Land reclamation is a process of ecosystem reconstruction, for which it is very important to keep co-adaptation between plants and the below ground habitat. In order to keep the co-adaptation among plant species, thic...Land reclamation is a process of ecosystem reconstruction, for which it is very important to keep co-adaptation between plants and the below ground habitat. In order to keep the co-adaptation among plant species, thickness of covering soil and medium of covering soil to establish a self-regulating ecosystem, the thickness of covering soil of land reclamation for plants in different living forms by synusia structure of plant below-ground habitat and medium of covering soil by ecological factors of plant below-ground habitat were studied. Synusia structure of plant below-ground habitat was recognized through investigation on structure and root of plant community, and ecological factors were determined through soil profile investigation. The thickness and medium of covering soil of land reclamation for the tree, the shrub and the herb were proposed.展开更多
Anthropogenic activities and natural processes are continuously altering the mountainous environment through deforestation, forest degradation and other land-use changes. It is highly important to assess, monitor and ...Anthropogenic activities and natural processes are continuously altering the mountainous environment through deforestation, forest degradation and other land-use changes. It is highly important to assess, monitor and forecast forest cover and other land-use changes for the protection and conservation of mountainous environment. The present study deals with the assessment of forest cover and other land-use changes in the mountain ranges of Dir Kohistan in northern Pakistan, using high resolution multi-temporal SPOT-5 satellite images. The SPOT-5 satellite images of years 2004, 2007, 2010 and 2013 were acquired and classified into land-cover units. In addition, forest cover and land-use change detection map was developed using the classified maps of 2004 and 2013. The classified maps were verified through random field samples and Google Earth imagery(Quick birds and SPOT-5). The results showed that during the period 2004 to 2013 the area of forest land decreased by 6.4%, however, area of range land and agriculture land have increased by 22.1% and 2.9%, respectively. Similarly, barren land increased by 1.1%, whereas, area of snow cover/glacier is significantly decreased by 21.3%. The findings from the study will be useful for forestry and landscape planning and can be utilized by the local, provincial and national forest departments; and REDD+ policy makers in Pakistan.展开更多
Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the...Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the object and the context in which it is inserted in the image. The objective of this study was to investigate the performance of different classification methods for land cover mapping in the vicinity of the Alto Ribeira Tourist State Park, a Brazilian Atlantic rainforest area. Two classification methods were tested, including i） a hybrid per-pixel classification using the image processing software ERDAS Imagine version 9.1 and ii） an object-based classification using the software eCognition version 5. In the first method, six different classes were established, while in the second method, another two classes were established in addition to the six classes in the first method. Accuracy assessment of the classification results presented showed that the object-based classification with a Kappa index value of 0.8687 outperformed the per-pixel classification with a Kappa index value of 0.2224. Application of the user＇s knowledge during the object-based classification process achieved the desired quality; therefore, the use of inter-relationships between objects, superelasses, subclasses, and neighboring classes were critical to improving the efficiency of land cover classification.展开更多
文摘Land reclamation is a process of ecosystem reconstruction, for which it is very important to keep co-adaptation between plants and the below ground habitat. In order to keep the co-adaptation among plant species, thickness of covering soil and medium of covering soil to establish a self-regulating ecosystem, the thickness of covering soil of land reclamation for plants in different living forms by synusia structure of plant below-ground habitat and medium of covering soil by ecological factors of plant below-ground habitat were studied. Synusia structure of plant below-ground habitat was recognized through investigation on structure and root of plant community, and ecological factors were determined through soil profile investigation. The thickness and medium of covering soil of land reclamation for the tree, the shrub and the herb were proposed.
基金akistan Space and Upper Atmospheric Research Commission(SUPARCO),for the provision of SPOT satellite imagesnational center of excellence in Geology(NCEG)+1 种基金University of Peshawar and Department of ForestryShaheed Benazir Bhutto University,Sheringal
文摘Anthropogenic activities and natural processes are continuously altering the mountainous environment through deforestation, forest degradation and other land-use changes. It is highly important to assess, monitor and forecast forest cover and other land-use changes for the protection and conservation of mountainous environment. The present study deals with the assessment of forest cover and other land-use changes in the mountain ranges of Dir Kohistan in northern Pakistan, using high resolution multi-temporal SPOT-5 satellite images. The SPOT-5 satellite images of years 2004, 2007, 2010 and 2013 were acquired and classified into land-cover units. In addition, forest cover and land-use change detection map was developed using the classified maps of 2004 and 2013. The classified maps were verified through random field samples and Google Earth imagery(Quick birds and SPOT-5). The results showed that during the period 2004 to 2013 the area of forest land decreased by 6.4%, however, area of range land and agriculture land have increased by 22.1% and 2.9%, respectively. Similarly, barren land increased by 1.1%, whereas, area of snow cover/glacier is significantly decreased by 21.3%. The findings from the study will be useful for forestry and landscape planning and can be utilized by the local, provincial and national forest departments; and REDD+ policy makers in Pakistan.
基金Supported by the Sa o Paulo Research Foundation (FAPESP), Brazil
文摘Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the object and the context in which it is inserted in the image. The objective of this study was to investigate the performance of different classification methods for land cover mapping in the vicinity of the Alto Ribeira Tourist State Park, a Brazilian Atlantic rainforest area. Two classification methods were tested, including i） a hybrid per-pixel classification using the image processing software ERDAS Imagine version 9.1 and ii） an object-based classification using the software eCognition version 5. In the first method, six different classes were established, while in the second method, another two classes were established in addition to the six classes in the first method. Accuracy assessment of the classification results presented showed that the object-based classification with a Kappa index value of 0.8687 outperformed the per-pixel classification with a Kappa index value of 0.2224. Application of the user＇s knowledge during the object-based classification process achieved the desired quality; therefore, the use of inter-relationships between objects, superelasses, subclasses, and neighboring classes were critical to improving the efficiency of land cover classification.
