Forest cover change and its driving forces in Fagita Lekoma District,Ethiopia

This study investigated forest cover change and the driving forces behind it in Fagita Lekoma District of Ethiopia that resulted in increased forest cover,which might be uncommon outside this case study area.The LULC change analysis was made from 2003 to 2017 based on Landsat images.Socioeconomic analysis was carried out to identify the major driving forces that resulted in LULC change.A questionnaire survey,focused group discussion,key informant interviews and field observation were employed to analyze the link between LULC change and the driving forces.The 15-year period(2003–2017)image analysis revealed that the coverage of forest lands,built-up areas and grassland has increased by 256%,100%and 96%,respectively,at the expense of cultivated lands and wetlands.The increased forest cover is due to the woodlots expansion of Acacia decurrens Willd,which are designed for sustainable livelihoods and a land revitalization strategy in the study area.Rapid population growth,an increasing demand for charcoal and subsequent market opportunities,preferred qualities of A.decurrens or black wattle to halt land degradation as well as to improve land productivity,have been identified as the major driving forces of forest cover change.Chi squared analysis revealed that:a comparative cash income from the sale of A.decurrens;a dependency on natural forests;the distance from the district administrative center;the size of the active labor force,and the area of land owned have significantly affected the cover change.The major forest cover change is due to the expansion of A.decurrens plantations that have socioeconomic and environmental implications to improve rural livelihoods and revitalize the land.Thus,the positive experiences identified in this study should be scaled-up and applied in other similar settings.

Forest cover change and its effects on the livelihood of the dependent local people:the case of Sesheke district of Zambia

Objective-To investigate forest cover change in Masese Local Forest Reserve and its effects on the livelihoods of the dependent communities;to establish the occurrence of forest cover change in Masese Local Forest Reserve;to determine the extent of forest cover change in Masese from 1990to 2005;to determine the tree species that have been affected by forest cover change in Masese; and to assess the effects of forest cover change on the livelihoods of the dependent communities. Methods-Interviews and questionnaire were conducted with a proportion of 36households from Maondo and 84households from Mulimambango settlements.Scenes of landsat images of 1990,2000, 2005and Earth Google image for Masese were used for map analysis.Also remote sensing was used to analyze landsat images and Google image to detect forest and non-forest classes.Results and Conclusion-Forest cover change has adverse implication on the provision of wood forest products and nonwood forest products to the dependent local communities.The declining status of dominant Baikiaea Forest that has exploitable species for building materials and fuel wood has affected the livelihoods of the dependent local communities.There is also increased cost and shortage of fire wood and building materials due to deforestation in Masese Forest Reserve.

Forest cover dynamics in Palas Valley Kohistan, Hindu Kush-Himalayan Mountains, Pakistan

Forest cover change in the mountainous region is driven by a variety of anthropogenic and natural factors.The Hindu Kush-Himalayan Mountains has experienced a considerable vegetation cover change due to intensive human activities,such as population growth,proximate causes,accessibility,unstable political situations,government policy failure and poverty.The present study seeks to find out the impact of population growth and road network expansion on forest cover of Palas valley based on remotely sensed data and employing geospatial techniques.Changes in forest cover were determined by classifying time-series satellite images of Landsat and Sentinel 2 A.The images of October 1980,2000,2010 and 2017 were classified into six land cover classes and then the impact of population growth and accessibility on forest cover was analyzed.Furthermore,forest cover and land-use change detection map was prepared using classified images of 1980 and 2017.The data were collected mainly from field visits(ground verification),census reports,Communication and Works Department,Kohistan.Satellite imageries were obtained from the United States Geological Survey’s websites and classified in ERDAS imagine 2014 and ESRI ArcGIS 10.2.1 using supervised classification-maximum likelihood algorithm.Result of this study revealed that a substantial reduction in forest cover has taken place mainly in the proximity of human settlements.On the average,during the study period,annually more than 460 hectares of forest area has been converted into other uses.

Disturbance and forest recovery in the Monarch Butterfly Biosphere Reserve,Mexico

Analysis of the change in forest cover is important to determine stand dynamics and the processes involved in disturbance and recovery.Forests of the core zone of the Monarch Butterfly Biosphere Reserve were studied using photo interpretation techniques,considering biennial changes between 1999 and 2013 and changes over the whole period of study 1999–2013.Error matrices were elaborated to determine the processes of change involved in both recovery and disturbance.The biennial changes for the whole period amounted to 2274 ha;343 ha accounted as degraded in more than one biennial period.The total changes in forest cover between 1999 and 2013 involved 4902 ha,out of which,2912 ha were affected by disturbance,and 1990 ha were recovered.For density and 2013 vegetation cover maps,the overall accuracy was 95.6%and 90.2%,respectively.By combining both maps,gradual processes were revealed that were not evident in separate analyses.This methodology is useful for the management and conservation of natural protected areas.

Evolution of forest cover in Portugal: A review of the 12th–20th centuries

Portugal＇s forests in the 12th century were dominated by the Fagaceae represented by Quercus and Castanea, and several pine species From the 12th century onwards, forests underwent changes in their management starting with protection and ultimately leading to intense exploitation. The massive naval construction during the maritime expansion （mainly in the 15th-16th centuries） involved felling of approximately 5 million trees mainly Quercus suber, Pinus pinea and other Quercus species. Cumulative fuel-wood consumption of 959 Mm3 during 1300-1854 was attributed to demographic expansion while the deforestation rate during 1636-1854 accounted for a minimum of 72.6% and a maximum of 96% of total forest cover. The volume of timber used in railway sleepers from 1856 onwards might have reached 0.5 Mm3. The last quarter of the 20th century increased the forest cover of Portugal through the World Bank program of Eucalyptus globulus reforestation.

Towards long-multitemporal change detection using SVI differencing by integrated DWT
ISOCLUS: a model for forest temporal dynamics mapping

Characterisation and mapping of land cover/land use within forest areas over long-multitemporal intervals is a complex task.This complexity is mainly due to the location and extent of such areas and,as a consequence,to the lack of full continuous cloud-free coverage of those large regions by one single remote sensing instrument.In order to provide improved long-multitemporal forest change detection using Landsat MSS and ETMin part of Mt.Kenya rainforest,and to develop a model for forest change monitoring,wavelet transforms analysis was tested against the ISOCLUS algorithm for the derivation of changes in natural forest cover,as determined using four simple ratio-based Vegetation Indices:Simple Ratio(SR),Normalised Difference Vegetation Index(NDVI),Renormalised Difference Vegetation Index(RDVI)and modified simple ratio(MSR).Based on statistical and empirical accuracy assessments,RDVI presented the optimal index for the case study.The overall accuracy statistic of the wavelet derived change/no-change was used to rank the performances of the indices as:RDVI(91.68%),MSR(82.55%),NDVI(79.73%)and SR(65.34%).The integrated discrete wavelet transform
ISOCLUS(DWT
ISOCLUS)result was 42.65%higher than the independent ISOCLUS approach in mapping the change/no-change information.The methodology suggested in this study presents a cost-effective and practical method to detect land-cover changes in support of decision-making for updating forest databases,and for long-term monitoring of vegetation changes from multisensor imagery.The current research contributes to Digital Earth with regards to geo-data acquisition,data mining and representation of one forest systems.

Assessment of the three factors affecting Myanmar’s forest cover change using Landsat and MODIS vegetation continuous fields data

Long-term observation of the earth is essential for studying the factors affecting global environmental changes.Digital earth technology can facilitate the monitoring of global environmental change with its ability to process vast amounts of information.In this study,we map the forest cover change of Myanmar from 2000 to 2005 using a training data automation procedure and support vector machines algorithm.Our results show that Myanmar’s forests have declined 0.68%annually over this six-year period.We validated our derived change results and found the overall accuracy to be greater than 88%.We also assessed forest loss from protected areas,areas close to roads,and areas subject to fire,which were most likely to lose forested area.The results revealed the main reasons for forest losses in some hotspots to be increased agricultural conversion,fire,and the construction of highways.This information is useful for identifying the driving forces behind forest changes and to support environmental policy development in Myanmar.

A remotely sensed tracking of forest cover and associatedtemperature change in Margalla hills

Worldwide, forest degradation is a serious environmental issue, and inPakistan, forest wealth is depleting at the highest rate in South Asia. Toensure sustainable development goals of environmental stewardship,social development and economic growth, a sound monitoring andregulatory mechanism is essential for tracking forest cover changes. Thisstudy aims to quantify the decline of forest reserves and associatedtemperature variations in a relatively unexplored biodiversity hotspot ofIslamabad, Margalla Hills National Park (MHNP). Imagery acquired byLandsat TM (Thematic Mapper) for the year 1992, 2000 and 2011 areused to assess the spatial and temporal changes occurred over the lasttwo decades (from 1992 to 2011). A robust hybrid-classification routineis implemented to monitor the changes in forest cover and ANOVAalong with Tukey’s HSD (Honestly Significant Difference) test is used totest the significance of temperature variation associated with a shift inland cover classes. The results showed a significant growth insettlements, agricultural area and barren soil whereas water body, lowervegetation, scrub and pine forest are diminishing. In both decades, thetemperature alteration associated with a change in land cover classesare statistically significant (confirmed by ANOVA and Tukey’s HSD tests)for most of the land use/land cover classes. Based on these findings, thisstudy concludes that forests are dwindling at MHNP and the degradingcondition of the forest is below par and necessitates the promotion ofconservation practices to minimize ecological disturbances.

Development of time series stacks of Landsat images for reconstructing forest disturbance history

Forest dynamics is highly relevant to a broad range of earth science studies,many of which have geographic coverage ranging from regional to global scales.While the temporally dense Landsat acquisitions available in many regions provide a unique opportunity for understanding forest disturbance history dating back to 1972,large quantities of Landsat images will need to be analysed for studies at regional to global scales.This will not only require effective change detection algorithms,but also highly automated,high level preprocessing capabilities to produce images with subpixel geolocation accuracies and best achievable radiometric consistency,a status called imagery-ready-to-use(IRU).This paper describes a streamlined approach for producing IRU quality Landsat time series stacks(LTSS).This approach consists of an image selection protocol,high level preprocessing algorithms and IRU quality verification procedures.The high level preprocessing algorithms include updated radiometric calibration and atmospheric correction for calculating surface reflectance and precision registration and orthorectification routines for improving geolocation accuracy.These automated routines have been implemented in the Landsat Ecosystem Disturbance Adaptive System(LEDAPS)designed for processing large quantities of Landsat images.Some characteristics of the LTSS developed using this approach are discussed.

Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges

The compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth’s land cover at Landsat resolutions of 30 m.In this article,we describe the methods to create global products of forest cover and cover change at Landsat resolutions.Nevertheless,there are many challenges in ensuring the creation of high-quality products.And we propose various ways in which the challenges can be overcome.Among the challenges are the need for atmospheric correction,incorrect calibration coefficients in some of the data-sets,the different phenologies between compila-tions,the need for terrain correction,the lack of consistent reference data for training and accuracy assessment,and the need for highly automated character-ization and change detection.We propose and evaluate the creation and use of surface reflectance products,improved selection of scenes to reduce phenological differences,terrain illumination correction,automated training selection,and the use of information extraction procedures robust to errors in training data along with several other issues.At several stages we use Moderate Resolution Spectro-radiometer data and products to assist our analysis.A global working prototype product of forest cover and forest cover change is included.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

Using the NASA Earth Exchange platform,the North American Forest Dynamics(NAFD)project mapped forest history wall-to-wall,annually for the contiguous US(1986–2010)using the Vegetation Change Tracker algorithm.As with any effort to identify real changes in remotely sensed time-series,data gaps,shifts in seasonality,misregistration,inconsistent radiometry and cloud contamination can be sources of error.We discuss the NAFD image selection and processing stream(NISPS)that was designed to minimize these sources of error.The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration,unreliability of the pre-2009 L5 cloud cover assessments algorithm,missing growing-season imagery and paucity of clear views.Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study.Over 150,000+Landsat images were considered for the NAFD project.Optimally,one high quality cloud-free image in each year or a total of 12,152 images would be used.However,to accommodate data gaps and cloud/shadow contamination 23,338 images were needed.In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.