Global Land Cover Facility Research Articles

Use of GIS and RS Tools for Analysis of Land Use Land Cover and Land Surface Temperature: A Case Study of District Khairpur, Pakistan

Land use and land cover (LULC) monitoring plays an important role in sustainable planning and management of resources. This research focuses on analysing historical LULC changes over the Khairpur district of Sindh province of Pakistan. Remote Sensing and Geographic Information System (RS & GIS) tools have been employed using the maximum likelihood algorithm of the supervised classification method. Temporal data of the latest high-resolution satellite imagery provided by NASA GLCF (Global Land Cover Facility), Landsat 8 Operational Land Imager (OLI), and Landsat 4, 5 Thematic Mapper (TM) for 2001, 2010, 2015, and 2020 were acquired from Earth Explorer of United States Geological Survey (USGS). The study area is classified into four major classes namely Barren Land, Vegetation, Built-up areas, and Water Bodies. Analysis revealed that for 2001 and 2005 there was no change in barren land area, whereas in 2010 slight decrease in barren land was found which further decreased for the analysis period of 2020, overall barren land class decreased at a rate of 07% (i.e., 74% to 67%) during the analysis period. Also, vegetation and water bodies classes experienced variations throughout the analysis period, however built-up areas showed constant increase throughout the analysis period where built-up area classes increased from 9% to 15%. Whereas land surface temperature (LST) throughout the analysis period showed increasing trends, for both high ranges and low ranges. It was analysed that the areas having dominancy of the barren land class experienced the highest temperature ranges whereas low temperature ranges were discernible in the areas having vegetation covers. It can be concluded from the study that barren land covers the major area of the study area and there is an increase in built-up areas which can further enhance the LST in the study area.

Potential Impacts of Flooding on Alluvial Gold Mining Activities in Parts of Ilesha-Egbe Gold Field, Osun State, Nigeria.

The study mapped mining communities in parts of Ilesha-Egbe gold field in Osun State, South-West (SW) Nigeria, with their respective mining sites, their elevation above sea level and the average depth of mining pits in meters. This was done with a view to determining the potential impacts of flooding on mining activities in these areas. Geological map from Nigeria Geological Survey Agency (NGSA), Advanced Space borne Thermal Emission and Reflection Radiometer- Global Digital Elevation Model (ASTER-GDEM) from Global Land Cover Facility (GLCF) and topographic map from Office of the Surveyor General of the Federation (OSGOF) in Nigeria were used for this study. Geology and topographic maps were interpreted for drainage channels and rivers. These and other information were incorporated in mapping and interpreting the mine localities with their respective characteristics. ASTER-DEM was used to generate elevation information like DEM and slope. Stream ordering was done for the digitized drainages and buffering analysis was done for the respective mining points to determine how the mines will be affected in the event of a flood. Results indicate that the study area is well drained with abundant alluvial gold deposit with mines lying on drainage channel. In the events of flood, mine pit will be filled or partially filled with water and areas with pay-streaks easily flooded. Water runs down slope rather than infiltrates and run-off causes flooding at the lower courses of the water body and this provides for gold dust recharge downstream, opening up new gold exploitation areas.

Space-based Mapping and Assessment of a Three-decade Urban Landcover Dynamics towards a Smart Federal Capital City, Abuja, Nigeria

A general notion from majority of researchers noted that connecting rural-urban services with Information Technology (IT), Internet of Things (IoT), Information Communication Technology (ICT) and Artificial Intelligence (AI) is making cities smarter. This is because, the global urban population is expected to grow by 63% between 2014 and 2050 – compared to an overall global population growth of 32% during the same period. The Federal Capital City (FCC), Abuja, Nigeria is no exception to urban population growth which requires IT, IoT, ICT and AI technologies if she must be regarded as a Smart City. This study was, therefore, aimed at mapping and assessing a three-decade urban dynamics of the FCC, Abuja, towards ascertaining the suitability of the FCC, Abuja being regarded as a Smart City. Three (3) epochs of Landsat ETM+ data from the US Global Land Cover Facility web platform was analyzed using the maximum likelihood algorithm to process the Remote Sensing images for thirty (30) years time period (2000, 2010, and 2020). The study shows that the urban builtup land cover increased significantly from 72.88 km2 (22.04%) in year 2000 to 145.77km2 (44.09%) in 2020. As the causative alteration of natural vegetation paved the way for urban infrastructure, the study re-affirms a corresponding effects on the decrease in light vegetation cover from 119.85km2 (36.25%) in 2000, to 29.24km2 (8.84%) in 2010, and down to as low as 13.49km2 (4.08%) in 2020. Other land covers also decreased due to population upsurge and physical urban developments. The findings confirm the suitability of the FCC, Abuja as an emerging Smart City as the study further revealed a number of efforts made to digitalized government services through e-governance. The total (overall) accuracy of the supervised classifications of LULC for 2000, 2010, and 2020 images were 97.3%, 99.2% and 99% respectively with corresponding strong positive Kappa statistics of 0.95, 0.99 and 0.97. It is recommended that Smart City initiatives anchored on digital hub tools such as IoT, AI and ICT; Remote Sensing; and GIS Technologies be deployed in the ongoing and future city-wide development initiatives in order to fast track smart, smooth, effective and efficient service delivery in the FCC, Abuja, Nigeria.

ASSESSING FOREST AND AGRICULTRAL LAND UNDER LAND USE CHANGE USING REMOTE SENSING: A CASE STUDY OF BAHAWALPUR CITY (PAKISTAN)


 
 
 Rapid urbanization and development build a great pressure on the agricultural land in urban and semi-urban areas. As a result, there is reduction in agricultural and forest areas in different cities of the developing countries. The present study was conducted in Bahawalpur district of Pakistan. Six remote sensing satellite images of Landsat Enhanced Thermal Mapper and ETM+ were obtained from Global Land Cover Facility of United States Geological Survey’s Earth Explorer and GLOVISE with an interval of three years from 2003 to 2018 (16 years) were processed for the study area (Bahawalpur City). Major land use classes identified for this study included forest, agriculture, barren and urban. Temporal changes of the four land use classes were detected and its impact on covered area by each land use class over the study period was computed. Results indicated that acreage of forest and barren land was decreased by 89.3% and 57.6%, respectively, while that of agriculture and urban area was increased by 34.5% and 45.5%, respectively, over the period of sixteen years from 2003 to 2018. These changes in land use cover might be owing to urbanization, deforestation and land conversion in the study area.
 
 

Assessment of Urban Sprawl in Sargodha City using Remotely Sense Data

The current study focuses on tracking urban sprawl in one of the rapidly growing cities of Pakistan i.e., Sargodha. The secondary cities have the capacity to persuade people from rural areas to relocate. In this regard, the current study is unique in that it will give a comprehensive analysis of urban sprawl of Sargodha City. The remotely sensed data is used for this purpose. The study is primarily based on the collecting of both primary and secondary data. For the last 30 years, from 1987 to 2017, primary data was gathered from the United States Geological Survey (USGS) and the Global Land Cover Facility (GLCF). ERDAS Imagine 2013 is used to classify land use using remotely sensed data. The Kappa Coefficient was used to compute the accuracy assessment of classified maps. Maps are used to depict a comparative analysis of urban sprawl in the city. In addition, regression analysis and simple statistical computations are also utilised to assess dynamic changes in urban sprawl. From 1987 to 2017, a 10-year interval was used to measure change in built-up land using an equation. According to the findings of the study, Sargodha City has experienced considerable changes in land use patterns. This current study is beneficial for policymakers to design the city in a well-planned manner. The appropriate design of cities can pave the way for higher living standards in rapidly growing cities of Pakistan.

Spatial Expansion and Population Growth Analysis of Ogbomoso Metropolis to Forestall Overwhelming Available Infrastructures

The requirement of land for an array of uses as population grows and cities open up to further development is at an astronomical rate. This has resulted in effort to convert areas covered by water bodies into dry land. This notwithstanding, land has remain a relatively fixed asset which cannot be massively expanded by any means, but its utilization can be managed to ensure its sustainability. Most human activities are land based hence how land is used have a ripple effect on most aspects of our lives and the environment. The way and manner land is being used relative to population growth of an area must be monitored to avoid environmental degradation. This research attempts an analysis of the Land Use and Land Cover (LULC) changes of Ogbomoso metropolis between the years 1985 and 2015 and makes projections for the next 30years at regular interval of 10years. Secondary data obtained through Remote Sensing were adopted for the research. Landsat imageries TM 1985, 1995 and ETM+ imageries of 2005 and 2015 were downloaded from the Global Land Cover Facility (GLCF) while Remote Sensing techniques was adopted for data processing and analysis. Population data obtained for the study area from the National Population Commission (NPC) were used for the population projection. Land Consumption Rate and Land Absorption Coefficient were introduced to aid in the quantitative assessment of the change. Analysis of the results showed the alarming rate of growth in built-up area between the periods considered and suitable recommendations was made on measures to properly manage such growth.

ASSESSMENT OF AFFORESTATION PROGRAMME AND COMMUNITY PERCEPTION IN GUMEL LOCAL GOVERNMENT AREA, JIGAWA STATE

This study assessed afforestation programme and community perception in Gumel Local Government area of Jigawa state. Field data collection was done using structured questionnaire and Landsat satellite imageries. A total of two hundred (200) questionnaire were distributed to the 200 sample size drawn from the sample area using a multi-stage sampling design technique. In a similar way, Landsat data were collected for a period of thirty (30) years using Landsat TM for 1988 and 1998 with Landsat ETM for 2008 and landsat-8 operational land imager (OLI) for 2018 using Earthexplorer. A 30m by 30m resolution Landsat image of the study area was obtained from NASA website. The images were downloaded from the Global Land Cover Facility of the University of Maryland (GLCF, 2018) and the United States Geological Survey (USGS) and spatially referenced in the Universal Transverse Mercator (UTM) projection with datum World Geodetic System (WGS). The images were extracted to Tiff formats for processing and classification using maximum likelihood classifier in Idrisi Selva. The collected data were subjected to analysis such as mean, simple percentage, graphs and tables. Results shows that between the year 1988 to 2018, afforestation in Gumel Local Government Area of Jigawa State increases significantly due to the success of the afforestation programme. It was however recommended that Government agencies in charge of forestry activity are thereby encouraged to put up measures in ensuring the avoidance of forest encroachment activities so as to ensure abundance trees and land covers.

Regional Sampling of Forest Canopy Covers Using UAV Visible Stereoscopic Imagery for Assessment of Satellite-Based Products in Northeast China

Canopy cover is an important parameter affecting forest succession, carbon fluxes, and wildlife habitats. Several global maps with different spatial resolutions have been produced based on satellite images, but facing the deficiency of reliable references for accuracy assessments. The rapid development of unmanned aerial vehicle (UAV) equipped with consumer-grade camera enables the acquisition of high-resolution images at low cost, which provides the research community a promising tool to collect reference data. However, it is still a challenge to distinguish tree crowns and understory green vegetation based on the UAV-based true color images (RGB) due to the limited spectral information. In addition, the canopy height model (CHM) derived from photogrammetric point clouds has also been used to identify tree crowns but limited by the unavailability of understory terrain elevations. This study proposed a simple method to distinguish tree crowns and understories based on UAV visible images, which was referred to as BAMOS for convenience. The central idea of the BAMOS was the synergy of spectral information from digital orthophoto map (DOM) and structural information from digital surface model (DSM). Samples of canopy covers were produced by applying the BAMOS method on the UAV images collected at 77 sites with a size of about 1.0 km 2 across Daxing’anling forested area in northeast of China. Results showed that canopy cover extracted by the BAMOS method was highly correlated to visually interpreted ones with correlation coefficient ( r ) of 0.96 and root mean square error (RMSE) of 5.7%. Then, the UAV-based canopy covers served as references for assessment of satellite-based maps, including MOD44B Version 6 Vegetation Continuous Fields (MODIS VCF), maps developed by the Global Land Cover Facility (GLCF) and by the Global Land Analysis and Discovery laboratory (GLAD). Results showed that both GLAD and GLCF canopy covers could capture the dominant spatial patterns, but GLAD canopy cover tended to miss scattered trees in highly heterogeneous areas, and GLCF failed to capture non-tree areas. Most important of all, obvious underestimations with RMSE about 20% were easily observed in all satellite-based maps, although the temporal inconsistency with references might have some contributions.

Assessment of Land Use/Cover Change Using Remote Sensing and GIS Techniques: A Case of Osogbo and Its Peripheral Areas in Nigeria

The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing city areas. Landsat satellite imageries of three different time periods, i.e., Landsat Thematic Mapper (TM) of 1982, 2000 and 2018 were acquired by Global Land Cover Facility Site (GLCF) and earth explorer site, quantify the changes in the Osogbo and its peripheral areas from 1982 to 2018 over a period of 36 years. These data sets were imported in ArcGIS 10.3, ERDAS Imagine and IDRIS Selva, satellite image processing softwares to create a false colour composite (FCC), supervised classification methodology was employed using maximum likelihood technique. The images of the study area were categorized into four different classes namely Core-urban, Peri-urban, Vegetation, water body. The results indicate that during the last thirty-six (36) years, Core-Urban land and water body have been increased by 2.74% (38.20 km2) and 0.98% (13.69 km2) while Peri-Urban land, and vegetation cover have decreased by 0.35% (5.00 km2), and 3.36 % (46.87 km2), respectively. The results quantify the land cover change patterns in the city and its peripheral area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyse changes in land cover over time that can be used as inputs to land management and policy decisions.

Exploring Plantation Development and Land Cover Changes in the Meme-Mungo Corridor of Cameroon

There is an apparent nexus between the development of plantations and changes in landcover. The Meme-Mungo Corridor is an example par excellence of a tropical plantation corridor in Cameroon which has witnessed significant expansion in tropical plantations of cocoa, banana, rubber and oil palm, among others. This paper analyzes the connection between land cover changes and plantation development over a 42-year period (1960 and 2012). A total of 100 households were sampled using the systematic sampling technique. Furthermore, multispectral data, obtained from the Global Land Cover Facility (GLCF, 2005) were used in the classification of the study area. These images were processed using Geographic Information System (GIS) and Remote Sensing (RS) software and further compiled into a GIS database using ESRI ArcGIS software. The results showed that between 1960 and 2012, a more than 50% increase in the surface area of plantation crops was registered, leadingto a corresponding change in the land cover situation. Based on this, the study probed into the implications of further plantation development on land cover; further land cover changes could be attributed to the extension of plantations. This paperrecommends among others, the need for intensive agriculture to be encouraged so as to ensure an increase in agricultural output against the backdrop of a decline in agricultural space. Furthermore, augmenting agro-product value chains will stem the loss of agro-produce due to perishability. This will contribute to regulate extensive plantation development in the area.

Quantitative Assessment of Land Cover Sensitivity to Desertification in Maigatari Local Government Area, Jigawa State, Nigeria

Desertification alludes to land degradation in arid, semi-arid and sub-humid regions resulting from various variables, counting climatic variations and human activities. When land degradation transpire within the world’s drylands. It regularly makes desert-like conditions. Land degradation occurs all over, but is characterized as desertification when it occurs within the drylands. The study employed adjusted MEDALUS methodology using eleven indicators rainfall, evapotranspiration, aridity, soil texture, soil depth, slope gradient, drainage density, plant cover, erosion protection, sensitivity desertification index and Normalized Difference Vegetation Index (NDVI). Remote Sensing and GIS were the main techniques used in the indices computations and mapping. Thus, Shuttle Rader Topographic Map (SRTM) and Landsat 8 satellite imagery for the year 2019 with 30 meter resolution, captured in the month of August (rainy season), covering the study area were acquired from Global Land cover Facility (GLCF) University of Maryland. The study finds that the duration and intensity of rainfall is declining especially at the edge of the desert, extreme north and western part of the area. Rain quickly drained through infiltration and surface runoff which carried the little nutrients attached to the soil. Rainfall and climate is of arid type recording about 300-400mm of rainfall and the soil is low in organic matter content making it weak and less fertile and support only the cultivation of cereals and legumes. The study recommends that there is need to strengthen the laws and policies in controlling desertification and land degradation, establishment of shelterbelts to control desertification and act also as wind breakers and encourage the use of modern techniques such as drip irrigation to check the rate of infiltration and runoff. 
 Keyword: Desertification; Sensitivity; MEDALUS; GIS; Maigatari

Effects of Land Use and Land Cover Change on Tse Gavar Forest Reserve, Vandeikya Local Government Area, Benue State, Nigeria

Forests are considered to be the very basis for human existence as they touch virtually every aspect of human endeavour. Despite the numerous benefits of forests, the world is experiencing unprecedented degradation of forest and its resources; this is mainly attributed to land use and land cover (LULC) change. Therefore, monitoring of these changes has become a necessity. Hence, the use of remotely sensed data in conjunction with GIS for land use and land cover analysis of Tse Gavar community forest in Vandeikya Local Government Area would definitely enhance the available data for sustainable management and promotion of community forest in the State. This study made use of mostly secondary data from pre-existing satellites imageries. The Landsat TM for 1986, Landsat ETM+ for 2001 and 2012 as well as OLI for 2018 images were sourced from the Earthexplorer platform from United States Geological Surveys (USGS), Global Land Cover Facility (GLCF) and GloVis. Images were subjected to various image processing techniques and supervised classification was carried out on the various images. The classification resulted in classes of farmland, other vegetation, forest area and bare land. The percentage of LULC in Tse Gavar Forest Reserve indicated that farmland increased from 5.78% in 1986 to 18.25% in 2018. Shrubland also increased from 3.06% in 1986 to 21.08% in 2018. Forested area decreased from 84.17% in 1986 to 59.38% in 2018. The magnitude of land use/land cover change within the 32 years period showed that 9.36 Ha of the forest area was lost to other forms of land use, the bare land area lost within the period was 0.09 Ha to other land uses. Farmland area increased by 4.32 Ha within the period, shrubland increased by 5078.88 km2. It was established that just like other protected areas, land use and land cover changes are going on in the Tse Gavar community forest reserve. Enrichment planting of the reserve was recommended.

Land suitability evaluation for agricultural use using GIS and remote sensing techniques: The case study of Ma’an Governorate, Jordan

The present study illustrates the Spatial-temporal dynamics of Land use/Land cover (LULC), and locate land suitability for agricultural use. Landsat satellite images of three different years 1990, 2000 and 2018 over 28 years were acquired from Global Land Cover Facility Site (GLCF) and earth explorer. Land suitability for agriculture use was assessed on five criteria; rainfall, temperature, slope percentage, soil types and water Wells distribution. The different geospatial layers were transferred using suitability coding system to produce the suitability maps for rainfed and irrigated areas using weighted overlay method. Ma’an Governorate covers approximately 37% of the total area of Jordan, and consists mostly of uncultivated land 33304.66 km2 (99.49%). Three main LULC classes were identified of the three years; 1990, 2000 and 2018; forest and irrigated areas have been fluctuated between 86.00 km2 (0.26%), 108.06 km2 (0.32) and 102.68 km2 (0.31%), built-up area increased by 24.00 km2, (0.07%), 41.88 km2 (0.13%) and 68.66 km2 (0.21%), while the bare land has been decreased from 33366 km2 (99.67%),33476 km2 (99.55%) and 33304.66 km2 (99.49%) during 1990, 2000 and 2018 respectively. land suitability for the agricultural use (rainfed areas and irrigated crops); Data from the five parameters (mentioned above) are used for spatial analysis applying weighted overlay method. The results showed that only about (0.2%) from the total area of Ma’an is highly suitable for agriculture dependent on rainfall. While about (1.4%) is high suitable for the irrigation crops. The main reason of the low levels of land suitability for agriculture is very low soil fertility, and the water scarcity.

The Application of Airborne Geophysical and Satellite Imagery Data in the Delineation of Rock Boundaries and Structural Lineaments in Anka Sheet 52, Northwestern, Nigeria

The understanding of different lithologies and geological structures is a major task of geologists for accurate geological map during geological mapping exercise. In doing so, geologist must be able to cover broad areas of the surface or subsurface of the earth through collection of reliable remote sensing data over a wide region. The Landsat ETM + from Global Land Cover Facility (GLCV), Shuttle Radar Thematic Mapper- Digital Elevation Model (SRTM, DEM) data from Global Mapper version 14, Airborne Magnetic and Radiometric data from Nigeria Geological Survey Agency (NGSA) was acquired and interpreted with the help of computer-image processing technology such as Oasis Montaj and ArcGIS software to process, display and represent results covering the study area (Anka sheet 52). The basis of this technology is the representation of the radiometric data in a digital raster format that contain both amplitude and spatial information. In this format, the data was analyzed, enhanced for visual inspection and combined with other types of data to form colour composite images that clearly subdivide the Basement complex rocks into Pan-African Granites from the Metasediments and the most eye-catching feature is the basement-sedimentary contact. Also, a major NE–SW trending structural lineament referred to as the Anka Fault trends for almost 25km and other subsidiary lineaments trending NW–SE with few E–W trends. Keywords: Landsat ETM + , Magnetic, Radiometric, Structural Lineament, Satellite Imagery. DOI : 10.7176/JEES/10-1-05 Publication date: January 31 st 2020

Water level fluctuations of Lake Tana and its implication on local communities livelihood, northwestern Ethiopia

ABSTRACT Lake Tana is a shallow inland lake with an average depth of 9 m. It is fresh water lake with the total area of 3150 km2.The lake level has experienced a rapid water level fluctuation in recent years. The study was aimed at analysing the water level fluctuation of Lake Tana. Four Landsat images acquired at different times from the United States Geological Survey have been processed and analysed by using the ERDAS and ARC-GIS softwares to detect changes in the lake area through time. In addition to this, the long-time lake level and climate data obtained from National Metrological Agency were analysed using a linear regression model to complement the lake level change. Focus group discussion, key informant interview and direct observation were held to analyse the impact of lake level fluctuation on the livelihood of the community. The result of the study indicated that more than 180 km2 of Lake Tana area has been converted to farm and other land uses during the last 35 years. The climate variability has been observed for the study period. There was continuous lake level fluctuation because of land-use changes, climate variability and water regulation for hydropower productions. Water level fluctuation of the lake had impacted on land use and its environment. The land use and regulated water at Chara Chara weirs, which are the contributing factors for Lake Tana water level fluctuation, should be managed regularly and critically. Abbreviations: ERDAS, Earth resource dynamic analysis system; GLCF, Global Land Cover Facility; FGD, Focus Group Discussions; IPCC, the Inter-Governmental Panel on Climate Change

Influence of land cover on lightning and convective precipitation over the European continent

The impact of land cover on lightning and convective precipitation in the summertime over Europe was analysed using five-year data. Lightning data were obtained with the Optical Transient Detector (OTD) at a 0.5° × 0.5° spatial resolution and the convective precipitation data were calculated by the NCEP/DOE AMIP-II Reanalysis at a ∼1.9° × 1.9° spatial resolution. Data concerning land cover were obtained from the Global Land Cover Facility, although the original 14 categories were grouped into seven categories (water, forest, shrubland, grassland, cropland, bare ground and urban). For all latitude ranges, forested areas tend to increase convective activity during the warm period of the year, and the general effect of shrubland areas is to suppress convective activity. The behaviour of convection in relation to grasslands and croplands depends on latitude. At low latitudes both vegetation types tend to increase convection during the summer. At high latitudes, grassland and cropland areas appear to be associated with the opposite effect in relation to convection: grass suppresses and crops enhance it. Finally, bare soil tends to decrease convective activity. These results seem to be related to the impact of vegetation on soil moisture and roughness. In general, vegetation areas associated with high soil moisture contents and high values in roughness length tend to enhance convective activity.

Remote sensing appraisal of Lake Chad shrinkage connotes severe impacts on green economics and socio-economics of the catchment area.

Lake Chad commonly serves as a major hub of fertile economic activities for the border communities and contributes immensely to the national growth of all the countries that form its boundaries. However, incessant and multi-decadal drying via climate change pose greater threats to this transnational water resource, and adverse effects on ecological sustainability and socio-economic status of the catchment area. Therefore, this study assessed the extent of shrinkage of Lake Chad using remote sensing. Landsat imageries of the lake and its surroundings between 1987 and 2005 were retrieved from Global Land Cover Facility website and analysed using Integrated Land and Water Information System version 3.3 (ILWIS 3.3). Supervised classification of area around the lake was performed into various land use/land cover classes, and the shrunk part of its environs was assessed based on the land cover changes. The shrinkage trend within the study period was also analysed. The lake water size reduced from 1339.018 to 130.686 km2 (4.08–3.39%) in 1987–2005. The supervised classification of the Landsat imageries revealed an increase in portion of the lake covered by bare ground and sandy soil within the reference years (13 490.8–17 503.10 km2) with 4.98% total range of increase. The lake portion intersected with vegetated ground and soil also reduced within the period (11 046.44–10 078.82 km2) with 5.40% (967.62 km2) total decrease. The shrunk part of the lake covered singly with vegetation increased by 2.74% from 1987 to 2005. The shrunk part of the lake reduced to sand and turbid water showed 5.62% total decrease from 1987 to 2005 and a total decrease of 1805.942 km2 in area. The study disclosed an appalling rate of shrinkage and damaging influences on the hydrologic potential, eco-sustainability and socio-economics of the drainage area as revealed using ILWIS 3.3.

Development of a spectral‐pattern‐analysis‐based method for automated water body extraction using Landsat image data: A case study in central Vietnam and southern Laos

AbstractWater body mapping is an important application of optical remote sensing. Methods for classifying water bodies using multispectral image data have been successfully developed for water resource monitoring and management. However, in most cases, these traditional methods provide only partial automation capabilities. In this study, we propose a new spectral‐pattern‐analysis‐based (SPAB) method for water body extraction using simplified spectral patterns (SSPs). Simplified spectral patterns are a generalized transformation of spectral patterns from analogue to digital format, realized by nonrepetitive pairwise comparison of reflectance values between two bands. Simplified spectral patterns allow for the direct incorporation of spectral patterns into the recognition process. The advantage of this method compared to traditional methods is that the SPAB method allows automation of water body classification using an SSP database. In this study, we selected a mountainous region in central Vietnam and southern Laos as a study site. Four Landsat 8 OLI scenes from 2015 and four Landsat 7 ETM+ scenes from 2001 and 2002 were used. The results of our proposed method were compared with visual interpretation, normalized differential water index (NDWI) thresholding, and the Global Inland Water (GIW) dataset provided by the Global Land Cover Facility of the University of Maryland. It is concluded that the classification results of the SPAB method agree by more than 98.0% with NDWI results for Landsat 8 OLI images, and by more than 95.0% with the GIW dataset for Landsat 7 ETM+ images.

Transition Modeling of Land-Use Dynamics in the Pipestem Creek, North Dakota, USA

Significant land-use changes in North Dakota have been reported and are widespread over the entire state. Such changing patterns may portend localized impairment to agricultural watersheds. In this study, Land-use Land-cover (LULC) change was modeled using geostatistics. The study area was within the Pipestem Creek watershed, a part of the Missouri Watershed James Subregion of North Dakota, USA. Landsat Thematic mapper images from the years 2007, 2011 and 2015 were used as preliminary data. LULC information for these datasets was acquired from the Global Land-cover facility and Landsat Program. Data analysis, spectral classification and post classification techniques were applied on the datasets. A transition matrix was derived using a Markov chain Monte Carlo (MCMC) model. This study demonstrates that the integration of satellite remote sensing, GIS and statistics may be an effective approach for analyzing the direction, rate, and spatial pattern of land-use change.

REGIONAL TRENDS OF LAND USE AND LAND COVER TRANSFORMATION IN BRAZIL IN 2001-2012

Regional trends of land use/land cover transformation in Brazil during 2001—2012 were analyzed in the following order: 1) identification of the types of transitions for different land use and land cover categories and aggregated groups of transformation processes based on the Global Land Cover Facility datasets, 2) analysis of national agricultural and forestry statistics to find out the principal socioeconomic drivers, 3) land cover and land use data merging to elaborate comprehensive typology of land use/land cover changes on a regional level. The study evealed 96 types of transitions between land cover categories, aggregated into 10 groups corresponding to driving processes. It was found that the main processes of land cover transformations is related to both natural and anthropogenic origins. Cropping and deforestation are anthropogenic processes, flooding and draining are the principal natural ones. Transformation of cultivated lands and reforestation are combined natural and anthropogenic. The contribution of natural factors is higher in the states of the North (Amazonia) and the Northeast macroregions; in the Center-West and the South anthropogenic factors make larger contribution. We have also detected considerable land use/land cover changes caused by agricultural development in densely populated states of the Southeast and the South. In both macroregions planted area expands due to increase of soybeans and sugar cane production, while area of pastures is shrinking. The trends of transformations of agricultural land use revealed as a result of statistical data analysis, match with transitions of land cover categories belonging to the aggregated group of cropping processes. Transformations of land cover types with predominance of shrub vegetation were the most problematic to interpret because of lack of comparable statistical data on pastures.