Forest structure changes continuously by natural and anthropogenic effects. Because the level of goods and services provided by forest ecosystems are related to this structure, some attributes have to be controlled wh...Forest structure changes continuously by natural and anthropogenic effects. Because the level of goods and services provided by forest ecosystems are related to this structure, some attributes have to be controlled while they are being managed. In this paper we describe the long-term temporal changes in land area and landscape metrics related to different land uses of a managed forest in Turkey. The study was carried out for the Daday Forest Planning Unit located in the west Black Sea region of northern Turkey. The total area is 16,813 ha and besides wood production, it is managed for erosion control, public health, aesthetics, and recreation. Stand type maps that were constructed in 1970,1989, 1999, and 2010 were used in this analysis. Transition matrixes that illustrate area changes among cover types and temporal changes on some landscape metrics were obtained using Geographic Information Systems. Stands were separated into small patches, and thus the number of patches increased nearly two-fold between 1970 and 2010. The total forest edge increased and through the associated fragmentation, the amount of core forest area decreased at the landscape scale. Landscape metrics were applied to digitized versions of historical maps to assess how forest area changed. Human use of the land has changed, forest management practices have evolved, and these along with natural forest growth have contributed to interesting changes in landscape character.展开更多
In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a ...In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.展开更多
Remote-sensing data for protected areas in northern Togo, obtained in three different years （2007, 2000, and 1987）, were used to assess and map changes in land cover and land use for this drought prone zone. The nor...Remote-sensing data for protected areas in northern Togo, obtained in three different years （2007, 2000, and 1987）, were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index （NDVI） was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images. Maximum likelihood classification was applied to the 2007 image （ETM＋2007） using a supervised classification process. Seven vegetation classes were defined from training data sets. The seven classes included the following biomes： riparian forest, dry forest, flooded vegetation, wooded savanna, fallows, parkland, and water. For these classes, the overall accuracy and the overall kappa statistic for the classi- fied map were 72.5% and 0.67, respectively. Data analyses indicated a great change in land resources; especially between 1987 and 2000 proba- bly due to the impact of democratization process social, economic, and political disorder from 1990. Wide-scale loss of vegetation occurred during this period. However, areas of vegetation clearing and regrowth were more visible between 2000 and 2007. The main source of confusion in the contingency matrix was due to heterogeneity within certain classes. It could also be due to spectral homogeneity among the classes. This research provides a baseline for future ecological landscape research and for the next management program in the area.展开更多
We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-r...We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-resolution remote sensing （RS） satellite images. Deforestation identified in this way （hereafter, RSD） was compared to administrative data on deforestation. We also compared high-resolution satellite images （HR-RSD） and actual deforestation based on categories which were Intergovernmental Panel on Climate Change data. RSD generated by medium-resolution satellite images overesti- mated the amount of deforested area by 1.5-2.4 times the actual deforested area, whereas RSD generated by HR- RSD underestimated the amount of deforested area by 0.4-0.9 times the actual area. The highest degree of matching （90 %） was found in HR-RSD with a grid interval of 500 m and the accuracy of HR-RSD was the highest, at 67 %. The results also revealed that the largest cause of deforestation was the establishment of settlements followed by conversion to cropland and grassland. We conclude that for the identification of deforestation using satellite images, HR-RSD with a grid interval of 500 m is most suitable.展开更多
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 ...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.展开更多
As more and more farmland is converted to forestry, the need for effective decision support regarding the use of land in the fragile ecological environment of the Loess Plateau hilly-gully area. The Luoyugou watershed...As more and more farmland is converted to forestry, the need for effective decision support regarding the use of land in the fragile ecological environment of the Loess Plateau hilly-gully area. The Luoyugou watershed was chosen as the study area to calculate the single dynamic degree, integrated dynamic degree, and change indexes of land use, as well as the land-use type transition matrix. This was done by interpreting the TM and SPOT images of the Luoyugou watershed in 1986, 1995, and2004 and making statistical analysis. The results of ou statistical analysis show that the conversion of slope farm land to terrace and forest land plays a dominant role in land-use changes in the Luoyugou watershed from 1986 to2004. The land-use changes are mainly driven by popula tion growth, socio-economic development, consume spending, and investment in forest ecology.展开更多
文摘Forest structure changes continuously by natural and anthropogenic effects. Because the level of goods and services provided by forest ecosystems are related to this structure, some attributes have to be controlled while they are being managed. In this paper we describe the long-term temporal changes in land area and landscape metrics related to different land uses of a managed forest in Turkey. The study was carried out for the Daday Forest Planning Unit located in the west Black Sea region of northern Turkey. The total area is 16,813 ha and besides wood production, it is managed for erosion control, public health, aesthetics, and recreation. Stand type maps that were constructed in 1970,1989, 1999, and 2010 were used in this analysis. Transition matrixes that illustrate area changes among cover types and temporal changes on some landscape metrics were obtained using Geographic Information Systems. Stands were separated into small patches, and thus the number of patches increased nearly two-fold between 1970 and 2010. The total forest edge increased and through the associated fragmentation, the amount of core forest area decreased at the landscape scale. Landscape metrics were applied to digitized versions of historical maps to assess how forest area changed. Human use of the land has changed, forest management practices have evolved, and these along with natural forest growth have contributed to interesting changes in landscape character.
基金supported by the National High Technology Research and Developmemt Program of China (No2007AA12Z162)the Program for New Century Excellent Talents in University, Ministry of Education (NoNCET-06-0476)the Jiangsu Provincial 333 Engineering for High Level Talents(No.BK2006505)
文摘In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.
基金supported by the Chinese Ministry of Sciences and Technology--the host of China-Africa Science and Technology Partnership Program(CASTEP)the National Special Research Program for Forestry Welfare of China(201104009)
文摘Remote-sensing data for protected areas in northern Togo, obtained in three different years （2007, 2000, and 1987）, were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index （NDVI） was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images. Maximum likelihood classification was applied to the 2007 image （ETM＋2007） using a supervised classification process. Seven vegetation classes were defined from training data sets. The seven classes included the following biomes： riparian forest, dry forest, flooded vegetation, wooded savanna, fallows, parkland, and water. For these classes, the overall accuracy and the overall kappa statistic for the classi- fied map were 72.5% and 0.67, respectively. Data analyses indicated a great change in land resources; especially between 1987 and 2000 proba- bly due to the impact of democratization process social, economic, and political disorder from 1990. Wide-scale loss of vegetation occurred during this period. However, areas of vegetation clearing and regrowth were more visible between 2000 and 2007. The main source of confusion in the contingency matrix was due to heterogeneity within certain classes. It could also be due to spectral homogeneity among the classes. This research provides a baseline for future ecological landscape research and for the next management program in the area.
文摘We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-resolution remote sensing （RS） satellite images. Deforestation identified in this way （hereafter, RSD） was compared to administrative data on deforestation. We also compared high-resolution satellite images （HR-RSD） and actual deforestation based on categories which were Intergovernmental Panel on Climate Change data. RSD generated by medium-resolution satellite images overesti- mated the amount of deforested area by 1.5-2.4 times the actual deforested area, whereas RSD generated by HR- RSD underestimated the amount of deforested area by 0.4-0.9 times the actual area. The highest degree of matching （90 %） was found in HR-RSD with a grid interval of 500 m and the accuracy of HR-RSD was the highest, at 67 %. The results also revealed that the largest cause of deforestation was the establishment of settlements followed by conversion to cropland and grassland. We conclude that for the identification of deforestation using satellite images, HR-RSD with a grid interval of 500 m is most suitable.
基金The work was supported by the Shanghai Science and Technology Innovation Fund for Soft Science(17692102400)the Shanghai Pujiang Program(17PJC098).
文摘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.
基金supported by the National Basic Research Program of China (2007CB407207)National Natural Science Foundation of China (30800888)
文摘As more and more farmland is converted to forestry, the need for effective decision support regarding the use of land in the fragile ecological environment of the Loess Plateau hilly-gully area. The Luoyugou watershed was chosen as the study area to calculate the single dynamic degree, integrated dynamic degree, and change indexes of land use, as well as the land-use type transition matrix. This was done by interpreting the TM and SPOT images of the Luoyugou watershed in 1986, 1995, and2004 and making statistical analysis. The results of ou statistical analysis show that the conversion of slope farm land to terrace and forest land plays a dominant role in land-use changes in the Luoyugou watershed from 1986 to2004. The land-use changes are mainly driven by popula tion growth, socio-economic development, consume spending, and investment in forest ecology.
