The moisture then condenses and falls as rain, according to Nuttal. Only about 38 percent of the precipitation is generated over oceans and seas. Africa was characterised by divergent climate conditions ranging from dry to moist. With climate change, this was becoming more pronounced with the frequent occurrence of floods and droughts. They are a buffer against extreme floods and droughts," said Nuttal.
The more frequent return of drought and loss of life from floods was an indication that climate change has set in, he added. Trees not only moderate climate, but act as water reservoirs, sources of medicine, and habitats for wildlife which earned countries like Kenya millions of dollars in foreign exchange through tourism. Kenya, one of the countries in East Africa that has been affected by severe droughts in recent decades, has had a high rate of deforestation.
Kenya Environmentalist and Nobel Peace laureate, Wangari Maathai, has estimated that the country needs to conserve at least 10 percent of its indigenous forest cover. The deforestation of the Mau Forest has continued unabated, Nuttal said, noting that charcoal burnig and farming activities were the main causes of the destruction. An estimated 11, sq km of the forest have been affected by the destruction.
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Assessing poverty-deforestation links: Evidence from Swat, Pakistan
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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. Introduction Himalayan mountain ecosystems are under severe stress because of population pressure [ 1 , 2 ] amplified by climate change [ 3 ].
For this reason, habitat fragmentation and degradation are clearly evident [ 4 , 5 , 6 ]. Massive forest destruction began in this region during the early British Government rule s , when forest wood was consumed for infrastructure development and commercial use [ 7 , 8 ]. Most forest studies within this region have concentrated on the Eastern Himalayas in Nepal and India, with the results extrapolated to the entire Himalayan region [ 7 ].
Until recently, adequate attention has not been given to understand the cryosphere i. Still, a comprehensive understanding of the ecological conditions e. In Pakistan, the current forest cover extent and deforestation rates are contentious issues among stakeholders. According to the first comprehensive remote sensing based on a national land cover assessment under the Forestry Sector Master Plan FSMP , the forest area totals 3. Out of this 3. Taking the FSMP study as the baseline, a national forest and range resource study observed that annual deforestation in natural forests was 27, ha during —, giving an annual decline of 0.
The Global Forest Resource Assessment reported forest cover to be 2. Few countries have reliable data from comparable assessments over time [ 13 ], and this lack of data is a sizable obstacle for efficient forest management policies in these countries. This review highlights the lack of systematic assessments and large area estimates of changes to forest cover in Pakistan. Because the United States Geological Survey USGS is continuing to acquire global satellite images through Landsat 8 [ 16 ] and has made the archived images publicly available [ 17 ], there is the possibility to monitor forest changes both retrospectively and prospectively.
In addition to being timely and cost effective [ 18 ], satellite based monitoring enables a transparent and reliable [ 19 ] means to monitor forest cover conditions. Although errors in the interpretation of spectral response and human bias exist [ 20 , 21 ], remote sensing remains to play key role in identifying and estimating deforested and reforested areas [ 22 , 23 ]. In the Himalayas, the application of remote sensing was introduced in the mids [ 24 ] to identify and analyze the Land Use Land Cover LULC pattern [ 25 , 26 , 27 ]. Through the analysis of the spatial and temporal patterns of deforestation and the identification of key variables related to deforestation, efforts are being made to identify the driving forces behind changes to forest cover [ 28 , 29 , 30 , 31 , 32 ].
Climate change, Deforestation and Corruption Combine to Drown Pakistan
The objective of this study is to produce reliable large-scale datasets on the extent of forest cover and its changing trends by way of comprehensive mapping of forest cover in the mountain region of Western Himalaya, Pakistan. The vegetation in the Himalayas, as in any mountainous region, is essentially determined by the topography, climate, geology, rocks and soil. The Western Himalayas is a zone of lower monsoon rainfall in the summer and heavy snow fall in the winter. The classification of Himalayan vegetation into broad categories has been characterized by reference [ 33 ] and later refined for Pakistan [ 34 ].
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A wide variety of forest types are found in Western Himalayas ranging from tropical forest to alpine scrub, which can be classified into seven major classes Figure 1 [ 34 ]. Alpine Scrub: This type of forest begins immediately above the tree limit at m and extends until m. This zone comprises stunted woods alternating with meadows. The scrub consists of Junipreus squamata , Junipreus recurva , etc. Sub Alpine Forests: These forests lay immediately above the temperate zone forest at the tree line extending from — m.
Dry Temperate Forests: The principal components of this forest type are Cedrus deodara and Pinus wallichiana , which occupy belts ranging from m to m. Moist Temperate Forests: This forest type comprises evergreen oaks and conifers that cover the temperate zone of Western Himalaya between an altitude of — m.
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The dominant species in this region are Cedrus deodara , Picea smythiana and the oak species Quercus incana and Quercus dilatata. Sub-Tropical Coniferous Forests: Formations of Pinus roxburghi cover the entire outer range between altitudes of — m. In its lower elevation zones, this region is mixed with species such as Shorea robusta , and on its upper altitude range it is associated with species such as Quercus incana. These are forests of low or moderate height and mostly consist of deciduous tree species.
Tropical Dry Deciduous Forests: These occur along foothills and are found to an elevation of m with Shorea robusta as the dominant species. For the acquisition of optical satellite data in northern Pakistan, the months of August to October are considered to be the most suitable because of the least amount of cloud and snow cover during this period. The entire archive was examined thoroughly to locate the images captured during September and October Table S1, Supplementary Material. Bearing in mind the extensive temporal record and relatively consistent spatial and radiometric characteristics, the Landsat satellite data offers a reliable source of appropriate resolution data that is critical for the quantification of land change over reasonably long time periods [ 36 ].
The data for the administrative boundaries at the sub-district level was accessed from the data portal in reference [ 37 ]. The use of multi-temporal satellite data for large area mapping poses a number of challenges, including geometric correction errors, noise arising from atmospheric effects and changing illumination errors [ 38 ].
New research shows community forest management reduces both deforestation and poverty
For these reasons, pre-processing is necessary to remove or minimize such errors. Each image was normalized for solar irradiance by converting the digital number values to TOA reflectance. Reference [ 40 ] showed that per scene BRDF adjustments improve radiometric response and land cover characterizations. Subsequently, TOA reflectance was converted into ground reflectance through an atmospheric correction process. Second Simulation of the Satellite Signal in the Solar Spectrum 6S is an advanced radiative transfer code that is designed to simulate the solar radiation reflectance by a coupled atmosphere-surface system for a wide range of atmospheric, spectral and geometric conditions [ 41 ].
The code calculates the atmospheric correction coefficients xa, xb and xc for each band separately based on the input data, providing an indication of the most likely atmospheric conditions during image acquisition. Additionally, the 6S model accounts for adjacency effects based on the view and azimuth angles of the sensor [ 43 ]. The topography of mountainous areas causes reflectance issues that must be corrected for the subsequent analysis of the associated satellite data.
In this study, the C-correction [ 44 , 45 ] method was applied to compensate for differences in solar illumination induced by the topography using SAGA GIS [ 46 ]. The foremost step is the identification of classes that are to be mapped. Conventionally, the system would contain classes that are exhaustive and mutually exclusive; in fuzzy systems, this requirement can be relaxed, allowing intergradations of classes and mixed communities [ 15 ].
Fourteen land cover classes were identified Table 1. There are a plethora of methods that can be used to map forest cover using satellite imagery. However, forest cover maps have been derived from methods that are relatively effort-intense [ 45 , 47 ].
This study used a semi-automated i. Performing a semi-automated classification, such as supervised classification, is desirable to provide reliable data over time to monitor the future state of forests [ 50 , 51 ]. The training areas or spectral signatures collected during the training phase can easily be used and refined if new information is available in future exercises of similar nature [ 52 ]. Landsat satellite images taken in are foremost for the classification process. Training sites were identified and marked on the satellite data by polygons, which represent homogenous areas for each land-cover type.
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