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.     

Growing stock estimation through stratified sampling on satellite remote sensing data

Aerial photographs are being extensively used for forest surveys i.e. forest cover type mapping, assessment of growing stock, estimation of area, vegetation studies, etc. Satellite remote sensing technology offers new possibilities and scope for achieving some of the above applications with higher accuracy and reliability. The assessment of growing stock through subjective stratification has also become possible with increase in spatial and spectral resolution. In the present study, the LANDSAT TM FCC (1966) has been visually interpreted on the basis of tonal characteristics. Stratified random sampling method has then used for determination of number of sample units for collection of ground Inventory data. Using regression equations, the volume per hectare of individual forest cover types were calculated. Satellite remote sensing data has been used for initial stratification, distribution of sample plots and calculation of area under various forest cover types. Estimate has been made for available commecial and non-commercial growing stocks in the study area.     

The dynamics in the distribution of mangrove forests in Pichavaram,South India – perception by user community and remote sensing

This study aims to monitor the forest cover of Pichavaram mangroves, South India over a period of 40 years using remote sensing, and to record the status of mangroves as perceived by the local community. Out of 1471 ha of total reserved forest area, mangroves occupy 906 ha. The remote sensing maps show that there was a loss of 471 ha from 1970 to 1991 and a gain of 531 ha in 2011. Nearby 20 hamlets depend on mangroves for their livelihood. A village survey conducted at Pichavaram shows that more than 90% of the local community is well aware of the prevailing species, their importance especially after the 2004 tsunami and the impact of management practices, increased rainfall and contribution of local community in the recent increased area of mangroves. The same can be noticed from the high-resolution IKONOS image showing the artificial canal network in the restored region and from rainfall records.     

Application of remote sensing technology for Impact Assessment of Watershed Development Programme

The current study was taken up to investigate the utility of remote sensing and GIS tools for evaluation of Integrated Wasteland Development Programme (IWDP) implemented during 1997–2001 in Katangidda Nala watershed, Chincholi taluk, Gulbarga district, Karnataka. The study was carried out using IRS 1C, LISS III data of December 11, 1997 (pre-treatment) and November 15, 2002 (post-treatment) covering the watershed to assess the changes in land use / land cover and biomass that have changed over a period of five years (1997–2002). The images were classified into different land use/land cover categories using supervised classification by maximum likelihood algorithm. They were also classified into different biomass levels using Normalized Difference Vegetation Index (NDVI) approach. The results indicated that the area under agriculture crops and forest land were increased by 671 ha (5.7%) and 1,414 ha (11.94%) respectively. This is due to the fact that parts of wastelands and fallow lands were brought into cultivation. This increase in the area may be attributed to better utilization of surface and ground waters, adoption of soil and water conservation practices and changes in cropping pattern. The area under waste lands and fallow lands decreased by 1,667 ha (14.07%) and 467 ha (3.94%), respectively. The vegetation vigour of the area was classified into three classes using NDVI. Substantial increase in the area under high and low biomass levels was observed (502 ha and 19 ha respectively). The benefit-cost analysis indicates that the use of remote sensing and GIS was 2.2 times cheaper than the conventional methods. Thus, the repetitive coverage of the satellite data provides an excellent opportunity to monitor the land resources and evaluate the land cover changes through comparison of images for the watershed at different periods.     

Assessment and monitoring of estuarine mangrove forests of Goa using satellite remote sensing

The present study highlights the application of satellite remote sensing in the assessment and monitoring of the mangrove forests along the coastline in Goa state of India. Based on onscreen visual interpretation techniques various land use and land cover classes have been mapped and classified. An attempt has been made to analyse changes in the mangrove forest cover from 1994 to 2001 using IRS-1B LISS-II and IRS-1D LISS-III data. An increase in the mangrove vegetation in the important estuaries has been found during 1994 and 2001. During this period, the mangrove forest increased by 44.90 per cent as a result of increased protection and consequent regeneration. Plantation of mangrove species has been raised in 876 ha (1985 to 1997) by the State Forest Department¨     

Land use/land cover mapping and change detection in part of eastern ghats of tamil nadu using remote sensing and GIS

In the present study an attempt has been made to map land use/land cover and change detection analysis in Kolli hill, part of Eastern Ghats of Tamil Nadu, using remote sensing and GIS. About 467 ha increase has been observed in single crop category and about 434 ha decrease has been observed in land with or without scrub category. Majority of the area (13639 ha) is under scrubland. Lesser changes could be noticed in double crop, plantation and barren/rocky categories. Necessary measures should be taken to utilize the scrubland and to prevent the conversion of cropland into scrubland. The identified wastelands, which are suitable for agriculture, have to be utilized optimally to improve the economy of the people.     

Soil Loss Mapping for Sustainable Development and Management of Land Resources in Warora Tehsil of Chandrapur District of Maharashtra: An Integrated Approach Using Remote Sensing and GIS

The study area is characterized by low and fluctuating rainfall pattern, thin soil cover, predominantly rain-fed farming with low productivity coupled with intensive mining activities, urbanization, deforestation, wastelands and unwise utilization of natural resources causing human induced environmental degradation and ecological imbalances, that warrant sustainable development and optimum management of land resources. Spatial information related to existing geology, land use/land cover, physiography, slope and soils has been derived through remote sensing, collateral data and field survey and used as inputs in a widely used erosion model (Universal Soil Loss Equation) in India to compute soil loss (t/ha/yr) in GIS. The study area has been delineated into very slight (<5 t/ha/yr), slight (5–10 t/ha/yr), moderate (10–15 t/ha/yr), moderately severe (15–20 t/ha/yr), severe (20–40 t/ha/yr) and very severe (>40 t/ha/yr) soil erosion classes. The study indicate that 45.4 thousand ha. (13.7% of TGA) is under moderate, moderately severe, severe and very severe soil erosion categories. The physiographic unit wise analysis of soil loss in different landscapes have indicated the sensitive areas, that has helped to prioritize development and management plans for soil and water conservation measures and suitable interventions like afforestation, agro-forestry, agri-horticulture, silvipasture systems which will result in the improvement of productivity of these lands, protect the environment from further degradation and for the ecological sustenance.     

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.     

基于北京二号与地理国情数据的林地提取

由于地理国情林地数据不包含实地面积小于400 m²的树木或四旁单排林,若仅利用地理国情的林地数据统计区域森林覆盖率,将对四旁树面积较大地区的林地统计结果产生较大误差。为提取区域内准确的林地覆盖与空间分布状况,本文借助地理国情地表覆盖数据,提出了一种基于北京二号高分辨率遥感影像的林地提取方法。首先,根据遥感影像光谱特征,将研究区按植被、道路、铁路、建筑用地进行地类划分,并基于遥感影像进行各地类的样本提取,通过可分离检验的样本利用最大似然分类提取研究区内植被覆盖范围;然后,借助地理国情地表覆盖数据,使用叠置分析剔除误分、错分地类,得到区域林地的空间分布。试验结果表明：(1)研究区内林地覆盖率为20.3%,尚未满足北京新一轮林地规划需求;(2)地理国情地表覆盖数据内林地面积占提取林地总面积的54.03%,说明在部分地区使用本文方法对地理国情林地数据进行补充是有必要的。通过将试验结果与遥感影像进行目视比对并结合外业调查结果发现,提取的林地空间分布情况与实际分布基本相符。本文为地理国情的应用提供了一种新方法,研究结果可辅助区域的绿色发展规划,有助于构建科学的生态空间格局。     

Impact Assessment of Watershed Programme Through Remote Sensing and Geographical Information System

Impact assessment of watershed development activity assumes greater importance in present day agriculture. Considering the ability of remote sensing technology in watershed monitoring and impact assessment, a study was carried out to investigate the Impact Assessment of Karnataka Watershed Development Project (DANIDA) in Koralahallihalla Sub watershed in Sindagi taluk of Bijapur district in Northern Karnataka using satellite data of two periods i.e., IRS 1?C, LISS-III data of 30 December, 1997 (pre-treatment) and IRS P6, LISS-III data of 17 December, 2004 (post-treatment). The land use/land cover map was derived from the supervised classification. The results revealed that there has been no major shift in cropping patterns over a period of 7?years (1997?C2004). However, rabi cropped area has decreased drastically (187?ha), which might be due to the continuous droughts that occurred during the implementation period. On the other hand, kharif and double cropped area have increased marginally (103?ha and 96?ha, respectively). Increase in double cropped area showed that there was increase in irrigated land, which were earlier being used as rainfed and wastelands turned in to cultivated lands as seen in scrub lands and rabi cropped areas of the sub watershed. Wastelands in the sub-watershed has decreased marginally (36?ha). The vegetation vigour of the sub-watershed has been derived from the NDVI maps of both the periods. These NDVI maps indicate that there was a significant change in biomass status of the sub watershed. The vegetation vigour of the area was classified into three classes using NDVI. Substantial increase in the area under high and low biomass levels was observed (319?ha and 77?ha, respectively). The benefit-cost analysis indicates that the use of remote sensing technology was 2 times cheaper than the conventional methods. Thus, the repetitive coverage of the satellite data provides an excellent opportunity to monitor the land resources and evaluate the land cover changes through comparison of images for the watershed at different periods.     

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).     

Temporal studies of land use/land cover in varaha river basin, andhra pradesh, india

Land use/land cover investigation have been carried out in Varaha river basia (VRB) using remote sensing data of 1986 and 1992 and the changes in land use/land cover during the period are estimated Visual interpretation techniques have been followed to delineate various land use/laad cover categories It is inferred that the land use/land cover pattern of the area is controlled by local topography, climate and resourees, The tesults revealed significant changes in the area of built-up land irrigated land, plantation degraded forest and upland over a period of six years.     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

Monitoring of forest cover type and landuse classes through remote sensing techniques

Ranikhet tahsil being situated in mountaineous region of the Himalaya has been influenced by fast changes in forest cover and landuse during the recent past. Remote sensing technique has been employed to monitor the changes in forest cover and imporant landuse classes. Landsat MSS (FCC) and Landsat TM (FCC) of 1972 and 1986 respectively has been visually interpreted. The study highlights the potential of remote sensing techniques for monitoring the changes in forest cover and land use classes.     

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.     

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.     

像素级和对象级高分辨率遥感图像变化检测分析

高分辨率遥感图像具有丰富的纹理信息,而像素级变化检测方法主要分析图像的光谱信息,导致将像素级变化检测方法用于高分辨率遥感图像具有一定的局限性。因此,本文提出了一种像素级与对象级相结合的高分辨率遥感图像变化检测方法,解决了像素级与对象级变化检测方法中存在的椒盐现象、误检等问题。首先,结合高分辨率遥感图像的多维特征,构建遥感图像变化检测模型;其次,利用随机森林分类器对图像进行分类,得到像素级变化检测结果;最后,将像素级变化检测结果与图像对象分割结果进行融合,得到图像变化区域和不变区域。试验结果表明,该算法具有较高的准确率和检测精度。     

基于变化向量分析（CVA）的土地利用／覆盖变化动态监测（Ⅱ）—变化类型的确定方法

以光谱直接比较为基础的变化向量分析法是一种非常有效的土地利用／覆盖变化动态监测方法，在双窗口变步长阈值搜寻方法确定变化和非变化像元的基础上，提出了参考图像分类并结合变化向量方向余弦最小距离分类的变化类型确定方法，同时应用该方法在北京市海淀区进行了实验研究，得到了较为理想的结果。变化类型的判断精度达到70％以上，显示了新方法的优越性和技术可行性。