International Science Index
Assessment of Urban Heat Island through Remote Sensing in Nagpur Urban Area Using Landsat 7 ETM+ Satellite Images
Urban Heat Island (UHI) is found more pronounced as a prominent urban environmental concern in developing cities. To study the UHI effect in the Indian context, the Nagpur urban area has been explored in this paper using Landsat 7 ETM+ satellite images through Remote Sensing and GIS techniques. This paper intends to study the effect of LU/LC pattern on daytime Land Surface Temperature (LST) variation, contributing UHI formation within the Nagpur Urban area. Supervised LU/LC area classification was carried to study urban Change detection using ENVI 5. Change detection has been studied by carrying Normalized Difference Vegetation Index (NDVI) to understand the proportion of vegetative cover with respect to built-up ratio. Detection of spectral radiance from the thermal band of satellite images was processed to calibrate LST. Specific representative areas on the basis of urban built-up and vegetation classification were selected for observation of point LST. The entire Nagpur urban area shows that, as building density increases with decrease in vegetation cover, LST increases, thereby causing the UHI effect. UHI intensity has gradually increased by 0.7°C from 2000 to 2006; however, a drastic increase has been observed with difference of 1.8°C during the period 2006 to 2013. Within the Nagpur urban area, the UHI effect was formed due to increase in building density and decrease in vegetative cover.
Markov Random Field-Based Segmentation Algorithm for Detection of Land Cover Changes Using Uninhabited Aerial Vehicle Synthetic Aperture Radar Polarimetric Images
The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.
Landcover Mapping Using Lidar Data and Aerial Image and Soil Fertility Degradation Assessment for Rice Production Area in Quezon, Nueva Ecija, Philippines
Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.
Performance Analysis of Artificial Neural Network Based Land Cover Classification
Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.
Hydrological Modelling of Geological Behaviours in Environmental Planning for Urban Areas
Runoff,decreasing water levels and recharge in urban areas have been a complex issue now a days pointing defective urban design and increasing demography as cause. Very less has been discussed or analysed for water sensitive Urban Master Plans or local area plans. Land use planning deals with land transformation from natural areas into developed ones, which lead to changes in natural environment. Elaborated knowledge of relationship between the existing patterns of land use-land cover and recharge with respect to prevailing soil below is less as compared to speed of development. The parameters of incompatibility between urban functions and the functions of the natural environment are becoming various. Changes in land patterns due to built up, pavements, roads and similar land cover affects surface water flow seriously. It also changes permeability and absorption characteristics of the soil. Urban planners need to know natural processes along with modern means and best technologies available,as there is a huge gap between basic knowledge of natural processes and its requirement for balanced development planning leading to minimum impact on water recharge. The present paper analyzes the variations in land use land cover and their impacts on surface flows and sub-surface recharge in study area. The methodology adopted was to analyse the changes in land use and land cover using GIS and Civil 3d auto cad. The variations were used in computer modeling using Storm-water Management Model to find out the runoff for various soil groups and resulting recharge observing water levels in POW data for last 40 years of the study area. Results were anlayzed again to find best correlations for sustainable recharge in urban areas.
Urban Heat Island Intensity Assessment through Comparative Study on Land Surface Temperature and Normalized Difference Vegetation Index: A Case Study of Chittagong, Bangladesh
Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.
Relocation of Livestocks in Rural of Canakkale Province Using Remote Sensing and GIS
Livestock production is one of the most important components of rural economy. Due to the urban expansion, rural areas close to expanding cities transform into urban districts during the time. However, the legislations have some restrictions related to livestock farming in such administrative units since they tend to create environmental concerns like odor problems resulted from excessive manure production. Therefore, the existing animal operations should be moved from the settlement areas. This paper was focused on determination of suitable lands for livestock production in Canakkale province of Turkey using remote sensing (RS) data and GIS techniques. To achieve the goal, Formosat 2 and Landsat 8 imageries, Aster DEM, and 1:25000 scaled soil maps, village boundaries, and village livestock inventory records were used. The study was conducted using suitability analysis which evaluates the land in terms of limitations and potentials, and suitability range was categorized as Suitable (S) and Non-Suitable (NS). Limitations included the distances from main and crossroads, water resources and settlements, while potentials were appropriate values for slope, land use capability and land use land cover status. Village-based S land distribution results were presented, and compared with livestock inventories. Results showed that approximately 44230 ha area is inappropriate because of the distance limitations for roads and etc. (NS). Moreover, according to LULC map, 71052 ha area consists of forests, olive and other orchards, and thus, may not be suitable for building such structures (NS). In comparison, it was found that there are a total of 1228 ha S lands within study area. The village-based findings indicated that, in some villages livestock production continues on NS areas. Finally, it was suggested that organized livestock zones may be constructed to serve in more than one village after the detailed analysis complemented considering also political decisions, opinion of the local people, etc.
Land Use Land Cover Changes in Response to Urban Sprawl within North-West Anatolia, Turkey
In the present study, an attempt was made to state the Land Use Land Cover (LULC) transformation over three decades around the urban regions of Balıkesir, Bursa, and Çanakkale provincial centers (PCs) in Turkey. Landsat imageries acquired in 1984, 1999 and 2014 were used to determine the LULC change. Images were classified using the supervised classification technique and five main LULC classes were considered including forest (F), agricultural land (A), residential area (urban) - bare soil (R-B), water surface (W), and other (O). Change detection analyses were conducted for 1984-1999 and 1999-2014, and the results were evaluated. Conversions of LULC types to R-B class were investigated. In addition, population changes (1985-2014) were assessed depending on census data, the relations between population and the urban areas were stated, and future populations and urban area needs were forecasted for 2030. The results of LULC analysis indicated that urban areas, which are covered under R-B class, were expanded in all PCs. During 1984-1999 R-B class within Balıkesir, Bursa and Çanakkale PCs were found to have increased by 7.1%, 8.4%, and 2.9%, respectively. The trend continued in the 1999-2014 term and the increment percentages reached to 15.7%, 15.5%, and 10.2% at the end of 30-year period (1984-2014). Furthermore, since A class in all provinces was found to be the principal contributor for the R-B class, urban sprawl lead to the loss of agricultural lands. Moreover, the areas of R-B classes were highly correlated with population within all PCs (R2>0.992). Depending on this situation, both future populations and R-B class areas were forecasted. The estimated values of increase in the R-B class areas for Balıkesir, Bursa, and Çanakkale PCs were 1,586 ha, 7,999 ha and 854 ha, respectively. Due to this fact, the forecasted values for 2,030 are 7,838 ha, 27,866, and 2,486 ha for Balıkesir, Bursa, and Çanakkale, and thus, 7.7%, 8.2%, and 9.7% more R-B class areas are expected to locate in PCs in respect to the same order.
Rice Area Determination Using Landsat-Based Indices and Land Surface Temperature Values
In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.
Surface Water Flow of Urban Areas and Sustainable Urban Planning
Urban planning is associated with land transformation from natural areas to modified and developed ones which leads to modification of natural environment. The basic knowledge of relationship between both should be ascertained before proceeding for the development of natural areas. Changes on land surface due to build up pavements, roads and similar land cover, affect surface water flow. There is a gap between urban planning and basic knowledge of hydrological processes which should be known to the planners. The paper aims to identify these variations in surface flow due to urbanization for a temporal scale of 40 years using Storm Water Management Mode (SWMM) and again correlating these findings with the urban planning guidelines in study area along with geological background to find out the suitable combinations of land cover, soil and guidelines. For the purpose of identifying the changes in surface flows, 19 catchments were identified with different geology and growth in 40 years facing different ground water levels fluctuations. The increasing built up, varying surface runoff are studied using Arc GIS and SWMM modeling, regression analysis for runoff. Resulting runoff for various land covers and soil groups with varying built up conditions were observed. The modeling procedures also included observations for varying precipitation and constant built up in all catchments. All these observations were combined for individual catchment and single regression curve was obtained for runoff. Thus, it was observed that alluvial with suitable land cover was better for infiltration and least generation of runoff but excess built up could not be sustained on alluvial soil. Similarly, basalt had least recharge and most runoff demanding maximum vegetation over it. Sandstone resulted in good recharging if planned with more open spaces and natural soils with intermittent vegetation. Hence, these observations made a keystone base for planners while planning various land uses on different soils. This paper contributes and provides a solution to basic knowledge gap, which urban planners face during development of natural surfaces.
Land-Use Suitability Analysis for Merauke Agriculture Estates
Merauke district in Papua, Indonesia has a strategic position and natural potential for the development of agricultural industry. The development of agriculture in this region is being accelerated as part of Indonesian Government’s declaration announcing Merauke as one of future national food barns. Therefore, land-use suitability analysis for Merauke need to be performed. As a result, the mapping for future agriculture-based industries can be done optimally. In this research, a case study is carried out in Semangga sub district. The objective of this study is to determine the suitability of Merauke land for some food crops. A modified agro-ecological zoning is applied to reach the objective. In this research, land cover based on satellite imagery is combined with soil, water and climate survey results to come up with preliminary zoning. Considering the special characteristics of Merauke community, the agricultural zoning maps resulted based on those inputs will be combined with socio-economic information and culture to determine the final zoning map for agricultural industry in Merauke. Examples of culture are customary rights of local residents and the rights of local people and their own local food patterns. This paper presents the results of first year of the two-year research project funded by The Indonesian Government through MP3EI schema. It shares the findings of land cover studies, the distribution of soil physical and chemical parameters, as well as suitability analysis of Semangga sub-district for five different food plants.
Effects of Urbanization on Land Use/Land Cover and Stream Flow of a Sub-Tropical River Basin of India
Rapid urbanization changes the land use/land cover pattern of a developing region. Due to these land surface changes, stream flow of the rivers also changes. It is important to investigate the factors affecting hydrological characteristics of the river basin for better river basin management planning. This study is aimed to understand the effect of Land Use/Land Cover (LU/LC) changes on stream flow of Upper Bhima River basin which is highly stressed in terms of water resources. In this study, Upper Bhima River basin is divided into two adjacent sub-watersheds: Mula-Mutha (urbanized) sub-watershed and Bhima (non-urbanized) sub-watershed. First of all, LU/LC changes were estimated over 1980, 2002, and 2009 for both Mula-Mutha and Bhima sub-watersheds. Further, stream flow simulations were done using Soil and Water Assessment Tool (SWAT) for the streams draining both watersheds. Results revealed that stream flow was relatively higher for urbanized sub-watershed. Through Sensitivity Analysis it was observed that out of all the parameters used, base flow was the most sensitive parameter towards LU/LC changes.
Modelling of Groundwater Resources for Al-Najaf City, Iraq
Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.
Development of Map of Gridded Basin Flash Flood Potential Index: GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue Provinces
Flash flood is occurred in short time rainfall interval:
from 1 hour to 12 hours in small and medium basins. Flash floods
typically have two characteristics: large water flow and big flow
velocity. Flash flood is occurred at hill valley site (strip of lowland of
terrain) in a catchment with large enough distribution area, steep
basin slope, and heavy rainfall. The risk of flash floods is determined
through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash
Flood Potential Index (FFPI) is determined through terrain slope
flash flood index, soil erosion flash flood index, land cover flash
floods index, land use flash flood index, rainfall flash flood index.
Determining GBFFPI, each cell in a map can be considered as outlet
of a water accumulation basin. GBFFPI of the cell is determined as
basin average value of FFPI of the corresponding water accumulation
basin. Based on GIS, a tool is developed to compute GBFFPI using
ArcObjects SDK for .NET. The maps of GBFFPI are built in two
types: GBFFPI including rainfall flash flood index (real time flash
flood warning) or GBFFPI excluding rainfall flash flood index.
GBFFPI Tool can be used to determine a high flash flood potential
site in a large region as quick as possible. The GBFFPI is improved
from conventional FFPI. The advantage of GBFFPI is that GBFFPI is
taking into account the basin response (interaction of cells) and
determines more true flash flood site (strip of lowland of terrain)
while conventional FFPI is taking into account single cell and does
not consider the interaction between cells. The GBFFPI Map of
QuangNam, QuangNgai, DaNang, Hue is built and exported to
Google Earth. The obtained map proves scientific basis of GBFFPI.
Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines
The underutilization of biomass resources in the
Philippines, combined with its growing population and the rise in
fossil fuel prices confirms demand for alternative energy sources. The
goal of this paper is to provide a comparison of MODIS-based and
Landsat-based agricultural land cover maps when used in the
estimation of rice hull’s available energy potential. Biomass resource
assessment was done using mathematical models and remote sensing
techniques employed in a GIS platform.
Determination of Potential Agricultural Lands Using Landsat 8 OLI Images and GIS: Case Study of Gokceada (Imroz) Turkey
In present study, it was aimed to determine potential
agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale
province, Turkey. Seven-band Landsat 8 OLI images acquired on
July 12 and August 13, 2013, and their 14-band combination image
were used to identify current Land Use Land Cover (LULC) status.
Principal Component Analysis (PCA) was applied to three Landsat
datasets in order to reduce the correlation between the bands. A total
of six Original and PCA images were classified using supervised
classification method to obtain the LULC maps including 6 main
classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area-
Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was
performed by checking the accuracy of 120 randomized points for
each LULC maps. The best overall accuracy and Kappa statistic
values (90.83%, 0.8791% respectively) were found for PCA images
which were generated from 14-bands combined images called 3-
Digital Elevation Model (DEM) with 15 m spatial resolution
(ASTER) was used to consider topographical characteristics. Soil
properties were obtained by digitizing 1:25000 scaled soil maps of
Rural Services Directorate General. Potential Agricultural Lands
(PALs) were determined using Geographic information Systems
(GIS). Procedure was applied considering that “Other” class of
LULC map may be used for agricultural purposes in the future
properties. Overlaying analysis was conducted using Slope (S), Land
Use Capability Class (LUCC), Other Soil Properties (OSP) and Land
Use Capability Sub-Class (SUBC) properties.
A total of 901.62 ha areas within “Other” class (15798.2 ha) of
LULC map were determined as PALs. These lands were ranked as
“Very Suitable”, “Suitable”, “Moderate Suitable” and “Low
Suitable”. It was determined that the 8.03 ha were classified as “Very
Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate
Suitable” for PALs. In addition, 756.56 ha were found to be “Low
Suitable”. The results obtained from this preliminary study can serve
as basis for further studies.
Assessment of Agricultural Land Use Land Cover, Land Surface Temperature and Population Changes Using Remote Sensing and GIS: Southwest Part of Marmara Sea, Turkey
Land Use Land Cover (LULC) changes due to human
activities and natural causes have become a major environmental
concern. Assessment of temporal remote sensing data provides
information about LULC impacts on environment. Land Surface
Temperature (LST) is one of the important components for modeling
environmental changes in climatological, hydrological, and
agricultural studies. In this study, LULC changes (September 7, 1984
and July 8, 2014) especially in agricultural lands together with
population changes (1985-2014) and LST status were investigated
using remotely sensed and census data in South Marmara Watershed,
Turkey. LULC changes were determined using Landsat TM and
Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM
and OLI images were classified using supervised classification
method to prepare LULC map including five classes including Forest
(F), Grazing Land (G), Agricultural Land (A), Water Surface (W),
Residential Area-Bare Soil (R-B) classes. The LST image was also
derived from thermal bands of the same dates.
LULC classification results showed that forest areas, agricultural
lands, water surfaces and residential area-bare soils were increased as
65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In
comparison, a dramatic decrement occurred in grazing land (107985
ha) within three decades. The population increased 29% between
years 1984-2014 in whole study area. Along with the natural causes,
migration also caused this increase since the study area has an
important employment potential. LULC was transformed among the
classes due to the expansion in residential, commercial and industrial
areas as well as political decisions. In the study, results showed that
agricultural lands around the settlement areas transformed to
residential areas in 30 years.
The LST images showed that mean temperatures were ranged
between 26-32°C in 1984 and 27-33°C in 2014. Minimum
temperature of agricultural lands was increased 3°C and reached to
23°C. In contrast, maximum temperature of A class decreased to
41°C from 44°C. Considering temperatures of the 2014 R-B class and
1984 status of same areas, it was seen that mean, min and max
temperatures increased by 2°C.
As a result, the dynamism of population, LULC and LST resulted
in increasing mean and maximum surface temperatures, living
spaces/industrial areas and agricultural lands.
Use of Data of the Remote Sensing for Spatiotemporal Analysis Land Use Changes in the Eastern Aurès (Algeria)
Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
The Threats of Deforestation, Forest Fire, and CO2 Emission toward Giam Siak Kecil Bukit Batu Biosphere Reserve in Riau, Indonesia
A biosphere reserve is developed to create harmony
amongst economic development, community development, and
environmental protection, through partnership between human and
nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR)
in Riau Province, Indonesia, is unique in that it has peat soil
dominating the area, many springs essential for human livelihood,
high biodiversity. Furthermore, it is the only biosphere reserve
covering privately managed production forest areas. In this research, we aimed at analyzing the threat of deforestation
and forest fire, and the potential of CO2 emission at GSKBB BR. We
used Landsat image, arcView software, and ERDAS IMAGINE 8.5
Software to conduct spatial analysis of land cover and land use
changes, calculated CO2 emission based on emission potential from
each land cover and land use type, and exercised simple linear
regression to demonstrate the relation between CO2 emission
potential and deforestation. The result showed that, beside in the buffer zone and transition
area, deforestation also occurred in the core area. Spatial analysis of
land cover and land use changes from years 2010, 2012, and 2014
revealed that there were changes of land cover and land use from
natural forest and industrial plantation forest to other land use types,
such as garden, mixed garden, settlement, paddy fields, burnt areas,
and dry agricultural land. Deforestation in core area, particularly at
the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife
Reserve, occurred in the form of changes from natural forest in to
garden, mixed garden, shrubs, swamp shrubs, dry agricultural land,
open area, and burnt area. In the buffer zone and transition area,
changes also happened, what once swamp forest changed into garden,
mixed garden, open area, shrubs, swamp shrubs, and dry agricultural
land. Spatial analysis on land cover and land use changes indicated
that deforestation rate in the biosphere reserve from 2010 to 2014 had
reached 16 119 ha/year. Beside deforestation, threat toward the
biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the
area, in which 9 355 ha of core area, and 92 368 ha of buffer zone
and transition area. Deforestation and forest fire had increased CO2
emission as much as 24 903 855 ton/year.
Spatial-Temporal Clustering Characteristics of Dengue in the Northern Region of Sri Lanka, 2010-2013
Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Using Time-Series NDVI to Model Land Cover Change: A Case Study in the Berg River Catchment Area, Western Cape, South Africa
This study investigates the use of a time-series of
MODIS NDVI data to identify agricultural land cover change on an
annual time step (2007 - 2012) and characterize the trend. Following
an ISODATA classification of the MODIS imagery to selectively
mask areas not agriculture or semi-natural, NDVI signatures were
created to identify areas cereals and vineyards with the aid of
ancillary, pictometry and field sample data for 2010. The NDVI
signature curve and training samples were used to create a decision
tree model in WEKA 3.6.9 using decision tree classifier (J48)
algorithm; Model 1 including ISODATA classification and Model 2
not. These two models were then used to classify all data for the
study area for 2010, producing land cover maps with classification
accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2
was subsequently used to create land cover classification and change
detection maps for all other years. Subtle changes and areas of
consistency (unchanged) were observed in the agricultural classes
and crop practices. Over the years as predicted by the land cover
classification. Forty one percent of the catchment comprised of
cereals with 35% possibly following a crop rotation system.
Vineyards largely remained constant with only one percent
conversion to vineyard from other land cover classes.
Urban Growth Prediction in Athens, Greece, Using Artificial Neural Networks
Urban areas have been expanded throughout the
globe. Monitoring and modelling urban growth have become a
necessity for a sustainable urban planning and decision making.
Urban prediction models are important tools for analyzing the causes
and consequences of urban land use dynamics. The objective of this
research paper is to analyze and model the urban change, which has
been occurred from 1990 to 2000 using CORINE land cover maps.
The model was developed using drivers of urban changes (such as
road distance, slope, etc.) under an Artificial Neural Network
modelling approach. Validation was achieved using a prediction map
for 2006 which was compared with a real map of Urban Atlas of
2006. The accuracy produced a Kappa index of agreement of 0,639
and a value of Cramer's V of 0,648. These encouraging results
indicate the importance of the developed urban growth prediction
model which using a set of available common biophysical drivers
could serve as a management tool for the assessment of urban
The Effect of Land Cover on Movement of Vehicles in the Terrain
This article deals with geographical conditions in
terrain and their effect on the movement of vehicles, their effect on
speed and safety of movement of people and vehicles. Finding of the
optimal routes outside the communication is studied in the Army
environment, but it occur in civilian as well, primarily in crisis
situation, or by the provision of assistance when natural disasters
such as floods, fires, storms etc., have happened. These movements
require the optimization of routes when effects of geographical
factors should be included. The most important factor is the surface
of a terrain. It is based on several geographical factors as are slopes,
soil conditions, micro-relief, a type of surface and meteorological
conditions. Their mutual impact has been given by coefficient of
deceleration. This coefficient can be used for the commander`s
decision. New approaches and methods of terrain testing,
mathematical computing, mathematical statistics or cartometric
investigation are necessary parts of this evaluation.
Land Use Changes in Two Mediterranean Coastal Regions: Do Urban Areas Matter?
This paper focuses on Land Use and Land Cover Changes (LULCC) occurred in the urban coastal regions of the Mediterranean basin in the last thirty years. LULCC were assessed diachronically (1975-2006) in two urban areas, Rome (Italy) and Athens (Greece), by using CORINE land cover maps. In strictly coastal territories a persistent growth of built-up areas at the expenses of both agricultural and forest land uses was found. On the contrary, a different pattern was observed in the surrounding inland areas, where a high conversion rate of the agricultural land uses to both urban and forest land uses was recorded. The impact of city growth on the complex pattern of coastal LULCC is finally discussed.
Assessing Land Cover Change Trajectories in Olomouc, Czech Republic
Olomouc is a unique and complex landmark with
widespread forestation and land use. This research work was
conducted to assess important and complex land use change
trajectories in Olomouc region. Multi-temporal satellite data from
1991, 2001 and 2013 were used to extract land use/cover types by
object oriented classification method. To achieve the objectives, three
different aspects were used: (1) Calculate the quantity of each
transition; (2) Allocate location based landscape pattern (3) Compare
land use/cover evaluation procedure. Land cover change trajectories
shows that 16.69% agriculture, 54.33% forest and 21.98% other areas
(settlement, pasture and water-body) were stable in all three decade.
Approximately 30% of the study area maintained as a same land cove
type from 1991 to 2013. Here broad scale of political and socioeconomic
factors was also affect the rate and direction of landscape
changes. Distance from the settlements was the most important
predictor of land cover change trajectories. This showed that most of
landscape trajectories were caused by socio-economic activities and
mainly led to virtuous change on the ecological environment.
Photogrammetric Survey on the Natural Gas Pipeline Projects of Iran-Turkey- Europe (ITE)
The ITE Project is a project that has 1800 km length
and across the Turkey's land through east to west. The project of
pipeline enters geographically from Iran to Doğubayazit (Turkey) in
the east, exits to Greece from Ipsala province of Turkey in the west.
This project is the one of the international projects in such scale that
provides the natural gas of Iran and Caspian Sea through the
European continent. In this investigation, some information will be
given about the methods used to verify the direction of the pipeline
and the technical properties of the results obtained. The cost of
project itself entirely depends on the direction of the pipeline which
would be as short as possible and the specifications of the land cover.
Production standards of 1/2000 scaled digital orthophoto and vectoral
maps as a results of the use of map production materials and methods
(such as high resolution satellite images, and digital aerial images
captured from digital aerial cameras), will also be given in this report.
According to Turkish national map production standards, TM
((Transversal Mercator, 3 degree) projection is used for large scale
map and UTM (Universal Transversal Mercator, 6 degree) is used for
small scale map production standards. Some information is also given
about the projection used in the ITE natural gas pipeline project.
Spatial Structure and Process of Arctic Warming and Land Cover Change in the Feedback Systems Framework
This paper examines the relationships between and
among the various drivers of climate change that have both climatic
and ecological consequences for vegetation and land cover change in
arctic areas, particularly in arctic Alaska. It discusses the various
processes that have created spatial and climatic structures that have
facilitated observable vegetation and land cover changes in the
Arctic. Also, it indicates that the drivers of both climatic and
ecological changes in the Arctic are multi-faceted and operate in a
system with both positive and negative feedbacks that largely results
in further increases or decreases of the initial drivers of climatic and
vegetation change mainly at the local and regional scales. It
demonstrates that the impact of arctic warming on land cover change
and the Arctic ecosystems is not unidirectional and one dimensional
in nature but it represents a multi-directional and multi-dimensional
forces operating in a feedback system.
Urban Land Cover Change of Olomouc City Using LANDSAT Images
This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.
Estimating Spatial Disaggregation of Urban Thermal Responsiveness on Summer Diurnal Range with a Numerical Modeling Approach in Bangkok, Thailand
Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.
Seasonal Water Quality Trends in the Feitsui Reservoir Watershed, Taiwan
Protecting is the sources of drinking water is the first
barrier of contamination of drinking water. The Feitsui Reservoir
watershed of Taiwan supplies domestic water for around 5 million
people in the Taipei metropolitan area. Understanding the spatial
patterns of water quality trends in this watershed is an important
agenda for management authorities. This study examined 7 sites in the
watershed for water quality parameters regulated in the standard for
drinking water source. The non-parametric seasonal Mann-Kendall-s
test was used to determine significant trends for each parameter.
Significant trends of increasing pH occurred at the sampling station in
the uppermost stream watershed, and in total phosphorus at 4 sampling
stations in the middle and downstream watershed. Additionally, the
multi-scale land cover assessment and average land slope were used to
explore the influence on the water quality in the watershed. Regression
models for predicting water quality were also developed.