Impact of Pastoral Practices on Forest Cover and Regeneration in the Outer Fringes of Kedarnath Wildlife Sanctuary,Western Himalaya

The study reports the impact of migratory livestock in the buffer area of Kedarnath Wildlife Sanctuary. The cumulative impacts of livestock grazing, fuel wood extraction and other anthropogenic pressures on forest cover in and around camping sites have been analyzed using satellite data and field observations. Multi-date satellite data were used to map the forest cover around 16 seasonal livestock camps. An annual loss of about 7.25 ha of forest covers during 1976–1990, 13.57 ha during 1990–1999 and 11.46 ha during 1999–2005 are recorded. A loss of 108.53 ha of forestland has been estimated during 1976–1990, about 122.16 ha during 1990–1999 and 68.78 ha during 1999–2005. It is also observed that many of the isolated camping sites are now connected due to loss of vegetation. Phytosociological analysis indicates that the number of seedlings and saplings in three species of Quercus (Q. leucotrichophora, Q. floribunda and Q. semecarpifolia) as compared to mature tress is very less around cattle camping sites. The ratio of number of sapling with seedling and trees indicates that the status of sapling is nil to very poor, an indication of loss of saplings due to either trampling or grazing.     

Land cover dynamics monitoring with Landsat data in Kunming,China: a cost-effective sampling and modelling scheme using Google Earth imagery and random forests

Changes in forest composition impact ecological services, and are considered important factors driving global climate change. A hybrid sampling method along with a modelling approach to map current and past land cover in Kunming, China is reported. MODIS land cover (2001–2011) data-sets were used to detect pixels with no apparent change. Around 3000 ‘no change points’ were systematically selected and sampled using Google Earth’s high-resolution imagery. Thirty-five per cent of these points were verified and used for training and validation. We used Random forests to classify multi-temporal Landsat imagery. Results show that forest cover has had a net decrease of 14385?ha (1.3% of forest area), which was primary converted to shrublands (11%), urban and barren land (2.7%) and agriculture (2.5%). Our validation indicates an overall accuracy (Kappa) of 82%. Our methodology can be used to consistently map the dynamics of land cover change in similar areas with minimum costs.     

Quantifying Four Decades of Changes in Land Use and Land Cover in India’s Kailash Sacred Landscape: Suggested Option for Priority Based Patch Level Future Forest Conservation

Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land.     

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).     

Modeling for Prediction of Land Cover Changes Based on Bio-physical and Human Factors in Zagros Mountains, Iran

The rapid population growth and ongoing development activities has resulted in natural resources demolition. However, the dynamics of the natural resources in relation to different biophysical and socio-economic factors are still remains poorly understood. The present study investigates the basic natural resources i.e. forest, rangeland and surface water bodies’ status using satellite data for the years 1990, 1998, and 2006, and their change detection in relation to biophysical and socio-economic factors. Monitoring land-use/cover change detection using remotely sensed data has been a well recognized technique. The analysis of change detection revealed eleven important land cover changes, which occurred during the past 16 years (1990–2006) in the region. The rate of land cover change was observed to vary across the sub periods and a general decline of forest cover and increase in rangelands and water bodies was observed. Logistic regression model was employed to analyze the relationship between changes and explanatory factors. The land cover change results and logistic models developed in this study are useful in supporting natural resources management efforts and provide useful information for managers/policy makers in formulation of sustainable management strategies for the region.     

Implications of land use change on the national terrestrial carbon budget of Georgia

Background  

Globally, the loss of forests now contributes almost 20% of carbon dioxide emissions to the atmosphere. There is an immediate need to reduce the current rates of forest loss, and the associated release of carbon dioxide, but for many areas of the world these rates are largely unknown. The Soviet Union contained a substantial part of the world's forests and the fate of those forests and their effect on carbon dynamics remain unknown for many areas of the former Eastern Bloc. For Georgia, the political and economic transitions following independence in 1991 have been dramatic. In this paper we quantify rates of land use changes and their effect on the terrestrial carbon budget for Georgia. A carbon book-keeping model traces changes in carbon stocks using historical and current rates of land use change. Landsat satellite images acquired circa 1990 and 2000 were analyzed to detect changes in forest cover since 1990.     

Development of National Database on Long-term Deforestation in Sri Lanka

Sri Lanka is one of the biodiversity hotspots of the world. This study has utilized satellite remote sensing and GIS techniques to generate a nation-wide database on forests, forest types and land use/land cover of Sri Lanka. Spatial assessment of forest cover changes was carried out for the periods 1976–1985, 1985–1994, 1994–2005 and 2005–2014. The landscape fragmentation analysis has carried out to calculate the spatial and temporal patterns of forest. Land use/land cover map was prepared representing seven classes in 2014. The plantations occupy a large area (34.2%) followed by forests (33.4%) and agriculture (26.1%) in 2014. During the period of 1976–2014, the forest has been decreased by 5.5%. From 1976 to 1985 forest recorded a loss at an annual rate of 0.49%. This annual rate decreased to 0.01% during 2005–2014 indicates declining trend of deforestation and effective conservation measures. The study found deforestation hotspots in south east and northern most parts of the Sri Lanka. Total number of patches estimated has increased from 15193 in 1976 to 16136 in 2014. The study has found that main causes of deforestation in Sri Lanka were due to expansion of agriculture and plantations. The extent of change detected in the study through geospatial techniques has significance to the forest ecology and management of natural landscapes in Sri Lanka.     

遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km² in 1990 to 3 794.9 km² in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).     

Delineation of soil associations for a part of tamil nadu by digital processing of landsat multispectral data

The utility of Landsat multispectral data for small scale soil mapping has been demonstrated in this study. The scene used for the study has path-row number 153-054 of Landsat-1 dated 26th February, 1973 covering parts of Ramnad, Tirunelveli and Kanyakumari districts of Tamil Nadu. Associations of sub groups have been delineated on 1 : 250,000 scale using computer-aided multispectrcl data analysis system (M-DAS). Soil map prepared using the computer has been found to be camparable with the soil map prepared by conventional methods at the same scale. Apart from the soil associations, other land use/land cover classes like water bodies forest/scrub/hiliy areas, crcps etc. were also categorised in the colour coded soil map.     

Capturing ephemeral forest dynamics with hybrid time-series and composite mapping in the Republic of Panama

Measuring and progressing toward international goals of curbing deforestation and improving livelihoods of people who depend on forests requires nuanced understanding of forests and the processes surrounding deforestation and degradation. Despite rapid improvements in Earth Observation technology, monitoring of tropical forests remains hindered by persistent cloud cover, heterogeneous landscapes, long wet seasons, and small and ephemeral clearings masked by rapid growth. A hybrid method is presented that combines elements of both time-series and compositing approaches to best overcome these obstacles to map forest cover and change in the Republic of Panama based on Landsat imagery. The resulting Panama Vegetation-Cover Time-Series (PVCTS) maps depict forest cover in Panama from 1990 to 2016 at 30 m resolution. Acknowledging the fuzzy boundary between forest and non-forest classes, these maps employ a hierarchical classification scheme that reflects the natural process of regeneration and can accommodate different definitions of forest and deforestation. Classification accuracy is 97–98 % between forest/non-forest categories and 76–81 % for deforestation events. The maps show a slight greening of Panama from 1990 to 2016 caused by expansion of young secondary growth. The annual rate of deforestation in mature forest has remained around -0.6 %/yr, although young forests have matured at a similar rate such that there is no net loss of forest. While estimates of total forest cover are similar to official national estimates depending on forest definition, there is little agreement in location of deforestation events.     

The Forest Types and Ages Cleared for Land Development in Puerto Rico

On the Caribbean island of Puerto Rico, forest, urban/built-up, and pasture lands have replaced most formerly cultivated lands. The extent and age distribution of each forest type that undergoes land development, however, is unknown. This study assembles a time series of four land cover maps for Puerto Rico. The time series includes two digitized paper maps of land cover in 1951 and 1978 that are based on photo interpretation. The other two maps are of forest type and land cover and are based on decision tree classification of Landsat image mosaics dated 1991 and 2000. With the map time series we quantify land-cover changes from 1951 to 2000; map forest age classes in 1991 and 2000; and quantify the forest that undergoes land development (urban development or surface mining) from 1991 to 2000 by forest type and age. This step relies on intersecting a map of land development from 1991 to 2000 (from the same satellite imagery) with the forest age and type maps. Land cover changes from 1991 to 2000 that continue prior trends include urban expansion and transition of sugar cane, pineapple, and other lowland agriculture to pasture. Forest recovery continues, but it has slowed. Emergent and forested wetland area increased between 1977 and 2000. Sun coffee cultivation appears to have increased slightly. Most of the forests cleared for land development, 55%, were young (1-13 yr). Only 13% of the developed forest was older (41-55+ yr). However, older forest on rugged karst lands that long ago reforested is vulnerable to land development if it is close to an urban center and unprotected.     

Spatial modeling and validation of forest cover change in Kanakapura region using GEOMOD

Deforestation is recognized as one of the most significant components in LULCC and global changes scenario. It is imperative to assess its trend and the rate at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. Present study was taken up in Kanakapura and surrounding areas located on the fringes of Western Ghats biodiversity hot-spots. Temporal satellite data from Landsat was classified into forest cover maps. Drivers of forest cover changes such as roads and settlements were used in order to create predicted map of the region using GEOMOD tool in Idrisi Andes. The predicted map was then validated using actual land cover map of same year prepared from Landsat data. The validated map was found to be 84.26 % accurate. The validation was also tested using ROC approach which was found to be 0.614. The model was then further extended to predict forest cover losses for year 2015. The results highlight ongoing deforestation in the areas adjoining Western Ghats. It also presents an application of the tool and the validation methods which can be used in predictive modeling related studies.     

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.     

Measures of spatio-temporal accuracy for time series land cover data

Remote sensing is a useful tool for monitoring changes in land cover over time. The accuracy of such time-series analyses has hitherto only been assessed using confusion matrices. The matrix allows global measures of user, producer and overall accuracies to be generated, but lacks consideration of any spatial aspects of accuracy. It is well known that land cover errors are typically spatially auto-correlated and can have a distinct spatial distribution. As yet little work has considered the temporal dimension and investigated the persistence or errors in both geographic and temporal dimensions. Spatio-temporal errors can have a profound impact on both change detection and on environmental monitoring and modelling activities using land cover data. This study investigated methods for describing the spatio-temporal characteristics of classification accuracy. Annual thematic maps were created using a random forest classification of MODIS data over the Jakarta metropolitan areas for the period of 2001–2013. A logistic geographically weighted model was used to estimate annual spatial measures of user, producer and overall accuracies. A principal component analysis was then used to extract summaries of the multi-temporal accuracy. The results showed how the spatial distribution of user and producer accuracy varied over space and time, and overall spatial variance was confirmed by the principal component analysis. The results indicated that areas of homogeneous land cover were mapped with relatively high accuracy and low variability, and areas of mixed land cover with the opposite characteristics. A multi-temporal spatial approach to accuracy is shown to provide more informative measures of accuracy, allowing map producers and users to evaluate time series thematic maps more comprehensively than a standard confusion matrix approach. The need to identify suitable properties for a temporal kernel are discussed.     

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.     

Deforestation and fragmentation of seasonal tropical forests in the southern Yucatán,Mexico (1990–2006)

The southern Yucatán (SY) has been recognized as a hotspot of biodiversity with great risk of deforestation. Land change analysis, based on classified Landsat TM and ETM?+?satellite imagery (1990, 2000 and 2006), was used to estimate the annual deforestation rates of 141 land management units of the SY, and spatial patterns of forest fragmentation around and within the Calakmul Biosphere Reserve (CBR), which comprises approximately one-third of the region. Results indicate a decrease in annual deforestation rates over 1990–2006, from 0.15% year^?1 to 0.06% year^?1, but with significant sub-regional variations in the quantity and rate of forest loss. Despite a decline in deforestation during this period, there was considerable fragmentation both inside and outside the CBR. While population pressures and the expansion of pasture have caused deforestation across the region, agricultural intensification, diversified income strategies and reserve conservation may have contributed to reduced forest loss during the study period.     

3D Visualization for the Analysis of Forest Cover Change

Abstract

Visualization techniques have been developed to recreate natural landscapes, but little has been done to investigate their potential for illustrating land cover change using spatio‐temporal data. In this work, remote sensing, geographic information systems (GIS) and visualization techniques were applied to generate realistic computer visualizations depicting the dynamic nature of forested environments. High resolution digital imagery and aerial photography were classified using object‐oriented methods. The resulting classifications, along with preexisting land cover datasets, were used to drive the correct placement of vegetation in the visualized landscape, providing an accurate representation of reality at various points in time. 3D Nature's Visual Nature Studio was used to construct a variety of realistic images and animations depicting forest cover change in two distinct ecological settings. Visualizations from Yellowstone National Park focused on the dramatic impact of the 1988 fire upon the lodgepole pine forest. For a study area in Kansas, visualization techniques were used to explore the continuous human‐land interactions impacting the eastern deciduous forest and tallgrass prairie ecotone between 1941 and 2002. The resulting products demonstrate the flexibility and effectiveness of visualizations for representing spatio‐temporal patterns such as changing forest cover. These geographic visualizations allow users to communicate findings and explore new hypotheses in a clear, concise and effective manner.     

深圳市30年土地利用时空变化及驱动力分析

利用1980~2010年时间序列遥感影像,利用土地变化的变化率、变化贡献率和转移矩阵,从时间和空间上分析了土地利用/土地覆盖的变化特征,并结合单因子相关分析和主成分分析等方法,探讨深圳市土地利用变化的驱动因子。结果显示,30年来深圳市的土地利用发生了巨大变化:城乡用地扩张剧烈,增加了55 077.24 hm2,增长率为265.19%;耕地、林地、水域面积迅速减少,耕地减少33 949.17 hm2,减少率为73.93%。研究时段内,人类活动增强以及影响范围扩大是引起深圳市城乡用地急速增长和耕地下降的主因,且土地利用变化受社会经济驱动力的影响逐步增强。     

Remote Sensing and Geographical Information System for canopy cover mapping

Availability of remote sensing data from earth observation satellites has made it convenient to map and monitor land use/land cover at regional to local scales. A land cover map is very critical for a various planning activities including watershed planning. The spectral and spatial resolutions are major constraints for mapping the crop resources at microlevel. The cropping pattern zones have been mapped using the false color composite, physiography, irrigation and toposheets. The IRS LISS-III data is classified into various categories depending on spectral reflectance from crop canopy and are overlaid on cropping zones map. The re-classified resultant map provides land use/land cover information including dominant cropping systems. The canopy cover is estimated monthly considering the crop calendar for the area.     

Forest cover monitoring using remote sensing and GIS — A case study in Dhaulkhand range of Rajaji National Park,Uttar pradesh

Rajaji National Park in U.P. is a protected area where large number of nomad population live within the park area. Their dependence on the forest for cattle rearing and firewood has caused degradation of the forests. Proximity to settlements outside the park further adds to the problems. In the present study, forest cover and river, bed changes have been attempted by using temporal aerospace data of the year 1960 and 1993. Subsequently, PAMAP GIS package has been used for the change detection analysis. The study indicates that the land cover changes are mainly due to biotic factors. Some of the important changes in forest cover are: (i) transformation of mixed forest to scrub forest in 67 ha (ii) the sal mixed and mixed sal forest categories have replaced sal forest in 262 ha (iii) significant increase in forest plantation i.e. 2075 ha in the year 1960 to 3793 ha in 1993 (iv) eighteen times increase in Chirpine area, it increased from 13 ha in 1960 to 230 ha in 1993. The land cover changes in 6663 ha (45%) out of 14962 ha of the study area. The consequential changes in the river beds due to the change in the forest cover was also analyzed. During this period river beds with boulders have increased by 87 ha. These river bed changes include lengthening and broadening of river and change in river course.