River Water Quality Model Based on Remote Sensing Information Methods——A Case Study of Lijing River in Guilin City

River water quality models based on remote sensing information models are superior to pure water quality models because they combine the inevitability and risk of geographical phenomena and can take complex geographical characteristics into account. A water quality model for forecasting COD has been established with remote sensing in- formation modeling methods by monitoring and analyzing water quantity and water quality of the Lijing River reach which flows through a complicated Karst mountain area. This model provides a good tool to predict water quality of complex rivers. It is validated by simulating contaminant concentrations of the study area. The results show that remote sensing information models are suitable for complex geography. It is not only a combined model of inevitability and risk of the geographical phenomena, but also a semi-theoretical and semi-empirical formula, providing a good tool to study organic contaminants in complicated rivers. The coefficients and indices obtained have limited value and the model is not suitable for all situations. Some improvements are required.

Comparison Between Radial Basis Function Neural Network and Regression Model for Estimation of Rice Biophysical Parameters Using Remote Sensing

The radial basis function (RBF) emerged as a variant of artificial neural network. Generalized regression neural network (GRNN) is one type of RBF, and its principal advantages are that it can quickly learn and rapidly converge to the optimal regression surface with large number of data sets. Hyperspectral reffectance (350 to 2500 nm) data were recorded at two different rice sites in two experiment fields with two cultivars, three nitrogen treatments and one plant density (45 plants m-2). Stepwise multivariable regression model (SMR) and RBF were used to compare their predictability for the leaf area index (LAI) and green leaf chlorophyll density (GLCD) of rice based on reffectance (R) and its three different transformations, the first derivative reffectance (D1), the second derivative reffectance (D2) and the log-transformed re?ectance (LOG). GRNN based on D1 was the best model for the prediction of rice LAI and GLCD. The relationships between different transformations of reffectance and rice parameters could be further improved when RBF was employed. Owing to its strong capacity for nonlinear mapping and good robustness, GRNN could maximize the sensitivity to chlorophyll content using D1. It is concluded that RBF may provide a useful exploratory and predictive tool for the estimation of rice biophysical parameters.

Integrated Evaluation Model for Eco-Environmental Quality in Mountainous Region Based on Remote Sensing and GIS

Based on Remote Sensing （RS）, Geographic Information System （GIS）, and combining Principal Component Analysis, this paper designed a numerical integrated evaluation model for mountain eco-environment on the base of grid scale. Using this model, we evaluated the mountain eco-environmental quality in a case study area-the upper reaches of Minjiang River, and achieved a good result, which accorded well with the real condition. The study indicates that, the integrated evaluation model is suitable for multi-layer spatial factor computation, effectively lowing man＇s subjective influence in the evaluation process; treating the whole river basin as a system, the model shows full respect to the circulation of material and energy, synthetically embodies the determining impact of such natural condition as water-heat and landform, as well as human interference in natural eco-system; the evaluation result not only clearly presents mountainous vertical distribution features of input factors, but also provides a scientific and reliable thought for quantitatively evaluating mountain eco-environment.

STUDY ON FOREST FIRE DANGER MODEL WITH REMOTE SENSING BASED ON GIS

Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.

New Mathematical Model Based on Affine ransformation for Remote Sensing Image with High Resolution

This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model is strict,and the map function of each transformation is the first order polynomials and other simple function.The final calculation of the parameters is for the linear equations with good status.As a result,the problem of the relativity of image parameter calculation is solved completely.Some experiments are carried out.

Feasibility study on the binary-parameter retrieval model of ocean suspended sediment concentration based on MODIS data

This paper brought out a new idea on the retrieval of suspended sediment concentration, which uses both the water-leaving radiance from remote sensing data and the grain size of the suspended sediment. A principal component model and a neural network model based on those two parameters were constructed. The analyzing results indicate that testing errors of the models using the two parameters are 0.256 and 0.244, while the errors using only water-leaving radiance are 0,384 and 0.390. The stability of the models with grain size parameter is also better than the one without grain size. This research proved that it is necessary to introduce the grain size parameter into suspended sediment concentration retrieval models in order to improve the retrieval precision of these models.

Hyperspectral Inversion Model of Available Potassium Content in Red Soil of Eucalyptus Plantation in Northern Guangxi

Soil information is the basis of soil management and precise variable fertilization. The traditional method of obtaining soil information through chemical detection of laboratory has high cost and poor timeliness, which is difficult to meet the needs of digital forestry, soil monitoring and real-time management of nutrients. Taking red soil of Eucalyptus plantation in northern Guangxi as the research object, the spectral data of samples with different soil available potassium contents were measured, and the spectral characteristics were analyzed, and the inversion model was established by using PLS method. The results showed that the spectral sensitive bands of available potassium content in red soil of the region mainly concentrated in 400-600, 1 450, 2 200 nm and so on. After the first derivative transformation, the redundant information in the original spectral data can be significantly reduced, and the correlation between spectral indexes and soil available potassium content can be improved. The full-band modeling results of R and FDR were better than those of significant bands. The optimal model was full-band-FDR-PLS, R2=0.862, and RMSE=2.718. The results of this study can be used for the application of near-earth remote sensing in Guangxi, such as soil digital mapping, precise variable fertilization and real-time monitoring of soil available potassium.

Geological Controls and Prospectivity Mapping for Manganese Ore Deposits Using Predictive Modeling Comparison:An Integration of Outcrop and Remote Sensing Data,Sinai Microplate,Egypt

One of the most controversial minerals in their origin and occurrence around the world is manganese deposits.The Abu Zenima area is rated one of the most economically important places where manganese ore deposits(Mn ODs)are located in the southwest Sinai microplate,Egypt.These deposits are confined with the Um Bogma Formation(UBF)and the reserves of this region are relatively small.In this study,optical and radar data are used in a new challenge as an attempt to reach the closest controls and setting of Mn ODs.Moreover,Frequency Ratio(FR)and Logistic Regression(LogR)predictive models are applied to integrate different geospatial thematic maps,to predict new potential resource zones for increasing the ranges of mining quarries.Landsat8 OLI,Sentinel-2A Multi Spectral Instrument and Radar(Sentinel-1B)data are combined for mapping Mn ODs locations and their relationship with geological structures and the surrounding rocks.Band ratio,Principal and Independent Component Analysis techniques and four classification algorithms were implemented to the optical’VNIR and SWIR bands.Unusually,the interferometric processing steps for Sentinel-1 data were made for understanding the tectonic features in the area.The FR and LogR models are validated during fieldwork with known Mn ODs locations.Results indicate that processed images are capable of differentiation of UBF which broadly distributed in the central and southern parts of the area.Mn ODs possibly formed by thermal events that attributed to paleo-volcanic events before the rift stage.The high accuracy of LogR model(0.902)suggests that high Mn ODs potential zones are identified within the intersected fault zones near granitic units.This integration is recommended for discriminating hydrothermally Mn ODs in other arid geographic regions.

The research on the remote sensing＇s information tree model of the Nansha coral islets and reef＇s spatial structure

Based on the Nansha coral islets and reef's time-space attributes,and the intension and extension of the remote sensing information, the concept model and concept system of coral islets and reef are proposed.Then twin-tree remote sensing information model for different kinds of reef is constructed by using abstracted islets and reef's primitive, and the structure recognition system for coral islets and reef type is developed.

RemotesensingstudiesintheHaikouBayCalculationofthedepositionparameters

By making use of the distinguishing features of repetitive imagery of the same area by satellite remote sens-ing, a method of extracting water areas at different tidal levels from the images of bays at different times was adopted toestablish a calculating model for tidal surface and a method of finding a sum by layers was used to establish a calculatingmodel for the deposition parameter. Moreover, by making use of the calculating models for the deposition parameter andfor tidal level, the deposition parameter for the sea area less than 0 m was calculated for the Haikou Bay at two differentperiods of time: during the period of 1965 ￣ 1984 the total amount of deposits was 4 . 8 x 106 m3, and the sedimentationrate was 2 . 5 x 105 m3/a; during the period from 1984 to 1990, the total amount of deposits was - 8 . 9 x 105 m3 and thesedimentation rate was -1 . 5 x 105 m3/a.

A Comparison of SWAT Model Calibration Techniques for Hydrological Modeling in the Ganga River Watershed

恒河是印度最长的河流,目前正遭受人类活动和气候变化的影响,其中瓦拉纳西区域所受的影响尤为严重。预计气候变化和不断扩张的人口会进一步影响水资源的有效利用。本研究利用水土评价工具(soil and water assessment tool,SWAT)模型进行水文模拟,研究区选择恒河流经的印度北方邦南部地区,覆盖面积达15 621.612 km^2。本研究主要目标如下:(1)检验SWAT模型在径流和产沙量预测方面的可行性和适用性,(2)对序贯不确定性分析(SUFI-2)、普适似然不确定性估计(GLUE)和并行求解(ParaSol)这3种常规校准算法进行对比分析,并确定出最佳校准算法。SWAT模型中输入数据的来源为航天飞机雷达地形测绘任务(SRTM)获取的数字高程模型(DEM)、Landsat-8卫星图像、土壤数据和逐日气象数据。首先,本研究将研究流域划分为46个子流域,使用土地利用/土地覆被(LULC)图和土壤图创建了水文响应单元(HRU)。然后,构建了基于SUFI-2、GLUE和ParaSol算法的模型,并基于5类标准对这些校准算法进行了比较,标准包括目标函数、使用概念、性能、P因子和R因子值。研究结果表明:(1) SUFI-2算法需要的运行时间较少,同时校准结果最好,ParaSol算法最差;(2)使用SUFI-2算法对模型进行校准后,获得对模拟结果影响最显著的5个敏感参数——主河道水力传导率(CH_K2)、USLE方程水土保持因子(USLE_P)、主河道曼宁系数值(CH_N2)、地表径流滞后时间(SURLAG)以及土壤有效含水量(SOL_AWC);(3) 40号子流域(SW#40)产生的径流量最大,土地利用类型为荒地的36号子流域(SW#36)的产沙量最大,达到50 t·a^(–1)。研究区的平均蒸散量为411.55 mm·a^(–1)。校准后的模型可以用于探究未来LULC的变化、气候变化和土壤侵蚀的影响。

RS-and-GIS-Supported Forecast of Grassland Degradation in Southwest Songnen Plain by Markov Model

By taking Daan city in Jilin Province as a research object and by using TM image in 1989 and ETM + image in 2001 from American LANDSAT satellite,all kinds of maps and documentation,information of grassland,saline-alkalized land,cropland,water area and forestland is extracted by man-computer interactive interpretation method with ArcView and ArcInfo GIS software, and statistics data is acquired. On the basis of this the changing trend of land use types in the next ten years is forecasted and analyzed with Markov model. The results indicate that the problem of grassland degradation in the study area is quite serious.

Remote sensing and geographic information systems techniques in studies on treeline ecotone dynamics

We performed a meta-analysis on over 100 studies applying remote sensing(RS)and geographic information systems(GIS)to understand treeline dynamics.A literature search was performed in multiple online databases,including Web of Knowledge(Thomson Reuters),Scopus(Elsevier),BASE(Bielefeld Academic Search Engine),CAB Direct,and Google Scholar using treeline-related queries.We found that RS and GIS use has steadily increased in treeline studies since 2000.Spatialresolution RS and satellite imaging techniques varied from low-resolution MODIS,moderate-resolution Landsat,to high-resolution WorldView and aerial orthophotos.Most papers published in the 1990s used low to moderate resolution sensors such as Landsat Multispectral Scanner and Thematic Mapper,or SPOT PAN(Panchromatic)and MX(Multispectral)RS images.Subsequently,we observed a rise in high-resolution satellite sensors such as ALOS,GeoEye,IKONOS,and WorldView for mapping current and potential treelines.Furthermore,we noticed a shift in emphasis of treeline studies over time:earlier reports focused on mapping treeline positions,whereas RS and GIS are now used to determine the factors that control treeline variation.

Remote Sensing Technology for Identification of Alteration Information of Gold Deposits in the Eastern Tianshan Area, Xinjiang

Based on specific well-exposed rocks useful for high-quality remote sensing interpretation in the gold-prospecting area in the eastern Tianshan, this paper gives a detailed description of a remote sensing model for metallogenic prediction. The model reveals that multi-spectral remote sensing data are integrated with high-resolution remote sensing data, and enhanced extraction and visual description of weak remote sensing information are used for prospecting. This model has tested in the given gold deposit, and used successfully in Au-Cu prospecting in the Kalatage area.

Identification of Contamination Information of Vegetation in Coal Mines Based on Hyperspectral Remote Sensing Data

The development and application of the hyper-spectral remote sensing (HRS) in the environment investiga-tion and evaluation of coal mines have been discussed in detail. By using Hyperion HRS technology and field spectrummeasuring and integrating traditional geological method as well as laboratory chemical measurement, the absorptionspectrum features and the spectral variation rules of vegetation caused by coal mine waste piles were studied. Based onthe spectral modeling methods and Vegetation Red Edge Parameter (VREP), the diagnose spectra information andspectral variation parameter were extracted, and the mapping methods of VREP were researched. The spatial distribu-tions of contaminative vegetation have been quickly found out.This study has provided technical supports for the envi-ronment investigation and pollution management of coal mines.

Remote Sensing Study of Gold Biogeochemical Effects in the Western Guangdong-Hainan Region——A Case Study of the Hetai Gold Deposit

The vegetation has been poisoned by gold in the western Guangdong-Hainan region. The gold content ofthe leaves there is as high as 10-1961 times the abundance, the chlorophyll content is 10%-30% lower thanthat of the vegetation in metamorphic terrains and 10%-20% higher than that in granite terrains, and thecarotenoid content is 10%-44% lower than the background value. The water content of leaves is 10% to 20%lower than the background value. The cells of leaves are deformed and broken. The leaf surface shows colourspots and becomes yellow or dark green. The spectral reflectance of the leaf surface is 5%-30% higher than thebackground value: the spectral shape has shifted 5-15 nm to the short wavelength. The gray scales of eanopyon images of Landsat TM and airborne imaging scanner (AIS) are 10%-100% higher than the backgroundvalues. On Landsat TM and AIS false colour images, plants poisoned by gold display a yellow color, whichdisinguishes them from background plants. According to the spectral and image features of goldbiogeochemical effects, the author has constructed a gold information system and expert prediction system,and thus two gold target areas and two gold prospect areas have been identified rapidly, economically andaccurately in the western Guangdong-Hainan region which is extensively covered by vegetation.

The Role of Remote Sensing and GIS for Locating Suitable Mangrove Plantation Sites along the Southern Saudi Arabian Red Sea Coast

This paper investigated a methodology for locating suitable sites for establishing mangrove plantations along the south Saudi Arabian Red Sea coast based on Geological characteristics, geomorphology and discharge of drainage effluents as primary sitting criteria. Remote sensing Satellite imagery and digital elevation models were interpreted to determine most of the parameters, the rest were measured in field. In the study, it was found that some healthy mangrove stands now exist along the Red Sea coast near the city of Jizan although many stands have been destroyed in recent years due to rapid development, infilling and over-grazing and use of the mangroves as fuel. Remote sensing satellite imagery was used to map exiting Mangrove stands of different densities along the study area. The study determined that mangrove stands are primarily concentrated in the southern part of the study area and that they are sparsely found northward. Interpretation of A Landsat Thematic Mapper panchromatic band image and DEM showing that red sea coast along the study area are mainly covered by fans of ten drainage basins where the Flood potentiality of these basins was determined. The study was able to determine that three areas, which have a moderate to low flash flood potential, have the necessary environmental elements necessary to support mangroves. One, in particular, would be the best site to establish a mangrove plantation project.

Classification Method Research to Remote Sensing Images

与遥感技术的快速的开发，遥感图象的分辨率逐渐地被改进；然后，人们能从这些 images.Thus 提取更有用的数据和信息，从遥感图象的一个重要信息抽取方法-图象分类，在 phenophase 和乐队作文特征上成为越来越多的 important.Based ，这篇论文第一在遥感图象分类讨论背景参数的重要角色；然后基于

基于遥感多参数和CNN-Transformer的冬小麦单产估测

为了提高冬小麦单产估测精度,改善估产模型存在的高产低估和低产高估等现象,以陕西省关中平原为研究区域,选取旬尺度条件植被温度指数(VTCI)、叶面积指数(LAI)和光合有效辐射吸收比率(FPAR)为遥感特征参数,结合卷积神经网络(CNN)局部特征提取能力和基于自注意力机制的Transformer网络的全局信息提取能力,构建CNN-Transformer深度学习模型,用于估测关中平原冬小麦产量。与Transformer模型(R^(2)为0.64,RMSE为465.40 kg/hm^(2),MAPE为8.04%)相比,CNN-Transformer模型具有更高的冬小麦单产估测精度(R^(2)为0.70,RMSE为420.39 kg/hm^(2),MAPE为7.65%),能够从遥感多参数中提取更多与产量相关的信息,且对于Transformer模型存在的高产低估和低产高估现象均有所改善。基于5折交叉验证法和留一法进一步验证了CNN-Transformer模型的鲁棒性和泛化能力。此外,基于CNN-Transformer模型捕获冬小麦生长过程的累积效应,分析逐步累积旬尺度输入参数对产量估测的影响,评估模型对于冬小麦不同生长阶段的累积过程的表征能力。结果表明,模型能有效捕捉冬小麦生长的关键时期,3月下旬至5月上旬是冬小麦生长的关键时期。

新疆地区西昆仑和田玉遥感信息提取与找矿远景区圈定

新疆地区和田玉主要产在西昆仑至阿尔金一带,这些地区属于高海拔和严寒地区,难以直接开展地质调查工作。当前遥感技术已在热液型矿床的找矿工作中取得重要进展。和田玉矿床属于热液型矿床,地表会留下明显的矿物蚀变信息,通过遥感信息技术寻找和田玉矿床在理论上是可行的。本次研究在西昆仑康西瓦地区,使用哨兵二号、ASTER等多光谱数据和高分5号高光谱数据提取与和田玉矿化有关的蚀变信息,构建了一个以蚀变信息为主的遥感找矿找矿模型,圈定了多处和田玉遥感找矿远景区,并对找矿远景区进行了野外验证。在选取的多个和田玉遥感找矿远景区内,发现了和田玉矿的典型蚀变类型,即蛇纹石化与透闪石化,以及多处出露地表的大理岩和多处正在开采的玉石矿。野外验证结果表明,本次研究采用的和田玉遥感勘查技术是有效的。