'West Jilin Province' in this paper means Zhenlai, Baicheng, Taonan, Da'an,Tongyu, Fuyu, Songyuan, Qian'an, Changling, also includes Gongzhuling, Shuangliao, Lishu, Siping andNong' an which have be...'West Jilin Province' in this paper means Zhenlai, Baicheng, Taonan, Da'an,Tongyu, Fuyu, Songyuan, Qian'an, Changling, also includes Gongzhuling, Shuangliao, Lishu, Siping andNong' an which have been suffered from desertification. In west Jilin Province there are three sandzones passing through, they are Xiang (Xianghai) -Wu (Ulan Tug) sand zone, Hai-Feng sand zone, andTao'er River right bank sand zone. The desertification area of west Jilin Province is 819 100 ha,making up 12. 5% of the total land area. Among desertification types, in Jilin Province lightdesertification is the major, then is medium decertification, hevey desertification is the least.According to the comparison of the interpretation results of the Landsat images of the 1980s and the1990s by remote sensing and GIS techniques, it can be seen that the desertification area in westJilin Province basically didn't change on the whole, only increased 6130 ha, making up 0. 8% of thedesertification area, change scale is less than 1%. Evidently, desertification is controlled mostly,but some areas are continuing deterioration. The desertification process of China can be dividedinto three types according to origin nature, they are sandy steppe desertification, fixed sandarea(sand land) activation and dunes transfer invasion. Reasons of desertification of West JilinProvince are analyzed, they include natural factors (such as material source factors, chimatefactors) and artificial factors (such as destroying grass to reclaim, steppe decreasing greatly,illegally feeling shelter forest stands, constructing reservoir to influence eco-environment etc. ).Some suggestions are put forward as follows: establishing the social project for ecologicalreconstruction of degenerated land; intensifying planning and management of land use, revertingfarmland into forestland or pasture in a planned way. The key desertification control is to dependmainly on policy and management, then control techniques.展开更多
The management of forest corridors and related ecology is one of the effective strategies to minimize the adverse effects of forest degradation. It controls the connectivity of inhabitant species and the connection of...The management of forest corridors and related ecology is one of the effective strategies to minimize the adverse effects of forest degradation. It controls the connectivity of inhabitant species and the connection of the isolated patches. This study analyzed spatial and temporal forest physical degradation based on forest cover change and forest fragmentation in the Gishwati-Mukura biological corridor from 1990-2019. Remotely sensed datasets, Geographical Information System (GIS) and FRAGSTATS software were used to analyze the spatial and temporal physical degradation and changes in forest cover. The results indicated that the Gishwati-Mukura corridor experienced massive deforestation where approximately 7617.1 ha (64.22%) of forest cover was completely cleared out, which implies an annual forest loss of 262.6 ha·year<sup>-</sup><sup>1</sup> (2.21%) during 1990-2019. The forest cover transitions patterns and geostatistical analysis indicated that extensive deforestation was associated with intensive agriculture. The results demonstrated that agriculture has dramatically increased from 29.46% in 1990 to 57.22% in 2019, with an annual increase of 1.97%. Since Gishwati-Mukura has changed to National Park (NP), it lacks diversified scientific studies addressing the analysis of the remote and spatial patterns to investigate its physical degradation and landscape dynamics. This research study will serve as remote forest analysis gap-filling and as the cornerstone of numerous other research that will contribute to the improvement of the connectivity assessments along the Gishwati-Mukura corridor and other related ecosystems.展开更多
Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, ...Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1∶250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and ArcView softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility ( SE ) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation, physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120.330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29.41 % of the total land area has slight or moderate desertification and 37.465 % is facing severe desertification.展开更多
Regional vegetation pattern dynamics has a great impact on ecosystem and climate change. Remote sensing data and geographical information system （GIS） analysis were widely used in the detection of vegetation pattern...Regional vegetation pattern dynamics has a great impact on ecosystem and climate change. Remote sensing data and geographical information system （GIS） analysis were widely used in the detection of vegetation pattern dynamics. In this study, the Yellow River Delta was selected as the study area. By using 1986, 1993, 1996, 1999 and 2005 remote sensing data as basic information resource, with the support of GIS, a wetland vegetation spatial information dataset was built up. Through selecting the landscape metrics such as class area （CA）, class percent of landscape （PL）, number of patch （NP）, largest patch index （LPI） and mean patch size （MPS） etc., the dynamics of vcgetation pattern was analyzed. The result showed that the change of vegetation pattern is significant from 1986 to 2005. From 1986-1999, the area of the vegetation, the percent of vegetation, LPI and MPS decreased, the NP increased, the vegetation pattern tends to be fragmental. The decrease in vegetation area may well be explained by the fact of the nature environment evolution （Climate change and decrease in Yellow River runoff） and the increase in the population in the Yellow River Delta. However, from 1999 2005, the area of the vegetation, the percent of vegetation, LPI and MPS increased, while the NP decreased. This trend of restoration may be due to the implementation of water resources regulation for the Yellow River Delta since 1999.展开更多
The land desertification in Xinjiang was monitored and analyzed based on RS and GIS techniques. Satellite data interpretation was adopted to obtain the general situation of Xinjiang’s land desertification in assistan...The land desertification in Xinjiang was monitored and analyzed based on RS and GIS techniques. Satellite data interpretation was adopted to obtain the general situation of Xinjiang’s land desertification in assistance with the sampling method and on-the-spot investigations. Related monitoring and investigations showed that Xinjiang was facing with severe wide range land desertification, and its desertified area made up 77.08% of the total monitoring area. As for land types, the desertified farmland accounted for 1.92% of the total monitoring area, desertified woodland 4%, desertified grassland 45%, and unused land 49%. Accordingly, as for desertification degrees, non-desertified land occupied 22.92%, weak desertified land 5.69%, medium-degree desertified land 16.58%, severe desertified land 33.19% and super severe desertified land 21.61%. Finally, as for inducing factors, wind-eroded desertification made up 58.23%, water-eroded desertification 8.69%, salinization desertification 6.52% and frozen-melt eroded desertification 3.64%. Xinjiang’s land desertification tended to get worse and the harnessing mission remained hard.展开更多
文摘'West Jilin Province' in this paper means Zhenlai, Baicheng, Taonan, Da'an,Tongyu, Fuyu, Songyuan, Qian'an, Changling, also includes Gongzhuling, Shuangliao, Lishu, Siping andNong' an which have been suffered from desertification. In west Jilin Province there are three sandzones passing through, they are Xiang (Xianghai) -Wu (Ulan Tug) sand zone, Hai-Feng sand zone, andTao'er River right bank sand zone. The desertification area of west Jilin Province is 819 100 ha,making up 12. 5% of the total land area. Among desertification types, in Jilin Province lightdesertification is the major, then is medium decertification, hevey desertification is the least.According to the comparison of the interpretation results of the Landsat images of the 1980s and the1990s by remote sensing and GIS techniques, it can be seen that the desertification area in westJilin Province basically didn't change on the whole, only increased 6130 ha, making up 0. 8% of thedesertification area, change scale is less than 1%. Evidently, desertification is controlled mostly,but some areas are continuing deterioration. The desertification process of China can be dividedinto three types according to origin nature, they are sandy steppe desertification, fixed sandarea(sand land) activation and dunes transfer invasion. Reasons of desertification of West JilinProvince are analyzed, they include natural factors (such as material source factors, chimatefactors) and artificial factors (such as destroying grass to reclaim, steppe decreasing greatly,illegally feeling shelter forest stands, constructing reservoir to influence eco-environment etc. ).Some suggestions are put forward as follows: establishing the social project for ecologicalreconstruction of degenerated land; intensifying planning and management of land use, revertingfarmland into forestland or pasture in a planned way. The key desertification control is to dependmainly on policy and management, then control techniques.
文摘The management of forest corridors and related ecology is one of the effective strategies to minimize the adverse effects of forest degradation. It controls the connectivity of inhabitant species and the connection of the isolated patches. This study analyzed spatial and temporal forest physical degradation based on forest cover change and forest fragmentation in the Gishwati-Mukura biological corridor from 1990-2019. Remotely sensed datasets, Geographical Information System (GIS) and FRAGSTATS software were used to analyze the spatial and temporal physical degradation and changes in forest cover. The results indicated that the Gishwati-Mukura corridor experienced massive deforestation where approximately 7617.1 ha (64.22%) of forest cover was completely cleared out, which implies an annual forest loss of 262.6 ha·year<sup>-</sup><sup>1</sup> (2.21%) during 1990-2019. The forest cover transitions patterns and geostatistical analysis indicated that extensive deforestation was associated with intensive agriculture. The results demonstrated that agriculture has dramatically increased from 29.46% in 1990 to 57.22% in 2019, with an annual increase of 1.97%. Since Gishwati-Mukura has changed to National Park (NP), it lacks diversified scientific studies addressing the analysis of the remote and spatial patterns to investigate its physical degradation and landscape dynamics. This research study will serve as remote forest analysis gap-filling and as the cornerstone of numerous other research that will contribute to the improvement of the connectivity assessments along the Gishwati-Mukura corridor and other related ecosystems.
文摘Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1∶250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and ArcView softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility ( SE ) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation, physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120.330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29.41 % of the total land area has slight or moderate desertification and 37.465 % is facing severe desertification.
文摘Regional vegetation pattern dynamics has a great impact on ecosystem and climate change. Remote sensing data and geographical information system （GIS） analysis were widely used in the detection of vegetation pattern dynamics. In this study, the Yellow River Delta was selected as the study area. By using 1986, 1993, 1996, 1999 and 2005 remote sensing data as basic information resource, with the support of GIS, a wetland vegetation spatial information dataset was built up. Through selecting the landscape metrics such as class area （CA）, class percent of landscape （PL）, number of patch （NP）, largest patch index （LPI） and mean patch size （MPS） etc., the dynamics of vcgetation pattern was analyzed. The result showed that the change of vegetation pattern is significant from 1986 to 2005. From 1986-1999, the area of the vegetation, the percent of vegetation, LPI and MPS decreased, the NP increased, the vegetation pattern tends to be fragmental. The decrease in vegetation area may well be explained by the fact of the nature environment evolution （Climate change and decrease in Yellow River runoff） and the increase in the population in the Yellow River Delta. However, from 1999 2005, the area of the vegetation, the percent of vegetation, LPI and MPS increased, while the NP decreased. This trend of restoration may be due to the implementation of water resources regulation for the Yellow River Delta since 1999.
文摘The land desertification in Xinjiang was monitored and analyzed based on RS and GIS techniques. Satellite data interpretation was adopted to obtain the general situation of Xinjiang’s land desertification in assistance with the sampling method and on-the-spot investigations. Related monitoring and investigations showed that Xinjiang was facing with severe wide range land desertification, and its desertified area made up 77.08% of the total monitoring area. As for land types, the desertified farmland accounted for 1.92% of the total monitoring area, desertified woodland 4%, desertified grassland 45%, and unused land 49%. Accordingly, as for desertification degrees, non-desertified land occupied 22.92%, weak desertified land 5.69%, medium-degree desertified land 16.58%, severe desertified land 33.19% and super severe desertified land 21.61%. Finally, as for inducing factors, wind-eroded desertification made up 58.23%, water-eroded desertification 8.69%, salinization desertification 6.52% and frozen-melt eroded desertification 3.64%. Xinjiang’s land desertification tended to get worse and the harnessing mission remained hard.
