The Review of Land Use/Land Cover Mapping AI Methodology and Application in the Era of Remote Sensing Big Data

With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.

ON THE SHARP GROWTH,COVERING THEOREMS FOR NORMALIZED BIHOLOMORPHIC MAPPINGS IN C^n

In this article, a normalized biholomorphic mapping f defined on bounded starlike circular domain in Cn is considered, where z = 0 is a zero of order k ＋ 1 of f（z） - z. The sharp growth, covering theorems for almost starlike mappings of order α and starlike mappings of order α are established. Meanwhile, the construction of the above mappings on bounded starlike circular domain in Cn is also discussed, it provides the extremal mappings for the growth, covering theorems of the above mappings.

Creation of New Global Land Cover Map with Map Integration

We present here a new approach to the development of a global land cover map. We combined three existing global land cover maps (MOD12, GLC2000, and UMD) based on the principle that the majority view prevails and validated the resulting map by using information collected as part of the Degree Confluence Project (DCP). We used field survey information gathered by DCP volunteers from 4211 worldwide locations to validate the new land cover map, as well as the three existing land cover maps that were combined to create it. Agreement between the DCP-derived information and the land cover maps was 61.3% for our new land cover map, 60.3% for MOD12, 58.9% for GLC2000, and 55.2% for UMD. Although some of the improvements we achieved were not statistically significant, this project has shown that an improved land cover map can be developed and well-validated globally using our method.

On Growth and Covering Theorem for Almost Spiallike Mapping of Type β with Order α

Let f（x） be an almost spirallike mapping of type β with order B on unit ball B of complex Banach space X. In this paper, we consider the growth and covering theorems for f（x）, we also prove that the estimation is precise when β=0 and still give growth upper bound and distortion upper bound for subordinate mapping. This result include some results known.

NORMALIZED DIFFERENCE SNOW INDEX SIMULATION FOR SNOW-COVER MAPPING IN FOREST BY GEOSAIL MODEL

The snow-cover mapping in forest area is always one of the difficult points for optical satellite remote sensing. To investigate reflectance variability and to improve the mapping of snow in forest area, GeoSail model was used to simulate the reflectance of a snow-covered forest. Using this model, the effects of varying canopy density, solar illumination and view geometry on the performance of the MODIS (Moderate-resolution Imaging Spectroradiometer) snow-cover mapping algorithm were investigated. The relationship between NDSI (Normalized Difference Snow Index), NDVI (Normalized Difference Vegetation Index) and snow fraction was discussed in detail. Results indicated that the weak performance would be achieved if fixed criteria were used for different regions especially in the complicated land cover components. Finally, some suggestions to MODIS SNOWMAP algorithm were put forward to improve snow mapping precision in forest area based on the simulation, for example, new criteria should be used in coniferous forest, that is, NDSI greater than 0.3 and NDVI greater than zero. Otherwise, a threshold on view zenith angle may be used in the criteria such as 45°.

LAND-COVER DENSITY-BASED APPROACH TO URBAN LAND USE MAPPING USING HIGH-RESOLUTION IMAGERY

Nowadays, remote sensing imagery, especially with its high spatialresolution, has become an indispensable tool to provide timely up-gradation of urban land use andland cover information, which is a prerequisite for proper urban planning and management. Thepossible method described in the present paper to obtain urban land use types is based on theprinciple that land use can be derived from the land cover existing in a neighborhood. Here, movingwindow is used to represent the spatial pattern of land cover within a neighborhood and seven windowsizes (61mx61m, 68mx68m, 75mx75m, 87mx87m, 99mx99m, 110mx110m and 121mxl21m) are applied todetermining the most proper window size. Then, the unsupervised method of ISODATA is employed toclassify the layered land cover density maps obtained by the moving window. The results of accuracyevaluation show that the window size of 99mx99m is proper to infer urban land use categories and theproposed method has produced a land use map with a total accuracy of 85%.

On Growth and Covering Theorem for Spiallike Mapping of Type β with Order α

In this paper, we consider growth and covering theorem for f（x）, where f（x） is spiallike mapping of type β with order α defined on unit ball B of complex Banach space, and x=0 is zero of order k＋1 for f（x）-x. We also dicate that the estimation is precise when β=0 and still give growth upper bound and distortion upper bound for subordinate mapping. This result include some results known.

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.

Inferring Spatial Distribution Patterns in Web Maps for Land Cover Mapping

Web maps represent an effective source for land cover mapping in capturing human activities.However,due to spatial heterogeneity,previous research has mainly focused on generating land cover maps in partial areas.Inferring spatial distribution patterns in Web maps may provide an alternative perspective on improving map production on a larger scale.This paper represents a novel approach to investigating the spatial distribution in Web maps for land cover mapping.First,linear features from Web maps are utilised to delineate parcels with insufficient Web map data for classification.Then,spatial factors are constructed from point and polygon features to identify the spatial variety of Web maps,with an artificial neural network classifier being adopted to classify land cover automatically.Land cover mapping is finally proposed by combining classified parcels and existing polygon features.The proposed method is applied in Guangzhou,Guangdong Province,using a Web map from AutoNavi.The results show an approximately 88%classification accuracy and an overall mapping accuracy of 85.06%.The results indicate that the proposed approach has the potential to be utilised in land cover mapping,and the constructed spatial factors are effective at characterising land cover information.

Land Cover Map Delineation, for Agriculture Development, Case Study in North Sinai, Egypt Using SPOT4 Data and Geographic Information System

Land cover map for a part of North Sinai was produced using the FAO—Land Cover Classification System (LCCS) of 2004. The standard FAO classification scheme provides a standardized system of classification that can be used to analyze spatial and temporal land cover variability in the study area. This approach also has the advantage of facilitating the integration of Sinai land cover mapping products to be included with the regional and global land cover datasets. The total study area is 7450 km2 (1,773,842) feddans. The landscape classification was performed on SPOT4 data acquired in 2011 using combined multi-spectral bands of 20 meter spatial resolution. Geographic Information System (GIS) was used to edit the classification result in order to reach the maximum possible accuracy. GIS was also used to include all necessary information. The identified vegetative land cover classes of the study area are irrigated herbaceous crops, irrigated tree crops and rain fed tree crops. The non-vegetated land covers in the study area include: bare rock, bare soil, bare soil stony, bare soil very stony, bare soil salt crusts, loose and shifting sands and sand dunes. The water bodies were classified as artificial perennial water bodies (fish ponds and irrigated canals) and natural perennial water bodies as lakes (standing) and rivers (flowing). Artificial surfaces in the study area include linear and non-linear. The produced maps and the statistics of the different land covers are included in the following sub-sections.

On Growth and Covering Theorem for Strongly Spirallike Mapping of Type β with Order α

In this paper, we deduce growth and covering theorem for f（x） by the other means,where f（x） is strongly spirallike mapping of type β with order α defined on Unit Ball B of complex Banach space, and still give growth upper bound and distortion upper bound for subordinate mapping.

On Growth and Covering Theorem for a Kind of Spiral-like Mappings

In this paper, we deduce growth and covering theorem for f（x） by the othermeans where f（x） is strongly spiral-like mapping of type β with order α defined on UnitBall B of complex Banach space and still give growth upper bound and distortionbound for subordinate mapping.

The Covering Theorems for Normalized Holomorphic Mappings on Bounded Starlike Circular Domains in C^n

In this paper, we will investigate convex domains and starlike domains which contain the image set of normalized holomorphic mappings on bounded starlike circular domains in Cn.

Covering Theorems on Two Classes of Quasi-conformal Mappings

In this paper we define two classes of quasiconformal mappings, and study theircovering properties by methods of module. We obtain some new results. In the meantime,we give new methods to prove Koebe 1/2 covering theorem on convex conformal mappings.

WEAK SEQUENCE-COVERING MAPPING AND CS-NETWORK

A mapping f: X→Y is called weak sequence-covering if whenever {ya} is a sequence in Y converging to y ∈ Y, there exist a subsequence {ynk} and xk∈f^-1(ynk)(k∈N) ,x∈f^-1 (y) such that xk→x. The main results are: (1) Y is a sequential, Frechet, strongly Frechet space iff every weak sepuence-covering mapping onto Y is quotient, pseudo-open, countably bi-quotient respectively, (2) weak sequence-covering mapping preserves cs-network and certain k-(cs-)networks, thus some new mapping theorems on k-(cs-)notworks are proved.

Environmental Sensitivity Index Mapping for Environmental Sustainable Cleanup along NAOC Pipeline, Asemoku, Delta State, Nigeria

During emergency response to oil spills incident accurate information is required in order to reduce the risk associated with oil spill disasters. This study focuses on Environmental Sensitivity mapping for sustainable environmental clean-up and contingency planning along the 3.0 km of AGIP pipeline at Asemoku in Delta State, Nigeria. Geographic information systems (GIS) techniques were used to create an Environmental Sensitivity Index (ESI) map in the study area. A 2018 Google Earth Satellite imagery of the study area was downloaded, and landuse/cover classification scheme comprising of Vegetation, Farmland, Water Body, Wetland, built up area and Bare Surface was adopted. Existing categorization, ranking and classification of the inland habitat were adopted and used to create a Landuse/cover Environmental Sensitivity Index (ESI) map, while the buffer zones of 100 m, 200 m, 300 m and 400 m were adopted. In the ArcGIS 10.8 environment, the landuse/cover map was generated and buffer distances of 100 m, 200 m, 300 m and 400 m were created on the landuse/cover map to ascertain the features that are vulnerable and could be at risk in the event of oil spill. This study established that the Natural Vegetation areas are the most vulnerable and sensitive feature as a result of their size along the created buffer zones. Findings from this study thus provide insight into the most sensitive land-use/land-cover, in the event of a spill or emergency oil spill clean-up response.

一种新的基于MSC和ISOMAP的快速流形学习算法

针对等距特征映射(ISOMAP)算法计算复杂度高的问题,提出了一种新的基于最小子集覆盖(MSC)策略的快速等距特征映射算法(Fast-ISOMAP)。与原始的ISOMAP算法相比,Fast-ISOMAP算法在不显著改变原始ISOMAP算法嵌入性能的条件下,大大提高了算法的计算效率,也适用于大规模流形学习问题。在标准数据集上的实验结果验证了该算法的有效性。

ON THE BOREL DIRECTION OF K-QUASIMEROMORPHIC MAPPINGS

For the K-quasimeromorphic mappings, a precise fundamental inequality for the angular domain is established. Prom this, the Borel direction of the K-quasimeromorphic mappings of zero order is derived.

The Sequence-covering Compact Images of Paracompact Locally Compact Spaces

This paper gives internal characterizations of some sequence covering compact images and compact covering compact images of paracompact locally compact spaces, which improve some results on compact images of locally compact metric spaces.

QUASIMEROMORPHIC MAPPINGS OF SEVERAL COMPLEX VARIABLES

The definitions of quasimeromorphic mappings from Cn to P1n, where P1 C U {∞}, P1n= P1×P1× ×P1(n-times) are introduced. From an inequality of the value distribution of quasimeromorphic functions of single variable, it follows that a normal criterion for the family of quasimeromorphic functions of several complex variables. Futhermore, a normal criterion for the family of quasimeromorphic mappings from Cn to P1n has been obtained.