Main Land Cover Types Research Articles

Pollen-based temporal-spatial land cover reconstruction in North China for the last 6,000 years

Based on 74 fossil pollen records and relative pollen productivity estimates for 29 plant taxa, we produced a quantitative reconstruction of regional vegetation change in North China over the past 6,000 years, using the combined MAT-REVEALS approach. The results include the spatial dynamics of the five main land cover types (Pinus, coniferous trees excluding Pinus, deciduous trees, grassland and bare ground) for three time slices: 6 ka, 3 ka and 0.05 ka. From 6 ka to the present, the total vegetation cover decreased from 64% to 61% (i.e., bare ground increased from 36% to 39%), mainly because of decreases in the cover of deciduous trees (from 19% to 14%). At the same time, the cover of coniferous trees increased (from 10% to 14%), and that of herb plants was largely unchanged (from 34% to 33%). The vegetation cover was greater at high latitudes and altitudes than at lower latitudes and in lowland areas. On the regional scale, temperate coniferous forest with Larix and Betula was dominant in the Greater Khingan Mountains, while in the Changbai Mountains, deciduous forest (decreasing from 72% to 56%) gradually transitioned to coniferous-deciduous mixed forest (Pinus and coniferous trees increased from 1% to 18%). The deciduous forest was dominated by Quercus, Betula and Pinus and occurred mainly in the warm temperate mountains of North China, where the vegetation cover was relatively high before 3 ka (>70%), before decreasing substantially to 55% at 0.05 ka. Grassland with Artemisia and Poaceae was the main land cover type in the North China Plain and in the temperate steppe region where forest vegetation was relatively sparse. The spatial dynamics of the land cover types appear to have been affected by climate change; climatic cooling in the second half of the Holocene led to the southward migration of coniferous trees. At the same time, human activities were likely the cause of the reduction of the regional vegetation cover, especially the tree cover.

Consistency Analysis and Accuracy Assessment of Three Global Ten-Meter Land Cover Products in Rocky Desertification Region—A Case Study of Southwest China

Rocky desertification is one of the most critical ecological and environmental problems in areas underlain by carbonate rocks globally. Land cover and land use in the region affects large-scale ecosystem processes on a global scale, and many Earth system models rely on accurate land cover information. Therefore, it is important to evaluate current global land cover products and to understand the differences between them, and the findings of these studies can provide guidance to different researchers when using or making land cover products. Whereas there are many studies on the assessment of coarser resolution land cover products, there are few studies on the assessment of higher resolution land cover products (10 m). In order to provide guidance for users of 10 m data, this paper uses the rock deserted southwest region of China as the experimental area. We analyzed the consistency and accuracy of the FROM-GLC, ESA WorldCover 10 and ESRI products using spatial pattern consistency, absolute accuracy assessment of three validation samples, and analyzed their intrinsic relationships among classification systems, classification methods, and validation samples. The results show that (1) the overall accuracy of the FROM-GLC product is the highest, ranging from 49.47 to 62.42%; followed by the overall accuracy of the ESA product, ranging from 45.13 to 64.50%; and the overall accuracy of the ESRI product is the lowest, between 39.03 and 61.94%. (2) The consistency between FROM-GLC and ESA is higher than the consistency between other products, with an area correlation coefficient of 0.94. Analysis of the spatial consistency of the three products shows that the proportion of perfectly consistent areas is low at 44.89%, mainly in areas with low surface heterogeneity and more homogeneous cover types. (3) Across the study area, the main land cover types such as forest and water bodies were the most consistent across the three product species, while the grassland, shrubland, and bareland were lower. All products showed high accuracy in homogeneous areas, with local accuracy varied in other areas, especially at high altitudes in the central and western regions. Therefore, land cover users cannot use these products directly when conducting relevant studies in rocky desertification areas, as their use may introduce serious errors.

Land Cover Changes in Selected Areas Next to Lagoons Located on the Southern Coast of the Baltic Sea, 1984–2021

The aim of the study is the evaluation of land cover changes in selected areas next to three lagoons (the Curonian Lagoon, the Vistula Lagoon and the Szczecin Lagoon) located on the southern coast of the Baltic Sea (in Lithuania, Russia, Poland and Germany) from 1984 to 2021. The changes are evaluated using multispectral (visible light—RGB and near infrared—NIR) satellite images from the Landsat 5 and Sentinel-2 sensors. Due to their high importance for ecosystem services, two main land cover types are evaluated, i.e., forest area and inland water reservoirs. The classification of the images is performed using a random forest algorithm. Areas of water bodies and forests are evaluated for the years 1984 and 2021. During period 1984–2021, positive changes in land cover are observed in all three regions included in the study. In almost all parts, with the exception of the Polish part of the area located next to the Szczecin Lagoon, of these regions, an increase in forest area is observed. The increase ranges from 0.1% (Poland, area next to the Vistula Lagoon) to 1.2% (Germany, area next to the Szczecin Lagoon). The area of inland water reservoirs has not changed significantly in the long term. Despite the global warming, no reduction in the area of these water reservoirs is observed, even new seminatural reservoirs have been created in some parts of the study area.

A method for estimating spatially continuous soil moisture from the synergistic use of geostationary and polar-orbit satellite data

Soil moisture (SM) is a key variable in the surface energy balance and water cycle, and its spatiotemporal dynamics are of great significance to climate, agriculture and other fields. Optical remote sensing has been widely used to estimate SM with relatively fine spatial resolution. However, optical observations are easily contaminated by clouds, making it difficult to obtain spatially continuous SM over large regions. In the present study, a semimonthly SM dataset over the study area of the entire Inner Mongolia region with nearly full spatial coverage was derived from the synergistic use of China’s Feng-Yun (FY) geostationary (FY-4A) and polar-orbit (FY-3D) observations, following a previously developed trapezoid feature space in a pixel-to-pixel manner. A preliminary assessment was conducted to evaluate the performances of the proposed method over two main dominant land cover types (grassland and cropland) in the study region, where the China Meteorological Administration Land Data Assimilation System (CLDAS) and the Soil Moisture Active Passive (SMAP) SM products were provided as references. The results indicated that the estimated SM was well correlated to the referenced SM datasets, with a significant correlation coefficient varying from 0.5 to 0.8. Furthermore, for the grassland (cropland), unbiased root mean square errors of approximately 0.062 (0.097) m3/m3 and 0.055 (0.069) m3/m3 can be found when comparing the estimated SM with the CLDAS and the SMAP product, respectively.

Change Detection for Wasit Province’s Land Coverbetween 2013 and 2020

It is well known that On Earth there are only a few places, which are now intheir natural state and have not been affected by human activity in any way. These human activities lead to significant changes in land use at the regional and local levels. In this research, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the main land cover types (vegetation, water, soil, bare area, and urban) in Wasit province. The result of supervised classification for two classified Landsat-8 images for 2020, 2013 after combining 13 subclasses: Water area in 2013 (0.719%) increases to (1.521%) in 2020, vegetation class increases from (2.864) to (6.148%). Urban increases from 2.095% to 4.629%, Bare area in 2020 became 24.307% but in 2013 was 29.03% and finally, soil decreased from (15.821%) to (13.922%).

Multidimensional diversity of bird communities across spatial variation of land cover in Zoige on the eastern Qinghai-Tibetan Plateau

BackgroundSpatial variation of land cover can result in the changes of community similarities and biotic homogenization, whereby the increasing similarity would reduce the adaptive capacity of biotic assemblages to further disturbance, and degenerate ecosystem services they offer. However, it remains scarce to integrate multidimensional diversity for unveiling how variations in land cover may influence the patterns and processes of biotic homogenization in the Anthropocene. In this study, we examined how spatial variation of land cover could alter taxonomic, phylogenetic and functional homogenization of bird communities simultaneously in a compound ecosystem of Zoige Marsh on the eastern Qinghai-Tibetan Plateau. Acting as the largest alpine marsh and peatland in the world, Zoige Marsh has undergone great changes in the land cover pattern due to climate change and anthropogenic activities.MethodsWe conducted transect surveys for bird communities over six years (2014‒2019) during breeding seasons in four main land cover types (meadow, woodland, village and marsh), representing the spatial variation of land covers in the study area. We compared multidimensional diversity (taxonomic, phylogenetic and functional diversity) among land covers to assess the effects of spatial variation in land cover type on bird communities, particularly whether this variation has homogenized biotic communities.ResultsBird communities during breeding seasons were different and complementary in the four land covers. Taxonomic, phylogenetic and functional similarities were significantly lower in meadow than in the other three types, i.e. woodland, village and marsh. However, when we controlled for the effects of taxonomic similarities, the pattern of phylogenetic similarities almost reversed, with the highest standardized effect size (SES) phylogenetic similarity in meadow; and we found no significant difference in SES functional similarity among land covers.ConclusionsOur results suggest that spatial variation of land cover can play a crucial role in regulating multiple dimensions of bird diversity in Zoige Marsh. The findings indicate that taxonomic, phylogenetic and functional homogenization of bird communities may differently response to the variation of land covers. It thus highlights not only the relative roles of different land covers in maintaining biodiversity and community structures of birds, but also the urgency of retarding ecosystem degradations on the eastern Qinghai-Tibetan Plateau.

Surface Tradeoffs and Elevational Shifts at the Largest Italian Glacier: A Thirty-Years Time Series of Remotely-Sensed Images

Biodiversity loss occurring in mountain ecosystems calls for integrative approaches to improve monitoring processes in the face of human-induced changes. With a combination of vegetation and remotely-sensed time series data, we quantitatively identify the responses of land-cover types and their associated vegetation between 1987 and 2016. Fuzzy clustering of 11 Landsat images was used to identify main land-cover types. Vegetation belts corresponding to such land-cover types were identified by using species indicator analysis performed on 80 vegetation plots. A post-classification evaluation of trends, magnitude, and elevational shifts was done using fuzzy membership values as a proxy of the occupied surfaces by land-cover types. Our findings show that forests and scrublands expanded upward as much as the glacier retreated, i.e., by 24% and 23% since 1987, respectively. While lower alpine grassland shifted upward, the upper alpine grassland lost 10% of its originally occupied surface showing no elevational shift. Moreover, an increase of suitable sites for the expansion of the subnival vegetation belt has been observed, due to the increasing availability of new ice-free areas. The consistent findings suggest a general expansion of forest and scrubland to the detriment of alpine grasslands, which in turn are shifting upwards or declining in area. In conclusion, alpine grasslands need urgent and appropriate monitoring processes ranging from the species to the landscape level that integrates remotely-sensed and field data.

Spatial variation in major water quality types and its relationships with land cover in the middle and lower reaches of Aral Sea Basin

Water resources and environmental issues in the Aral Sea Basin of Central Asia are global concerns. In this study, the water quality variables (i.e., basic physical and chemical attributes, different forms of nutrients, other elements, cations, and anions) from 21 sampling sites in the middle and lower reaches of Aral Sea Basin were measured in 2019 to explore water environmental variations and their causes. Spatial variation in 20 water quality variables was investigated, and the representative water quality types, spatial differences, and their causes were identified via multivariate analysis methods (i.e., principal component analysis and cluster analysis). Furthermore, the effects of land cover on the spatial variation in water quality types were explored. The results showed that: 1) the values of electronic conductivity (EC) and total dissolved solids (TDS) increased from the middle to the lower reaches, and the highest values were in the Aral Sea. This indicates that the concentrations of anions and cations increased from the middle to the lower reaches. For the nutrient variables, high phosphorous concentrations were in the middle reaches of Amu Darya, and high nitrate-nitrogen concentrations were in the Syr Darya. For the different forms of carbon, the highest concentrations were in the Amu Darya, particularly in the delta area of lower reaches. 2) The water quality at all sampling sites can be divided into three water quality types according to the similarity classification of water quality variables. The first type had low concentrations for most water quality variables, which were distributed in the middle reaches of Syr Darya and the Aral Sea. The second type had high concentrations of different forms of nitrogen and phosphorus, which were distributed in the middle and lower reaches of Amu Darya. The third type had high concentrations of carbon, anions, and cations, which were distributed in the Aral Sea. The water quality concentrations of the first and second types were mainly due to rock weathering processes on bare land, and the anions and cations were mainly derived from the weathering of silicates and evaporites. The concentrations of the third type were mainly due to the evaporation and crystallization processes of a dry climate, and the anions and cations were mainly derived from the weathering of silicates and evaporites, which may also be affected by carbonate weathering. 3) With an increase in the buffer zone radius for each sampling point (0.5 km to 10 km), the significant land cover changed from bare land to water, shrubland, grassland, mixed farmland, and vegetation for the first water quality type; the most significant land cover was water. There were no significant relationships between the second water quality type and land cover. For the third water quality type, the significant land cover changed from water to water, mixed farmland, and vegetation - the most significant land cover was water. Therefore, spatial variation in the water quality variables was mainly affected by the local climate conditions (i.e., climatic drought and intensive evapotranspiration) and the mainland cover types (i.e., bare land, water, farmland, grassland, and urban). To improve the water environmental conditions in the middle and lower reaches of Aral Sea Basin, stream flow should be increased to recharge the Aral Sea and weaken the evaporation and crystallization processes in the lower reaches of Aral Sea. Vegetation restoration and a return of farmland to forest and grassland should also be strengthened in the riparian zone, particularly in the middle and lower reaches of Amu Darya and Syr Darya and the Aral Sea.

Interannual Characteristics of Fine Particulate Matter in North China and Its Relationship with Land Use and Land Cover Change

Fine particulate matter (PM2.5) is an important component of air pollution, and thus it is meaningful to analyze its influencing factors. According to existing literature, most studies to date have focused on the relationship between PM2.5 and meteorological or economic factors, whereas fewer have analyzed the relationship between PM2.5 and land use and land cover change (LUCC). This study employed spatial distribution data of PM2.5 and land use and land cover data to analyze the relationship between dynamic characteristics of PM2.5 and LUCC. A geographically weighted regression (GWR) model and spatial analysis tools based on ArcGIS were used to analyze the relationship between PM2.5 dynamic characteristics and LUCC. North China was selected as the study area, and the results showed that ① The spatial pattern of PM2.5 in North China was high in the southeast and low in the northwest for 18 years. From a time perspective, the PM2.5 reached its maximum value in 2006 and has maintained a high value since then. The PM2.5 exceeded the permissible standard in most of the cities, with serious environmental pollution generally. ② The main land use and land cover types in North China from 2000 to 2015 were cropland, woodland, and grassland, and the land use and land cover change showed a trend of great decline in cropland and a great increase in construction land. ③ The results of the GWR model showed that local R2 is low in non-LUCC areas and high in LUCC areas, and the PM2.5 dynamic characteristics have a significant response to LUCC. ④ For different land use and land cover types, the distribution of PM2.5 showed a trend of construction land > cropland > water area > grassland > woodland > unused land, for different types of LUCC. PM2.5 concentration increased when natural land changed to artificial land and decreased when artificial land changed to natural land.

SUSLE: a slope and seasonal rainfall-based RUSLE model for regional quantitative prediction of soil erosion

The Revised Universal Soil Loss Equation (RUSLE) models are most widely used for quantitative prediction of soil erosion. However, these models have many shortcomings. For example, the annual total rainfall is often adopted, ignoring the inhomogeneity of seasonal rainfall. The adopted vegetation coverage indexes (VCIs) are usually the annual average vegetation coverage or VCIs obtained by monitoring on a specific day, ignoring the seasonal changes in VCIs during the year. In addition, the impact of slope on the conservation practices factor is not considered. To overcome these problem, this study aims to propose a seasonal and slope factor-based RUSLE (SUSLE) model that considers the seasonal changes in rainfall and VCIs and the effect of slope on the conservation practices factor. Based on GIS and remote sensing, the quantitative prediction of soil erosion in Ningdu County, Jiangxi Province, in 2017 is taken as a case study. The traditional RUSLE model and the proposed SUSLE model are analyzed and compared. Results show that the overall distribution characteristics of soil erosion in the two models are similar that the SUSLE model is more consistent than the RUSLE model in all erosion levels and that the prediction performances of the SUSLE model in the very low, moderate, and high erosion levels are better than those of the RUSLE model. The distribution characteristics of soil erosion in different periods and the relationships between soil erosion and environmental factors (e.g., slope and land use) under the SUSLE model are discussed. The results show that the maximum erosion area occurred in spring and the minimum area in autumn; the soil erosion amount on slopes of 8~25° reached 65.14% of the total amount; bare grassland and cultivated land are the main land cover types impacted by soil erosion in Ningdu County.

A Spatio-Temporal Analysis of Active Fires over China during 2003–2016

Fire is a common circumstance in the world. It causes direct casualties and economic losses, and also brings severe negative influences on the atmospheric environment. In the background of climate warming and rising population, it is important to understand the fire responses regarding the spatio-temporal changes. Thus, a long-term change analysis of fires is needed in China. We use the remote sensed MOD14A1/MYD14A1 fire products to analyze the seasonal variations and long-term trends, based on five main land cover types (forest, cropland, grassland, savannas and urban areas). The fires are found to have clear seasonal variations; there are more fires in spring and autumn in vegetated lands, which are related to the amount of dry biomass and temperature. The fire numbers have significantly increased during the study period, especially from spring to autumn, and those have decreased in winter. The long-term fire trends are different when delineated into different land cover types. There are significant increasing fire trends in grasslands and croplands in North, East and Northeast China during the study period. The urban fires also show increasing trends. On the contrary, there are significant decreasing fire trends in forests and savannas in South China where it is most densely vegetated. This study provides an overall analysis of the spatio-temporal fire changes from satellite products, and it may help to understand the fire risk in the changing climate for a better risk management.

Vertical differentiation of land cover in the central Himalayas

Characterized by obvious altitudinal variation, habitat complexity, and diversity in land cover, the Mt. Qomolangma region within the central Himalayas is one of the most sensitive areas to climate change in the world. At the same time, because the Mt. Qomolangma region possesses the most complete natural vertical spectrum in the world, it is also an ideal place to study the vertical structure of alpine land cover. In this study, land cover data for 2010 along with digital elevation model data were used to define three methods for dividing the northern and southern slopes in the Mt. Qomolangma region, i.e., the ridgeline method, the sample transect method, and the sector method. The altitudinal distributions of different land cover types were then investigated for both the northern and southern slopes of the Mt. Qomolangma region by using the above three division methods along with ArcGIS and MATLAB tools. The results indicate that the land cover in the study region was characterized by obviously vertical zonation with the south-six and north-four pattern of vertical spectrum that reflected both the natural vertical structure of vegetation and the effects of human activities. From low to high elevation, the main land cover types were forests, grasslands, sparse vegetation, bare land, and glacier/snow cover. The compositions and distributions of land cover types differed significantly between the northern and southern slopes; the southern slope exhibited more complex land cover distributions with wider elevation ranges than the northern slope. The area proportion of each land cover type also varied with elevation. Accordingly, the vertical distribution patterns of different land cover types on the southern and northern slopes could be divided into four categories, with glaciers/snow cover, sparse vegetation, and grasslands conforming to unimodal distributions. The distribution of bare land followed a unimodal pattern on the southern slope but a bimodal pattern on the northern slope. Finally, the use of different slope division methods produced similar vertical belt structures on the southern slope but different ones on the northern slope. Among the three division methods, the sector method was better to reflect the natural distribution pattern of land cover.

Consistency Analysis of Remote Sensing Land Cover Products in the Tropical Rainforest Climate Region: A Case Study of Indonesia

Land cover changes in tropical rainforest climate zones play an important role in global climate change and the functioning of the Earth’s natural system. Existing research on the consistency of different land cover products has mainly focused on administrative divisions (continental or national scales). However, the ongoing production of large regional or global land cover products with higher resolutions requires us to have a better grasp of confusing land types and their geographical locations for different zoning (e.g., geographical zoning) in order to guide the optimization of strategies such as zoning and sample selection in automated land cover classification. Therefore, we selected the GlobeLand30-2010, GLC_FCS30-2015, and FROM_GLC2015 global land cover products with a 30-m resolution covering Indonesia, which has a tropical rainforest climate, as a case study, and then analyzed these products in terms of areal consistency, spatial consistency, and accuracy evaluation. The results revealed that (a) all three land cover products revealed that forest is the main land cover type in Indonesia. The area correlation coefficient of any two products is better than 0.89; (b) the areas that are completely consistent among the three products account for 58% of the total area of Indonesia, mainly distributed in the central and northern parts of Kalimantan and Papua, which are dominated by forest land types. The spatial consistency of the three products is low, however, due to the complex surface types and staggered distributions of grassland, shrub, cultivated land, artificial surface, and other land cover types in Java, eastern Sumatra, and the eastern, southern, and northwestern sections of Kalimantan, where the elevation is less than 200 m. Given these results, land cover producers should take heed of the classification accuracy of these areas; (c) the absolute accuracy evaluation demonstrated that the GLC_FCS30-2015 product has the highest overall accuracy (65.59%), followed by the overall accuracy of the GlobeLand30-2010 product (61.65%), while the FROM_GLC2015 exhibits the lowest overall accuracy (57.71%). The mapping accuracy of the three products is higher for forests and artificial surfaces. The cropland mapping accuracy of the GLC_FCS30-2015 product is higher than those of the other two products. The mapping accuracy of all products is low for grassland, shrubland, bareland, and wetland. The classification accuracy of these land cover types requires further improvement and cannot be used directly by land cover users when conducting relevant research in tropical rainforest climate zones, since the utilization of these products could lead to serious errors.

Assessing Changes in Ecosystem Service Values in Response to Land Cover Dynamics in Jiangxi Province, China.

This paper examines the ecosystem service values of Jiangxi province, China using the benefit transfer approach. The land cover dynamics results show that cropland and forest are the main land cover types in Jiangxi province. Urban land drastically increased after 2000, expanding from 846.54 km2 in 2000 to 2317.48 km2 in 2015. Forest and water obviously decreased across the study periods. Consequently, the total ecosystem service values decreased from 37.91 × 1010 Yuan in 1995 to 35.27 × 1010 Yuan in 2015. The values showed a declining trend, especially during the 1995–2000 period. The largest declines in ecosystem service values were caused by decreases in forest and water cover. Regulating services experienced the largest declines in ecosystem services value. Moreover, water supply showed the largest decline in ecosystem service value between 1995 and 2015. Not surprisingly, food production increased in the whole period, especially in the 1995–2000 period. Forest and cropland played the most important roles in the total ecosystem service values of Jiangxi province. We then discussed the relationship among ecosystem services based on the ecosystem service trade-off degree. The results show that the dominant relationship among ecosystem services in Jiangxi province was synergy; thus synergy mostly occurred in all ecosystem services except for food production from 1995 to 2015. However, during the 1995–2000 period, trade-offs mainly existed in both food production and waste treatment. The proportion of synergy greatly increased in the 2000–2015 period, and the synergistic relationship between waste treatment and other ecosystem services increased. However, the trade-off relationship between food production and other ecosystem services still has not improved, which should be concerned in the future. Changes in the percentage share of cropland showed a declining trend; thus, the potential risk of cropland loss should be monitored.

Copernicus Global Land Cover Layers—Collection 2

In May 2019, Collection 2 of the Copernicus Global Land Cover layers was released. Next to a global discrete land cover map at 100 m resolution, a set of cover fraction layers is provided depicting the percentual cover of the main land cover types in a pixel. This additional continuous classification scheme represents areas of heterogeneous land cover better than the standard discrete classification scheme. Overall, 20 layers are provided which allow customization of land cover maps to specific user needs or applications (e.g., forest monitoring, crop monitoring, biodiversity and conservation, climate modeling, etc.). However, Collection 2 was not just a global up-scaling, but also includes major improvements in the map quality, reaching around 80% or more overall accuracy. The processing system went into operational status allowing annual updates on a global scale with an additional implemented training and validation data collection system. In this paper, we provide an overview of the major changes in the production of the land cover maps, that have led to this increased accuracy, including aligning with the Sentinel 2 satellite system in the grid and coordinate system, improving the metric extraction, adding better auxiliary data, improving the biome delineations, as well as enhancing the expert rules. An independent validation exercise confirmed the improved classification results. In addition to the methodological improvements, this paper also provides an overview of where the different resources can be found, including access channels to the product layer as well as the detailed peer-review product documentation.

A Climate-Smart Approach to the Implementation of Land Degradation Neutrality within a Water Catchment Area in Kenya

At the sub-national level, the United Nations Convention to Combat Desertification (UNCCD) proposes the analysis and contextualization of land degradation-neutrality (LDN) at a water catchment scale to provide decision support for the formulation of policies and programmes towards transformative LDN interventions. Building on a number of national LDN studies in Kenya, an approach for the implementation of LDN that is based on the spatial and temporal characterization of key land degradation and climate change variables was defined. For a selected water catchment area, the LDN baseline was computed, the drivers that affect land degradation and regeneration trends within the main land cover types were identified and described, the trends of key climate change variables were described, and appropriate sustainable land management interventions for the main land cover types were identified. A climate-smart landscape approach that delineated the catchment area into zones focused on adaptation, and both adaptation and mitigation objectives was then proposed. The operationalization of a climate-smart landscape will require significant investment to not only provide an understanding of the bio-physical processes and interactions occurring at the catchment level but also to develop the institutional and technical capacities of relevant actors. The landscape approach proposed for the catchment area has the potential to improve livelihoods and the productivity of ecosystems while concurrently facilitating synergies between land degradation, climate change, and other development objectives.

Using MODIS data to analyse the ecosystem water use efficiency spatial-temporal variations across Central Asia from 2000 to 2014

It is important to understand the carbon-water cycle, which accurately reflects the temporal and spatial variabilities in ecosystem water use efficiency (WUE). In this study, the Mann-Kendall (MK) test was used to study the variabilities in the spatial patterns of the gross primary production (GPP), evapotranspiration and WUE across Central Asia [the Xinjiang Uyghur Autonomous Region (XJ) in China (CHN), Kazakhstan (KAZ), Turkmenistan (TKM), Uzbekistan (UZB), Kyrgyzstan (KGZ), and Tajikistan (TJK)] from 2000 to 2014. We compared the change results by country, land cover type, population density, and human influence. In addition, the results of GPP, evapotranspiration (ET), and WUE parameter tests were combined and classified to analyse the causes of the changes in WUE. The results showed that (1) the time series of GPP, ET and WUE exhibited no significant changes. The spatial distribution of the WUE exhibited significant increases in the northern part of KAZ, the Ili Valley and the alpine region in KGZ and exhibited decreases in south Xinjiang and the irrigated area of UZB. (2) The main land cover types that exhibited changes in WUE were farmlands and grasslands, and areas with a medium population density exhibited large WUE changes. (3) The increased WUE resulted from an increased GPP and decreased ET. The increased GPP was because of increased precipitation and the Green for Grain Project, and the decreased ET was due to the response of vegetation to drought stress; the decreased WUE was mainly caused by changes in the crops planted and unreasonable water use practices in the irrigated agricultural areas in Central Asia. This study, which is based on the variabilities in WUE spatial patterns, should provide a theoretical basis for ecosystems in arid land areas.

The potential distribution and disappearing of Yunnan snub-nosed monkey: Influences of habitat fragmentation

Analysisof environmental variables and organism occurrence records offers insight that can be used to predict potential distribution areas and habitat fragmentation. For large landscapes, modeling is the most convenient and effective way to conduct habitat research. Two species distribution models, BIOMOD2 and FRAGSTATS 4.2, were given data on environmental variables and organism occurrence records as input and used to predict the potential suitable habitat and habitat fragmentation for the Yunnan snub-nosed monkey (Rhinopithecus bieti). Our results estimated the total area of potentially suitable habitat for R. bieti as 7412.82 km2, but only 4164.58 km2 was found to be inhabited by R. bieti. We found that the main land cover type in the potential suitable distribution area of R. bieti was evergreen needle-leaf forest (6153.95 km2, 83.02%). Comparison of inhabited and suitable but uninhabited habitats showed that areas actually inhabited by R. bieti had a lower patch density (PD) and higher largest patch index (LPI) than uninhabited habitats only in evergreen needle-leaf forest. The potential suitable habitats of R. bieti has increased significantly, but the actual distribution has shrunk from 1997 to 2017. Although the government has made great progress in protecting R. bieti, logging that took place before the regulations and the boundary effect of roads and rivers resulted in the local extinction of R. bieti in some potentially suitable areas. In view of this, we propose to establish a national park for Yunnan snub-nosed monkeys. We also suggest protecting the potentially suitable but currently empty habitats for later release of R. bieti. Successfully reintroducing R. bieti into areas where it formerly lived will require continual and careful habitat monitoring.

An analysis of the drivers that affect greening and browning trends in the context of pursuing land degradation-neutrality

Understanding the drivers of land degradation and regeneration is crucial for planning appropriate responses within both degraded and non-degraded land. In this paper, using Kenya as the study area, we sought to identify the key drivers that affect greening and browning trends within the 4 main land cover types (agriculture, forest, grassland and shrubland) and within an area characterised by land cover change. The methodological approach used was the random forest classification algorithm, whereby the dependent variable was represented as 4 classes of NDVI greening and browning trends (strong browning, moderate browning, moderate greening, and strong greening). The explanatory variables (n = 28) were broadly grouped into 2 categories, natural and anthropogenic, and included a number of variables as proxies for broad socio-economic development. All models showed strong performance, and the mean values for accuracy and Kappa were 0.96 and 0.95, respectively. Variables that repeatedly featured as the 5 most important variables across the datasets were: travel time to an urban area, distance to towns, distance to roads, distance to rivers, slope and vulnerability to climate change impacts. When the variables were grouped by SDGs, the results obtained showed that the variables grouped under the SDGs 15 (life on land), 8 (economic growth) and 13 (climate action) cumulatively accounted for approximately 80% of the prediction of the greening and browning trends. Our results raise the following considerations to enrich on-going and future policy and planning discussions aimed at addressing LDN: the implementation of LDN should be anchored on tried and tested SLM interventions; further analysis of the drivers of greening and browning trends should be undertaken at the sub-national level; integrated approaches that lead to greater alignment across multiple development priorities, including climate change, should be promoted; and targeted enforcement of environmental legislation is needed to deter processes and activities that are likely to lead to the degradation of land.

Developing land-cover driver model for estimating the intensity of surface urban heat islands using landsat 8 satellite imagery

It is of utmost importance to understand and monitor the impact of urban heat islands on ecosystems and overall human health in the context of climate change and global warming. This research was conducted in a tropical city, Hanoi, with a major objective of assessing the quantitative relationships between the composition of the main land-cover types and surface urban heat island phenomenon. In this research, we analyzed the correlation between land-cover composition, percentage coverage of the land cover types, and land surface temperature for different moving window sizes or urban land management units. Landsat 8 OLI (Operational Land Imager) satellite data was utilized for preparing land-cover composition datasets in inner Hanoi by employing the unsupervised image clustering method. High-resolution (30m) land surface temperature maps were generated for different days of the years 2016 and 2017 using Landsat 8 TIRS (Thermal Infrared Sensor) images. High correlations were observed between percentage coverage of the land-cover types and land surface temperature considering different window sizes. A new model for estimating the intensity of surface urban heat islands from Landsat 8 imagery is developed, through recursively analyzing the correlation between land-cover composition and land surface temperature at different moving window sizes. This land-cover composition-driven model could predict land surface temperature efficiently not only in the case of different window sizes but also on different days. The newly developed model in this research provides a wonderful opportunity for urban planners and designers to take measures for adjusting land surface temperature and the associated effects of surface urban heat islands by managing the land cover composition and percentage coverage of the individual land-cover types.