Forest Biomass and Land Cover Change Assessment of the Margalla Hills National Park in Pakistan Using a Remote Sensing Based Approach

Climate change is one of the greatest threats recently, of which the developing countries are facing most of the brunt. In the fight against climate change, forests can play an important role, since they hold a substantial amount of terrestrial carbon and can therefore affect the global carbon cycle. Forests are also an essential source of livelihood for a remarkably high proportion of people worldwide and a harbor for rich global biodiversity. Forests are however facing high deforestation rates. Deforestation is regarded as the most widespread process of land cover change (LCC), which is the conversion of one land cover type to the other land cover type. Most of this deforestation occurs in developing countries. Agricultural expansion has been reported as the most significant widespread driver of deforestation in Asia, Africa, and Latin America. This deforestation is altering the balance of forest carbon stocks and threatening biodiversity. Pakistan is also a low forest cover country and faces high deforestation rates at the same time, due to the high reliance of local communities on forests. Moreover, it is also the most adversely affected by climate change. Agricultural expansion and population growth have been regarded as the most common drivers of deforestation in Pakistan. Financial incentives such as ‘Reducing Emissions from Deforestation and Forest Degradation, and the Role of Conservation of Forest Carbon, Sustainable Management of Forests and Enhancement of Forest Carbon Stocks’ (REDD+) offer hope for developing countries for not only halting deforestation but also alleviating poverty. However, such initiatives require the estimation of biomass and carbon stocks of the forest ecosystems. Therefore, it becomes necessary that the biomass and carbon potentials of the forests are explored, as well as the LCCs are investigated for identifying the deforestation and forest degradation hit areas. Based on the aforementioned, the following research objectives/sub-objectives were investigated in the MHNP, which is adjoined with the capital city of Pakistan, Islamabad; A) Forest Biomass and Carbon Stock Assessment of Margalla Hills National Park (MHNP) A.1) Aboveground Biomass (AGB) and Aboveground Carbon (AGC) assessment of the Subtropical Chir Pine Forest (SCPF) and Subtropical Broadleaved Evergreen Forest (SBEF) using Field Inventorying Techniques A.2) Exploring linear regression relationship between Sentinel-1 (S1) and Sentinel-2 (S2) satellite data with the AGB of SCPF and SBEF A.3) AGB estimation combining remote sensing and machine learning approach B) LC Classification and Land Cover Change Detection (LCCD) of MHNP for the time-period between 1999 and 2019 B.1) LC Classification for the years 1999, 2009 and 2019 using Machine Learning Algorithm B.2) LCCD of MHNP between 1999 to 2019

Micro-topography associated to forest edges

Forest edges are often defined as the discontinuity between the forest habitat and an adjacent open habitat, thus they are based on a clear difference in the structure of the dominant vegetation. However, beside this very general definition, in the field we can observe a large diversity of edges, with often different kinds of micro-topography features: bank, ditch, stone wall, path, etc. As these elements are rather common in many temperate forest edges, it seems important to start to characterize them more clearly and with consistency. From a set of observations in south-western France, we build a first typology of the micro-topographic elements associated to forest edges. For each of them we describe the process, natural or human induced, at their origin, and according to the literature available, we identify some of their key ecological roles. Banks, generated by the differential erosion between forest and crops along slopes, are especially analyzed since they are the most common micro-topographic element in our region. It offers many micro-habitat conditions in the soil used by a wide range of species, notably by several bee species. More research is required to study in details the importance of such micro-topographic elements

Spatial Dynamics of Forest Cover and Land Use Changes in the Western Himalayas of Pakistan

The current study deals with the mapping and evaluation of forest and land use cover changes in the western Himalayas, Pakistan. These forest types include i) Moist temperate forests ii) Mixed coniferous forests and iii) Sub-tropical broad leaved forests. Moist temperate forest mostly consists of evergreen conifers with some of oaks and deciduous trees. Subtropical pine forest are mostly dominated by Pinus roxburghii. These forest type are mostly mixed by Pinus roxburghii and other coniferous species like Pinus wallichiana at the upper ranges in Dewal, Angoori, Nambal, Aucha and Khanitak etc. The broad-leaved subtropical forests are recorded on the hills and in the lower slopes of Himalaya near Islamabad and Rawalpindi. The high quantity of vegetation index were observed in winter season as compared to summer. The Landsat satellite images of years 1988, 1998, 2008 and 2018 were classified into land-cover units. Vegetation land decreased in the total area whereas the bare land class increased in the total. Water class further reduced and the built- up class increased up in the Murree area, Pakistan

Analyzing Land Cover Change Using Remote Sensing and GIS: A Case Study of Gilgit River Basin, North Pakistan

Mountainous areas of northern Pakistan are rich in biodiversity, glaciers and key watershed of Indus Riversystem which provide ecosystem services for their inhabitants. These regions have experienced extensive deforestationand are presently vulnerable by rapid land cover changes, therefore an effective assessment and monitoring is essentialto capture such changes. The aim of this study is to analyze the observed changes in land cover over a period of thirtynine years, divided into three stages (1976-1999, 1999-2008 and 2008-2015). Four images from Landsat 2Multispectral Scanner System (MSS), Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper andLandsat 8 Operation Land Imager data were obtained to detect land cover change. This study used supervisedclassification-maximum likelihood algorithm in ERDAS imagine to identify land cover changes perceived in GilgitRiver Basin, Pakistan. The result showed that the range land, glaciers, water bodies, built-up/agricultural cover are themajor categories that have been altered by the natural and anthropogenic actions. In 1976, built up/agriculture, rangeland, water bodies and glacier cover was 1.13%, 45.3%, 0.66% and 13.2%, respectively. Whereas in 2015, builtup/agriculture, range land, water bodies and glacier cover was 3.25%, 12.7%, 0.91% and 8.2%, respectively. Thesesland cover shifts posed acute threat to watershed resources. Therefore, a comprehensive watershed resourcemanagement is essential or otherwise, these resources will deplete rapidly and no longer be capable of playing their rolein socioeconomic and sustainable environmental development of the are