote are less common in the alteration zones of the area under study. A combination of CET structural complexity, circular features, and alteration zones produced a potential mineralization map, pointing out numerous prospective zones for mineralization that are proximate to areas where artisanal mining activities are carried out. The predictive map was validated by projecting the known prospect zones in the study area, reflecting an agreement between the known occurrences and the higher classes of the predictive zone. The techniques in the current research can be adopted as a direct indicator for structural mapping and detecting alteration zones related to mineralization elsewhere.

Bi-Temporal Analysis of Vegetation Index on Land Surface Temperature in Kottayam, Kerala

The impact of NDVI (Normalized Difference Vegetation Index) on the LST (Land Surface Temperature) as well as on the genesis of surface heat islands in urban areas during two different time periods was assessed in Kottayam district, Kerala, India. Landsat TM, Landsat OLI and TIRS imagery from the years 1988 and 2020 were employed to scrutinize the relationship between NDVI and LST. The area covered under different NDVI classes were quantified. The finding indicated that NDVI of the research region decreased from 0.77 in 1988 to 0.59 in 2020, resulting in an increase in LSTmax from 34.46 °C in 1988 to 40.63 °C in 2020. Decrease in NDVI resulted in an increase in the high UHI class from 20.83 km2 in 1988 to 660.59 km2 and from 7.26 km2 to 181.35km2 in the very high UHI class. An inverse relationship was observed between NDVI and LST, with Pearson coefficients of 0.5737 and 0.5199 for 1988 and 2020, respectively, which indicates that NDVI could serve as a crucial metric for evaluating LST and UHI effects. Future research will explore the effect of seasonal variability in LULCC on LST, day and night time UHI and their impacts on human health and energy consumption.

Updating glacier inventories on the periphery of Antarctica and Greenland using multi-source data

Abstract Melting and calving of glaciers and ice caps in Antarctica and Greenland could potentially contribute significantly to global sea level rise. Updates to existing outlines that provide critical glacier baseline information in both regions could help in the analysis of particular changes in glacier parameters such as area and volume from time-series inventories. Here we synthesize previously established techniques and apply new multi-source datasets to update glacier outlines in selected test areas of Antarctica and Greenland, as well as to reduce uncertainties and errors during the mapping process. The workflow includes mapping glacier boundaries, subdividing glaciers by watersheds and assigning glacier attributes. Complicated glacier scenarios and updating challenges in polar regions are discussed and demonstrated by representative case studies. For the first time in Antarctica, we analyze the effect of terminus types on mapped glacier areas, and in Greenland we compare the differences with glacier mapping results using Landsat OLI and ETM+. With new data sources, the methods described in this study might help to create glacier outlines on a larger scale in Antarctica and Greenland. Although data sources can be substituted, the enormous amount of manual labor required to update glacier inventories remains a significant challenge.

Investigation and Identification of Govkhoni PLAIN using Sat Light Images (Land Sat ETM )

Investigation and Identification of Govkhoni PLAIN using Sat Light Images (Land Sat ETM )