For centuries, the rapid development of human society has already made activity dominant factor in terrestrial ecosystem. As city greatest importance China, capital Beijing experienced eco-environmental changes with unprecedented economic and population growth during past few decades. To better understand ecological transition its correlations Beijing, Landsat Thematic Mapper (TM) Operational Land Imager (OLI) images were used to investigate vegetation coverage using a dimidiate pixel model....

The WorldView-3 (WV-3) satellite is a new sensor with high spectral resolution, which equips eight multispectral bands in the visible and near-infrared (VNIR) additional shortwave infrared (SWIR). In order to meet requirements of large-scale geological mapping, this paper assessed WV-3 data for lithological mapping comparison Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) Operational Land Imager (OLI/Landsat-8) data. study area located Pobei Xinjiang Uygur Autonomous...

The multispectral commercial satellite-WorldView-3 (WV-3) has the highest spatial, spectral and radiation resolutions among satellites currently can generate good data in shortwave infrared (SWIR). study area is located Pobei of Xinjiang Uygur Autonomous Region, which rich mineral resources. analyses some typical altered hydroxy-bearing, iron-bearing, carbonate-bearing minerals could establish several Principal Component Analysis (PCA) models indices, using visible near (VNIR) (SWIR)...

The Advanced Hyperspectral Imager (AHSI), carried by the Gaofen-5 (GF-5) satellite, is first hyperspectral sensor that simultaneously offers broad coverage and a spectrum. Meanwhile, deep-learning-based approaches are emerging to manage growing volume of data produced satellites. However, application potential GF-5 AHSI imagery in lithological mapping using methods currently unknown. This paper assessed for comparison with Shortwave Infrared Airborne Spectrographic (SASI) data. A multi-scale...

In recent years, convolutional neural networks (CNNs) have been increasingly leveraged for the classification of hyperspectral imagery, displaying notable advancements. To address issues insufficient spectral and spatial information extraction high computational complexity in image classification, we introduce MDRDNet, an integrated network model. This novel architecture is comprised two main components: a Multiscale 3D Depthwise Separable Convolutional Network CBAM-augmented Residual...

Land surface temperature (LST) is an important input parameter to characterize urban environmental heat change. Existing satellite-borne thermal infrared sensor technology cannot completely support the applications using high spatial resolution LST, such as analysis of environment and energy consumption assessment. Downscaling LST alternative method retrieve resolution. In this paper, we propose improved multi-factor geographically weighted regression (MFGWR) algorithm for downscaling. More...

Fractal and multi-fractal content area method finds application in a wide variety of geological, geochemical geophysical fields. In this study, the fractal content-gradient was used on 1:10,000 scale to delineate anomalies associated with copper mineralization. Analysis data from Yangla super large Cu-Pb-Zn polymetallic ore district using method, combined other geological area, indicates that ore-prospecting should focus Cu as main metal Pb-Zn Au auxiliary metals. The types deposits include...

Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this essential management and environmental protection. In recent years, there are increasingly large number pieces research on land surface classification by conducting multi-source remote sensing data. However, in order achieve the best result, how select optimal feature combination key issue. This study creatively combines Out Bag data with Recursive Feature Elimination...

The accurate mapping of tea plantations is significant for government decision-making and environmental protection tea-producing regions. Hyperspectral Synthetic Aperture Radar (SAR) data have recently been widely used in land cover classification, but effective integration these plantation requires further study. This study developed a new feature-level image fusion method called LPPSubFus that combines locality preserving projection subspace (SubFus) to map plantations. Based on...

The purposes are to solve the isomorphism encountered while processing hyperspectral remote sensing data and improve accuracy of in extracting classifying lithological information. Taking rocks as research object, Backpropagation Neural Network (BPNN) is introduced. After image normalized, spectrum spatial information feature extraction targets construct a deep learning-based model. performance model analyzed using specific instance data. Results demonstrate that overall Kappa coefficient...

The thermal airborne hyperspectral imager (TASI), which has 32 channels that provide continuous spectral coverage within wavelengths of 8 to 11.5 μm, is very beneficial for land surface temperature and emissivity (LSE) retrieval. In remote sensing applications, important features classification environmental monitoring, global climate change, target recognition studies. This paper proposed a separation method via sparse representation (SR-TES) with TASI data, employs sparseness differences...

Considering the important roles of carbonate rock fraction in karst rocky desertification areas and their potential for indicating damage to vegetation, improved knowledge is desired assess application spectroscopy remote sensing characterizing quantifying biophysical constituents landscapes. In this study, we examined spectra major surface direct evidence absorption features attributable fraction. Using spectral feature analysis with continuum removal, observed that there are overlapping...

Despite the successful application of multimodal deep learning (MDL) methods for land use/land cover (LULC) classification tasks, their fusion capacity has not yet been substantially examined hyperspectral and synthetic aperture radar (SAR) data. Hyperspectral SAR data have recently widely used in classification. However, speckle noise heterogeneity with imaging mechanism hindered MDL integrating Accordingly, we proposed a feature method called Refine-EndNet that combines dynamic filter...

Accurately mapping tea plantation distribution is crucial to environmental protection and sustainable development. Hyperspectral synthetic aperture radar (SAR) data have recently been widely used in land cover classification, but their ability extract regions still needs be confirmed. Compared with traditional pixel-based image analysis (PBIA), object-based (OBIA) for more worthy of implementation. This study explored the performance Gaofen-5 (GF-5) copolarized SAR using pixel- support...

äº‘è¦†ç›–ä½œä¸ºå¤©æ°”å’Œæ°”å€™å˜åŒ–çš„ä¸€ä¸ªé‡è¦å› å­,对地表-大气能量平衡和水循环有着重要的影响,å› æ­¤,å¿«é€Ÿã€å‡†ç¡®åœ°åˆ©ç”¨å«æ˜Ÿé¥æ„ŸæŠ€æœ¯æ£€æµ‹äº‘è¦†ç›–å ·æœ‰é‡è¦çš„å®žç”¨ä»·å€¼å’Œç§‘å­¦æ„ä¹‰ã€‚åˆ©ç”¨å«æ˜Ÿé¥æ„Ÿæ•°æ®,å°¤å ¶æ˜¯å¸¸ç”¨çš„Moderate Resolution Imaging Spectroradiometer（MODIS）影像数据,å› å ¶å ·æœ‰è¾ƒé«˜çš„å ‰è°±å’Œæ—¶é—´åˆ†è¾¨çŽ‡,以及2330 km扫描å¹...

利用模拟数据,评价Autonomous Atmospheric Compensation（AAC）算法的抗噪性,认为AAC算法的抗噪性较弱。基于TASI实测数据,利用AAC算法开展反演计算时,è®¡ç®—ç»“æžœå‘ˆçŽ°å‡ºå¤šæ ·æ€§é—®é¢˜ã€‚ç»“åˆIn-scene Compensation（ISACï¼‰ç®—æ³•ä¸­é»‘ä½“åƒå ƒçš„æ ‡å®šæ–¹æ³•,提出了一种复合改进算法。首å...

The prediction of regional land use and cover change is important to the local human life economic development. To build a model faces two challenges: one select appropriate driving factors; other improve accuracy. In this paper, we selected seven factors natural, social aspects proposed coupling combining ANN Markov_CA predict changes (LUCC) in Beijing, China. Using get transition rules for CA can accuracy prediction. We verified by compare simulated result with actual data, error was...