Assessment of Fragmentation and Disturbance Patterns in Eastern Ghats: A Case Study in R.V. Nagar Range,Visakhapatnam District,Andhra Pradesh,India

At present the biodiversity in Eastern Ghats is threatened by loss of habitats, exploitation and unscientific management of natural resources, forest fire, biological invasion and other anthropogenic pressures. In this context, we have assessed the forest cover changes, fragmentation and disturbance in the R.V. Nagar Range of Eastern Ghats region, Andhra Pradesh using satellite remote sensing and GIS techniques. Satellite data of IRS-1A LISS II of 1988 and IRS-P6 LISS III of 2006 were assessed for forest cover changes in 1 sq.km grid and generated as Sensitivity Index map. Further the road and settlement buffer of 1000 m was generated to represent Threat Index map. From 1988 to 2006, the forest cover had a total cover loss of 35.2 sq.km and increase in scrub cover by 7.2%. Over all change analysis from 1988 to 2006 with reference to forest cover indicates, negative changes (loss of forest area) accounted for 48.1 sq.km area and positive changes (gain of forest) for an area of 12.1 sq.km of area. The results of the change detection using multi-date satellite imagery suggest degradation in forest cover over two decades, which necessitates the conservation measures in this range with high priority.     

Exploring the spatial and temporal dynamics of land use in Xizhuang watershed of Yunnan, southwest China

Over the last two decades, China has introduced a series of agricultural and forestland use reforms, aiming to feed the largest population in the world and maintain ecological services locally and nationally. This paper studies the impacts of local government-driven reforestation on land use and land cover change, as well as its further impacts on livelihoods of upland farmers in Xizhuang watershed. An analysis of aerial photographs and ASTER satellite imagery from 1987 to 2002, respectively, showed that the forest has significantly increased at the expense of decreasing farmland. However, the monoculture reforestation of pine has caused both biophysical and socio-economic consequences. This case study also shows forestry decentralization in China remains incomplete. Land use and land cover change is also a political economic issue. Some of the reforms designed to protect forest resources have had a negative impact on rural livelihoods.     

Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques

Watershed prioritization has gained importance in natural resources management, especially in the context of watershed management. Morphometric analysis has been commonly applied to prioritization of watersheds. The present study makes an attempt to prioritize sub-watersheds based on morphometric and land use characteristics using remote sensing and GIS techniques in Kanera watershed of Guna district, Madhya Pradesh. Various morphometric parameters, namely linear and shape have been determined for each sub-watershed and assigned ranks on the basis of value/relationship so as to arrive at a computed value for a final ranking of the sub-watersheds. Land use/land cover change analysis of the sub-watersheds has been carried out using multi-temporal data of IRS LISS II of 1989 and IRS LISS III of 2001. The study demonstrates the significant land use changes especially in cultivated lands, open scrub, open forest, water bodies and wastelands from 1989 to 2001. Based on morphometric and land use/land cover analysis, the sub-watersheds have been classified into three categories as high, medium and low in terms of priority for conservation and management of natural resources. Out of the seven sub-watersheds, two sub-watersheds viz., SW1 and SW6 qualify for high priority, whereas SW7 has been categorised as medium priority based on the integration of morphometric and land use change analysis.     

Prioritization of Sub-watersheds in Khanapara–Bornihat Area of Assam–Meghalaya (India) Based on Land Use and Slope Analysis Using Remote Sensing and GIS

Improper utilization of natural resources without any conservation work is the prime cause of the watershed deterioration. Fast developmental activities and population pressure in the hills of Khanapara?CBornihat area near Guwahati city (about 10?km east of Guwahati) results rapid alteration of the land use/land cover in the recent times. This also causes the growth of land use over the unsuitable topography. As a result, there is a general degradation of the natural resources within the area. So, urgent measures have to be adopted to take up the conservation measure for the management of natural resources. Watershed wise conservation is considered to be the most acceptable and convenient approach. In the context of watershed management, watershed prioritization gained importance in natural resource management. The present study makes an attempt to prioritize the sub-watersheds for adopting the conservation measure. The prioritization is based on land use and slope analysis using Remote Sensing and GIS techniques in Khanapara?CBornihat area of Assam and Meghalaya state (India). The study area of 323.17?sq. km is divided into three 5th order, four 4th order and two 3rd order sub-watersheds. Land use/Land cover change analysis of the sub-watersheds has been carried out using multi temporal data of SOI toposheets of 1972 and IRS LISS III imagery of 2006. The study shows the significance changes in land use pattern especially in settlement and forest lands from 1972 to 2006. Slope map of the sub-watersheds prepared from the contour values in the toposheets show the wide variation of slope in the area ranging from 0° to 87°. Based on the extent/nature of land use/land cover changes over time and land use/land cover??slope relationship analysis, the sub-watersheds are classified into three categories as high, medium and low in terms of priority for conservation and management of natural resources.     

Modelling Changes in Land Cover Patterns in Mtunzini,South Africa Using Satellite Imagery

Land is the basic resource that is needed by man in order to survive: It provides humans with living space, nutrition and energy resources. The rapid growth of the human population, climate change and pollution on a catastrophic scale has caused the quality of land resources to be compromised. Remote sensing is a useful tool in land cover change detection providing information to decision makers. The aim of this study was to evaluate land cover changes in the Mtunzini area in South Africa over the past 18 years; determine why changes have occurred and predict land cover patterns for future years. In this study a supervised classification was used to detect land cover classes of the Mtunzini area from 1992 to 2009 using four Landsat images in the time series analysis. The supervised classification had an accuracy of 80.80 % which was used to model land cover changes. Commercial sugar cane and forest plantation classes increased throughout the time series. It was estimated in the modelling procedure that bushland (42.11 %) and bare soil (35 %) would be changed to commercial sugar cane. This is indicative of the expanding agriculture sector in Mtunzini. Natural vegetation is predicted to be disturbed: 18 % of bushland and 15.07 % of dense bush are expected to be replaced by rural dwellings. This is owing to a potential increase in the rural population and a reduced local economic growth. This study highlights the need for increased vigilance of the forestry industry and commercial sugar cane farms which may be encroaching on natural vegetation and livelihoods of local residents. Strategic planning and proper management of natural vegetation types is needed as these land cover types are decreasing rapidly.     

近20年哈尔滨市呼兰区土地利用覆盖变化及驱动分析

本文基于哈尔滨市呼兰区1998—2018年Landsat TM影像数据和社会经济数据,通过ENVI、ArcMap等软件,采用监督分类、土地利用变化模型、典型相关分析法等方法,科学系统地分析了1998—2010、2010—2018、1998—2018年3个不同时段的土地利用覆盖变化特征,并对土地利用覆盖变化驱动因素进行了分析。结果表明,哈尔滨市呼兰区20年间呈居民地和水域面积增加、耕地变化不大、林草不断减少的土地利用覆盖变化格局,且前8年的变化速度和幅度大于后12年。该区土地利用覆盖变化的影响因素包括自然环境因素、社会经济因素及人口因素。     

基于MNDWI特征空间的水体追踪识别方法研究

水体作为国土资源的关键要素,其水体面积变化在水资源调查、变化检测及大型水利设施建设评估等方面具有非常重要的意义.由于区域山体阴影、建筑等因素的干扰影响,带来域内所有湖库水体进行一次性提取的难点,文中以landsat8为数据源,研究提出一种M NDWI+水体追踪识别的方法;并以京津冀区域为例,应用本方法在该区域湖库水体的...     

Changes in landuse/landcover patterns and human population growth in the Lake Chivero catchment,Zimbabwe

The land use and land cover pattern of a region is a consequence of natural and socio-economic factors and their utilization by man in time and space. In this study, we hypothesized that land use and land cover change patterns in the Lake Chivero catchment, Zimbabwe, were related to its human population dynamics. Using nonparametric correlation coefficients (Spearman’s rho, ρ), we found that bareland, cropland and built-up land had positive relations with human population growth of ρ = 0.7, ρ = 0.9 and ρ = 1, respectively. Grassland/shrubland, water and forest, on the other hand, had a negative relationship with human population growth of ρ = ?0.9, ρ = ?0.7 and ρ = ?0.667, respectively. However, these relationships were only significant (p < 0.05) for cropland, grassland/shrubland and built-up land. Human population dynamics in the Lake Chivero catchment could be one of the major drivers of land use and land cover change in the catchment between 1986 and 2014.     

Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities

In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol − all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land management planning, and the implementation of the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD).     

玛河流域景观生态风险评价与时空分异

以玛纳斯河流域作为研究区,结合特殊的干旱区山地-绿洲-荒漠系统(Mountain-Oasis-Desert System简称MODS),综合考虑遥感影像数据光谱信息和纹理特征,将研究区分为耕地、林地、草地、水体、裸地、居民地、工业用地和冰川/永久积雪等8个景观类型,利用FRAGSTATS软件计算景观指数,引入生态风险的指数,将研究区划为低、较低、中、较高、高生态风险区五级,评估其景观格局的生态风险时空变化特征。结果表明:1)1990—2015年间,玛纳斯河流域景观变化主要表现为耕地、建设用地的增加以及水体、冰川/永久积雪面积的缩减;2)玛纳斯河流域的景观生态风险等级空间分布具有明显的差异,较低风险区的面积变化较为明显,低、较低生态的风险区比重有所上升,除此以外,林、草地类型各生态风险的等级所占比重的起伏波动具有明显的差异。建议应当合理地利用土地资源,尽量保护林地、草地等景观脆弱行较低的原生景观类型,禁止为开垦耕地而破坏林地、草地;增加土地的利用效率,更要对高等、较高生态风险区加强监管。     

The nature and possible causes of land cover change (1984 –1996) along a rainfall gradient in southeastern Botswana

Land cover change analysis was undertaken in semi-arid southeastern Botswana. The aim was to determine how remotely sensed data could be applied over time and under different rainfall regimes to help assess the relative significance of biophysical and human factors in causing land cover change in a rapidly evolving developing world context. To this purpose, land cover changes were studied along an east (hardveld)-west (sandveld) gradient of decreasing rainfall and decreasing population density. Three years of Thematic Mapper imagery from 1984, 1994 and 1996, covering the period from the 1980s drought to the 1990s ‘normal’ rainfall regime were analysed using supervised classification techniques. Land cover change analysis revealed that over a large part of the study area the dry and more biophysically vulnerable western sandveld showed greater vegetation recovery than the eastern hardveld with its more productive soils and higher rainfall. Underlying causes behind this apparent reversal of trends are inferred to be mainly socioeconomic in nature and particularly related to higher population density due to the rise of salaried urban occupation opportunities in the hardveld. This work concludes that, while biophysical causes of change are important, the human dimension is regarded as being more significant especially where human factors negate otherwise positive biophysical effects in an agrarian developing country.     

基于TM遥感影像的淮安市土地利用变化分析

随着社会的快速发展,人类活动的日益频繁,地球表面发生了翻天覆地的变化。遥感技术以其独特的优势成为土地利用调查和变化研究的重要技术手段。本文以淮安市1995年和2006年的TM遥感影像为主要数据,依据土地利用类型的光谱特征,采用NDVI,NDWI,NDBI和非监督分类方法分别提取耕地、林地、草地、水体和建筑用地类型,并对提取结果从结构和变化角度进行分析。结果证明:1)依据地物光谱特征,采用不同模型分别提取土地利用类型的方法切实可行;2)淮安市是一个以农用地为主、水资源丰富、城镇化水平较低的地区;在1995~2006年间,耕地、水域和草地分布呈减少的趋势,林地和建筑用地呈不断增加的趋势。     

1975年—2018年白洋淀湿地变化分析

白洋淀湿地生态功能重要、战略地位特殊,研究其时空变化规律具有重要意义。本文基于1975年—2018年间10期Landsat卫星遥感影像,辅以2017年—2018年高分二号（GF-2）卫星遥感影像,在野外考察湿地类型及其覆被特征基础上,人机交互解译获取各期土地利用/覆被分类图,从面积变化、类型转化、景观格局变化方面分析了近43年白洋淀湿地变化时空特征,讨论了影响分析结果的不确定性因素以及湿地变化成因。结果表明：1975年—2018年白洋淀湿地面积总体呈减少趋势,净变化-68.20 km²（-24.83%）。其中,1975年—1990年湿地面积波动性小、基本稳定,1990年—2011年湿地面积持续性减少,2011年—2018年湿地面积呈现增加趋势。湿地与非湿地类型相互转换区域主要分布于淀区南部、西部、北部的水体—水生植物—耕地—建设用地过渡区域。近43年白洋淀湿地景观趋于破碎、复杂和异质。遥感影像选取月份、年份,以及土地利用/覆被分类体系、分类方法,是影响分析结果的主要不确定性因素。气候、水文等自然因素变化,叠加工农业及城镇生活用水、上游水利工程蓄水、地下水开采等人为因素变化,是白洋淀湿地面积减少、趋于干化的成因。     

基于地表类型的山地海绵城市生态建设评估

建设海绵城市是城市雨洪管理的重要举措。但山地海绵城市建设仍在发展探索阶段,并未建立全面的评估体系。目前,山地城市建设未充分利用地表类型信息及评估标准较少结合地形因素。针对此问题,本文基于城市地表覆被类型和地形因素,建立山地海绵城市的生态评估指标。首先获取研究区域两时相地类信息;然后计算地类变化检测结果,并结合高程和坡度评估区域海绵城市建设;最后经评估可知,在两时相间,绿地率增加了0.22%,不透水面率增加了0.46%,建设用地向中地势区间发展,同时获悉其余地类间的变化状况。结果表明,该区域绿地率增加,天然水体保护较好,透水面占比大于不透水面,生态建设与建设用地发展符合山地海绵城市建设原则。     

Reducing landscape heterogeneity for improved land use and land cover (LULC) classification across the large and complex Ethiopian highlands

This paper presents a land use and land cover (LULC) classification approach that accounts landscape heterogeneity. We addressed this challenge by subdividing the study area into more homogeneous segments using several biophysical and socio-economic factors as well as spectral information. This was followed by unsupervised clustering within each homogeneous segment and supervised class assignment. Two classification schemes differing in their level of detail were successfully applied to four landscape types of distinct LULC composition. The resulting LULC map fulfills two major requirements: (1) differentiation and identification of several LULC classes that are of interest at the local, regional, and national scales, and (2) high accuracy of classification. The approach overcomes commonly encountered difficulties of classifying second-level classes in large and heterogeneous landscapes. The output of the study responds to the need for comprehensive LULC data to support ecosystem assessment, policy formulation, and decision-making towards sustainable land resources management.     

Monitoring of deforestation and land use changes (1925–2012) in Idukki district,Kerala, India using remote sensing and GIS

The studies on forest cover change can reveal the status of forests and facilitate for its conservation planning. Idukki is the largest district in the state of Kerala having a total geographical area of 5019 km². The objectives of the present study are to map forest cover in Idukki district using multi-temporal remote sensing data (1975, 1990, 2001 and 2012) and topographical maps (1925), to analyze the trends in deforestation and land use changes. Overall statistics for the period of 1925 indicate that about 4675.7 km² (93.2 %) of the landscape was under forest. The forest cover in 2012 was estimated as 2613.4 km² (52.1 %). Recently, due to the implementation of policies and protection efforts, the rate of deforestation was greatly reduced. The commencement of hydroelectric projects during 1925–1990 responsible for an increase of area under water bodies by inundating other land uses. The long term analysis shows agricultural area been decreasing and commercial plantations been increasing in the district. There has been a significant increase in the area of plantations from 1236.2 km² (1975) to 1317.3 km² (2012).     

Modelling for prediction of global deforestation based on the growth of human population

Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms.     

Tracking desertification on the Mongolian steppe through NDVI and field-survey data

Abstract

Changing environmental and socio-economic conditions make land degradation, a major concern in Central and East Asia. Globally satellite imagery, particularly Normalized Difference Vegetation Index (NDVI) data, has proved an effective tool for monitoring land cover change. This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau. Findings established a significant correlation between same-year field observation (line transects) and NDVI data, enabling an historical land cover perspective to be developed from 1998 to 2006. Results show variable land cover patterns in Mongolia with a 16% decrease in plant density over the time period. Decline in cover identified by NDVI suggests degradation; however, continued annual fluctuation indicates desertification – irreversible land cover change – has not occurred. Further, in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources. In combination of the two research methods – remote sensing and field surveys – strengthen findings and provide an effective way to track desertification in dryland regions.     

Snow and forest cover assessment of uttaranachal state using irs 1c wifs data

In this study, IRS 1C WiFS data have been used for the assessment of two natural resources i.e. forest cover and snow cover. These two resources have a great role to play in various hydrological studies such as floods, soil erosion and water pollution etc. Therefore their assessment is very useful in various hydrological studies and management of these resources. The assessment of snow and forest cover have been made on the basis of multispectral classification and classification of NDVI images. Newly created Uttaranchal state has been taken as the study area. These two resources have been estimated for all the thirteen districts of the state separately. The forest cover area estimated in this study is compared with the available data sets of Forest Survey of India (FSI). The estimated forest is 52%, whereas the forest cover reported by the FSI is 44.5% of the total geographical area of the state. The snow cover is estimated for the period after winter season i.e. maximum snow cover and before next winter season i.e. minimum snow cover. It is found that one quarter of the state is under snow cover covering six districts of the state. As such no estimate of snow cover at regional scale has been made so far therefore comparison of the present assessment could not be made.     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.