Faisal Mueen Qamer

Measuring impacts of community forestry program through repeat photography and satellite remote sensing in the Dolakha district of Nepal.

During the 1990s community-based forest management gained momentum in Nepal. This study systematically evaluates the impacts that this had on land cover change and other associated aspects during the period 1990-2010 using repeat photography and satellite imagery in combination with interviews with community members. The results of the study clearly reflect the success of community-based forest management in the Dolakha district of the mid-hills of Nepal: during the study period, the rate of conversion of sparse forest into dense forest under community-based management was found to be between 1.13% and 3.39% per year. Similarly, the rate of conversion of non-forest area into forest was found to be between 1.11% and 1.96% per year. Community-based forest management has resulted in more efficient use of forest resources, contributed to a decline in the use of slash-and-burn agricultural practices, reduced the incidence of forest fires, spurred tree plantation, and encouraged the conservation and protection of trees on both public and private land. The resulting reclamation of forest in landside areas and river banks and the overall improvement in forest cover in the area has reduced flash floods and associated landslides.

Integration of WorldView-2 and airborne LiDAR data for tree species level carbon stock mapping in Kayar Khola watershed, Nepal

Abstract Integration of WorldView-2 satellite image with small footprint airborne LiDAR data for estimation of tree carbon at species level has been investigated in tropical forests of Nepal. This research aims to quantify and map carbon stock for dominant tree species in Chitwan district of central Nepal. Object based image analysis and supervised nearest neighbor classification methods were deployed for tree canopy retrieval and species level classification respectively. Initially, six dominant tree species ( Shorea robusta, Schima wallichii, Lagerstroemia parviflora, Terminalia tomentosa, Mallotus philippinensis and Semecarpus anacardium ) were able to be identified and mapped through image classification. The result showed a 76% accuracy of segmentation and 1970.99 as best average separability. Tree canopy height model (CHM) was extracted based on LiDAR’s first and last return from an entire study area. On average, a significant correlation coefficient ( r ) between canopy projection area (CPA) and carbon; height and carbon; and CPA and height were obtained as 0.73, 0.76 and 0.63, respectively for correctly detected trees. Carbon stock model validation results showed regression models being able to explain up to 94%, 78%, 76%, 84% and 78% of variations in carbon estimation for the following tree species: S. robusta, L. parviflora, T. tomentosa, S. wallichii and others (combination of rest tree species).

Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan

The Himalayan mountain forest ecosystem has been degrading since the British ruled the area in the 1850s. Local understanding of the patterns and processes of degradation is desperately required to devise management strategies to halt this degradation and provide long-term sustainability. This work comprises a satellite image based study in combination with national expert validation to generate sub-district level statistics for forest cover over the Western Himalaya, Pakistan, which accounts for approximately 67% of the total forest cover of the country. The time series of forest cover maps (1990, 2000, 2010) reveal extensive deforestation in the area. Indeed, approximately 170,684 ha of forest has been lost, which amounts to 0.38% per year clear cut or severely degraded during the last 20 years. A significant increase in the rate of deforestation is observed in the second half of the study period, where much of the loss occurs at the western borders along with Afghanistan. The current study is the first systematic and comprehensive effort to map changes to forest cover in Northern Pakistan. Deforestation hotspots identified at the sub-district level provide important insight into deforestation patterns, which may facilitate the development of appropriate forest conservation and management strategies in the country.

Deforestation trends and spatial modelling of its drivers in the dry temperate forests of northern Pakistan — A case study of Chitral

Deforestation is a major environmental challenge in the mountain areas of Pakistan. The study assessed trends in the forest cover in Chitral tehsil over the last two decades using supervised land cover classification of Landsat TM satellite images from 1992, 2000, and 2009, with a maximum likelihood algorithm. In 2009, the forest cover was 10.3% of the land area of Chitral (60,000 ha). The deforestation rate increased from 0.14% per annum in 1992–2000 to 0.54% per annum in 2000–2009, with 3,759 ha forest lost over the 17 years. The spatial drivers of deforestation were investigated using a cellular automaton modelling technique to project future forest conditions. Accessibility (elevation, slope), population density, distance to settlements, and distance to administrative boundary were strongly associated with neighbourhood deforestation. A model projection showed a further loss of 23% of existing forest in Chitral tehsil by 2030, and degradation of 8%, if deforestation continues at the present rate. Arandu Union Council, with 2212 households, will lose 85% of its forest. Local communities have limited income resources and high poverty and are heavily dependent on non-timber forest products for their livelihoods. Continued deforestation will further worsen their livelihood conditions, thus improved conservation efforts are essential.

Forest Condition Monitoring Using Very-High-Resolution Satellite Imagery in a Remote Mountain Watershed in Nepal

Satellite imagery has proven extremely useful for repetitive timeline-based data collection, because it offers a synoptic view and enables fast processing of large quantities of data. The changes in tree crown number and land cover in a very remote watershed (area 1305 ha) in Nepal were analyzed using a QuickBird image from 2006 and an IKONOS image from 2011. A geographic object-based image analysis (GEOBIA) was carried out using the region-growing technique for tree crown detection, delineation, and change assessment, and a multiresolution technique was used for land cover mapping and change analysis. The coefficient of determination for tree crown detection and delineation was 0.97 for QuickBird and 0.99 for IKONOS, calculated using a line-intercept transect method with 10 randomly selected windows (1×1 ha). The number of tree crowns decreased from 47,121 in 2006 to 41,689 in 2011, a loss of approximately 90 trees per month on average; the area of needle-leaved forest was reduced by 140 ha (23%) over the same period. Analysis of widely available very-high-resolution satellite images using GEOBIA techniques offers a cost-effective method for detecting changes in tree crown number and land cover in remote mountain valleys; the results provide the information needed to support improved local-level planning and forest management in such areas.

Prediction of Kashmir markhor habitat suitability in Chitral Gol National Park, Pakistan

The Kashmir markhor, Capra falconeri cashmiriensis, is classified as endangered throughout its range because of habitat loss, unsustainable hunting and competition with domestic livestock. We investigated environmental factors influencing species distribution in Chitral Gol National Park (CGNP) based on the ‘presence-only’ dataset and predicted the potential distribution of markhor in order to compute a habitat suitability (HS) map using ecological niche factor analysis (ENFA). Kashmir markhor presence-only data was recorded for a period of four years during 2003–2007 from 487 point locations in summer, spring and winter. The geographical position of animals and the related topographic and habitat variables were used to accurately assess species occurrence within the study area and to predict its distribution. ENFA is used to describe distribution patterns and to identify key variables influencing the ecological niche of markhor. The ENFA model revealed that markhor occurred at a mean elevation of 2818 m with a mean slope of 33.4°. The species requirements seem different from the average habitat conditions available in the study area. Whereas the specialisation factor indicated some specific habitat requirements of markhor, it was found that they still occupied a wider ecological niche. The model suggested that markhor avoid higher elevations but showed a strong relationship with comparatively steep slopes. ENFA computed 25% of the area of CGNP under suitable and optimal conditions for the long-term existence of Kashmir markhor in CGNP. ENFA computed a HS map for markhor showing its widespread distribution within the study area. Steep slopes and a lower to medium elevation range were mostly preferred by markhor.

Reform Earth Observation Science and Applications to Transform Hindu Kush Himalayan Livelihoods—Services-Based Vision 2030

The Hindu Kush Himalayas (HKH) region with 210 million people living in the region poses significant scientific and technological challenges for livelihood improvement due to subsistence economy, livelihood insecurity, poverty, and climate change. The inaccessibility and complex mountain environmental settings carved special niche for Earth Observation (EO) science and significant contributions were made in the food security and disaster risk reduction sectors. The differentiated capacities of users to develop and use EO capabilities, challenges in outreaching the EO products to last mile users call for innovative ways of packaging EO products into actionable knowledge and services. This calls for great degree of reformation on EO community to tailor-made region specific EO sensors and models, mechanisms of synergizing EO knowledge with local traditional systems in addressing multiscale, and integrated end-to-end solutions. The paper addresses prospects and challenges of 2015–2030 to achieve success in three critical livelihood support themes viz food security, floods, and forest-based carbon mitigation. Different improvements in EO sensor and models to extend less than a day, all-weather imaging, improved hydro-meteorological forecasts, vegetation stress, and community carbon monitoring models are identified as priority areas of improvement. We envisage and propose mechanisms on how these EO advances could amalgamate into Essential HKH Variables (EHVs) on the lines of global Essential Climate Variables (ECVs) to provide turnkey-based actionable knowledge and services through global and regional cooperation. The complex web of users and orienting them toward adoption of EO services through multi-tier awareness, expertise development, policy advocacy, and institutionalization is also discussed. The paper concludes that the EO community needs to reform significantly in blending their science and applications with user-driven, need-based domains to provide better societal services and HKH livelihood transformation.

Forest inventory and analysis in Gilgit-Baltistan: A contribution towards developing a forest inventory for all Pakistan

Purpose The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve. Design/methodology/approach Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation. Findings Representative circular 556 forest sample plots of 1,000 m2 contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813. Research limitations/implications Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned. Practical implications Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation. Originality/value This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.

Review of Ecosystem Monitoring in Nepal and Evolving Earth Observation Technologies

Nepal, a Himalayan country, is situated on the southern slopes of the central Himalayas and represents about one-third of its whole length. Nepal has a population of around 26.5 million and a large proportion of this rely upon land-based activities for their livelihoods. Its elevation ranges 60–8848 masl which constitutes 10 major ecoregions providing diverse ecosystem services crucial for its inhabitants as well as downstream populations. At the ecosystem level, changes in structure, function, patterns of disturbance, and potential impacts of climate change on species are notable concerns. Earth Observation (EO) technologies are being applied for the monitoring and assessment of Nepal on various scales. Since recently, EO supported assessments are also being linked to decision-making processes. In this chapter, we review the status of EO based assessment of key ecosystem components, including forests, rangelands, agro-ecosystems, and wetlands in Nepal. The chapter also looks at the current information gaps and potential use of upcoming satellite technology developments in the context of Nepal.