Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine

Human activities in many parts of the world have greatly changed the natural land cover. This study has been conducted on Pichavaram forest, south east coast of India, famous for its unique mangrove bio-diversity. The main objectives of this study were focused on monitoring land cover changes particularly for the mangrove forest in the Pichavaram area using multi-temporal Landsat images captured in the 1991, 2000, and 2009. The land use/land cover (LULC) estimation was done by a unique hybrid classification approach consisting of unsupervised and support vector machine (SVM)-based supervised classification. Once the vegetation and non-vegetation classes were separated, training site-based classification technology i.e., SVM-based supervised classification technique was used. The agricultural area, forest/plantation, degraded mangrove and mangrove forest layers were separated from the vegetation layer. Mud flat, sand/beach, swamp, sea water/sea, aquaculture pond, and fallow land were separated from non-vegetation layer. Water logged areas were delineated from the area initially considered under swamp and sea water-drowned areas. In this study, the object-based post-classification comparison method was employed for detecting changes. In order to evaluate the performance, an accuracy assessment was carried out using the randomly stratified sampling method, assuring distribution in a rational pattern so that a specific number of observations were assigned to each category on the classified image. The Kappa accuracy of SVM classified image was highest (94.53 %) for the 2000 image and about 94.14 and 89.45 % for the 2009 and 1991 images, respectively. The results indicated that the increased anthropogenic activities in Pichavaram have caused an irreversible loss of forest vegetation. These findings can be used both as a strategic planning tool to address the broad-scale mangrove ecosystem conservation projects and also as a tactical guide to help managers in designing effective restoration measures.     

Application of remote sensing in monitoring environmental change in ore area-Take Panzhihua V-Ti magnetite as an example

Remote sensing is an effective method to monitor environmental change. To study the influence of mining and mine dump on the environment of mine, remote sensing is used to monitor the change of land use and vegetation in the ore area, and to forecast the ecological environment by considering the mining speed. Remote sensing images at different periods were collected in the study, which include MSS images in 1975, TM images in 1990, 1995, 2000 and 2005, and SPOT-5 images in 2002. At the same time, relief map and geological map of the ore area were also collected as assistant data for remote sensing interpretation. After color synthesis, enhancing treatment and geometrical revision, the interpreted dynamic information on remote sensing images was edited with ARC/INFO software, to build a dynamic monitoring database for land use in the ore area from 1975 to 2005 and a database for land use in 1975, 1990, 1995, 2000, 2002 and 2005. Through interpretation, it is found that, after 30 years of mining activities, the vegetation area in the Panzhihua mining area was reduced from 9352.6 ha in 1975 to 8195.6 ha in 2005, and its grassland area from 1053 ha in 1975 to 795.5 ha in 2002. After that, the grassland area increased to 869.1 ha in 2005 because of re-cultivation of some mine dumps.     

Multi-temporal landsat images based on eco-environmental change analysis in and around Chah Nimeh reservoir,Balochestan (Iran)

Chah Nimeh reservoirs have served as a water storage facility, especially during droughts over the last three decades. It is also an important wintering site for migratory birds. In this study, thematic mapper time-series data were derived from Landsat images for prolonged droughts that occurred in two satellite images (2002 and 2011). The data derived from these images were used for the detection of changes in land cover and water storage in the reservoirs. First, a vegetation cover map was produced using soil-adjusted vegetation index and field sampling. Subsequently, land use/cover maps were generated using supervised and hybrid image classification method. Using the spatial change detector (SCD v1.0) software extension, the layers were combined and the change map was generated. The overall accuracy of the produced thematic images was assessed in regards to quantity and allocation disagreements. A total of five classes were defined in this investigation: deep water, shallow water, vegetation, salt land and bare land. The results showed that during the period of study, water volume reduced and vegetation cover increased, especially around the reservoirs that are important as shelter for wintering migratory birds. Comparison of land use/cover maps showed the increase in total available surface of shallow water, which indicated an increase in the habitats for surface feeding and diving birds.     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

Urban land use/land cover changes in the Tema metropolitan area (1990–2010)

Land use and land cover changes are local and place specific, occurring incrementally in ways that often escape our attention. This study sought to detect changes in land cover in the Tema Metropolis of Ghana from 1990 to 2010. Multispectral Landsat Thematic Mapper data sets of 1990, 2000 and 2007 were acquired, pre-processed and enhanced. Unsupervised classification of the images was performed and six land cover classes (water, wetlands, closed vegetation, open vegetation, cropped lands, and built-up) were derived. The post-classification change detection technique was performed to derive the changes in land cover and their corresponding change matrices. Between 1990 and 2010, built-up areas expanded steadily to become the most prevalent land cover type in the metropolis, reducing vegetation cover dramatically. High population growth with its attendant rise in the demand for housing, and increasing commercial activities, were found to have influenced land cover changes over the period.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.     

Desert riparian forest colonization in the lower reaches of Tarim River based on remote sensing analysis

The ecological water conveyance project that pipes water from Daxihaizi reservoir to lower reaches of Tarim River has been implemented ten times since 2000. After ecological water conveyance, restoration has taken place for vegetation along the dried-up lower reaches of the Tarim River. The changes of vegetation fluctuated yearly due to ecological water conveyance. In order to reveal the detailed process of vegetation changes, remote sensing images from 1999 to 2010 were all classified individually into vegetated and non-vegetated areas using the soil-adjusted vegetation index threshold method. Then inter-annual changes of vegetation over a period of 12 years were obtained using a post-classification change detection technique. Finally, spatial–temporal changes distribution of vegetation cover and its response to ecological water conveyance were analyzed. The results indicate: (1) vegetation area increased by 8.52 % overall after ecological water conveyance. Vegetation between 2003 and 2004 increased dramatically with 45.87 % while vegetation between 2002 and 2003 decreased dramatically with 17.83 %. (2) Vegetation area gain is greater than vegetation loss during 1999–2000, 2001–2002, 2003–2004 and 2009–2010 periods. Although vegetation restoration is obvious from 1999 to 2010, vegetation loss also existed except for the periods above. It indicates that vegetation restoration fluctuated due to ecological water conveyance. (3) Spatial distribution of vegetation restoration presented “strip” distribution along the river and group shaper in the lower terrain area, while spatial distribution of vegetation loss mainly located in the upper reaches of river and area far away from the river. (4) Vegetation restoration area had a positive relative with total ecological water conveyance volume. The scheme and season of ecological water conveyance had also influenced the vegetation restoration. The vegetation change process monitoring, based on continuous remote sensing data, can provide the spatial–temporal distribution of vegetation cover in a large-scale area and scientific evidences for implementing ecological water conveyance in the lower Tarim River.     

Impact assessment of land cover changes on the runoff changes on the extreme flood events in the Kelantan River basin

In the current years, changing the land cover/land use had serious hydrological impacts affecting the flood events in the Kelantan River basin. The flood events at the east coast of the peninsular Malaysia got highly affected in the recent decades due to several factors like urbanisation, rapid changes in the utilisation of land and lack of meteorological (i.e. change in climate) and developmental monitoring and planning. The Kelantan River basin has been highly influenced due to a rapid change in land use during 1984 to 2013, which occurred in the form of transformation of agricultural area and deforestation (logging activities). In order to evaluate the influence of the modifications in land cover on the flood events, two hydrological regional models of rainfall-induced runoff event, the Hydrologic Engineering Center (HEC)-Hydrologic Modeling System (HMS) model and improved transient rainfall infiltration and grid-based regional model (Improved TRIGRS), were employed in this study. The responses of land cover changes on the peak flow and runoff volume were investigated using 10 days of hourly rainfall events from 20 December to the end of December 2014 at the study area. The usage of two hydrological models defined that the changes in land use/land cover caused momentous changes in hydrological response towards water flow. The outcomes also revealed that the increase of severe water flow at the study area is a function of urbanisation and deforestation, particularly in the conversion of the forest area to the less canopy coverage, for example, oil palm, mixed agriculture and rubber. The monsoon season floods and runoff escalate in the cleared land or low-density vegetation area, while the normal flow gets the contribution from interflow generated from secondary jungle and forested areas.     

Monitoring land use/land cover change using multi-temporal Landsat satellite images in an arid environment: a case study of El-Arish,Egypt

Environment in arid conditions is dynamic and needs more investigation to understand the complexity of change. This spatiotemporal study will help to assess and monitor the land use and land cover change in the arid region of El-Arish area, where the climate and human activities are the major threats to rural development. In the past 11 years, dramatic changes of environment have been recorded in case studies. The post-classification comparison method was used to observe the changes using multi-temporal satellite images which were captured in the years 1999, 2001, 2005, and 2010. The overall accuracy of the produced thematic images was assessed regarding to the quantity and allocation disagreements. Five classes were defined in this investigation: bare soil, vegetation, urban, sand dunes, and fertile soil. From the year 1999 to 2010, fertile soil was increased by 13 %. Bare soil class occupied more than 50 % of land in the case study during for over a decade. From year 1999 to 2010, vegetation cover witnessed a dramatic increase. Soil and water management are the keys of land development and positive land use and land cover dynamics. Changing agricultural policies of using the available water resources are needed in the case study to prevent severe food shortage in the future.     

Monitoring of coal mining subsidence in peri-urban area of Zonguldak city (NW Turkey) with persistent scatterer interferometry using ALOS-PALSAR

This paper presents the results of spatiotemporal monitoring of surface subsidence over a mining area in Zonguldak Province of Turkey using Synthetic Aperture Radar (SAR) data, providing maps of subsidence rates in the radar line of sight direction. A total of 18 SAR images, acquired between January 2007 and June 2010 by the Japanese Advanced Land Observing Satellite, have been used to map the surface displacements using the Persistent Scatterer Interferometry technique. The use of Phased Array Type L-band Synthetic Aperture Radar data has proved useful for avoiding signal decorrelation and estimating surface deformation in the heavily vegetated study region. The technique enables the monitoring of continuous small displacements over a large area. Our findings present that many Persistent Scatterers were located on the vegetation cover. The results reveal areas of ground surface subsidence up to 44 mm/year that are well correlated with the underground coal mining galleries particularly in the Gelik region where the Karadon mining galleries are present.     

Relationship in metastasis of coal fire and land use/cover using thermal imagery and support vector machine classifier

The objective of the present study was to delineate temporal and spatial changes in the coal fire and land use/cover within Bastacolla area of Jharia coal field. Studying this variation helped to decipher interconnection among the dynamics of the coal fire and concomitant changes in land use/cover. The detection of coal fires during a span of 14 years along with transitioning land use/cover was cost-effective and enabled planning for management of coal resources and environment. Landsat series of satellite data of 2002, 2009, 2013, and 2016 were processed for generating land surface temperature profiles vis-a-vis classified land use/cover of the study area. A single cut-off temperature was derived for mapping of coal fires using land surface temperature profile from 2002 to 2016. The satellite images were classified using support vector machines, and for depicting land use/cover change, post-classification change detection was done. Classification accuracy obtained was excellent with kappa coefficient ranging from 0.897 for classified image of 2002 to 0.799 for classified image of 2016. Results revealed that coal fires had shifted to the central west part of the area. Furthermore, pockets of coal fire from northern and eastern part of the study area have diminished. OB dumps and coal quarry/coal dump may be attributed towards the spatial change in coal fire while; OB dumps showed connotation with the highest temperature zones. Ground verifications for temperature profiles and coal fires were carried out using thermal camera which enunciated good agreement with results.     

Investigating remote sensing indices to monitor drought impacts on a local scale (case study: Fars province,Iran)

As drought occurs in different climates, assessment of drought impacts on parameters such as vegetation cover is of utmost importance. Satellite remote sensing images with various spectral and spatial resolutions represent information about different land covers such as vegetation cover. Hence, the purpose of this study was to investigate the performance of satellite vegetation indices to monitor the agricultural drought on a local scale. In this regard, satellite images including Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data were used to evaluate vegetation cover and their gradual changes effects on agricultural drought. Fars province in Iran with relatively low precipitation values was selected as the study area. Modified Perpendicular Drought Index (MPDI), MPDI1, Vegetation Condition Index (VCI), Normalized Difference Vegetation Index Anomalies (NDVIA), and Standardized Vegetation Index (SVI), were evaluated to select the remote sensing based index with the best performance in drought monitoring. The performance of such indices were investigated during 13 years (2000–2013) for MODIS and 29 years (1985–2013) for AVHRR. To assess the efficiency of the satellite indices in drought investigation, Standardized Precipitation Index (SPI) data of five selected stations were used for 3, 6, and 9 month periods on August. The results showed that NDVI-based vegetation indices had the highest correlation with SPI in cold climate and long-term timescale (6 and 9 month). The highest correlation values between remote sensing based indices and SPI were acquired, respectively, in 9-month and 6-month time-scales, with the values of 43.5% and 40%. Moreover, VCI showed the highest capability for agricultural drought investigating in different climate regions of the study area. Overall, the results proved that NDVI-based indices can be used for drought monitoring and assessment in a long-term timescale on a local time-scale.

     

晋陕蒙接壤地区土地利用/覆盖变化及其驱动力研究——以神华集团大柳塔矿区为例

选择地处生态环境脆弱地区的晋陕蒙接壤地区能源化工基地的大柳塔矿区为研究区,利用1986年8月2日和2007年9月7日的TM卫星图像数据为信息源,应用遥感技术对其土地利用/覆盖变化进行研究。通过图像处理,划分出7种土地利用和地表覆盖景观类型,根据获取的景观类型变化参数对其结构与变化特征进行分析,得出研究区的生态变化趋势与驱动力。结果表明,煤矿大规模开采以来,研究区景观结构稳定性减弱,破碎度增强,人类活动在研究区生态环境变化过程中起主导作用。在矿区生态环境恢复中,应提高自然植被景观类型的有效规模,有利于增强生态系统的稳定性。     

吉林西部多时相遥感数据分类方案的构建及应用

为了深化遥感监测方法在生态环境调查中的应用,本文以吉林西部为试验区,设计了一种多时相遥感数据分类方案。该方案以物候信息为主,结合地物特征变量(植被、水体和土地信息)构建的多维特征空间数据集用于土地覆被分类。该遥感分类方案提取了9种地表覆被类型,结果表明:地表植被季节变化信息和土地利用信息的引入能明显改善土地覆被的分类精度;与基于原始波段的分类方案相比,多时相遥感数据分类方案的分类精度最好,总体分类精度为95.50%,Kappa系数为95.04%。     

An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain

The present paper is an attempt to integrate a semi-automated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.     

Quarrying and its effect on vegetation cover for a sustainable development using high-resolution satellite image and GIS

Huge vegetal losses caused by unsustainable quarrying practices have limited the role played by vegetation cover in mitigating the global impact of climate change. There is a need for a holistic study that will employ remotely sensed data in GIS domain to determine the extent of the effect of quarrying activities on vegetation cover in the study area. The need for extraordinary details with high accuracy and enhanced imagery has necessitated the use of Geo-Eye-1 satellite imagery with 1-m resolution for 2015. The study was carried out in Ebonyi State where 27 quarry sites were studied in six local government areas where mining activities were operated. The study employed geographical information system, Garmin eTrex GPS receiver and global positioning system. Geographical information was processed using ArcGIS to map the patterns and extent of land use. The findings from the study showed that the visual interpretation of the satellite image confirmed that white patches on the imagery were areas affected by intensified quarrying activities. The very dark green colours were interpreted as forest with no observed human activities. The supervised classification of land use also showed that quarrying activities occupied 0.1% of the study area with a total of 402.855 ha of green cover lost in Ebonyi State due to quarrying operations. Quarrying practices have destroyed arable lands, economic trees and forests in the area. This implies that there is a need for policies to be enforced with strict adherence to sustainable quarrying guidelines and consistent monitoring.     

青藏高原木里矿区及其周边土地覆被变化及景观格局脆弱性响应

矿区开发会导致周边土地覆被及景观格局发生剧烈变化, 但目前对青藏高原典型矿区及其周边土地覆被长时间序列变化缺乏动态监测, 尤其缺乏对景观格局脆弱性响应特征的深入认识, 因此无法针对矿区合理开发和生态修复等提出有效的科学指导。通过遥感技术和土地变化科学研究手段, 以及景观格局脆弱性概念, 对青藏高原北部木里矿区及周边1975 - 2016年土地覆被时空变化和景观格局脆弱性进行分析和评估。结果表明： 木里矿区在2000年后剧烈扩张, 导致周边土地覆被面积缩减, 其中高寒草甸湿地面积损失最大, 其次为其他和高寒草甸。矿区开发对周边生态系统的间接影响效应在逐渐增大, 表现为水域面积减少, 高寒草甸湿地出现退化以及矿区发生少量逆转。受矿区扩张影响, 区域景观格局脆弱性不断增强, 可能对周边生态系统服务功能产生负面影响。因此, 未来矿区的生态修复和规划过程中, 应当优化景观格局, 降低景观格局脆弱性。研究成果可为青藏高原及其他生态脆弱地区的矿区合理开发规划及生态修复等工程提供一定参考。     

Land use and land cover change and implication to watershed degradation by using GIS and remote sensing in the Koga watershed,North Western Ethiopia

Information on use/land cover change is important for planners and decision makers to implement sustainable use and management of resources. This study was intended to assess the land use land cover (LULC) change in the Koga watershed. The MSS of 1973, TM images of 1986, 1995 and 2011 were used together with survey and demographic data to detect the drivers of land cover changes. The result revealed that a remarkable LULC change occurred in the study area for the past thirty eight years. The area of cultivated and settlement has increased by 7054.6 ha, while, grass and bush lands decreased by 4846.5 and 3376 ha respectively. Wetland also declined from 580.2 ha to 68.3 ha. The growing demand for cultivable land and fuel wood were the major causes to the deterioration of grass and bush lands. Hence, the appropriate land use policy should be employed to sustain available resource in the watershed.     

Assessment of spatio-temporal variations in vegetation recovery after the Wenchuan earthquake using Landsat data

The 8.0-magnitude Wenchuan earthquake in 2008 damaged the ecology of northwestern Sichuan, China. This study assessed ecological changes within a few years of the earthquake through satellite observations of vegetation dynamics in the earthquake area. As an ecological indicator, the fractional vegetation cover was extracted using the Normalized Difference Vegetation Index based on multi-year Landsat images and was validated using airborne images. We found that the entire mountainous disaster area had recovered by 68.45 % 3 years after the 2008 earthquake. After rapid recovery of vegetation in 2009, the recovery process slowed. The vegetation recovery rate (VRR) in the area heavily damaged by landslides was slightly lower but nearly that of the entire disaster area. In addition, because of differences in the proportions of soil and rock in the damaged areas, recovery of vegetation in the southwest portion of the study area was slower than in the northeast areas. Topographic analysis of vegetation recovery patterns indicated that damage to vegetation was closely related to slope, while recovery of vegetation was more sensitive to elevation. The landscape analysis showed that the recovery rate (65.21 %) of the excellent vegetation cover type was slower than the overall VRR. This study suggests that vegetation recovery is a slow ecological process and that ecological restoration should be implemented in mountainous regions affected by the earthquake.     

Land subsidence and declining water resources in Quetta Valley, Pakistan

Extensive groundwater withdrawals in urban areas may cause water shortages, land subsidence, and water quality problems. The Quetta Valley is the largest population center in Balochistan province in western Pakistan. This area is arid and groundwater is the main water source for domestic and agricultural use. This work presents global positioning system (GPS) data and assessment of spatial and temporal variations in water levels. GPS data from two stations from mid-2006 to the beginning of 2009 show subsidence rate of 10 cm\year. Nine satellite images from 1975 to 2009 were classified and processed to quantify land cover and land use changes, which highlight an increase in agricultural areas in the central region of the Quetta Valley, as well as reduced vegetation on mountains. These data correspond to gradual temporal changes in water volumes in streams and lakes. Average temperatures have also increased and mean precipitation has decreased during this period. However, the greatest change in this area has been in population growth, which rose from 260,000 in 1975 to 1.2 million in 2010, mainly due to migration of refugees from war-torn neighboring Afghanistan. The Quetta Valley provides a good example for studying the impact of urbanization on water resources.