Land Imager Research Articles

Identifying vegetation patterns for a qualitative assessment of land degradation using a cellular automata model and satellite imagery.

We aim to identify the spatial distribution of vegetation and its growth dynamics with the purpose of obtaining a qualitative assessment of vegetation characteristics tied to its condition, productivity and health, and to land degradation. To do so, we compare a statistical model of vegetation growth and land surface imagery derived vegetation indices. Specifically, we analyze a stochastic cellular automata model and data obtained from satellite images, namely using the normalized difference vegetation index and the leaf area index. In the experimental data, we look for areas where vegetation is broken into small patches and qualitatively compare it to the percolating, fragmented, and degraded states that appear in the cellular automata model. We model the periodic effect of seasons, finding numerical evidence of a periodic fragmentation and recovery phenomenology if the model parameters are sufficiently close to the model's percolation transition. We qualitatively recognize these effects in real-world vegetation images and consider them a signal of increased environmental stress and vulnerability. Finally, we show an estimation of the environmental stress in land images by considering both the vegetation density and its clusterization.

CNN-LandCoverNet: An Effective Framework of Land Cover Classification Using Hybrid Metaheuristic-Aided Ensemble-Based Convolutional Neural Network

Land cover (LC) categorization is considered a necessary task of intelligent interpretation technology for remote sensing imagery that is intended to categorize every pixel to perform the predefined LC classification. Land Use and Land Cover (LULC) information has the ability to provide various insights in order to overcome environmental and socioeconomic impacts such as disaster risk, climate change, poverty, and food insecurity. Therefore, image categorization tasks are involved in conventional works, where the classical visual interpretation techniques completely depend upon professional knowledge as well as a professional’s classification experience, which is more susceptible to subjective awareness, inefficient, and time consuming. By overcoming this issue, the latest deep-structured approach is suggested to perform the LC image classification. Initially, the land images are gathered. Further, the collected images are employed for patch splitting, where the images are split into multiple patches. After splitting, the patches are fed to the Ensemble-based Convolutional Neural Network (ECNN), which is constructed with a Fully Convolutional Network (FCN), U-Net, DeepLabv3, and Mask Region-based Convolutional Neural Network (Mask R-CNN) for performing segmentation. Here, the hyperparameters are optimally tuned with the Hybrid Billiards-inspired Water Wave Algorithm (HB-WWA) by integrating the Billiards-inspired Optimization Algorithm (BOA) and Water Wave Algorithm (WWA). Finally, the classification is carried out with a fuzzy classifier. Thus, the performance is validated and measured through diverse metrics. Consequently, the developed work has demonstrated enhanced classification accuracy when tested on other existing algorithms.

Quantifying the Potential Contribution of Submerged Aquatic Vegetation to Coastal Carbon Capture in a Delta System from Field and Landsat 8/9-Operational Land Imager (OLI) Data with Deep Convolutional Neural Network

Submerged aquatic vegetation (SAV) are highly efficient at carbon sequestration and, despite their relatively small distribution globally, are recognized as a potentially valuable component of climate change mitigation. However, SAV mapping in tidal marshes presents a challenge due to optically complex constituents in the water. The emergence and advancement of deep learning-based techniques in the field of habitat mapping with remote sensing imagery provides an opportunity to address this challenge. In this study, an analytical framework was developed to quantify the carbon sequestration of SAV habitats in the Atchafalaya River Delta Estuary from field and remote sensing observations using deep convolutional neural network (DCNN) techniques. A U-Net-based model, Wetland-SAV Network, was trained to identify the SAV percent cover (high, medium, and low) as well as other estuarine habitat types from Landsat 8/9-OLI data. The areal extent of SAV was up to 8% of the total area (47,000 ha). The habitat areas and habitat-specific carbon fluxes were then used to quantify the net greenhouse gas (GHG) flux of the study area for with/without SAV scenarios in a carbon balance model. The total net GHG flux was in the range of −0.13 ± 0.06 to −0.86 ± 0.37 × 105 tonne CO2e y−1 and increased up to 40% (−0.23 ± 0.10 to −0.90 ± 0.39 × 105 tonne CO2e y−1) when SAV was accounted for within the calculation. At the hectare scale, the inclusion of SAV resulted in an increase of ~60% for the net GHG sink in shallow areas adjacent to the emergent marsh where SAV was abundant. This is the first attempt at remotely mapping SAV in coastal Louisiana as well as a first quantification of net GHG flux at the scale of hectares to thousands of hectares, accounting for SAV within these sub-tropical coastal delta marshes. Remote sensing and deep learning models have high potential for mapping and monitoring SAV in turbid sub-tropical coastal deltas as a component of the increasing accuracy of net GHG flux estimates at small (hectare) and large (coastal basin) scales.

Remote sensing of optical properties of smoke aerosols: simulation experiment and application based on spaceborne data

Measuring the microscopic and macroscopic optical properties of smoke aerosols is important in column concentration retrieval by remote sensing for environmental monitoring. Based on the radiation transfer theory, we constructed a physical model to correlate microscopic and macroscopic optical properties of smoke aerosols. According to the experiment, the mass extinction coefficient and mass angular scattering coefficient of smoke aerosols in the visible-near infrared (400 to 2400 nm) show the strongest extinction and scattering effects on the visible light, which are negatively correlated with wavelength. They were applied to smoke column concentration retrieval based on Landsat8/operational land imager and MODIS images by the established model. Then the optimal bands for smoke detection were analyzed. It indicates that the surface underlying the smoke has impact on the optimal band of smoke detection, and red-light band is optimal for vegetation background.

Spatial Evolution of Coastal Tourist City Using the Dyna-CLUE Model in Koh Chang of Thailand during 1990–2050

Spatial evolution can be traced by land-use change (LUC), which is a frontier issue in the field of geography. Using the limited areas of Koh Chang in Thailand as the research case, this study analyzed the simulation of its spatial evolution from a multi-scenario perspective on the basis of the 1900–2020 thematic mapper/operational land imager (TM/OLI) remote sensing data obtained through the transfer matrix model, and modified LUC and the dynamic land-use change model (Dyna-CLUE). Over the past 30 years, the expansion of recreation areas and urban and built-up land has been very high (2944.44% and 486.99%, respectively) along the western coast of Koh Chang, which replaced the original mangrove forests, orchards, and communities. Logistic regression analysis of important variables affecting LUC revealed that population density variables and coastal plain topography significantly affected LUC, which showed strong β coefficients prominently in the context of a coastal tourist city. The results of the LUC and logistic regression analyses were used to predict future LUCs in the Dyna-CLUE model to simulate 2050 land-use in three scenarios: (1) natural evolution scenario, where a large patch expansion of agricultural land extends along the edge of the entire forest boundary around the island, particularly the southwestern areas of the island that should be monitored; (2) reserved area protection scenario, where the boundary of the conservation area is incorporated into the model, enabling forest preservation in conjunction with tourism development; and (3) recreation area growth scenario, where the southern area is the most susceptible to change at the new road crossing between Khlong Kloi village to Salak Phet village, and where land-use of the recreation area type is expanding. The model-projected LUC maps provide insights into possible changes under multiple pathways, which could help local communities, government agencies, and stakeholders jointly allocate resource planning in a systematic way, so that the development of various infrastructures to realize the potential impact on the environment is a sustainable coastal tourist city development.

Research on the Japanese Translation of “Land Image” in Life by Lu Yao

Local culture; Land image; Japanese translation strategy; Translation method

Multi-Source Hydrological Data Products to Monitor High Asian River Basins and Regional Water Security

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in distributed river basin models. A pilot study was carried out on the Red River basin. Multiple hydrological data products were generated using the data collected by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018 was generated, including plant transpiration, soil evaporation, rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000 and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over the period 2013–2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy, and a new dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier, the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The seasonality in the glacier mass balance was observed by combining intensive field campaigns with continuous automatic observations. The linkage of the glacier and snowpack mass balance with water resources in a river basin was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modeling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements. In the case study on the Red River Basin, a new algorithm has been applied to disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture.

The structure and semantics of the early lyrics of Diman Belekov

The article analyzes the semantic features of D. Belekov's early lyrics, identifies the figurative and spatial dominants represented in the author's artistic world. In the temporal designation, the semantic structure is actualized in a series of images associated with spring, and primroses, a blooming apple tree, murmuring streams of meltwater, fields with thawed patches, etc., creating a holistic picture of the awakening nature, metaphorically embody the image of the younger generation. Toponymically and geographically, the dominant image is the image of the native land, which includes the entire complex of symbols-markers characteristic of the designation of the territory of Gorniy Altai (Altai Mountains). If the homeland for the lyrical hero of the poet becomes a source of strength and inspiration, then for his development he needs a movement understood as the development of the "other" space, actualized in the generalized image of blue distances and a crowded city with bright lights. The central theme in the poet's lyrics is the theme of the road, embodied in the motives of departure and return.

Between Jeju and Hanshin: intimate migration

ABSTRACT The Great Hanshin Earthquake, which struck western Japan on 17 January 1995, ushered in a year of social, economic, and political upheaval. In his prize-winning short story ‘“Aboji” o fumu’, Oda Makoto employs the earthquake to explore this broader upheaval and the unresolved postwar tensions that it revealed, in particular the legacy of Japan’s colonization of Korea. This article offers a close reading of Oda’s story, contextualizing it within his other writings, the events of 1995, and broader postwar history, particularly the migrant flow between the Korean island of Jeju and the Hanshin (Osaka-Kobe) region. It examines how Oda uses images of land and water, fixity and flow, to undermine the coherence of the nation and substitutes an understanding of the colonial legacy grounded in the local. This reading offers an example of how to recognize the significance of this year of upheaval, as it is represented in Japanese cultural production in and around 1995, as marking the start of a rupture with the postwar order that would be confirmed two decades later by another, greater catastrophe at Fukushima.

European Space Agency (ESA) Calibration/Validation Strategy for Optical Land-Imaging Satellites and Pathway towards Interoperability

Land remote sensing capabilities in the optical domain have dramatically increased in the past decade, owing to the unprecedented growth of space-borne systems providing a wealth of measurements at enhanced spatial, temporal and spectral resolutions. Yet, critical questions remain as how to unlock the potential of such massive amounts of data, which are complementary in principle but inherently diverse in terms of products specifications, algorithm definition and validation approaches. Likewise, there is a recent increase in spatiotemporal coverage of in situ reference data, although inconsistencies in the used measurement practices and in the associated quality information still hinder their integrated use for satellite products validation. In order to address the above-mentioned challenges, the European Space Agency (ESA), in collaboration with other Space Agencies and international partners, is elaborating a strategy for establishing guidelines and common protocols for the calibration and validation (Cal/Val) of optical land imaging sensors. Within this paper, this strategy will be illustrated and put into the context of current validation systems for land remote sensing. A reinforced focus on metrology is the basic principle underlying such a strategy, since metrology provides the terminology, the framework and the best practices, allowing to tie measurements acquired from a variety of sensors to internationally agreed upon standards. From this general concept, a set of requirements are derived on how the measurements should be acquired, analysed and quality reported to users using unified procedures. This includes the need for traceability, a fully characterised uncertainty budget and adherence to community-agreed measurement protocols. These requirements have led to the development of the Fiducial Reference Measurements (FRM) concept, which is promoted by the ESA as the recommended standard within the satellite validation community. The overarching goal is to enhance user confidence in satellite-based data and characterise inter-sensor inconsistencies, starting from at-sensor radiances and paving the way to achieving the interoperability of current and future land-imaging systems.

Land cover classification in a mixed forest-grassland ecosystem using LResU-net and UAV imagery

Using an unmanned aerial vehicle (UAV) paired with image semantic segmentation to classify land cover within natural vegetation can promote the development of forest and grassland field. Semantic segmentation normally excels in medical and building classification, but its usefulness in mixed forest-grassland ecosystems in semi-arid to semi-humid climates is unknown. This study proposes a new semantic segmentation network of LResU-net in which residual convolution unit (RCU) and loop convolution unit (LCU) are added to the U-net framework to classify images of different land covers generated by UAV high resolution. The selected model enhanced classification accuracy by increasing gradient mapping via RCU and modifying the size of convolution layers via LCU as well as reducing convolution kernels. To achieve this objective, a group of orthophotos were taken at an altitude of 260 m for testing in a natural forest-grassland ecosystem of Keyouqianqi, Inner Mongolia, China, and compared the results with those of three other network models (U-net, ResU-net and LU-net). The results show that both the highest kappa coefficient (0.86) and the highest overall accuracy (93.7%) resulted from LResU-net, and the value of most land covers provided by the producer’s and user’s accuracy generated in LResU-net exceeded 0.85. The pixel-area ratio approach was used to calculate the real areas of 10 different land covers where grasslands were 67.3%. The analysis of the effect of RCU and LCU on the model training performance indicates that the time of each epoch was shortened from U-net (358 s) to LResU-net (282 s). In addition, in order to classify areas that are not distinguishable, unclassified areas were defined and their impact on classification. LResU-net generated significantly more accurate results than the other three models and was regarded as the most appropriate approach to classify land cover in mixed forest-grassland ecosystems.

Maps, Earth Apps and Land Images: Different Tools for Different Skills

An analysis carried out on first (11-14) and second grade (14-18) Italian secondary school students and an in-depth analysis carried out in recent years, during the in the different stages of regional and national selections of the Earth Sciences Olympics, and particularly with the students participating in the learning week organized for who will make up the Italian team of the IESO -International Olympiad of Earth Science, highlighted widespread difficulties in the analysis of topographic maps. The decreasing diffusion of geography teaching in Italian schools, the increasing use of digital tools, apps and software, such as Google Earth and navigators, free and easy to use, has made the use of the topographic maps, and of the various thematic ones, among the students, substantially obsolete. If the use of digital tools has promoted digital skills, ease of orientation, even greater security in discovering new places, it is leading meanwhile to the loss of skills of observation, analysis and understanding of the context, that only the view of a large area included in a map and not in a few inches of a screen, can give. In reality, both resources constitute a formidable tool, not only for the discovery and knowledge of the territory, but for the growth of specific skills, which are crucial for the knowledge of a territory, but also indispensable in scientific research. In this research we analyse tools, models and pathways, which foresee the integration of the two resources, and which skills their integrated use can implement.

Single Maritime Image Defogging Based on Illumination Decomposition Using Texture and Structure Priors

Removing fog components from maritime images is more challenging than removing them from land images because of the complicated scattering effects. In this paper, we propose a single maritime image defogging algorithm based on illumination decomposition. First, we decompose a foggy input image into glow and glow-free layers by formulating an optimization problem and then solving it effectively, where the optimization variables are updated by closed-form solutions. Then, the fog components in the glow-free layer are removed using a defogging algorithm. Finally, the natural illumination in the glow layer is recovered using a compensation scheme to obtain the final fog-free image. Experimental results on real test images demonstrate that the proposed algorithm outperforms state-of-the-art algorithms in terms of both subjective and objective evaluation criteria.

Antenna Designs for CubeSats: A Review

Cube Satellites, aka CubeSats, are a class of nano satellites that have gained popularity recently, especially for those that consider CubeSats as an emerging alternative to conventional satellites for space programs. This is because they are cost-effective, and they can be built using commercial off-the-shelf components. Moreover, CubeSats can communicate with each other in space and ground stations to carry out many functions such as remote sensing (e.g., land imaging, education), space research, wide area measurements and deep space communications. Consequently, communications between CubeSats and ground stations is critical. Any antenna design for a CubeSat needs to meet size and weight restrictions while yielding good antenna radiation performance. To date, a limited number of works have surveyed, compared and categorised the proposed antenna designs for CubeSats based on their operating frequency bands. To this end, this paper contributes to the literature by focusing on different antenna types with different operating frequency bands that are proposed for CubeSat applications. This paper reviews 48 antenna designs, which include 18 patch antennas, 5 slot antennas, 4 dipole and monopole antennas, 3 reflector antennas, 3 reflectarray antennas, 5 helical antennas, 2 metasurface antennas and 3 millimeter and sub-millimeter wave antennas. The current CubeSat antenna design challenges and design techniques to address these challenges are discussed. In addition, we classify these antennas according to their operating frequency bands, e.g., VHF, UHF, L, S, C, X, Ku, K/Ka, W and mm/sub-mm wave bands and provide an extensive qualitative comparison in terms of their size, -10 dB bandwidths, gains, reflection coefficients, and deployability. The suitability of different antenna types for different applications as well as the future trends for CubeSat antennas are also presented.

Spatial Utopianism and Russian Images of Distant Lands, 1880–1900

Spatial Utopianism and Russian Images of Distant Lands, 1880–1900

Assessment of the open-mining prevalence on the territory of Moscow region

Lands disturbed by open cuts and associated dumps often become unsuitable for further use as construction sites. Disturbed lands are technogenically altered soils with new changed physicomechanical and physicochemical properties. The paper examines the results of researching the disturbed lands of common mineral resources open cuts in Moscow region, provides a description of the causes and types of land disturbance, as well as examples of images of disturbed lands on satellite images. For this purposes, thematic and topographic maps and remote sensing materials - satellite images of the territory of the Moscow region were used. The problems of impact of common mineral resources extraction on the natural complexes in the region, the scale of technogenic transformation of the earth surface as a result of open cuts mining as well as the geoecological problems arising in this case are considered. Numerical geoecological assessment of sand quarries in Moscow region is also given.

Assessing the spatial distribution of bamboo species using remote sensing in Cameroon

Bamboo resource assessment has witnessed great interest in the world with very little attention in the Congo Basin forests. This study was initiated to assess bamboo species distribution in Cameroon with respect to Agroecological Zones (AEZ), using remote sensing. Forty-eight sheets of Landsat 8/Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) instruments’ images were mosaiced with the Envi 5.3 software. The bamboo index (BI) was calculated and used to identify wild bamboo-growing regions in Cameroon. Maps of bamboo growing regions helped in ground truthing. GPS coordinates were used to validate the bamboo presence with an accuracy of 78%. The result showed that bamboo spatial area statistics was 794.60, 451 308.36, 241 295.87, 302 989.41 and 219 094.67 ha in Sudano-Sahel, Guinea Savannah, Western Highlands, Monomodal rainfall forests and Bimodal rainfall forest, respectively with a total of 1 215 482.91 ha. Bambusa vulgaris Schrad. ex J.C.Wendl.; Oxytenanthera abyssinica (A. Rich.) Munro; Phyllostachys sp.; Yushania alpina K. Schum; Ochlandra travancorica (Bedd.) Gamble; Dendrocalamus strictus (Roxb.) Nees; Phylostachys atrovaginata C. S. Chao & H.Y.Chou; Phyllostachys aurea Riviere & C. Riviere, were found in Cameroon. O. abyssinica was dominant in Agroecological zones 1 and 2; P. aurea in Agroecological zones 3; and B. vulgaris in respectively Agroecological zones 4 and 5. These results can orientate policies and planning towards a sustainable bamboo sector development and mitigating the effects of climate change in Cameroon. Key words: Spatial distribution, remote sensing, agroecological zone, climate change mitigation.

Inferring the potential impact of human activities on evapotranspiration in the Tumen River Basin based on LANDSAT imagery and historical statistics

AbstractUnderstanding the spatial and temporal changes in actual evapotranspiration (ETa) caused by different human activities is important for water management in water‐sensitive areas, because ETa plays a major role in regulating the availability of water on land. Thus, ETa observation is particularly important for observing land degradation in the watershed. This study used the operational simplified surface energy balance (SSEBop) model to perform ETa estimations and observations in the Tumen River Basin (TRB), covering the border of China and Democratic People's Republic of Korea (DPRK), over the last 30 years by using eight periods of clear‐sky LANDSAT Thematic Mapper/Operational Land Imager (TM/OLI) and thermal infrared sensor (TIRS) data. To assess the reliability of the ETa estimations, multilayer soil temperatures from the China Meteorological Administration (CMA) Land Data Assimilation System Version 2.0 (CLDAS‐V2.0) were utilized. The highest R2 (.71) between ETa and soil temperature was observed in layers shallower than 10 cm; this value of R2 gradually decreased to .57 at a depth of 200 cm. The average ETa of the TRB declined from 1.65 mm in 1985 to 1.03 mm in 2017. The impact of human activities on water loss (ETa) was determined by comparing land cover changes observed by an object‐based image analysis (OBIA) approach and economic activities between 1994 and 2008. Varying economic activities and water depletion in different soil layers may have led to the variable ETa values between the northern (China) and southern (DPRK) part of the TRB during the last three decades.

Contribution of Images ETM and GIS for the Detection of Dynamic Changes in Steppic Space in the Wilaya of Naama Under the Combined Effect of Climate Change and Socio-Spatial Mutations

This paper highlights the contribution of landsat images to the dynamic monitoring of the steppe area in the high Oran plains (Algeria). The qualitative and quantitative analysis of the rapid evolution of the landscape and especially the silting up in the cities demonstrate an interesting measurement which allows making a provisional assessment of the current state of the study area. This analysis will raise awareness among the population; the local elected officials and the decision maker about the extent of the sanding phenomenon. By using this analysis, the changes in surface condition between 1957 and 2002 which extracted from different images of Lands at MSS, TM and ETM+had been done. Consequently, three methods of detection of changes (rapid identification and quantification of changes, multidate colored composition technique and dynamic soil cover index techniques) were used to locate the different zones where underwent deep mutations, the special extension of the silting up and the degradation of the grounds inside the regions of the wilaya of Naâmaregion.It is important to note that we used the Olsson model for atmospheric corrections of images. This study is conducted in the high Oran plain which is administratively attached to the wilaya (department) of Naâma. It covers an area of 29,825 km2, between 32°08’and 34°16’ north latitude and 0°09’and 1°43’ west longitude. The use of remote sensing data through the dynamic soil covers index and the diachronic color-composite images allowed focusing the different changes that took place from 1987 to 2002. These changes which concern the changes in the ratio of landscape units in the steppe zone necessitate testing several indices of change (vegetation index, gloss index, curass index and principal component analysis) to minimize errors in the assessment of results of these changes. It is well known that the remote sensing for the result of dynamic changes is influenced by cyclical variations (season, weather conditions). Therefore the radiometric and atmospheric corrections to the images are necessary. Emphasis was placed on the processing of diachronic remote sensing data for the monitoring and development of silting in an arid environment concerning the southwestern part of the high Oran plains. In fact, this analysis revealed that for the entire study region, the surface silted areas increased from 1.38% in 1957 to 42.9% in 2002 or an area of 1,280,762 ha; which corresponds to an extension of 28,461.4 ha per year. It is important to note that the diachronic study involved delicate phases, in particular the choice of the mathematical model for the atmospheric correction (absolute or relative) of the satellite images as well as the determination of the parameter of the real reflectance of the soil for the test samples. This parameter requires adequate equipment (spectroradiometer) or a database on the absolute reflectance of objects. Also, in this study it is recognized that the indices are not very effective for detecting change in an arid zone where the characteristics of the soil and the presence of sand considerably influence the spectral aspect of objects.

Spatial characteristics analysis and vulnerability evaluation of agricultural land use environment

In view of the problems of low precision, high energy consumption, and poor flexibility of the spatial characteristics analysis and vulnerability evaluation methods of agricultural land use environment, a principal component analysis–based spatial characteristics analysis and vulnerability evaluation method of agricultural land use environment is proposed. The remote sensing image of agriculture land was corrected. According to the Cartesian moments before and after image transformation, the scale factor, rotation angle, and translation parameters of image transformation are calculated, and these parameters are used to correct the agricultural land use image. The environment information data is obtained from the corrected image. On this basis, the dynamic degree of single and compound land use types is calculated. Two dynamic values are used to get the spatial characteristic values of agricultural land use. According to the eigenvalue, the evaluation index of land use vulnerability is calculated. Through principal component analysis, the comprehensive index of agricultural land vulnerability was obtained. Compare the index with the evaluation index to judge the level of land use vulnerability. The experimental results show that the method has high accuracy, low energy consumption, and the highest sensitivity coefficient of 0.99.