Degree Of Desertification Research Articles

A multi-scale assessment of desertification severity in the Eastern Mediterranean region based on albedo-MSAVI feature space.

Resampling the same satellite image to conduct a multi-scale assessment of desertification can be accompanied by distortion of terrestrial objects and spectral information, which can lead to uncertainty in the generated information. To address this, this study assesses desertification severity in an area of arid and semi-arid climate in the Eastern Mediterranean (Jordan)that is characterised by cloudless scenesusingmulti-sensor data of the same scene at the same time. To this end, Sentinel-2 at 10 m and 60 m, Landsat-8 at 30 m and MODIS at 250 m and 500 m were collected to extract albedo and modified soil adjusted vegetation index (MSAVI), and subsequently to construct albedo-MSAVI feature space. Using the negative correlation between albedo and MSAVI, desertification degree index (DDI) was generated. The resulting multi-scale DDI maps bear a relative resemblance in terms of spatial distribution, patterns, and proportions. The DDI maps indicate that extremely serious and serious desertification are widespread, accounting for 50% of the study area, primarily in the eastern portions. However, finer DDI maps (10 m, 30 m and 60 m) are essential for detecting small-scale desertification characteristics due to their ability to capture local spatial variabilities, while coarser ones (250 m and 500 m) are better suited for capturing broad-scale desertification patterns driven by climatic factors, in which MODIS data exhibit a relatively higher positive correlation with seasonal average precipitation. Although finer DDI maps show higher accuracy compared to coarser ones, the accuracy of DDI maps of MODIS has shown an increase within a homogeneous landscape. Accordingly, synchronised multi-scale assessment of desertification severity is not only influenced by the spatial resolution but also by the landscape heterogeneity and the type of satellite sensor utilised. The multi-scale approach applied in this study can provide insights on scale-dependent desertificationthat help in devising overarching mitigation strategies.

Contribution of Litter and Root to Soil Nutrients in Different Rocky Desertification Grasslands in a Karst Area.

Litter and root decomposition is an important source of soil organic matter and nutrients. To ascertain the contribution of litter and root to natural grassland nutrients in rocky desertification areas, from March 2017 to January 2018, the continuous soil column method, collector method, and litter decomposition method were used to study the soil nutrients, litter and root biomass, decomposition, and nutrient release of potential, moderate, and severe rocky desertification grasslands, as well as their responses to rocky desertification. The results showed that the litter and root decomposition rate showed a trend of being first fast and then slow, and the decomposition rate of litter and root was greater than 50% after 300 days. The annual litter decomposition rates of potential, moderate, and severe rocky desertification grasslands were 69.98%, 62.14%, and 49.79%, respectively, and the annual decomposition rates of root were 73.64%, 67.61%, and 64.09%, respectively. With a deepening degree of rocky desertification, the litter and root decomposition rate decreased. The decomposition coefficients, k, of litter in potential, moderate, and severe rocky desertification grasslands were 1.128, 0.896, and 0.668, respectively, and the decomposition coefficients, k, of root were 1.152, 1.018, and 0.987, respectively. The nutrient release processes of litter and root were different, and the release mode ultimately manifests as "release". In rocky desertification grasslands, the organic carbon (OC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) released by litter and root decomposition were 18.93-263.03 g·m-2·yr-1, 1.79-5.59 g·m-2·yr-1, 0.18-0.47 g·m-2·yr-1, and 0.66-3.70 g·m-2·yr-1, respectively. The contribution of root to soil nutrients was greater than that of litter. The degree of rocky desertification was negatively correlated with the biomass, decomposition rate, and nutrient return amount of litter and root. The results of this study provide direct field evidence and illustrate the contribution of litter and root decomposition in rocky desertification grasslands to soil nutrients.

Thirty years’ spatio-temporal evolution of desertification degrees and driving factors in Turpan–Hami Basin, Xinjiang, China

Turpan-Hami (Tuha) Basin is in an extremely arid area, surrounded by mountains and desert with sparse vegetation. It has experienced serious desertification over the past 30 years, resulting in ecological environment and socio-economic issues. To reveal the temporal and spatial evolutions of desertification degrees in Tuha Basin, we first constructed an evaluation system for the desertification degree classification using vegetation and soil-related indices; then long-time series Landsat 5 TM/ Landsat8 OLI images and a C5.0 decision tree (DT) model were used to monitor large-scale desertification from 1990 to 2020. We applied a geographic detector to discover the driving forces between desertification changes and natural and human factors. The results demonstrated that the severe desertification (SD) accounted for the largest desertification degree, and the transitions of various desertification degrees mainly occurred between extremely severe desertification (ESD) and SD, which were considered the most active degrees. Only 9.4 % of Tuha Basin showed an expansion trend in desertification degree, with the most significant expansion occurred in 1990–1995. The proportion of 13.6 % desertification showed a reversion trend, with the most significant reversion occurred in 1995–2010. The main driving factors affecting the evolution of desertification degrees were precipitation and temperature, with the average q value higher than 0.95. Human activity factors such as year-end cropland area and population also impacted the patterns of desertification degree, with the q values of 0.9 and 0.7, respectively. The interactive detection enhanced the driving forces and the interaction between precipitation and other factors played a leading role in desertification degree changes. The results provide scientific data and a basis for desertification control and ecological protection in arid areas.

Response of preferential flow to soil − root − rock fragment system in karst rocky desertification areas

The response of preferential flow to the soil − root − rock fragment systems is essential for understanding the eco-hydrological processes in karst rocky desertification (KRD) areas. In this study, we investigated the soil properties, root, and rock fragment distribution characteristics and preferential flow in this system. Results show that there are differences in the development of preferential flow under five grades of rocky desertification: light rocky desertification (LRD) > potential rocky desertification (PRD) > non-rocky desertification (NRD) > moderate rocky desertification (MRD) > severe rocky desertification (SRD). Different degrees of rocky desertification have facilitating or inhibiting effects on preferential flow. LRD and PRD promote preferential flow with ratio of 6.6 %–9.6 %, while MRD and SRD inhibit preferential flow with ratio of 4.2 %–6.7 %. The preferential flow is simultaneously influenced by the components of soil − root − rock fragment systems. Root system indicators (i.e., root biomass, root bulk density, and root length density) generally decrease as grades of rocky desertification increase. The surface outcrops density, rock fragment density, and volume fraction tend to increase with grades of rocky desertification. A principal components analysis found that preferential flow of MRD and SRD is highly influenced by rock fragments, while LRD is more driven by root systems and soil properties. PRD is averagely influenced by the combination. These findings suggest that appropriate plant and rock fragment ratios can effectively avoid water loss in the form of preferential flow and more attention should be paid to the ecological problems of LRD and PRD areas.

Spatial-Temporal Process of Land Use/Land Cover and Desertification in the Circum-Tarim Basin during 1990–2020

The problem of desertification in the Tarim Basin, an area with a unique geography and climatic conditions, has received extensive research attention not only in China but also around the world. Between natural factors and human activities, the latter are considered the main cause of desertification, with the excessive use of land resources accelerating its risk. This study classified the degree of desertification into five types, no, light, moderate, severe, and extremely severe desertification, and focused on the spatio-temporal changes in LULC, desertification development, and their relationship in the Circum-Tarim Basin during the period of 1990–2020, and the results indicated the following. (1) Over the 30-year study period, farmland development was frequent in the basin. The total farmland area increased significantly by 1.40 × 104 km2, which resulted from the occupation of grassland (mainly low-covered and medium-covered grassland) and unused land (mainly saline–alkali land). (2) There was a general alleviation of the effects of desertification, but also local deterioration. The area of no-desertification land has significantly increased (an increase of 2.10 × 104 km2), and the degree of desertification has shifted significantly to adjacent lighter degrees, but the area of extremely severe desertification in certain regions has increased (an increase of 7.89 × 104 km2). (3) There was an inseparable relationship between LULC and desertification. Oasisization and desertification were two processes that interacted and were interrelated. There was an approximately 54.42% increase in no-desertification land area mainly occurring in the region where LULC types changed (Region II), although this area only accounted for 9.71% of the total area of the basin. There was an approximately 98.28% increase in the area of extremely severe desertification occurring where there were no changes in LULC types (Region I). Region II demonstrated the best effects of desertification prevention and control in the 30-year study period in the Circum-Tarim Basin. Land development and oasis expansion have led to concentrated water use, resulting in water scarcity in certain areas, which cannot support the needs of vegetation growth, thus aggravating the degradation. Hence, “adapting measures to local conditions, rational planning, zoning policies, precise prevention and control” will be the way forward for desertification control in the future in the Circum-Tarim Basin.

Transforming desertification patterns in Asia: Evaluating trends, drivers, and climate change impacts from 1990 to 2022

Owing to the combined effects of climate change and human activities, the type of desertification in the arid regions of Asia has undergone profound changes, and the problem of desertification has become increasingly prominent. To help address this problem, this study clarifies the transformation trends and characteristics of desertification types across Asia and discusses key areas for desertification prevention and control. Based on a series of Landsat satellite images, combined with the classification method of the desertification degree and a machine learning model, the desertification types, trends, and conversion degrees in the arid regions of Asia were systematically evaluated. In addition, the impact mechanism of climate change on the conversion between desertification types was evaluated. The primary results were as follows: (1) Various desertification types in the arid areas of Asia from 1990 to 2022 exhibited evident time series characteristics. Extremely severe desertification expanded from 1990 to 2009 and subsequently shrunk; (2) The degree of desertification in the arid regions of Asia exhibited different change characteristics in different periods, and the converted area of the same conversion type was different in different periods; (3) Different desertification conversion types in different periods have different drivers; however, overall, soil moisture has the greatest contribution to desertification conversion type. These results provide a scientific reference for the formulation of reasonable desertification prevention and control policies.

Spatiotemporal changes of desertification degree in the Algerian green barrier over the last four decades (1984–2020)

Desertification is a major challenge for the sustainable development of arid and semiarid regions worldwide. The major novelty of this study lies in assessing, for the first time, the desertification degree changes in the Algerian green barrier using remote sensing and the Analytic Hierarchy Process (AHP) approach from 1984 through 2020. Four widely used remote sensing indices (LSA, NDVI, TGSI, and PDSI) were used in the Google Earth Engine (GEE) cloud computing platform as indicators of desertification in the study area. The results of the accuracy assessment of the generated desertification degree maps for 1984, 2000, and 2020 show high Kappa coefficient values exceeding 80%. Overall, the degree of desertification of the green barrier increased from 1984 to 2020. The area of medium degree has decreased from 15393.21 km2 (37.70%) to 9624.43 km2 (23.57%) between 1984 and 2020, respectively; whereas the area of high degree has increased from 23907.08 km2 (58.55%) to 30502.52 km2 (74.70%) for the same period. The combination of remote sensing and the AHP technique has proven to be effective in the spatiotemporal monitoring of the desertification degree particularly in data–scarce regions. Our findings emphasize the high expansion of desertification across the green barrier area, which information is essential for adopting adequate strategies for desertification control in the future.

Soil Microbial Communities in Pseudotsuga sinensis Forests with Different Degrees of Rocky Desertification in the Karst Region, Southwest China

Rocky desertification (RD), a natural and human-induced process of land degradation in karst areas, has become the primary ecological disaster and one of the obstacles to sustainable ecological development in southwest China. Nevertheless, the variation of soil physical and chemical properties, bacterial and fungal communities, and their relationships in RD forests remains limited. Therefore, soil samples were collected from forests under four degrees of RD (NRD, non-RD; LRD, light RD; MRD, moderate RD; and SRD, severe RD) and subjected to high-throughput sequencing of 16S rRNA and ITS1 genes. The results showed a significant reduction in bacterial richness and diversity, while fungal richness and diversity decreased markedly and then showed a balanced trend with the increase in RD degree, indicating that bacteria and fungi did not present the same dynamics in response to the process of RD. The bacterial communities were dominated by Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, while the fungal communities were dominated by Basidiomycota, Ascomycota, and Mortierellomycota. The PCoA and NMDS demonstrated significant differences in microbial communities in study sites, among which the fungal communities in non-RD forest and LRD forest clustered together, suggesting that fungal communities were more stable than bacteria in RD forest. The db-RDA, Mantel test, and random forest model confirmed the important role of soil BD, pH, SOC, AN, and AP in driving microbial diversity and communities. The IndVal analysis suggested that Chloroflexi, Patescibacteria, Atheliales, and Cantharellales with high indicator values were identified as potential bio-indicators for RD forests. This study could not only improve our understanding of bacterial and fungal community dynamics across RD gradients, but also could provide useful information for the further use of microorganisms as indicators to reflect the environmental changes and ecosystem status during forest RD.

Study on the relationship between regional soil desertification and salinization and groundwater based on remote sensing inversion: A case study of the windy beach area in Northern Shaanxi

Soil desertification and salinization are important environmental concerns in arid regions, and their relationship with groundwater change must be further clarified. However, the relationships among soil desertification, salinization, and groundwater are difficult to investigate on a large spatiotemporal scale using traditional ground surveys. In the windy beach area in Northern Shaanxi (WBANS), desertification and salinization problems coexist; therefore, this area was selected as the study area. The feasibility of implementing large-scale remote sensing inversions to identify the degree of desertification and salinization was verified based on measured data, and the degree of influence of groundwater burial depth (GBD) on desertification and salinization was quantified using the geodetector and residual trend analysis methods. The results showed that the GBD in the WBANS presented an increasing trend and the degree of salinization showed a decreasing trend. Moreover, the joint influence of the unique natural environment and anthropogenic activities has led to increases in fractional vegetation cover and considerable improvements in the ecological environment. The intensity of desertification explained by GBD in the WBANS increased significantly (p < 0.01) at a rate of change of 0.0190/year, with high q-values above 0.66 for both Yuyang and Shenmu. The contribution rate of potential evapotranspiration and precipitation to salinization in Yuyang and Shenmu was >97 %, and the contribution rate of GBD to salinization in Dingbian, Jingbian, and Hengshan was 34.78 %, 31.15 %, and 29.41 %, respectively. Overall, the suitable GBD in the WBANS is 2–4 m. The study results provide a reference for research on the inversion, monitoring, and prevention of desertification and salinization dynamics on a large spatiotemporal scale and offer a scientific basis for rationally determining GBD.

Desertification simulation using wavelet and box-jenkins time series analysis based on TGSI and albedo remote sensing indices

Desertification has been listed as one of the most critical global environmental issues, posing a significant threat to life, particularly in arid and semiarid regions. Therefore, gaining a comprehensive understanding of the present and future desertification trends becomes imperative. This study employs a feature space model, which effectively captures land surface changes related to desertification, enabling the extraction of pertinent information. Subsequently, time series models are used to determine the most accurate desertification simulation. Twenty-one ETM + sensor images were utilized to calculate the Topsoil Grain Size (TGSI) and Albedo remotely sensed indexes. Constructing the Albedo-TGSI feature space, the Desertification Degree Index (DDI) was extracted for each year. Different levels of desertification were identified by applying a natural break classification on the DDI values, and corresponding break values were obtained. The representative desertification degree for each year was determined by calculating the average of the minimum and maximum break values, resulting in the generation of five distinct time series for five desertification degrees. Different ARIMA models and wavelet transforms were selected to simulate the various desertification degrees based on the analysis of autocorrelation and partial autocorrelation functions and trial and error, respectively. The most suitable ARIMA models with the lowest errors were identified as follows: ARIMA (1,0,7) for severe desertification, ARIMA (0,1,6) for high desertification, ARIMA (0,0,7) for moderate desertification, and ARIMA (3,0,6) for non-desertification degrees. Among the various wavelet transform families tested, the Symlet family proved to be the most effective, except for the low desertification degree. The following wavelet transforms yielded the best results for each degree of desertification: Symlet3 for severe desertification, Symlet7 for high desertification, Symlet7 for moderate desertification, Daubechies 5 (db5) for low desertification, and Symlet7 for non-desertification degree simulations, all exhibiting the minimum error rates.

The Latest Desertification Process and Its Driving Force in Alxa League from 2000 to 2020

Alxa League of Inner Mongolia Autonomous Region is a concentrated desert distribution area in China, and the latest desertification process and its driving mechanism under the comprehensive influence of the extreme dry climate and intense human activities has attracted much attention. Landsat data, including ETM+ images obtained in 2000, TM images obtained in 2010, and OLI images obtained in 2020, were used to extract three periods of desertification land information using the classification and regression tree (CART) decision tree classification method in Alxa League. The spatio-temporal variation characteristics of desertification land were analyzed by combining the transfer matrix and barycenter migration model; the effects of climate change and human activities on regional desertification evolution were separated and recombined using the multiple regression residual analysis method and by considering the influence of non-zonal factors. The results showed that from 2000 to 2020, the overall area of desertification land in Alxa League was reduced, the desertification degree was alleviated, the desertification trend was reversed, and the desertification degree in the northern part of the region was more serious than in the southern part. The barycenter of the slight, moderate, and severe desertification land migrated to the southeast, whereas the serious desertification land’s barycenter migrated to the northwest in the period of 2000–2010; however, all of them hardly moved from 2010 to 2020. The degree of desertification reversal in the south was more significant than in the north. Regional desertification reversal was mainly influenced by the combination of human activities and climate change, and the area accounted for 61.5%; meanwhile, the localized desertification development was mainly affected by human activities and accounted for 76.8%.

Impacts of Land Use and Climate Change on Ecosystem Services in Agro-pastoral Ecotone

Land use and climate change are the most important factors driving the change in ecosystem services (ESs). It is critical to understand the mechanisms behind such changes for improving ESs. However, there is still a lack of accurate understanding of change and dominant influencing factors of ESs in the agro-pastoral ecotone. This study took Naiman Banner, a typical farming pastoral ecotone in China, as the case study area. Based on the InVEST model, the revised wind erosion equation (RWEQ) and the revised universal soil loss equation (RUSLE) were used to calculate water yield, soil retention, and windbreak and sand-fixing in Naiman Banner in 2005 and 2015. Finally, the impacts of land use and climate change on these three ecosystem services were analyzed by using contribution rate formula, Pearson correlation coefficient, and geodetector methods. The results indicate that:① from 2005 to 2015, water yield and soil retention in Naiman Banner showed an overall upward trend, increasing by 22.41% and 6.74%, respectively, and windbreak and sand-fixing decreased by 66.24%. ② The change in water yield and windbreak and sand-fixing was mainly affected by climate change, and the change in soil retention was mainly affected by land use change. ③ Actual evapotranspiration change and land use change were the main factors affecting the spatial differentiation of water yield, with the explanatory powers of 94.50% and 50.05%, respectively. The main factors influencing the spatial differentiation of windbreak and sand-fixing were actual evapotranspiration change and land desertification degree, with the explanatory power of 19.84% and 16.15%, respectively. ④ The correlation of ESs in Naiman Banner was weak, and only windbreak and sand-fixing and water yield showed a weak significant synergy. Based on the results, we recommend that managers increase the proportion of grassland in sandy areas, implement closed management in pastoral areas, and introduce drip irrigation and other water-saving technologies in farmland, and ecological protection should continue to be given priority in city.

Temporal–Spatial Distributions and Influencing Factors of Heavy Metals As, Cd, Pb, and Zn in Alluvial Soils on a Regional Scale in Guangxi, China

Understanding the temporal–spatial distribution and influencing factors of heavy metals on a regional scale is crucial for assessing the anthropogenic impacts and natural variations in elemental geochemical behavior. This study evaluated the spatial distributions of the heavy metals As, Cd, Pb, and Zn as well as the driving mechanisms over the past 31 years in Guangxi, China, using three geochemical baseline projects (the Environmental Geochemical Monitoring Network Project (EGMON) project 1992–1996; the Geochemical Baseline (CGB) 1 project 2008–2012; and the CGB2 project 2015–2019). By calculating the variable importance using the random forest algorithm, it was found that natural factors are the primary drivers of the spatial distribution of heavy metals in the EGMON project, especially precipitation for As, the digital elevation model (DEM) for Cd and Pb, and temperature for Zn. Surface alluvial soils showed obvious heavy metal enrichment in the CGB1 project, with the gross domestic product (GDP) driving the spatial distribution of all heavy metals. In addition, the anomalous intensity and range of heavy metals in the CGB2 project decreased significantly compared with the CGB1 project, especially owing to the normalized difference vegetation index (NDVI) as a positive anthropogenic factor that improves the degree of rocky desertification, thus reducing the heavy metal contents of As and Pb, and the precipitation promoting the decomposition of Fe–Mn concretions and thus the migration of Cd and Zn. This research promotes an understanding of anthropogenic and natural influences on the spatiotemporal distribution of heavy metals and is of great significance for environmental monitoring and governance.

Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China

Oasification and desertification are two essential processes of land use and cover (LULC) change in arid regions. Compared to desertification, which is widely regarded as the most severe global ecological issue, the importance of oasification has not received universal recognition. However, neglecting oasification can lead to detrimental outcomes to the effectiveness of ecological governance by affecting the comprehensiveness of environmental policies proposed only based on desertification. Therefore, this study incorporates oasification into the examination of desertification by analyzing land use data for five representative periods spanning from 1980 to 2020, as well as socioeconomic and environmental data from 2000 to 2010. The aim is to evaluate the spatial and temporal dynamics of oasification and desertification in the Manas River Basin and identify the underlying factors driving these processes. The findings indicated that (1) the general trend of oasification and desertification exhibited the expansion of oases and the retreat of deserts. Specifically, the oasification area showed a “decrease-increase-decrease” pattern over time, while the desertification area consistently decreased. (2) In terms of spatial distribution, oasification and desertification displayed a transition from scattered and disordered patterns to an overall more organized pattern, with the hotspot area of desertification shifting from Shawan County to Manas County over time. (3) Population density, average land GDP, soil type and annual precipitation significantly influenced the degree of oasification, with driving force q-values above 0.4, which were the key factors driving oasification. Population density and average land GDP significantly affected the degree of desertification, with driving force q-values above 0.35, which were the key factors driving desertification. The driving force of all factors increased significantly after the interaction, and socioeconomic factors influenced oasification and desertification more than other factors. The study’s findings aim to provide a scientific basis for land resource use, ecological governance and sustainable development in the Manas River basin.

Analysis of Spatial-Temporal Changes and Driving Forces of Desertification in the Mu Us Sandy Land from 1991 to 2021

Desertification is one of the most critical environmental and socioeconomic issues in the world today. Located in the transitional region between the desert and the Loess Plateau, the Mu Us Sandy Land is one of the nine most environmentally sensitive areas in the world. Remote sensing provides an effective technical method for desertification monitoring. In order to analyze the spatiotemporal distribution of desertification in the Mu Us Sandy Land from 1991 to 2021, the “MSAVI-Albedo” model was employed to extract desertification data in 1991, 2002, 2009 and 2021. The clustering characteristics of desertification were analyzed based on Moran’s I statistic. Subsequently, the driving forces in desertification changes were investigated using a geographical detector to analyze the influence of soil, meteorology, and topography on desertification. Additionally, the impact of meteorological and human factors on desertification change in the Mu Us Sandy Land was assessed. From 1991 to 2021, the degree of desertification of the Mu Us Sandy Land showed an overall decreasing trend, and the percentage of land classified as undergoing extremely severe, severe, moderate and mild desertification was improved by 86.11%, 81.82%, 52.5% and 37.42%, respectively. The proportion of land classified as undergoing extremely severe desertification decreased from 29.22% to 5.62%, and the proportion of land undergoing no desertification increased from 4.16% to 18.33%. At the same time, the desertification center shifted westward, and the desertification distribution showed a clustering trend. It is known that different factors affect the formation and distribution of desertification in the Mu Us Sandy Land in the following order: soil, meteorology, and topography. Over the past 30 years, the mean annual temperature and annual precipitation increased at rates of 0.01871 °C/a and 1.0374 mm/a, respectively, while the mean annual wind speed decreased at a rate of 0.00945 m/s·a. These changes provided more favorable natural conditions for vegetation growth and sand fixation. Human factors, such as economic development, agriculture and animal husbandry practices, and the policy of returning farmland to forest (grassland) also had a significant impact on the desertification process, leading to a year-by-year improvement in the ecological environment of the Mu Us Sandy Land.

A hybrid physics-data-driven optimization model for grassland grazing management

Abstract This paper presents a hybrid physics-data-driven optimization model for grassland grazing management. It comprehensively assesses essential factors in the Abaga Banner grassland ecosystem, including soil moisture, vegetation biomass, desertification degree index, and soil compaction. Through a thorough analysis, the impacts of grazing patterns and intensity on the grassland’s physical characteristics and biomass are studied. Employing genetic algorithms, an optimal grazing model is formulated to minimize soil desertification throughout the year. The paper aims to contribute to grassland ecology restoration and ensure sustainable livelihoods for local herdsmen, offering a scientific foundation for promoting the sustainable growth of grassland husbandry.

Extraction of Rocky Desertification Information in the Karst Area Based on the Red-NIR-SWIR Spectral Feature Space

The complex topography, severe surface fragmentation and landscape heterogeneity of the karst region of southwest China make it extremely difficult to extract information on rocky desertification in the region. In order to overcome the disadvantages of the surface parameter-based feature space approach, which is difficult to construct and apply, this study uses the reflectance of Landsat 8 Operational Land Imager (OLI) in the red (Red), near-infrared (NIR) and shortwave infrared (SWIR) bands as the feature variables, and establishes a two-dimensional SWIR-NIR, Red-NIR and SWIR-Red reflectance spectral feature space. The three models of perpendicular rocky desertification index 1 (PRDI1), perpendicular rocky desertification index 2 (PRDI2) and perpendicular rocky desertification index 3 (PRDI3) were also constructed based on the variation of the degree of rocky desertification in each spectral feature space. The accuracy of the rocky desertification extracted by these three index models was verified and compared with the karst rocky desertification index (KRDI) and rocky desertification difference index (RSDDI), which are constructed based on the surface parameter feature space. The results show that: (1) The waveband reflectance-based feature space model provides a new method for large-scale rocky desertification information extraction, characterized by easy data acquisition, simple index calculation and good stability, and is conducive to the monitoring and quantitative analysis of rocky desertification in karst areas. (2) The overall accuracy and Kappa coefficient of PRDI1 are 0.829 and 0.784, respectively, both higher than other index models, showing the best applicability, accuracy and effectiveness in rocky desertification information extraction. (3) According to the results extracted from PRDI1, the total area of rocky desertification in Huaxi District of Guizhou province is 320.44 km2, with the more serious grades of rocky desertification, such as severe and moderate, mainly distributed in the southwestern, western and southeastern areas of Huaxi District. This study provides important information on the total area and spatial distribution of different degrees of rocky desertification in the study area, and these results can be used to support the local government’s ecological and environmental management decisions. The method proposed in this study is a scientific and necessary complement to the characteristic spatial methods based on different surface parameters, and can provide important methodological support for the rapid and efficient monitoring of karstic rocky desertification over large areas.

Comparison of aeolian desertification between the Moltsog Dune Field in Mongolia and the Ujimqin Dune Field in China

AbstractAeolian desertification is a severe ecological and environmental problem in arid regions. Research on its spatio‐temporal distribution, modelling and driving force is necessary to prevent the development of aeolian desertification. In this study, the Moltsog Dune Field in Mongolia and the Ujimqin Dune Field in China were selected as the study areas, as both contain dunes under similar physical conditions. Using LANDSAT data from 1988, 1995, 2002, 2009, 2016 and 2020, the spatial–temporal distribution and the degree of development of aeolian desertification in the two dune fields over the past 30 years were compared. Two periods of high‐resolution images were then used to compare the surface morphological changes induced by aeolian desertification in these dune fields. Climatic and socio‐economic data of the same period were used to compare and analyse the potential causes of changes in aeolian desertification in these regions. The results show that: (1) Over the last 30 years, the degree and development rate of aeolian desertification in the Ujimqin Dune Field were generally higher than those in the Moltsog Dune Field, and the former had a high degree of fragmented aeolian desertification patches with an expanding range. (2) The main form of aeolian desertification is the reactivation of fixed dunes, which includes the development of blowouts on the flat grassland under the influence of human activities in the Ujimqin Dune Field. (3) Desertification in Moltsog is mainly affected by climatic factors, while that in Ujimqin is mainly driven by anthropogenic activities. The latter is specifically affected by the high grazing intensity before 2000 and increased mining activities after 2000. These findings provide a reference for comparing the aeolian desertification process and meaningful information for preventing and controlling aeolian desertification and enabling the sustainable development of dune fields in arid regions.

Long-term responses in different karst agricultural production systems to farm management and climate change: A comparative prefecture-scale study in Southwest China

Rapid shifts have occurred in the agricultural production systems of the karst regions in Southwest China to meet increasing food demands. The responses of agricultural production vary under different degree of rocky desertification. However, the interactive effects of related driving factors on the food production sustainability of local crops are unknown. In this study, we quantified the impacts of seven key indicators—population, cropland area, multiple cropping index, irrigation area, fertilizer use, temperature and precipitation—on agricultural production in three rocky desertification grade regions from 1960 to 2011. We also classified these indicators into three categories: population, farm management and climate change. The results showed that farm management and population were the main drivers of increased food crop production, contributing 79.7% and 17%, respectively. In contrast, climate change had a limited influence on agricultural production. With increases in crop yield, the influences of some indicators were enhanced, and the negative impact on the environment was also increased; therefore, the sustainability of agricultural production systems could be adversely affected in the future. The agricultural production systems in mild rocky desertification areas (Zunyi) could meet the current food demands, while the areas with moderate and severe rocky desertification (Bijie and Qianxinan, respectively) are faced with substantial pressure. Although continuous improvements in agricultural production efficiency due to advances in modern science, technology and management have partly mitigated environmental pressure, rocky desertification poses a challenge to the sustainable development of agriculture in Southwest China. These findings provide a reference for adjusting farm management practices and climate change countermeasures in regions with different degrees of rocky desertification to achieve agricultural production sustainability in the future.

A dataset of desertification distribution in Mongolia in 2015

Desertification is one of the most serious eco-environmental and socio-economic problems in the world. Mongolia is a hot area of global desertification because of its fragile ecological environment and serious land degradation. In this study, based on Google Earth Engine platform, we selected Landsat7 remote sensing images, normalized vegetation index (NDVI), surface albedo (Albedo), improved soil adjusted vegetation index (MSAVI) and topsoil grain size index (TGSI) as desertification discrimination indexes, and combined the geographical division with desertification inversion characteristic space models to complete the fine inversion of Mongolian desertification information. In this way, we obtained a dataset of desertification distribution in Mongolia in 2015. The quality and accuracy of this dataset are verified by referring to field survey data and high-resolution Google Earth images. The overall evaluation accuracy is 87.00% and the Kappa coefficient is 83.19%. This dataset directly reflects the spatial distribution of different degrees of desertification in Mongolia, and can provide detailed and reliable data support for the delineation of key areas for desertification control and the formulation of restoration strategies in Mongolia. It is of great significance for the ecological environment and green and sustainable development of the China-Mongolia-Russia Economic Corridor.