TM Imagery Research Articles

Geo-Spatial Mapping of Land Use and Land Cover Changes in the Core and Periphery Area of Ranthambore Tiger Reserve, Rajasthan, India, 1975–2015

Abstract In the near future, natural resources are very rapidly diminishing all over the globe. Which is very unhealthy for land ecosystem services. In the biodiversity, Tiger is an icon of healthy wildlife which is considered as a vital factor for maintaining Universal Food Chain System. This research paper is based on “Geo-Spatial Mapping of land use and land cover changes in the Core and Periphery Area of Ranthambore Tiger Reserve, Rajasthan, India, 1975-2015, it’s a micro level Study based on primary and secondary data through GIS mapping and consider as a Socio-Economic & Physical factors to inter-connect with Tiger habitats. Especially, core and periphery LULC have been obtained from the Multispectral images from ETM and ETM+ sensors of Landsat and LISS-III and AWiFS sensors of Resourcesat-satellites. This study examines the spatial and temporal patterns of LULC change along the boundary of Ranthambhore in the Rajasthan from 1975 to 2015. Tiger Landscape change within all ecological zones will be evaluated. The Landsat TM and ETM imagery will be used to produce LULC classification maps for both areas using a hybrid supervised/unsupervised methods. LULC changes are measured using landscape metrics and change maps created by post-classification through change detection. Using all the raster maps and the final change detection of the reserve will be done through spatial analysis using the raster calculator tool in ArcGIS and Erdas and MS Excel 13. The study comes out with land use and land cover change in core and periphery areas of the reserve. The research also describes Human Encroachment, Impact on human colonization, interfere with domestic animals, Interbreeding, and the Migration in core and periphery areas, finally, the situation would be alarming for biodiversity of tiger habitat due to the high pressure of anthropogenic activities.

Dynamics and driving forces of main vegetation types in the Saihanba Nature Reserve, Hebei Province, China

To explore the changes of vegetation landscape pattern and its driving mechanism in Saihanba Nature Reserve, we analyzed vegetation type changes from 1989 to 2013 and the driving factors using random forest and Logistic regression models in conjunction with land dynamic degree indicator, based on three Landsat TM imageries obtained in 1989, 2000 and 2013. The results showed that the proportion of shrubland was always small in this area from 1989 to 2013. During 1989-2013, the proportion of shrubland rapidly decreased and plantation area significantly increased, while the area of grassland and natural secondary forest slightly changed. Key driving factors for the vegetation dynamics were dependent on vegetation type and time. The change of each vegetation type from 1989 to 2000 was significantly influenced by social factors, i.e. distance to road and total investment of afforestation. Since the implementation of the Natural Forest Protection Project and establishment of Saihanba Nature Reserve, the role of natural factors including elevation and aspect gradually became more important during the 2000-2013. The vegetation landscape dynamics were primarily determined by social activities, while the distribution patterns of vegetation types were probably controlled by natural factors in the study area.

On the possibility of using CORONA and Landsat data for evaluating and mapping long-term LULC: Case study of Iraqi Kurdistan

Modern land development is regarded as having begun in the 1960s and since then the pattern of land cover has changed considerably in many parts of the world. The majority of change detection studies have used Landsat MSS, TM, ETM+, and Landsat LDCM imagery and other satellite imagery to quantify and map land use changes for many parts of the globe from the early 1970s. In most applications however, (e.g., Balcik, Sanli, Goksel, Ulugtekin, & Dogru, 2009) land use changes dating back to the 60s are desirable. Given that most images start from the 70s, one possibility of overcoming this is to extend the timeline of change detection analysis beyond the first Landsat satellite imagery by cross-referencing with CORONA imagery to include the 1960s. The main objective of this study is to employ CORONA and Landsat images to perform change detection analysis using the Kurdistan region as a case study. Kurdistan region covers an area of 44957.1 km2 and the study period ranges from 1969 to 2014. The results of the maximum likelihood classification process for CORONA images show that these images may be classified successfully and accurately, showcasing the fact that the timeline of change detection analysis may be extended by using CORONA's unique historical images to include the period prior to the start of Landsat missions in 1972. For Kurdistan region, CORONA played a pivot role as baseline map as many of the changes occurred after 1974, when the Kurdish revolution ended. Its land use and land cover changes have been significant and may be divided into three stages: the first stage involves the destruction and demolition of the landscape between 1974 and 1991. The second stage is the stage of Kurdish freedom and peace involving minor changes in the landscape of the Kurdistan region that began in 1992 and lasted until 2002. Finally, the last stage is between late 2003 and the present date, period which, economic growth and population increase were the main factors influencing urban growth in the Kurdistan region. A positive non-linear relationship (R2 = 0.89) was found between population increase and urban growth using regression analysis for the study area during period 1969 to 2014. This case study therefore highlights the possibility of combining both CORONA and Landsat to study LULC change of any region prior to 1970s.

The impact of land use and land cover change on biodiversity within and adjacent to Kibasira Swamp in Kilombero Valley, Tanzania

AbstractWetlands are crucial ecosystems with multiple values and functions to a range of different stakeholders. The future of wetlands depends both on the legacy of the past and how they are currently used. Using 48 vegetation survey plots (0.08 ha) combined with Landsat 5 and 7 TM imagery, we assessed the influence of long‐term (1990–2011) land use and land cover change on the biodiversity of the Kibasira Swamp. Information on perceptions of adjacent communities on historical changes and drivers for the changes were also collected. Results showed an increase in the area covered by open water by 1% and forest by 4% between 1990 and 1998 whilst Cyperus papyrus L and cultivated land area decreased by 8% and 3%, respectively on the same period. Between 1998 and 2011, there was a decrease in areas covered by water by 35% and forest by 9% whereas C. papyrus L increased by 40% and cultivated land increased by 8%. These changes have affected the biodiversity of the swamp and adjacent to it as numbers of mammals have declined. However, the Swamp still provides extensive habitat for plants and bird species despite the ongoing human pressure. Interventions may be necessary to maintain biodiversity in Kibasira Swamp to ensure sustainable ecosystem services.

Assessment of Recent Glacier Changes and Its Controlling Factors from 1976 to 2011 in Baspa Basin, Western Himalaya

ABSTRACTHimalayan glaciers are normally difficult to monitor through field observations because of highly rugged and extremely inaccessible mountainous terrain. Thus, using Landsat data (MSS, ETM+ and TM), changes in glacier area, length, and debris cover have been delineated in the Baspa basin, which is a highly glacierized sub-basin of the Satluj River in the western Himalaya. Out of the total 109 glaciers inventoried through Landsat TM imagery (2011), 36 glaciers were found to be heavily debris covered (32.5 ± 2.0%). A shrinkage in glacier area of 41.2 ± 10.5 km2 (i.e., 18.1 ± 4.1%) at a rate of 1.18 ± 0.3 km2 a-1 from 1976 (227.4 ± 9.4 km2) to 2011 (186.2 ± 3.7 km2) has been recorded. The overall glacier retreat studied for 33 glaciers varied from 3.3 ± 0.03%, that is, 0.87 ± 0.06 km at a rate of 17.2 ± 1 m a-1 to 30 ± 6.6%, that is, 0.60 ± 0.04 km at a rate of 24.8 ± 0.2 m a-1. Consequently, the debris cover has increased by 23.5 ± 1.4 km2 (16.3 ± 3.8%) from 1976 to 2011. Overall, the clean, small sized, low-altitude glaciers with south to southwest aspect and relatively steep slope have lost maximum area, which indicated a major control of these factors on the glacier changes. Simultaneously, a trend estimation of observed climatic data (1976/1985–2008) of three meteorological stations (Sangla, Rakcham, and Chitkul) using Mann Kendall test, Sen’s Slope estimator and linear regression test revealed an increase in temperature and rainfall while a decline in snowfall. Importantly, the T min has increased significantly at 95% confidence level during all the studied periods. The mean annual T min and T max indicated a rising trend at a rate of 0.076 and 0.071 °C a-1. Thus, the changes in temperature and precipitation may be the major causes of accelerating the glacier ablation. The higher area changes (53.0 ± 0.4%), of small glaciers <0.5 km2 mark their sensitivity to climatic changes especially rising temperature. Under the warming climate, formation and progressive expansion of glacial lakes is expected because of the glacier recession in the basin. For instance, the Baspa Bamak Proglacial Lake at the snout of Baspa Bamak glacier has expanded continuously from 2000 onward.

Large‐scale regional delineation of riparian vegetation in the arid and semi‐arid Pilbara region, WA

AbstractMultiscene Landsat 5 TM imagery, Principal Component Analysis, and the Normalized Difference Vegetation Index were used to produce the first region‐scale map of riparian vegetation for the Pilbara (230,000 km2), Western Australia. Riparian vegetation is an environmentally important habitat in the arid and desert climate of the Pilbara. These habitats are supported by infrequent flow events and in some locations by groundwater discharge. Our analysis suggests that riparian vegetation covers less than 4% of the Pilbara region, whereas almost 10.5% of this area is composed of groundwater dependent vegetation (GDV). GDV is often associated with open water (river pools), providing refugia for a variety of species. GDV has an extremely high ecological value and are often important Indigenous sites. This paper demonstrates how Landsat data calibrated to Top of Atmosphere reflectance can be used to delineate riparian vegetation across 16 Landsat scenes and two Universal Transverse Mercator spatial zones. The proposed method is able to delineate riparian vegetation and GDV, without the need for Bidirectional Reflectance Distribution Function correction. Results were validated using ground truth data from local and regional scale vegetation surveys.

Land Cover Change in Northern Botswana: The Influence of Climate, Fire, and Elephants on Semi-Arid Savanna Woodlands

Complex couplings and feedback among climate, fire, and herbivory drive short- and long-term patterns of land cover change (LCC) in savanna ecosystems. However, understanding of spatial and temporal LCC patterns in these environments is limited, particularly for semi-arid regions transitional between arid and more mesic climates. Here, we use post-classification analysis of Landsat TM (1990), ETM+ (2003), and OLI (2013) satellite imagery to classify and assess net and gross LCC for the Chobe District, a 21,000 km2 area encompassing urban, peri-urban, rural, communally-managed (Chobe Enclave), and protected land (Chobe National Park, CNP, and six protected forest reserves). We then evaluate spatiotemporal patterns of LCC in relation to precipitation, fire detections (MCD14M, 2001–2013) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and dry season elephant (Loxodonta africana) aerial survey data (2003, 2006, 2012, 2013). Woodland cover declined over the study period by 1514 km2 (16.2% of initial class total), accompanied by expansion of shrubland (1305 km2, 15.7%) and grassland (265 km2, 20.3%). Net LCC differed importantly in protected areas, with higher woodland losses observed in forest reserves compared to the CNP. Loss of woodland was also higher in communally-managed land for the study period, despite gains from 2003–2013. Gross (class) changes were characterized by extensive exchange between woodland and shrubland during both time steps, and a large expansion of shrubland into grassland and bare ground from 2003–2013. MODIS active fire detections were highly variable from year to year and among the different protected areas, ranging from 1.8 fires*year−1/km2 in the Chobe Forest Reserve to 7.1 fires*year−1/km2 in the Kasane Forest Reserve Extension. Clustering and timing of dry season fires suggests that ignitions were predominately from anthropogenic sources. Annual fire count was significantly related to total annual rainfall (p = 0.009, adj. R2 = 0.50), with a 41% increase in average fire occurrence in years when rainfall exceeded long-term mean annual precipitation (MAP). Loss of woodland was significantly associated with fire in locations experiencing 15 or more ignitions during the period 2001–2013 (p = 0.024). Although elephant-mediated damage is often cited as a major cause of woodland degradation in northern Botswana, we observed little evidence of unsustainable pressure on woodlands from growing elephant populations. Our data indicate broad-scale LCC processes in semi-arid savannas in Southern Africa are strongly coupled to environmental and anthropogenic forcings. Increased seasonal variability is likely to have important effects on the distribution of savanna plant communities due to climate-fire feedbacks. Long-term monitoring of LCC in these ecosystems is essential to improving land use planning and management strategies that protect biodiversity, as well as traditional cultures and livelihoods under future climate change scenarios for Southern Africa.

Prairie or planted? Using time-series NDVI to determine grassland characteristics in Montana

Temperate grasslands are a highly threatened global biome. Complicating management and conservation strategy development, modern grasslands can be difficult to characterize across landscapes since they range from native and semi-native to completely non-native species compositions such as those found in heavily managed pastures. Similar to methods used to differentiate C3 and C4 grasses, we investigate the ability of using temporal variations in growth characteristics as an alternative pathway to predicting native versus introduced species composition across grassland landscapes. To do this, we conducted an exploratory analysis using a time-series of Normalized Difference Vegetation Index values as a measure of vegetation greenness with Landsat 5 TM imagery across a growing season and performed an unsupervised classification. Results from the classification were compared with field observation to determine if we can differentiate between native and introduced grassland types in the Northwest Glaciated Plains subecoregion of northeastern Montana. Our results indicated that we predicted grassland cover with 81% accuracy within our 200 km2 study area and 71% accuracy in our 5000 km2 secondary study area. Further extrapolation of our methodology, combined with the refinement of vegetation indices of time-series imagery, classification algorithms and the availability of data from planned Landsat and Sentinel missions, may provide the spatial detail necessary to improve grassland monitoring and rangeland management over large areas.

English

This study makes use of Markov chains modeling to predict sprawl and pattern of land use change in Akure region. Efforts were made to examine the trend of the expansion using Aerial Imagery Interpolation (AII). It focuses on overlaying of Landsat TM imageries of 1986, 2002, 2007 and 2014 to determine the land use changes and extent of expansion between 1985 and 2014. The land use were classified and displayed in colors for better visualization. With the aid of Markov chain modeling, the study made a projection of possible land use area and extent of expansion by the year 2034. Findings revealed continuous expansion in the growth of the city as evident in percentage increase of the built-up area. There were incompatible conversions in land uses and unguided expansions leading to undue encroachment into green areas at the suburbs. It was observed that without appropriate attention to adequate planning for effective measures, the trend of changing agricultural and forested lands to built-up areas will continue to increase with attendant effects on regional environment. Consequently, the study suggests effective zoning strategy and sustainable monitoring measures by different stakeholders in urban planning to check indiscriminate urban expansion in the study area. Key words: Urban sprawl, land-use pattern, markov chains, landsat TM imageries, Aerial Imagery Interpolation (AII).

Spatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements

We conducted spatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements. We showed that multitemporal TM data has the potential of rapidly estimating urban vegetation structural attributes including LAI, CC , and BA at an urban landscape level. Urban vegetation structural properties/attributes are closely linked to their ecological functions and thus directly affect urban ecosystem process such as energy, water, and gas exchange. Understanding spatiotemporal dynamics of urban vegetation structures is important for sustaining urban ecosystem service and improving the urban environment. The purposes of this study were to evaluate the potential of estimating urban vegetation structural attributes from multitemporal Landsat TM imagery and to analyze spatiotemporal changes of the urban structural attributes. We first collected three scenes of TM images acquired in 1997, 2004, and 2010 and conducted a field survey to collect urban vegetation structural data (including crown closure (CC), tree height (H), leaf area index (LAI), basal area (BA), stem density (SD), diameter at breast height (DBH), etc.). We then calculated and normalized NDVI maps from the multitemporal TM images. Finally, spatiotemporal urban vegetation structural maps were created using NDVI-based urban vegetation structure predictive models. The results show that NDVI can be used as a predictor for some selected urban vegetation structural attributes (i.e., CC, LAI, and BA), but not for the other attributes (i.e., H, SD, and DBH) that are well predicted by NDVI in natural vegetation. The results also indicate that urban vegetation structural attributes (i.e., CC, LAI, and BA) in the study area decreased sharply from 1997 to 2004 but increased slightly from 2004 to 2010. The CC, LAI, and BA class distributions were all skewed toward low values in 1997 and 2004. Moreover, LAI, CC, and BA of urban vegetation all present a decreasing trend from suburban areas to urban central areas. The experimental results demonstrate that Landsat TM imagery could provide a fast and cost-effective method to obtain a spatiotemporal 30-m resolution urban vegetation structural dataset (including CC, LAI, and BA).

Land‐Use and Land‐Cover Change in the Páramo of South‐Central Ecuador, 1979–2014

Land use and land cover were mapped between 3500 and 5000 meters above sea level m.a.s.l. in the Río Chambo basin in south-central Ecuador from Landsat MSS, TM, ETM and OLI imagery acquired between 1979 and 2014. The area mapped has been dominated by páramo and a variety of agricultural land uses since 1979. The main land-use transitions have been from páramo to agriculture, native forest to páramo and agriculture, and agriculture back to páramo. Significant areas of páramo have remained unchanged over the 35-year period analyzed, while the area of native forest has declined and that of bare soil increased. Plantations of non-native timber species increased from 1979 to 1999, but their area has now declined. Most land-use transformations have occurred at lower elevations in the 3500–5000 m.a.s.l. range. This is particularly the case for the loss of native forest and the degradation of páramo and agriculture to areas of bare (eroded) soils. A drivers-based approach revealed that these land-use transformations were related to import substitution and afforestation policies geared toward internal markets, exports and environmental conservation.

A weighted normalized difference water index for water extraction using Landsat imagery

ABSTRACTWater extraction is one of challenging topics in studies on remote-sensing applications. Spectral profiles and experiments indicate that existing water indices often misclassified turbid water, small waterbodies, and some land features in a shadow area. In this study, a new water index called weighted normalized difference water index (WNDWI) was proposed to reduce those errors and improve the mapping accuracy of waterbodies by using Landsat imagery. To test the performance of the newly proposed water index, two test sites (Tampa Bay, FL, USA and Xiangshan Harbour, Zhejiang, China) were selected and the performances of three existing water indices including the normalized difference water index (NDWI), the modified NDWI (MNDWI), and the automated water extraction index (AWEI) were compared with that of the WNDWI. In addition, a default threshold 0 and automatically thresholding methods including Otsu threshold method and multiple thresholds identified by valley points in a histogram curve were tested to determine an optimal threshold that can be used to separate water and non-water features from grey images created by the four water indices. The experimental results indicate that the overall accuracies (OAs) created with WNDWI were all higher than those created with the three existing water indices: NDWI, MNDWI, and AWEI in both sites. Moreover, the results thresholded by 0 owned or shared the highest OAs with the results segmented by some of non-zero thresholds obtained from Otsu method and multiple thresholds method. Therefore, using an appropriate threshold, the proposed method could extract waterbodies from Landsat TM imagery with a high accuracy.

An alternative method for estimating total impervious area in catchments using high-resolution colour aerial photography

Estimation of total impervious area (TIA) is a pre-requisite for ecohydrological research to allow for a direct prediction on stream ecosystem health within catchments. This paper presents an alternative to using multi-spectral imagery for estimating TIA at a catchment scale, by using high-resolution colour aerial photography. The method was applied to a number of catchments in South East Queensland, Australia, some of which were gauged and some of which were part of an Ecosystem Health Monitoring Program (EHMP). The results from this method were compared to TIA estimates, for some of the same catchments, that were derived through three other techniques, i.e. manual digitization of geo-referenced aerial photos, Brisbane City Council data derived from image analysis using Landsat TM imagery and rainfall runoff depth relationship. The high-resolution colour aerial photography method compared favourably to the other techniques with standard deviations of TIA (%) ranging between 0.8% and 8%. The major constraints were shading effects, particularly on roads and grassed areas, and from the similarity in colours between some surface types, some of which can be reduced by appropriate selection of signature colours and multiple iterations of a supervised classification. It was concluded that while infra-red spectral wave bands could help considerably, the high-resolution colour photography could be applied with confidence to derive catchment-scale TIA estimates.

APPLICATION OF VAN HENGEL AND SPITZER ALGORITHM FOR INFORMATION ON BATHYMETRY EXTRACTION USING LANDSAT DATA

Remote sensing technology provides an opportunity for effective and efficient bathymetry mapping, especially in areas which level of depth changes quickly. Bathymetry information is very useful for hydrographic and shipping safety. Landsat medium resolution satellite imagery can be used for the extraction of bathymetry information. This study aims to extract information from the Landsat bathymetry by using Van Hengel and Spitzer rotation algorithm transformation (1991) in the water of Menjangan Island, Bali. This study shows that Van Hengel and Spitzer rotation algorithm transformation (1991) can be used to extract information on the bathymetry of Menjangan Island. Extraction of bathymetric information generated from Landsat TM imagery data in March 19, 1997 had shown the depth interval of (-0.6) m to (-12.3) m and R2 value of 0.671. While Data LANDSAT ETM + dated June 23, 2000 resulted in depth interval of 0 m to (-19.1) m and R2 value of 0.796. Furthermore, data LANDSAT ETM + dated March 12, 2003 resulted in depth interval of 0 m to (-22.5) m and R2 value of 0.931.

Influence of different geographical factors on carbon sink functions in the Pearl River Delta

This study analyzed carbon fixation across different land use types in the Pearl River Delta to identify the influence of different geographical factors on carbon fixation ability. The methodology was based on interpreting land use data from TM imagery, MODIS13Q1 data, and climate data, using the improved CASA and GeogDetector models. The results show that: (1) From 2000 to 2013, the total carbon sink increased slightly, from 15.58 × 106 t to 17.52 × 106 t, being spatially low at the center and increasing outwards; (2) Proxy variables (topography and landform characteristics), influencing urbanization, significantly affect the carbon sink function of the Pearl River Delta region. The proportion of urban and other construction land showed increasing effect on the regional carbon sink each year. However, the spatial structure of land in the study area changed from complex to simple, with enhanced stability; consequently, the influence of landscape characteristics (landscape dominance and landscape perimeter area fractal dimension) on the regional carbon sink gradually decreased; (3) The influence of the same factors differed with different land use types. Slope and altitude were found to have the greatest influence on the carbon sink of cultivated land, while landscape perimeter area fractal dimension more significantly affected the forest carbon sink.

Identifying peri-urban growth in small and medium towns using GIS and remote sensing technique: A case study of English Bazar Urban Agglomeration, West Bengal, India

Land in the peri-urban interface is of vital importance as there is a lack of clarity in the planning and policies in this region whether they should be governed under the authority of rural administration. In general, these areas are frequently ignored as a specific area in the study of urbanization being neither pure urban nor pure rural. In this regard, an attempt has been taken to detect the spatio-temporal dynamics of sprawl, the nature of land transformation taken place in the identified peripheral settlements with high probability of urban development within the buffer zone of 2.5km around the boundaries of the two major urban bodies of Malda i.e. English Bazar municipality an Old Malda municipality. The secondary data of Census of India of 2011and Landsat TM imageries (1987, 2003, 2011 and 2015) have been employed to detect the evolutionary process with the view to capture the urban land-use growth by Land Use–Land Cover classification. The result shows that the built-up area has increased around 30% over the course of 28years span. Computations of Shannon’s Entropy, Urbanisation intensity index, built-up density have helped to explore the degree of transition taking place in each spatial unit under investigation. The spatial metrics with the gradient approach has revealed that beyond the buffer of 7km from the city centre the increase of residential land uses is maximum which is characterised by a fragmented pattern with nearest entropy value to log N. The suitability analysis in search of most prospective future urban centre suggests the maximum distribution of urban units in the western front of the ULBs.

Impact of Land Use/Land Cover Change on Surface Temperature Condition of Awka Town, Nigeria

This paper is aimed at identifying the land use/cover types in Awka in relation to their temporal dynamics, the extent of land use change in the city and effects of land use change on surface temperature. Multitemporal Landsat TM, ETM+ and OLI imageries were obtained at 15 years interval for 1986, 2000 and 2015 respectively. Image classification was conducted using supervised classification method. The result showed that built-up area has been on the increase, expanding from 9.55 sqkm in 1986 to 21.3 sqkm in 2000 and 21.45 sqkm in 2015. Cultivated lands have maintained a steady decline since 2000 having lost about 3.29 sqkm of its area. Similarly, vegetation, made up of dense, savanna and riparian, has been on a decline from a total of 33.69sqkm in 1986 to 21.407 sqkm losing about 12.29 sqkm of its area and increased by a mere 4.07 sqkm in 2015. These alterations had given rise to an average increase of 2.2°C in surface radiant temperature. This study recommends that relevant government planning agencies (ACTDA, ASHDC, etc.) should factor in the concept of greening and green spaces into their development policies and strategies to ensure that fair, conducive microclimate and sustainable environment is maintained in the Awka urban area.

Vibrational Spectroscopic Investigation on Bisthiourea Magnesium Sulphate (BTMS) Using Experimental and Computational [HF and DFT] Analysis

This paper quantifies the changes and present status of mangrove forest in Indian part of Sundarban from 1975 to 2014 using Landsat MSS (1975), TM (1990), ETM (2002) and OLM (2014) satellite imageries. The study used two image processing techniques: Maximum Likelihood Classification for the Land use and land cover analysis and NDVI for the vegetation characteristics and their temporal changes. The research found that the area of mangrove gradually decreases from 203752 hector (44%) to 132723 hector (31 %) and the barren land increases from 15078 hector (2.86 %) to 37247 hector (7.12%) due to natural ( sea level rise, salinization etc.) and anthropogenic (livelihood collection and shrimp farming etc.) disturbances and continuous land reclamation. Other land use categories like agriculture, water body, and sand deposition have approximately remained constant. The NDVI values were changed significantly only in 1990 due to the landward migration and defragmentation of mangrove forest. However, the paper signifies that the forest cover is constantly evolving due to deforestation, aggradation, erosion and forest rehabilitation programs in the Indian Sundarban.

Chapter 22 Remote sensing and GIS studies of alteration and predictive mineral exploration in the Central Volcanic Arc, Myanmar

The objective of this study is to identify alteration associated with ore deposits for predictive mineral exploration in the Central Volcanic Arc Belt (CVAB) of Myanmar (Figs 22.1 & 22.2). Modern techniques such as remote sensing (RS) and geographical information systems (GIS) were used to delineate structural lineaments and the hydrothermal alteration of the ore deposits. Landsat TM imagery and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are now used more routinely for mineral exploration and shortwave infrared (SWIR) channels can be applied to detect associated altered mineral assemblages. Landsat and ASTER data are also applied to map iron oxides, structure and alteration minerals, and predict zones of mineralization potential as well as recognize different lithologies. This method is applicable to other mineralized areas in Myanmar where the potential is currently unknown. Fig. 22.1. Map showing regional tectonic setting of Central Volcanic Arc Belt (CVAB), Myanmar. Fig. 22.2. Map showing detailed mineral occurrences in the Monywa and Kawlin–Wuntho areas along the CVAB, Myanmar. The Department of Geological Survey and Mineral Exploration (DGSE), Ministry of Natural Resources and Environmental Conservation, Myanmar is carrying out geological mapping and mineral prospecting in remote areas of Myanmar where it is not possible to cover large areas in a short period of time. Geological mapping and mineral exploration are required in mountainous terrains in the remote border regions of Myanmar. The use of modern techniques such as RS and GIS for geological survey is necessary in order to complete geological mapping of the whole country. Analysing and processing satellite imagery provide fast and effective methods for achieving this goal. Exploration geologists are engaged not only in the search for new mineral deposits, but also in the reassessment of existing deposits in order to identify the extent of ore bodies and mineralized zones. In its broadest sense, hydrothermal activity …

Mapping erosion and deposition changes in the protected wetlands of the Axios River Delta, N. Greece using remote sensing and GIS.

Our study explores the use of a range of image processing methods combined with Landsat TM imagery for mapping the morphodynamics of the delta of the Axios River, one of the largest rivers of Greece, between 1984 and 2009. The techniques evaluated ranged from the traditional spectral bands arithmetic operations to unsupervised and supervised classification method. Changes in coastline morphology and erosion and deposition magnitudes were also estimated from direct photo-interpretation of the TM images, forming our reference dataset. Our analysis, conducted in a GIS environment, showed noticeable changes in the coastline of the study area, with erosion occurring mostly in the early periods followed by deposition later on. In addition, relatively similar patterns of coastline change were obtained from the different approaches, albeit of different magnitude. The differences observed were largely attributed to the varying ability of the different approaches to utilise the spectral information content of the TM data, strongly linked to the relative strengths and weaknesses underlying the implementation of the different techniques. Notably, supervised classifiers based on machine learning showed the closest results to the photo interpretation of TM, evidencing a promising potential for monitoring shoreline changes over long timescales in a cost-effective and rapid manner.