Different Types Of Land Research Articles

Spatial Analysis of Land Use Land Cover Dynamics in the Madurai District Using Sentinel-2 Data and Supervised Learning Algorithms

Abstract. LULC, or Land Use and Land Cover, refers to the classification and description of different types of land and its usage patterns, including urban areas, forests, agricultural land, etc. In remote sensing, satellite imagery for LULC mapping is becoming more widespread. Numerous studies examine various approaches to improve mapping efficiency and accuracy, highlighting the significance of various data sources, machine learning algorithms, and categorization techniques. This study employs machine learning classifiers, namely Random Forest (RF), Support Vector Machine (SVM), Gradient Boosted Trees (GTB), Classification and Regression Trees (CART), and K-Nearest Neighbors (KNN) for land use and land cover (LULC) classification of Madurai district utilizing Google Earth Engine. The findings reveal the impressive performance of Random Forest, boasting an overall accuracy of 99.01 percent coupled with a commendable Kappa coefficient of 98.68. Conversely. However, amidst these commendable achievements, it’s noteworthy to highlight the nuanced variations observed between the accuracy of training and validation sets. This discrepancy is attributed to the intrinsic intricacies of the learning processes inherent within the algorithms, underscoring the nuanced nature of algorithmic methodologies and their implications on accuracy assessment within spatial analysis frameworks. The generated land use and land cover (LULC) map allows for a comparison between the ground truth data and the surveys conducted to assess issues such as water scarcity and the drying of natural and man-made water bodies.

Research on the Interaction Mechanism between Farmland Circulation and Non-Agricultural Industry from the Perspective of Equilibrium

The “three rights division” is a major innovation in China’s land system. Under the framework of “three rights division”, there are corresponding policy constraints on the circulation of management rights of different types of land. This paper constructs a dynamic equilibrium model of farmland management right transfer from the macro level, and studies the economic connection between farmland circulation and non-agricultural sectors. The results show that there is an obvious economic interaction mechanism between the circulation of agricultural land and the development of regional non-agricultural industries, and circulation is a channel to communicate the flow of factors between the agricultural sector and the non-agricultural sector, and its flow trend is significantly affected by policies. There is a certain threshold for the start of agricultural land circulation, and the critical condition is that the industrial capital stock of the non-agricultural sector reaches a certain level. Therefore, to effectively promote the circulation of agricultural land, we cannot completely rely on the market, and the government’s action is crucial. Based on the analysis, this paper puts forward corresponding policy suggestions on guiding the circulation of farmland and better playing the role of circulation in promoting industrial development.

Land use/cover drive functional patterns of bacterial communities in sediments of a subtropical river, China

The bacterial community in sediment serves as an important indicator for assessing the environmental health of river ecosystems. However, the response of bacterial community structure and function in river basin sediment to different land use/cover changes has not been widely studied. To characterize changes in the structure, composition, and function of bacterial communities under different types of land use/cover, we studied the bacterial communities and physicochemical properties of the surface sediments of rivers. Surface sediment in cropland and built-up areas was moderately polluted with cadmium and had high nitrogen and phosphorus levels, which disrupted the stability of bacterial communities. Significant differences in the α-diversity of bacterial communities were observed among different types of land use/cover. Bacterial α-diversity and energy sources were greater in woodlands than in cropland and built-up areas. The functional patterns of bacterial communities were shown that phosphorus levels and abundances of pathogenic bacteria and parasites were higher in cropland than in the other land use/cover types; Urban activities have resulted in the loss of the denitrification function and the accumulation of nitrogen in built-up areas, and bacteria in forested and agricultural areas play an important role in nitrogen degradation. Differences in heavy metal and nutrient inputs driven by land use/cover result in variation in the composition, structure, and function of bacterial communities.

Analysis of the Government’s Decision on Leasing Different Lands under Public Ownership of Land

Using the multinomial logit model, this paper investigates the factors influencing the government’s decision to lease different types of land in Shenzhen, China, including residential, industrial, commercial, and public service land. The aspects of the land attributes, economy and government at the district level, and land accessibility are considered as the influencing factors. Regarding the factors as the variables, the influencing factors supporting the district government decision to lease different types of land and the probability that a type of land will be consider to be leased by the government are investigated via the multinomial logit model. Using data of factors from 2005 to 2021 in Shenzhen, China, the results of the model can be obtained. After discussing and analyzing the results, it is shown that the land attribute, land accessibility, and economy and polity at the district level affect government decisions on leasing land; furthermore, industrial land is more likely to be leased by the district government than other types of land. Lastly, implications and suggestions for the district government are discussed.

Conceptual Design of an Unmanned Electrical Amphibious Vehicle for Ocean and Land Surveillance

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water missions with low monetary cost (EUR < 5 k, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then, a market research analysis focused on vehicles currently available and their technological advances is conducted to identify existing UV solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle with approximate dimensions of 1050 × 670 × 450 mm (length–width–height), enabled with 6 × 6 traction capable of reaching 20 km/h on land, which possesses amphibious capabilities of independent propulsion in water up to 8 kts and an estimated autonomy of over 60 min.

PEMETAAN JASA EKOSISTEM PENYEDIA PANGAN DI PROVINSI BALI

Ecosystem services are the benefits that humans obtain from ecosystems. With the growing demand to implement sustainable development, the need for information on ecosystem services is increasing as a consideration in various policies and development planning. In response to this need, the method that is often used is the preparation of ecosystem services maps using an approach obtained from land cover data. Many people think this method works well and saves a lot of time and money, especially for studying places on a global, regional, or national level, where it's easy to get data on land cover. The point of this study is to look at how the results of the 2018 and 2022 food supply ecosystem services maps compare. These maps were made by experts who thought about how ecosystem services could be used in different types of land and ecoregions. The Analytical Hierarchy Process (AHP) with the pairwise comparison method is used to figure out how much ecosystem services are worth in relation to land cover and ecoregions. The island of Bali was used as a study area, and food supply was the type of ecosystem service that was looked at. Ecoregion data results for 2022 with the high class being more dominant and having an area of 385,339.19 ha or the equivalent of 66.67%. Land cover in 2018 produced a dominant high class with an area of 288,931.82 ha or the equivalent of 48.74%. The land cover results in 2022 are predominantly high class with an area of 289,039.25 ha or the equivalent of 50.01% of the total area of the island of Bali. The analysis results from the combination of ecoregion and land cover in 2022 are predominantly high class with an area of 182,039.65 ha or the equivalent of 31.49%. Several factors can explain the connection between ecosystem processes and the benefits they provide, which can get around or lessen the problems with using land cover data. Keywords: Ecosystem Services; Expert Judgement; Ecoregion; Land Use Based Proxy

LAND AND PROPERTY RESOURCES OF AGRICULTURAL ENTERPRISES IN THE SYSTEM OF THEIR RESOURCE POTENTIAL

The article is devoted to the justification of the organizational and economic principles of management and rational use of land and property resources and the determination of the principles of their effective combination based on the study of modern determinants of the development of the resource potential of agrarian enterprises. The meaning and role of property resources in the activity of agricultural enterprises are revealed, and their components and importance for ensuring the technical base and efficient production processes are defined. It is substantiated that the modernization of the technical park and the improvement of technological processes help to ensure the competitiveness of agricultural enterprises, reducing costs and increasing the quality of products. Land and property resources are defined as the basis of the resource potential of agrarian enterprises, and their proper management and continuous improvement are critical factors of enterprises' sustainable development in the modern conditions of the market environment. The need for a complex approach to managing land and property resources, which considers the specifics of the industry, regional features, and modern trends, has been proven. A comprehensive approach to effectively managing agricultural enterprises' land and property resources is considered. The importance of developing development strategies, implementing advanced technologies, and improving staff qualifications is substantiated. It is noted that strategies such as crop rotation, agroecological monitoring, energy efficiency, and digitalization can be used to optimize the use of resources. These measures contribute to increasing the efficiency of agricultural enterprises in modern conditions. It is established that the context of the land use management system should pay special attention to the basic principles crucial for its effectiveness. Scientific approach, objectivity, economic justification, availability of feedback, consideration of regional specifics, and differentiated application to different types of land stand out among the main principles.

Characterizing urban GHG emissions based on land-use change—A case of Airport New City

Measuring greenhouse gas (GHG) emissions across different types of land is essential for urban planning during the transition to low-carbon cities. Urban land identification, based on remote sensing images and points of interest (POIs), has the potential to narrow down the statistical unit, helping achieve spatial visualization of GHG emissions below the city level and distinguish emission characteristics of different land-use types. Considering land type as a classification standard for GHG emissions, we constructed the modified STRIPAT-PLS model by identifying land-use types, reconstructing land-use GHG emissions (LUGEs) inventory, and extracting driving indexes, which calculated driving force and LUGEs that were missed in historical years. It deepened the depth and precision of GHG emissions research and provided a reference for LUGE reduction and land management below the city level where missing historical data on GHG inventories. The results showed that: 1) the modified STRIPAT-PLS model achieved a simulation accuracy of 94.9%, demonstrating the effectiveness of our research approach in depicting GHG emissions across different land-use types. 2) Land scale, socio-economic development, and industrial development were key factors that impacted agricultural land, residential land, and airport respectively. 3) Airport was the most significant carbon contributor, while industrial witnessed the highest growth in emission intensity; 4) the spatial analysis indicated decreasing differences in GHG emissions and an overall increase in emission intensity. In addition, the research proposed emission reduction priorities and strategies for each land type to promote low-carbon goals in airport cities.

3D LAND-MARINE PROPERTIES ADMINISTRATION IN THE CONTEXT OF SEA LEVEL RISE (SLR) – ISSUES & CHALLENGES

Abstract. The current scenario of understanding spatial objects with regards to land and marine environment seems lacking. Inevitably, the scenario in line with the global warming issues as being highly mentioned by world-bodies such as the United Nations (UN) on climate change, etc. Recently the statistics on earth surface temperature point towards high record temperatures that lead to sea-level rise and degradation of land surface area, in general. These situations caused other spatial objects (land and marine properties) to be affected by their physical properties’ changes (including geometries and locations). Thus, this paper attempts to review various aspects related to digital twins of land and marine spatial objects with respect to issues and challenges of multiple data acquisition techniques considering accuracy, data standard, seamless and integrated georeferenced data within the scenario as being reported in the 6th IPCC document. The situation warrants us to explore different types of land and marine properties (static and dynamic) where static properties are defined as immovable objects and vice versa for the dynamic environment. This paper also discusses on a brief experiment utilizing MERIT DEM (Multi-Error-Removed Improved-Terrain Digital Elevation Model), existing building footprints, simulated bathymetry, and land use datasets. The experiment reveals the prediction of the sea level rise according to the IPCC report. The gist of this paper to serve a motivation for our near-future research in the context of geospatial components and sea level rise (SLR).

ATTRIBUTION ANALYSIS OF CLIMATE CHANGE AND HUMAN ACTIVITIES TO WATER VOLUME VARIATION IN LARGE LAKES

Abstract. Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.

Application of photovoltaics on different types of land in China: Opportunities, status and challenges

Addressing pressing issues such as global climate change, dwindling fossil fuel reserves, and energy structure transitions, there is a global consensus on harnessing photovoltaic (PV) technology. As PV projects burgeon, they intensify the demand for land resources. Given land's scarcity, its efficient use for PV becomes paramount. Delving into the interplay between PV and land unveils prospects for maximizing PV's potential and optimizing land use. Notably, in-depth studies spanning various land categories for PV applications remain limited. This research offers a comprehensive examination of China's land and water classification standards and policies, thoroughly investigating PV opportunities, its prevailing status, and challenges across diverse land types. It emphasizes PV application methodologies, commercial models, and specific case analyses, encompassing PV on agricultural land, construction land, inland and coastal waters, as well as sandy, saline, and mudflat regions. Results spotlight a surge in synergistic applications within agricultural photovoltaic complementary, fishery PV complementary, and forestry PV complementary models, which constitutes 76 % of all reviewed studies. Bolstered by supportive policies, rooftop PV research is also seeing a significant uptick. Conversely, studies on PV applications in deserted lands, unused terrains, and coastal waters are sparse, representing a mere 2 % of the total, pinpointing areas ripe for future exploration. Ultimately, this research furnishes invaluable insights into pioneering “PV + Land” strategies that promise both ecological and economic dividends, thereby facilitating cogent PV land-use planning, administration, and decision-making.

Vis-NIR spectroscopy coupled with PLSR and multivariate regression models to predict soil salinity under different types of land use

Soil salinization is an important environmental challenging factor that threatens human life and food security. Therefore, accurate monitoring of soil salinization needs some low-cost measurement methods. One of the rapid and low costly methods is monitoring by using Vis-NIR spectroscopy methodology. For this aim, 84 points were selected in to take soil samples in different types of land uses such as bare lands, range lands, and farm lands. Soil salinity (ECe) was measured at all sampled soils. Moreover, spectral reflectance at various bands was recorded by using a portable spectrometer. The spectral reflectance at all wavelength ranges (i.e. from 400 to 2400 nm) and a combination of spectral reflectance from different wavelengths were used as input variables for developing PLSR (partial least squares regression) and MLR (multiple regression) models. The results indicated that the derived MLR model by using combinations of spectral reflectance from different wavelengths such as 1448, 1943 and 2400 nm as input variables performed better results to predict soil salinity (RMSE = 7.890 dS m−1, R2 = 0.728, and RPD = 2.024). In addition, the results of developed PLSR and MLR models showed that the MLR model performed better soil salinity predictions at farm lands and range lands, while the accurate prediction of soil salinity for range lands was found by using developed PLSR models. It was concluded that the employing Vis-NIR spectroscopy data under different types of land uses could predict soil salinity in a different level of accuracy.

Spatiotemporal implications of flooding on relocation risk in rural and urban coastal municipalities

The research on coastal hazards predicts substantial adverse impacts of chronic and episodic flooding on populated coastal areas. Despite the growing evidence about anticipated flood risks, many coastal communities are still not adapting. The observed disconnect between science on physical impacts and adaptation decision-making in part reflects stakeholders’ inability to envision the implications of these impacts on socioeconomic systems and the built environment in their jurisdictions. This inertia is particularly apparent in the discourse on flood-driven displacement and relocation. There is a lack of knowledge about direct and indirect flood impacts on community attributes and services that contribute to relocation decision-making. This study holistically evaluates the flood exposure on municipal features vital for socioeconomic stability, livelihoods, and quality of life across spatiotemporal scales. As such, it uses a more nuanced approach to relocation risk assessment than those solely focused on direct inundation impacts. It measures flood exposure of land use, land cover, and sociocultural and economic dimensions that are important drivers of relocation in selected rural and urban areas. The approach uses a 50-year floodplain to delineate populated coastal locations exposed to 2% Annual Exceedance Probability (AEP) storm surge projections adjusted for 2030, 2060, and 2090 sea level rise (SLR) scenarios. It then evaluates the potential impacts of this flood exposure on different types of land uses and critical socioeconomic assets in rural (Dorchester and Talbot Counties, Maryland, USA) and urban (Cities of Hampton, Norfolk, Portsmouth, and Virginia Beach, Virginia, USA) settings. The results show that some urban land uses, such as open space, military and mixed-use, and rural residential and commercial areas, might experience significantly more flooding. There are also notable differences in the baseline flood exposure and the anticipated rate and acceleration in the future among selected communities with significant implications for relocation planning.

An Empirical Study on the Mismatch Phenomenon in Utilizing Urban Land Resources in China

Effective land use contributes to sustainable urban development. However, there are various reports suggesting that urban land resources used mismatch to different extents in many Chinese cities. This study measures the degree of the mismatch phenomenon in utilizing urban land resources from a supply–demand perspective, and a mismatching coefficient, namely land resource mismatch (LRM), is adopted as the measurement. The data used for the empirical analysis are from a sample of 35 cities in China. The empirical study shows the effectiveness of employing the mismatching coefficient LRM model in evaluating the degree of the mismatch phenomenon in utilizing urban land resources. The research findings suggest the following: (1) Overall, the mismatch phenomenon in utilizing urban land resources is significant in China in the form of either supply shortage or over-supply. (2) The degree of the mismatch phenomenon is different between different types of land, with the land for administration and public services showing more serious mismatching and the land for commercial and business facilities showing less mismatching. (3) There are significant differences both in the type and the degree of land use mismatch among different cities, which are contributed largely by the intensity of local government’s controlling and planning role on land resources and the maturity of applying market mechanisms. The results from this study can inform the government of the importance and necessity of adopting effective policy measures for mitigating the mismatch phenomenon in utilizing urban land resources. The research method applied in this study can be applied in a larger context internationally for understanding the effectiveness of utilizing urban land resources.

Driving Forces on the Distribution of Urban Ecosystem’s Non-Point Pollution Reduction Service

In the context of increasing urbanization and worsening environmental pollution, nonpoint source pollution during high-frequency rainfall has become a major ecological problem that endangers residents in cities. This study takes Shenzhen as an example. On the basis of a large number of soil sample test data, and combined with relevant environmental variables, it has drawn the high-resolution, high-precision spatial distribution maps of soil attributes within the city. In addition, this paper combines the revised universal soil loss equation and the GeoDetector model to evaluate the supply capacity of nonpoint source reduction services in the city’s ecological space and the main driving factors of spatial distribution characteristics for different types of land. The study found that increasing soil point density and combining environmental variables can help improve the accuracy of spatial mapping for soil attributes. The ME, MSE, ASE, RMSE, and RMSSE of spatial mapping all meet the accuracy evaluation criteria and are better than many existing studies; the spatial distribution characteristics of soil attributes and nonpoint source reduction services show significant differences among the whole city, secondary administrative regions, and different types of land; the GeoDetector results show that among the three main types of land use (forested land, industrial land, and street town residential land), topographic factors, habitat-quality factors, and ecosystem types have the greatest impact on the spatial differentiation characteristics of nonpoint source reduction services. Among climate factors, only precipitation factors have the greatest impact on the spatial differentiation characteristics of services. Facing the above factors, the q-values calculated by the GeoDetector are all higher than 10%. The results of this study can provide information for making better decisions on regional ecological system management and soil protection and on restoration work aimed at improving nonpoint source reduction services.

Suitability evaluation of land reclamation as arable land in coal mining area based on catastrophe theory

Niumasi Coal Mine (located in Shaodong City, Hunan Province, China) was an important producing area of high-quality coking coal in Hunan Province. After large-scale mining of underground coal seams in the area, there has been a large area of surface subsidence and serious land damage. The damaged land urgently needs to be reclaimed. In this paper, the suitability of land reclamation as arable land in Niumasi coal mining area was comprehensively evaluated, and a catastrophe progression model (CPM) for the suitability evaluation of land reclamation as arable land in coal mining area was put forward with the help of the catastrophe theory. The suitability classification was divided into four grades: suitable, moderately suitable, less suitable, and unsuitable. Eleven parameters including terrain slope grade, effective thickness of soil layer, soil parent materials, soil contamination, organic content, alkali hydrolyzable nitrogen (N), available phosphorus (P), available potassium (K), ground collapse, land destruction extent, and conditions of irrigation and drainage were selected as evaluation indicators, and the classification standards of each evaluation indicator was determined. Using MATLAB software to generate a total of 1200 samples (300 samples per level) between the arrays corresponding to each level of standards according to the normal distribution principle, of which 800 samples were used as training samples to establish the catastrophe progression criteria, and 400 samples as test samples to verify the reliability of the proposed criteria. According to CPM, the suitability status of the four land samples in Shuijingtou working area of Niumasi Coal Mine were identified. The evaluation results show that the suitability level of three lands are all ‘Moderately suitable’, and one sample is ‘Unsuitable’. Mining coal has the greatest damage to paddy fields, followed by the dry farming lands and vegetable lands, and the least impact to the forest lands. CPM can not only evaluate the suitability of land reclamation, and comprehensively compare the suitability degrees, but also can assess the damage degree of coal mining to different types of lands. This paper aims to provide a new idea for the study of quantitative evaluation methods of land reclamation suitability. The results have reference and guiding significance for the comprehensive evaluation of the suitability of land reclamation as arable land in coal mining areas.Article highlightsThe catastrophe theory can be used to evaluate the suitability of land reclamation as arable land in coal mining area. A catastrophe progression model for the suitability evaluation of land reclamation as arable land in coal mining area was put forward.Using MATLAB software to establish the catastrophe progression criteria according to the normal distribution principle.The results have reference and guiding significance for the comprehensive evaluation of the suitability of land reclamation as arable land in coal mining areas.

Spatial correlation and influencing factors of the urban land transaction market in the Yangtze River Delta urban agglomeration

PurposeLand transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.Design/methodology/approachBased on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).FindingsThe price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.Originality/valueThis paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

Complex-Valued U-Net with Capsule Embedded for Semantic Segmentation of PolSAR Image

In recent years, semantic segmentation with pixel-level classification has become one of the types of research focus in the field of polarimetric synthetic aperture radar (PolSAR) image interpretation. Fully convolutional network (FCN) can achieve end-to-end semantic segmentation, which provides a basic framework for subsequent improved networks. As a classic FCN-based network, U-Net has been applied to semantic segmentation of remote sensing images. Although good segmentation results have been obtained, scalar neurons have made it difficult for the network to obtain multiple properties of entities in the image. The vector neurons used in the capsule network can effectively solve this problem. In this paper, we propose a complex-valued (CV) U-Net with a CV capsule network embedded for semantic segmentation of a PolSAR image. The structure of CV U-Net is lightweight to match the small PolSAR data, and the embedded CV capsule network is designed to extract more abundant features of the PolSAR image than the CV U-Net. Furthermore, CV dynamic routing is proposed to realize the connection between capsules in two adjacent layers. Experiments on two airborne datasets and one Gaofen-3 dataset show that the proposed network is capable of distinguishing different types of land covers with a similar scattering mechanism and extracting complex boundaries between two adjacent land covers. The network achieves better segmentation performance than other state-of-art networks, especially when the training set size is small.

Land Cover Classification by Gaofen Satellite Images Based on CART Algorithm in Yuli County, Xinjiang, China

High-resolution remote-sensing images can be used in human activity analysis and criminal activity monitoring, especially in sparsely populated zones. In this paper, we explore the applicability of China’s Gaofen satellite images in the land cover classification of Xinjiang, China. First of all, the features of spectral reflectance and a normalized radar cross section (NRCS) for different types of land covers were analyzed. Moreover, the seasonal variation of the NRCS in SAR (Synthetic Aperture Radar) images for the study area, Dunkuotan Village of Yuli County, China, was demonstrated by the GEE (Google Earth Engine) platform accordingly. Finally, the CART (classification and regression trees) algorithm of a DT (decision tree) was applied to investigate the classification of land cover in the western area of China when both optical and SAR images were employed. An overall classification accuracy of 83.15% with a kappa coefficient of 0.803 was observed by using GF-2/GF-3 images (2017–2021) in the study area. The DT-based classification procedure proposed in this investigation proved that Gaofen series remote-sensing images can be engaged to effectively promote the routine workflow of the administrative department.

Komparasi Pendapatan Usaha Tani Padi Karang Dukuh Di Dua Tipe Pasang Surut Kecamatan Mandastana

The Tabing Rimbah Village and Puntik Dalam Village are villages located in Mandastana District. Tabing Rimbah Village with typology B has 482 m2 of land, while Puntik Dalam Village has 91 m2 of land with typology C. From land types B and C tidal in Mandastana District there are different types of land, these differences will affect the production of rice produced which results in the income received by farmers. This study aims to determine the comparative income of rice farming in Karang Hamlet in two different types of tides in Mandastana District. The research was conducted in November 2021. The population was 165 type B rice farmers and 153 type C rice farmers with a sample of 15 type B farmers and 15 type C farmers using a purposive sampling technique. Data analysis used descriptive analysis, cost analysis and income comparison with the T test. The results showed that the income of type B tidal farmers obtained a total explicit cost of Rp. 629,236,127 and type C Rp.610,820,680 while the implicit cost for type B Rp.213,037,500 and type C Rp.203,267,750. With a total cost of Rp.842,273,627 for type B and Rp.814,088,430 for type C. There is a significant average difference in grain and rice income for farmers in type B and C tidal land in Mandastana District.