Glacier area change (1993-2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

Glacier inventories serve as critical baseline data for understanding the impacts of climate change on glaciers.The present study maps the outlines of glaciers in the Chandra-Bhaga Basin(western Himalaya)for the years 1993,2000,2010,and 2019 using Landsat Thematic Mapper(TM),Enhanced Thematic Mapper(ETM),and Operational Land Imager(OLI)datasets.A total of 251 glaciers,each having an area above 0.5 km^(2),were identified,which include 216 clean-ice and 35 debris-covered glaciers.Area changes are estimated for three periods:1993-2000,2000-2010,and 2010-2019.The total glacierized area was 996±62 km^(2) in 1993,which decreased to 973±70 km^(2) in 2019.The mean rate of glacier area loss was higher in the recent decade(2010-2019),at 0.036 km^(2),compared to previous decades(0.029 km^(2) in 2000-2010 and 0.025 km^(2) in 1993-2000).Supraglacial debris cover changes are also mapped over the period of 1993 and 2019.It is found that the supraglacial debris cover increased by 14.12±2.54 km^(2)(15.2%)during 1993-2019.Extensive field surveys on Chhota Shigri,Panchi II,Patsio,Hamtah,Mulkila,and Yoche Lungpa glaciers were carried out to validate the glacier outlines and supraglacial debris cover estimated using satellite datasets.Controls of various morphological parameters on retreat were also analyzed.It is observed that small,clean ice,south oriented glaciers,and glaciers with proglacial lakes are losing area at faster rates than other glaciers in the basin.

Formation process of cover collapse sinkholes related to groundwater level decline in karst areas

The decline in groundwater level is a key factor contributing to cover collapse in karst areas.In this study,the model tests and numerical simulations are conducted to reveal the breeding process and formation mechanism of cover collapse sinkholes caused by the decline of groundwater level in karst area.Firstly,the model tests confirm that the decline of groundwater level generates negative pressure at the lower edge of overlying soil.The negative pressure experiences four distinct phases during the groundwater drawdown process:rapid rise,slow decline,rapid decline,and gradual dissipation.The maximum negative pressure is influenced by the particle size distribution of the overlying soil.Then,the numerical simulations are carried out to investigate the change process of negative pressure caused by the loss of fillers in karst pipe.The simulated results indicate that the rate of groundwater decline and the thickness and initial void ratio of the overlying soil can affect the maximum negative pressure.As groundwater level drops,a negative pressure zone forms underground,causing tensile failure in the surrounding soil and creating an arched soil hole,which weakens the support for the overlying soil.This phenomenon can also lead to the collapse of the overlying soil under its self-weight.Groundwater table decline in karst areas can result in both internal and surface collapses.When the overlying soil is thin,internal and surface collapses occur simultaneously.In contrast,for thick overlying soil,internal collapse happens first,followed by a layer-by-layer collapse,ultimately forming sinkholes.Finally,the breeding process and formation mechanism of the Yujiawan Reservoir sinkholes are discussed.Geological conditions and groundwater level decline significantly affect internal collapse in karst areas,requiring careful consideration from on-site engineers.

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant(SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis(PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting(SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.

Support Vector Machines for Cloud Detection over Ice-Snow Areas

In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.

Analysis on the land use and cover change in Tianjin Binhai New Area based on the remote sensing

This paper carries out quantitative analysis on the land use/cover （LU/C） change of 13anjin Binhai New Area in recent 10 years through using land use transition matrix from the three-stage LU/C classification maps of 2000, 2005 and 2010 drafted by means of the National Land Classification System of China based on Landsat TM satellite remote sensing image and the Tianjin Binhai New Area 1：50 000 relief maps. On this basis, the impact of such driving factors as the economy and population on LU/C is further analyzed. The results show that the area of the building land in Binhai New Area has increased significantly over the ten years, and the greenland, wetland, and shoals of high ecological value have been dramatically transformed into the building land and unused land for the development and construction, and the change is more significant in the later five years.

The spatial-temporal changes of the land use/cover in the Dongting Lake area during the last decade

The research on the land use/cover change is one of the frontiers and the hot spots in the global change research. Based on the Chinese resource and environment spatial-temporal database, and using the Landsat TM and ETM data of 1990 and 2000 respectively, we analyzed the spatial-temporal characteristics of land use/cover changes in the Dongting Lake area during the last decade. The result shows that during the last ten years there were three land-use types that had changed remarkably. The cultivated land decreased by 0.57% of the total cultivated land. The built-up land and water area expanded, with an increase of 8.97% and 0.43% respectively. The conversion between land use types mostly happened among these three land-use types, especially frequently between cultivated land and water area. The land-use change speed of land-use type is different. Three cities experienced the greatest degree of land-use change among all the administrative districts, which means that the land use in these cities changed much quickly. The following changed area was the west and south of the Dongting Lake area. The slowest changed area is the north and east area.

Satellite monitoring of land-use and land-cover changes in northern Togo protected areas

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.

Forest Cover Change Assessment in Conflict-affected Areas of Northwest Pakistan: the Case of Swat and Shangla Districts

This study examines the spatial and temporal forest cover changes in Swat and Shangla districts to understand the deforestation pattern in context of the recent security conflict in these districts. We used multi-resolution satellite images to assess the long term deforestation from 2001 to 2009 and also to identify episodic forest cutting areas appeared during the conflict period of Oct. 2007 - Oct. 2008. There are only 58 ha of deforestation identified during the conflict period while 1268 ha of gross annual deforestation were assessed during last eight years. Most of the deforestation patches persist around the administrative boundaries at sub-district levels (tehsils) which can be attributed to ambiguity in unclear jurisdiction between the forest official. The results highlight that the forest cutting appeared in Swat and Shangla during the conflict period is not as significant when compared with the long term deforestation pattern in the area. On the one side the results of the study are supportive to the picture that emerges from international studies which report high rate of deforestation in the country and on the other side it negates any relation between the security situation and the increasing deforestation in the north western Pakistan. The study concludes that deforestation assessments require verification by independent sources of data, such as satellite imagery to improve our understanding of deforestation processes.

Land cover change in different altitudes of Guizhou-Guangxi karst mountain area, China： patterns and drivers

Topography, especially altitude, will influence the way, process and characteristics of land cover changes in mountainous area, simultaneously, the vertical difference of land cover changes will affect soil quality and regional ecological environment. Therefore, the gradient relationship analysis between land cover changes and altitude is very important for regional sustainability. This study investigated land cover dynamics based on land cover data from a typical mountainous area in the Guizhou-Guangxi karst mountain area, China, in 2000 and 2010, then explored the relationship between altitude and land cover change and analyzed different drivers of land cover change at different altitudes. Our findings are as follows. 1) From 2000 to 2010, the total area of land cover transition was 7167.04 km^2 or 2.8% of the region. The increasing area of build-up land(926.23 km^2) was larger than that of forest(859.38 km^2), suggesting that the urban construction speed was higher than that of reforestation. 2) Intensity of land cover transition in northwestern Guizhou-Guangxi karst mountain area was much larger than that of southeast part and their transition trend was also significantly different, which was consistent with regional population and economy. 3) Human activity was the most dramatic at altitudes between 0–500 m. For 500–1000 m, grassland mainly converted to forest and build-up land. Area of land cover transition was the greatest between 1000–1500 m, while above 1500 m, the transition of grassland was the most obvious. 4) The drivers of land cover change varied. Land cover change was positively correlated with gross domestic product and population density but was inversely related to relief amplitude. There were correlations between land cover change and distance to roads and rivers, and their correlations varied with altitude. By revealing patterns and causes of land cover changes in different altitudes, we hope to understand the vertical dependence of land cover changes, so as to improve land productivity and protect land ecological environment scientifically.

Monitoring of Land-Cover Dynamic Change in Lancangjiang River Cascaded Hydropower Area

The analysis of the 3 stages＇ （1988,1996,2000） variation of land-cover is performed according to Thematic Mapper （TM） and Enhancement Thematic Mapper（ETM） satellite image by combining ground GIS database with GPS field collected data in the area of Xiaowan-Dachaoshan Reservoirs of Lancangjiang River cascaded Hydropower Area. Consequently, the land-cover is divided into five subclasses, namely water, paddy field and wetland, bare dryland and sparse shrub, secondary forest and density forest. The result showed that the areas of bare land, upland and secondary forest decreased in 1988-1996, whereas from 1996 to 2000, water body and density forest keep invariability while the areas of paddy field and wetland, bare dryland and sparse scrub increasing and the area of secondary forest decrease; Features of reciprocal transformation between density forest and other type of land-cover had two points, i.e. secondary forest, bare dryland and sparse shrub converted to density forest; and density forest converted to secondary forest and paddy field and wetland. It reflects the dynamic variation of density forest; the area which slope less than 8° and greater than 15° shows bigger variation, however, less change in 8°-15°.

A decline in snow cover area of Passu and Ghulkin valleys between 1995 and 2022

The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This study aims to evaluate the up-to-date changes in snow cover in the western Karakoram region.We observed the snow cover changes in Passu and Ghulkin valleys in the Hunza River basin(HRB)of the Karakoram through multitemporal Landsat satellite data between 1995 and 2022.We found a significant reduction in snow cover in these valleys,with an average reduction rate of 0.42 km~2/yr,resulting in a total reduction of~11.46 km~2 between 1995 and 2022.This reduction in snow cover is consistent with the mass loss of glaciers in the Karakoram region in recent years.The decline in snow cover in these valleys is also consistent with the meteorological data.The temperature in summer(June)has significantly increased whereas the precipitation in the accumulation season(March)has decreased.These rapid changes suggest that it is crucially important to monitor the snow cover on a regular basis to support downstream management of snowmelt runoff.In addition,there is a need of planning for mitigation and adaptation strategies for snow-related hazards.

Dynamic Analysis of Land Cover in Four-Lake Area of Jianghan Plain Based on MODIS-EVI Time Series Data

According to the time series data of Enhanced Vegetation Index (EVI) in Four-Lake Area of Jianghan Plain during the period 2001-2007, we use Harmonic Analysis of Time Series (HANTS) to conduct cloud removing processing, and calculate the sum of square N of time series value of each pixel. The pixels with N>0.25 are classified as vegetation coverage area; the pixels with N<0.25 are classified as non-vegetation coverage area. As to vegetation coverage area, we use the second-order difference method to judge the frequency of peak value of EVI time series data. Within one year, the vegetation coverage area with peak value happening 1 time is woodland and grassland; the vegetation coverage area with peak value happening 2 times is arable land; the vegetation coverage area with peak value happening 3 times or more is vegetable land. Supervised classification method is used to identify cities, towns, water area in non-vegetation coverage area and woodland, grassland in vegetation coverage area. We draw the land cover classification diagram of Four-Lake Area in the period 2001-2007. In comparison with the land cover classification based on multitemporal ETM data in 2001, the difference of area of arable land is within 10%. Using MODIS-EVI data, we can rapidly and efficiently conduct land cover classification with low cost. The dynamic analysis results indicate that the area of arable land is in the process of declining, while the area of other cover types shows an increasing trend.

Preliminary Study on Dynamic Changes of Insect Communities in Airport Ground Cover Areas in Different Weather Conditions

[Objectives]This study was conducted to investigate insect activity rhythms in airport ground cover areas,and provide guidance for insect control and bird strike prevention.[Methods]The daily rhythm of insects in the northern area of the airport was studied,and their activity rhythms and characteristics under different weather conditions were analyzed.[Results]In rainy days,the insect number in the three sample areas was low.In cloudy days,insect activity was relatively stable,and insect number was consistent in the morning and evening,and maintained in a stable range,while in sunny weather,insect activity was increased,and the number changed greatly with time.For a single tussock plant growth area,the number of insects was at a relatively low level under rainy weather.In fine weather,the peak period of insect activity was between 10:00-11:00 and 14:00-15:00.[Conclusions]This study can provide a reference for the formulation of safe flight departure time.

Analysis on Change of the Vegetation Cover in Poyang Lake Area from 1991 to 2005

[Objective] The reseamh aimed to analyze variation of the vegetation cover in Poyang Lake area from 1991 to 2005. [Method] Based on Landsat TM remote sensing images of 1991 and 2005 in Poyang Lake area, NDVI dimidiate pixel model was used to calculate vegetation cover- age. By transfer matrix, temporal-spatial change of the vegetation cover grade in the area was analyzed. [ Result] Vegetation cover in this region overall presented increase trend from 1991 to 2005, and forestry area increased somewhat. But at the same time, farmland area decreased to some extent. Sandlot and bare land also increased slightly. [ Conclusion] Governments and relevant departments should reasonably allocate land re- sources and protect natural ecology environment.

Temporal and Spatial Variation Characteristics of Snow Cover Area in the Pamirs from 2010 to 2020

Scientific and comprehensive monitoring of snow cover changes in the Pamirs is of great significance to the prevention of snow disasters around the Pamirs and the full utilization of water resources. Utilize the 2010-2020 snow cover product MOD10A2, Synthesis by maximum, The temporal and spatial variation characteristics of snow cover area in the Pamirs in the past 11 years have been obtained. Research indicates: In terms of interannual changes, the snow cover area of the Pamir Plateau from 2010 to 2020 generally showed a slight decrease trend. The average snow cover area in 2012 was the largest, reaching 54.167% of the total area. In 2014, the average snow cover area was the smallest, accounting for only 44.863% of the total area. In terms of annual changes, there are obvious changes with the change of seasons. The largest snow area is in March, and the smallest snow area is in August. In the past 11 years, the average snow cover area in spring and summer showed a slow decreasing trend, and there was almost no change in autumn and winter. In terms of space, the snow cover area of the Pamirs is significantly affected by altitude, and the high snow cover areas are mainly distributed in the Karakoram Mountains and other areas with an altitude greater than 5000 meters.

Applicable Garden Ground Cover Plants in Arid Valleys of Ganzi Tibetan Area

The native and introduced ground cover plants were screened by field survey,cultivation test and configuration effect evaluation in arid valleys of Ganzi Tibetan area.A total of 205 species belonging to 140 genera,67 families were selected as applicable types.Among them,there were 53 species of evergreen shrubs,36 species of deciduous shrubs,17 species of woody vines,99 species of herbaceous plants;27 species of color-leafed plants,8 species of succulent plants.And 79 species were recommended as the best ground cover plants.Higher plants in Ganzi Tibetan area were increased to 5,362 species,1147 genera,244 families through screening.

Examining Rate of Built-Up Areas on the Vegetation Cover along River Riara Riparian within Kiambu Town, Kenya

Urban river riparian spaces and their natural systems are valuable to urban dwellers;but are increasingly affected and ruined by human activities and in particular, urbanization processes. In this research, land sat and sentinel satellite imagery apt for change detection in vegetation cover, both landsat and sentinel imagery, covering the period between 1970 and 2021 in epochs of 1973, 1984, 1993, 2003, 2015 and 2021 years were used to establish the correlation between vegetation cover and built-up area along River Riara river reserve. The images were analysed to extract the built-up areas along the river reserve, including the buildings, and the rate of human settlements, which influenced vegetation cover. Normalized Difference Built-Up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) were computed using the Short-Wave Infrared (SWIR) and the Near Infra-Red (NIR) bands to show the rate of change over the years. Results indicate NDVI values were high, compared to NDBI values along river Riara in the years 1973 and 1993 implying that there was more vegetation cover then. However, in the year 2021, the NDVI indicated the highest value at 0.88, with the complementary NDBI indicating the highest NDBI value at 0.47. This represents a significant increase in built-up areas since 2015 more than in previous epochs. Either, there was a significant increase in NDBI values, from 0.24 in 1993 to 0.47 in 2021. More so, the R-squared value at 0.80 informed 80% relationship between NDBI and NDVI values indicating a negative correlation.

Analysis of Application Status and Recommendations for Shade-Tolerant Lawns and Ground Cover Plants in the West Lake Scenic Area

Taking 8 parks in Xihu Scenic Area as the survey objects, this study found that there are 77 kinds of shade-tolerant lawns and ground cover plants under the forest in good growth condition, and there are 3 types of application forms: dense forest, sparse forest and forest edge. In response to the existing problems, it is proposed that it is necessary to adhere to principles of ecology, adapt to local conditions and plant suitable varieties in accordance with local conditions, develop and use new varieties of wild shade-tolerant lawns and ground cover plants, and strengthen the promotion of the mixed planting model of shade-tolerant lawns and ground cover plants, so as to provide guidance for the better use of shade-tolerant lawns and ground cover under the forest in the West Lake Scenic Area in the future.

Riparian habitat quality as an indicator of land use/land cover effects on riverine water quality

Riparian land use/land cover(LULC)plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients.Nevertheless,establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors.Water quality encompasses a multitude of physical,chemical,and biological parameters,while LULC represents a diverse array of land use types.Riparian habitat quality(RHQ)serves as an indicator of LULC.Yet,it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality.This study examines the interplay between RHQ,LULC and water quality,and develops a comprehensive indicator to predict water quality.We measured several water quality parameters,including pH(potential of hydrogen),TN(total nitrogen),TP(total phosphorus),T_(water)(water temperature),DO(dissolved oxygen),and EC(electrical conductivity)of the Yue and Jinshui Rivers draining to the Han River during 2016,2017 and 2018.The water quality index(WQI)was further calculated.RHQ is assessed by the InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)model.Our study found noticeable seasonal differences in water quality,with a higher WQI observed in the dry season.The RHQ was strongly correlated with LULC compositions.RHQ positively correlated with WQI,and DO concentration and vegetation land were negatively correlated with T_(water),TN,TP,EC,cropland,and construction land.These correlations were stronger in the rainy season.Human-dominated land,such as construction land and cropland,significantly contributed to water quality degradation,whereas vegetation promoted water quality.Regression models showed that the RHQ explained variations in WQI better than LULC types.Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.