Desertification Monitoring Research Articles

The Remote Sensing based Dynamic Monitoring of Land Desertification in Qinghai Province

The Remote Sensing based Dynamic Monitoring of Land Desertification in Qinghai Province

Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions

Land degradation and desertification has been ranked as a major environmental and social issue for the coming decades. Thus, the observation and early detection of degradation is a primary objective for a number of scientific and policy organisations, with remote sensing methods being a candidate choice for the development of monitoring systems. This paper reviews the statistical and ecological frameworks of assessing land degradation and desertification using vegetation index data. The development of multi-temporal analysis as a desertification assessment technique is reviewed, with a focus on how current practice has been shaped by controversy and dispute within the literature. The statistical techniques commonly employed are examined from both a statistical as well as ecological point of view, and recommendations are made for future research directions. The scientific requirements for degradation and desertification monitoring systems identified here are: (I) the validation of methodologies in a robust and comparable manner; and (II) the detection of degradation at minor intensities and magnitudes. It is also established that the multi-temporal analysis of vegetation index data can provide a sophisticated measure of ecosystem health and variation, and that, over the last 30 years, considerable progress has been made in the respective research.

Soil degradation, landscape and climate variations in a Mediterranean agro-forest system (Thriasio, Greece): proposal for a desertification indicator using time series analysis

As a contribution to soil degradation and desertification monitoring in the northern Mediterranean basin, the present study investigates long-term climate variations in the traditional agro-forest system of Thriasio Plain (Greece) by examining month average temperature, precipitation, relative humidity, Standardised Precipitation Index (SPI) and de Martonne index time series between 1958 and 2011. In the last twenty years, the area experienced an increased anthropogenic pressure due to urbanisation and industrialisation processes. Results indicate a moderate trend towards a warmer and drier climate with a slight increase in the range of the observed values for precipitation and temperature. Relative humidity decrease by 0.1% per year at both year and month base. Results point out the complexity of climate variations at the local scale and the importance of air humidity trends depending on rainfall and temperature regimes in the Mediterranean basin.

Feasibility of Vegetation Temperature Condition Index for monitoring desertification in Bulgan, Mongolia

Desertification monitoring as a main portion for understand desertification, have been conducted by many scientists. However, the stage of research remains still in the level of comparison of the past and current situation. In other words, monitoring need to focus on finding methods of how to take precautions against desertification. In this study, Vegetation Temperature Condition Index (VTCI), derived from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), was utilized to observe the distribution change of vegetation. The index can be used to monitor drought occurrences at a regional level for a special period of a year, and it can also be used to study the spatial distribution of drought within the region. Techniques of remote sensing and Geographic Information System (GIS) were combined to detect the distribution change of vegetation with VTCI. As a result, assuming that the moisture condition is the only main factor that affects desertification, we found that the distribution of vegetation in Bulgan, Mongolia could be predicted in a certain degree, using VTCI. Although desertification is a complicated process and many factors could affect the result. This study is helpful to provide a strategic guidance for combating desertification and allocating the use of the labor force.

Research Advance in Remote Sensing to Land Desertification Monitoring

This Land desertification has been a worldwide ecological and environmental problem. It is the significance for effective remedy of land desertification to monitor the desertification ,know well the present situation ,intensity as well as dynamic variation rules of the desertification. In recent years, remote sensing has become an important technology to monitor land desertification.Firstly, we summarize the research progress in monitoring land desertification using remote sensing data acquisition.Then, we discuss about themethods to extract information of land desertification from remote sensing image, which includes artificial visual interpretation, supervised classification, unsupervised classification, hierarchical decision tree classification, neural network classification and spectral mixture analysis£¬and also we comprehensively compare the strength and weaknesses of each method. Finally, We point out the problems in the remote sensing technology application to land desertification monitoring and put forward the development prospects in the application of remote sensing to monitoring land desertification.

Remote Sensing Integration Survey of Typical Land Types and Analysis of its Spectral Properties in Southeast of Yunnan Province

Karst rocky desertification is a major ecological disaster faced by the southeastern region of Yunnan Province, in China. The research of land use status in rocky desertification area is more and more concerned by human. Through remote sensing integrated survey ways to establish the spectral database of six kinds of typical land types, such as water, forest land, paddy field, grassland, dry land and bare land; then, Normalized Difference Vegetation Index (NDVI) processing and Tasseled Cap transformation processing for the spectral data; finally, the spectral characteristics and the variation of typical land types was analyzed and studied. The results indicated that, there are no significant differences of spectral of the six kinds of typical land types, after the processing of NDVI, the water, the forest land and grassland with larger vegetation coverage, and the paddy land, dry land and bare land with smaller vegetation coverage, can be well distinguish, but the distinction between forest land and grassland is bad, the distinction of paddy land, dry land and bare land is also bad; after the Tasseled Cap transformation processing, the dispersion degree of water, forest land, paddy field and grassland is better, the dispersion degree of dry land and bare land is a bit poor, need to be further studied. The remote sensing integrated survey and the analysis of spectral properties are important foundation for the Land Use / Land Cover Change (LUCC) and the dynamic monitoring of rocky desertification in southeastern rocky desertification region of Yunnan province.

Evaluation and Selection of Indicators for Land Degradation and Desertification Monitoring: Types of Degradation, Causes, and Implications for Management

Indicator-based approaches are often used to monitor land degradation and desertification from the global to the very local scale. However, there is still little agreement on which indicators may best reflect both status and trends of these phenomena. In this study, various processes of land degradation and desertification have been analyzed in 17 study sites around the world using a wide set of biophysical and socioeconomic indicators. The database described earlier in this issue by Kosmas and others (Environ Manage, 2013) for defining desertification risk was further analyzed to define the most important indicators related to the following degradation processes: water erosion in various land uses, tillage erosion, soil salinization, water stress, forest fires, and overgrazing. A correlation analysis was applied to the selected indicators in order to identify the most important variables contributing to each land degradation process. The analysis indicates that the most important indicators are: (i) rain seasonality affecting water erosion, water stress, and forest fires, (ii) slope gradient affecting water erosion, tillage erosion and water stress, and (iii) water scarcity soil salinization, water stress, and forest fires. Implementation of existing regulations or policies concerned with resources development and environmental sustainability was identified as the most important indicator of land protection.

Evaluation and Selection of Indicators for Land Degradation and Desertification Monitoring: Methodological Approach

An approach to derive relationships for defining land degradation and desertification risk and developing appropriate tools for assessing the effectiveness of the various land management practices using indicators is presented in the present paper. In order to investigate which indicators are most effective in assessing the level of desertification risk, a total of 70 candidate indicators was selected providing information for the biophysical environment, socio-economic conditions, and land management characteristics. The indicators were defined in 1,672 field sites located in 17 study areas in the Mediterranean region, Eastern Europe, Latin America, Africa, and Asia. Based on an existing geo-referenced database, classes were designated for each indicator and a sensitivity score to desertification was assigned to each class based on existing research. The obtained data were analyzed for the various processes of land degradation at farm level. The derived methodology was assessed using independent indicators, such as the measured soil erosion rate, and the organic matter content of the soil. Based on regression analyses, the collected indicator set can be reduced to a number of effective indicators ranging from 8 to 17 in the various processes of land degradation. Among the most important indicators identified as affecting land degradation and desertification risk were rain seasonality, slope gradient, plant cover, rate of land abandonment, land-use intensity, and the level of policy implementation.

The influence of soil, hydrology, vegetation and climate on desertification in El-Bayadh region (Algeria)

There has always been a link between water and desertification. Water, whether from rain or other sources, provides the ground moisture needed for the growth of vegetation cover. The availability of water resources directly affects the distribution of vegetation cover. Any damage to the vegetation cover is almost always accompanied by silting, which accelerates the desertification process. The phenomenon of desertification affects the arid and semi-arid areas of all continents. Its expansion is one of the major environmental problems of our times. According to the United Nations Convention to Combat Desertification, the term desertification signifies ‘‘land degradation resulting from various factors including climatic variations and human activities”. The problem of desertification, which is known as being the process of land degradation resulting principally from anthropogenic factors (plowing of steppe, overgrazing, land clearing, fires, deforestation (illegal logging), etc.) and leading to often irreversible repercussions, is a particular and urgent problem in the arid and semi-arid bioclimatic zones of the Tell Atlas. This work is part of the monitoring of desertification and of the impact of natural factors (soils, hydrology, vegetation and climate) in an area in the heart of south Oran’s high steppe plains, in the El Bayadh region of Algeria.

Extracting desertification from Landsat TM imagery based on spectral mixture analysis and Albedo-Vegetation feature space

Land desertification has been a worldwide environmental problem. Desertification monitoring and evaluation are very important content in desertification context. Scientific and accurate evaluation of desertification can provide scientific basis for decision making in mitigating desertification. Because of the advantage of large amount of information, short cycle and broad scope of data, less restrictions on the human and material resources and so on, remote sensing has become an important technology to monitor land desertification in the past 30 years. Desertification is the most typical and serious form of desertification in China, especially in the oasis zone distributed along inland rivers or in the lower reaches of inland rivers in northwestern China. Quantitative evaluation of the current desertification remote sensing methods used is mostly obtained through the vegetation index and vegetation cover, to gain information on the extent of desertification. As the arid and semiarid sparse vegetation cover, soil and soil moisture on the most common vegetation index have a greater effect. First, based on the spectral mixture analysis model, three kinds of endmember consisting of vegetation, water and bare soil were selected. The image dimensionality was reduced by the minimum noise fraction (MNF). The pixel purity index transformation was used to narrow the range of the endmember. On the scatter plot of MNF, three kinds of endmember were selected, and relative abundance distribution of each component was obtained by using linear spectral mixture model. Second, a spectral feature space composed of vegetation component and land surface albedo retrieved from Landsat TM Imagery was constructed to evaluate desertification present condition and degree quantificationally. Last, an empirical study was carried out taking the middle reaches of Heihe River as an example. Results indicated that this method makes full use of multi-dimensional remote sensing information, reflecting the desertification land cover, water, thermal environment and its changes, with a clear biophysical significance, and the index is simple, easy to obtain, high precision, and is conducive to quantitative analysis, monitoring and desertification assessment of desertification. It was rather ideal to assess desertification on the basis of Albedo-Vegetation feature space: correct prediction proportion of testing samples reached 90.3 %. This method was beneficial to the desertification quantitative analysis and monitoring with the characteristics of simple index, easy accessibility and high accuracy.

RETRACTED ARTICLE: Using remote sensing to quantify the fractional cover of vegetation and exposed bedrock within a complex landscape: applications for karst rocky desertification monitoring

Environ Monit Assess (2013) 185:1025DOI 10.1007/s10661-012-2944-yThis article has been retracted. After publication, the authorsdiscovered an error in the validation method that decided theaccuracy of the proposed remote-sensing method. The authorshave therefore requested retraction of this article for scientificreasons.Y. Yue

DESERT ECOSYSTEMS: MAPPING, MONITORING & ASSESSMENT USING SATELLITE REMOTE SENSING

Abstract. Desert ecosystems are unique but fragile ecosystems , mostly vulnerable to a variety of degradational processes like water erosion, vegetal degradation, salinity, wind erosion , water logging etc. Some researchers consider desertification to be a process of change, while others view it as the end result of a process of change. There is an urgent need to arrest the process of desertification and combat land degradation. Under the auspices of the United Nations Convention to Combat Desertification (UNCCD), Space Applications Centre, Ahmedabad has undertaken the task of mapping, monitoring and assessment of desertification carrying out pilot project in hot and cold desert regions in drylands on 1:50,000 scale followed by systematic Desertification Status Mappaing (DSM) of India on 1:500,000 scale.

Seasonal Variation of Surface Temperature–Modulating Factors in the Sonoran Desert in Northwestern Mexico

AbstractThe authors explore a new approach to monitoring of desertification that is based on use of results on the relation between albedo and surface temperature for the Sonoran Desert in northwestern Mexico. The criteria of predominance of radiation by using the threshold value of Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) were determined. The radiation mechanism for regulating the temperature of the surface and the definition of threshold values for AVHRR and MODIS NDVI have an objective justification for the energy budget, which is based on the dominance of radiation surface temperature regulation in relation to evapotranspiration. Changes in the extent of arid regions with AVHRR NDVI of <0.08 and MODIS NDVI of <0.10 can be considered to be a characteristic in the evolution of desertification in the Sonoran Desert region. This is true because, in a certain year, the time span of the period when radiation factor predominates is important for the desertification process.

Analysis on the Factors Influencing the Evolution of Desertification in Ningxia of China from 1999 to 2009

With the desertification monitoring data in 1999,2004 and 2009 in Ningxia,we analyzed the evolution of the desertification and its influencing factors in Ningxia.The area of desertification land decreased from 3.2074×106 hm2 in 1999 to 2.8988×106 hm2 in 2009 and reversed obviously during 1999-2009.The area of wind-erosion desertification land decreased from 1.5191×106 hm2 in 1999 to 1.3458×106 hm2 in 2009,and the area of water-erosion desertification land reduced from 1.6572×106 hm2 in 1999 to 1.4897×106 hm2 in 2009,while the area of saline desertification land increased from 3.11×104 hm2 in 1999 to 6.33×104 hm2 in 2009.The area of severe and moderate desertification land decreased obviously from 1.0098×106 hm2 and 1.4270×106 hm2 respectively in 1999 to 2.757×105 hm2 and 1.3838×106 hm2 respectively in 2009,while the area of slight desertification land increased obviously from 7.10×105 hm2 in 1999 to 1.1708×106 hm2 in 2009,so desertification degree weakened obviously.In desertification regions,vegetation cover was improved further and vegetation coverage increased.Among the climate and human factors affecting the evolution trend of desertification,the reversion of desertification was influenced decisively by national policy,comprehensive development and utilization project,establishing and perfecting of various ecological protection measurement and mechanism,public participating in combating desertification,and so on.The negative effect produced by climate change was offset by the positive effect of these human factors.However,the reversion of desertification was slowed down to some extent by the population pressure,the human unreasonable activities in historical period,the inefficient utilization of water resources,and so on.These human factors are the unfavorable factors in combating desertification,which needed to be overcome in the prevention and control of desertification in Ningxia in the future.

An information system for operational desertification monitoring at the local scale (SIELO software platform prototype)

Developper des modeles capables de fournir des indicateurs integrant des dimensions socio-economiques et environnementales dans leur diversite spatiale et temporelle, traitant de phenomenes a l’echelle locale, et mobilisables dans des systemes d’aide a la decision, reste un challenge d’actualite pour comprendre, spatialiser, suivre, evaluer et anticiper les dynamiques complexes de la desertification. Cet article presente la demarche modelisatrice imaginee, et la plateforme logicielle prototype intitulee « systeme d’information pour le suivi operationnel de la desertification a l’echelle locale » (SIELO) pour repondre a cet enjeu scientifique. Ce systeme tente de creer le lien entre : i) des indicateurs spatialises de risque de desertification prenant en compte la complexite systemique de la desertification ; et ii) le Land Cover Change observe. Le premier type de donnees est issu de modeles systemiques preexistants dans le SIEL. Le second type de donnees est extrait d’images satellites acquises selon des pas de temps reguliers. La demarche s’appuie sur des approches de spatialisation des connaissances, qui mobilise le « paysage » notamment. Dans cet article, nous mettons l’accent sur la description de la demarche proposee pour etablir ce lien, et sur les specificites qui la mettent en capacite d’alimenter un suivi operationnel de la desertification dans le cadre d’observatoires a l’echelle locale. Nous illustrons la faisabilite et l’operationnalite de sa mise en œuvre avec une premiere application a une zone aride tunisienne via un logiciel prototype developpe.

Remote Sensing Monitoring of Water Erosion Desertification in the Three Gorges Area

Dynamic monitoring of water erosion desertification in the Three Gorges Area was carried out by using remote sensing technology so as to find out the dynamic changes of water erosion desertification.The water erosion desertification information was extracted through the interpretation of two phase aviation orthoprojective images taken separately in 2003 and 2009,and then the changes of water erosion desertification in those years were summarized.The monitoring results show that the condition of water erosion desertification in the Three Gorges Area was improved obviously.The Three Gorges Area began storing water in 2003,and the water reached its highest level of 175 m in 2009.All kinds of water erosion desertification was reduced obviously,especially the moderate desertification.As for the improving degree,the mild water erosion desertification has been improved most evidently.

Monitoring in Dynamic Change of Desertification in the Region of Central Asia Based on NOAA/AVHRR Image

There are rather large parts of deserts and semi deserts in central Asia, belonging to the region of drought and semi-drought, with little annual precipitation and sharp change of daily and seasonal temperature change. This region is the concerning ecological fragile region in the study of global environmental change. The paper analyzed the landscape characteristics of desertification and soil desertification in the study area, as well as their relationship Based on the high-resolution TM image. And then, the 1km spatial resolution NOAA/AVHRR image was used to acquire the normalized difference vegetation index (NDVI). The vegetation coverage was estimated to ensure the monitoring index of desertification. The NDVI graph was overlapped with the image to set up the interpretation relationship between the ground objects and remote sensing features, on the basis of the relevant technique standards of desertification monitoring, its classification method, as well as the actual conditions. From the desertification interpretation, the area and degree of desertification could be monitored to analyze the changing trend of desertification in central Asia from 1989 to 2009. The results showed that the monitoring method used in the paper was with high reliability and practicality, which could do quick, macroscopic and timely monitoring of desertification in the region of central Asia.

Monitoring in Dynamic Change of Desertification in the Region of Central Asia Based on NOAA/AVHRR Image

There are rather large parts of deserts and semi deserts in central Asia, belonging to the region of drought and semi-drought, with little annual precipitation and sharp change of daily and seasonal temperature change. This region is the concerning ecological fragile region in the study of global environmental change. The paper analyzed the landscape characteristics of desertification and soil desertification in the study area, as well as their relationship Based on the high-resolution TM image. And then, the 1km spatial resolution NOAA/AVHRR image was used to acquire the normalized difference vegetation index (NDVI). The vegetation coverage was estimated to ensure the monitoring index of desertification. The NDVI graph was overlapped with the image to set up the interpretation relationship between the ground objects and remote sensing features, on the basis of the relevant technique standards of desertification monitoring, its classification method, as well as the actual conditions. From the desertification interpretation, the area and degree of desertification could be monitored to analyze the changing trend of desertification in central Asia from 1989 to 2009. The results showed that the monitoring method used in the paper was with high reliability and practicality, which could do quick, macroscopic and timely monitoring of desertification in the region of central Asia.

Processing and Application Evaluation of CBERS-1 Datain Desertification Monitoring

In this paper, the application effect of CBERS-1 data in desertification monitoring in Northwest China was analyzed and evaluated. The wavelength scopes of ban 2,3 and 4 of CBERS-1 data were similar to the same bands of TM data, so it was comparable with TM data. CBERS-1 composition images clearer displayed features of ground objects than TM images because of its higher spatial resolution compared with TM data. The results showed that CAERS-1 data may be applied to landuse mapping and desertification monitoring in desertified regions after deterministic processing. There had some speckles or stripe noises in each single band that can be partially reduced by noise-filtrating processing, and the displacements that can be eliminated through band matching. The satisfactory effects were gotten when above-mentioned image processing techniques were applied to survey of landuse and desertification of experiment region in Gulang County, Gansu Province.

Study of Spectral Re-building of Hyper-spectral Remote Sensing Images in Dsertification Areas

High spectral resolution is the main characteristic of hyper\|spectral remote sensing, it provide a possibility for us to directly abstract continuous spectrum curve of objects from image and to discern them by spectral match. However, before spectral re\|building, the spectrum which abstracted directly from image can not represent the true characteristic of objects. So, the main purpose of this study is to develop a simple and useful model in order to re\|build spectrum for hyper\|spectral remote sensing in desertification monitoring, it is also a key technique in the application of hyper\|spectral remote sensing. Based on the preprocessing of hyper\|spectral resolution data of desertification areas and spectral re\|sampling, through simulating the procedure of atmospheric radiation, a linear model was developed and applied in this paper to re\|build spectrum and got some satisfactory results, the correlation between re\|built spectrums and true spectrums is high. The research results showed that the linear has better practicality, it lay a better foundation for improving the precision of objection interpreting and quantitatively retrieves of information.