随着城市化进程的不断加快以及农业结构的不断优化，耕地受建筑占用、农业现代化发展、退耕、生产生活等因素的威胁越来越大，我国很多地区的耕地出现非农化、非粮化倾向。东乡族自治县在脱贫过程中，基础设施建设速度加快，不可避免地对当地耕地资源产生了负面影响，研究该地区非农化、非粮化耕地的空间特征及其变化趋势能够为当地非农化、非粮化耕地的优化调控提供理论依据。

本文以东乡族自治县为研究区，从范围提取、特征识别和预测分析三个方面展开相关研究工作。首先，探究以遥感影像为数据源的非农化、非粮化耕地提取方法，实现研究区内2015-2019年间4期非农化、非粮化耕地的提取；其次，从地类构成、坡度分布、景观格局和空间邻接四个方面对东乡族自治县非农化、非粮化耕地的空间特征进行研究；最后，对东乡族自治县2020-2024年的非农化、非粮化耕地变化趋势进行预测，并提出相应的优化调控方案。所得主要结论如下：

以遥感影像为数据源的非农化、非粮化耕地提取方法研究。①非农化耕地提取。采用面向对象的规则提取方法，分析样本的光谱特征、植被指数特征以及几何特征，针对不同地类构建提取规则实现分类，得到5期遥感影像分类结果并进行精度评价，叠加分析获取4期非农化耕地。结果表明：基于面向对象的规则提取方法进行分类，总体精度均高于82%，Kappa系数均高于0.78，所得的非农化耕地结果能够满足本研究需要；②非粮化耕地提取。结合基于交叉验证的递归特征消除法与随机森林分类法对研究区内种植主要粮食作物耕地进行提取，通过计算特征组合的决策系数之和得出NDVI和EVI为最优特征组合，使用随机森林分类法得到研究区内4期种植粮食作物耕地并进行精度评价，进一步获取4期非粮化耕地。结果表明：结合基于交叉验证的递归特征消除法与随机森林分类法对研究区内种植主要粮食作物耕地进行提取，总体精度均高于79%，Kappa系数均高于0.76，所得的非粮化耕地结果能够满足本研究需要。

（2）从地类构成、坡度分布、景观格局和空间邻接四个方面对东乡族自治县非农化、非粮化耕地的空间特征进行探究。结果表明：①地类构成特征：东乡族自治县非农化耕地以草地类型为主，非粮化耕地以种植非粮作物耕地为主；②坡度分布特征：东乡族自治县非农化耕地集中分布在6°~25°坡度区间，非粮化耕地主要集中分布在大于25°坡度区间；③景观格局特征：东乡族自治县各非农化耕地类型的斑块规模和图斑破碎程度均呈现增长趋势，非粮化耕地规模变化较小，未耕种作物耕地非粮化类型向图斑破碎程度小的方向发展，种植非粮作物耕地非粮化类型向图斑破碎程度大的方向发展；④空间邻接特征：东乡族自治县非农化耕地调整为未种植作物耕地的自然适宜性较高，非粮化耕地类型中，未种植作物耕地类型调整为草地的自然适宜性较高，种植非粮作物耕地调整为未种植作物耕地的自然适宜性较高。

（3）基于土地利用格局预测模型探究东乡族自治县2020-2024年非农化、非粮化耕地的变化趋势，并结合其空间特征，提出相应的优化调控意见。结果表明：2020-2024年间，东乡族自治县耕地的非农化流转受到了一定程度的抑制，而耕地的非粮化流转仍处于被促进阶段。对于东乡族自治县非农化耕地的优化调控，一是从政策上鼓励农民正确使用耕地，二是通过人工干预的方式引导非农化耕地向未耕种耕地转化；对于东乡族自治县非粮化耕地的优化调控，一是鼓励农户种植与其相邻耕地种植属性相同的农作物，二是通过提高粮作生产的机械化程度等方式降低粮食种植的成本，降低耕地撂荒率，三是合理规划布局种植非粮作物耕地，将零散的种植非粮食作物耕地集中化。

With the accelerating process of urbanization and the continuous optimization of agricultural structure, cultivated land is increasingly threatened by building occupation, agricultural modernization, returning farmland, production and life and other factors. Cultivated land in many areas of China tends to be non-agricultural and non-grain. In the process of poverty alleviation in Dongxiang Autonomous County, the acceleration of infrastructure construction eradication has a negative impact on the local cultivated land resources. Studying the spatial characteristics and change trend of non-agricultural and non-grain cultivated land in this area can provide a theoretical basis for the optimal regulation of local non-agricultural and non-grain cultivated land.

Taking Dongxiang Autonomous County as the study area, this paper carries out relevant research work from three aspects: range extraction, feature recognition and prediction analysis. Firstly, explored the extraction method of non-agricultural and non-grain cultivated land based on remote sensing images, so as to realize the extraction of four periods of non-agricultural and non-grain cultivated land from 2015 to 2019 in the study area; secondly, the spatial characteristics of non-agricultural and non-grain cultivated land in Dongxiang Autonomous County are studied from four aspects: land type composition, slope distribution, landscape pattern and spatial adjacency; finally, the change trend of non-agricultural and non-grain cultivated land in Dongxiang Autonomous County from 2020 to 2024 is predicted, and the corresponding optimal regulation scheme is put forward. The main conclusions are as follows:

(1) Research on the extraction method of non-agricultural and non grain cultivated land based on remote sensing images. ① Extraction of non-agricultural cultivated land. The object-oriented rule extraction method was used to analyze the spectral characteristics, vegetation index characteristics and geometric characteristics of the samples. The extraction rules are constructed for different land types to realize the classification. The classification results of five periods of remote sensing images are obtained and the accuracy is evaluated. The superposition analysis is used to obtain four periods of non-agricultural cultivated land. The results show that the overall accuracy of classification based on object-oriented rule extraction method is higher than 82%, and the Kappa coefficient is higher than 0.78. The results of non-agricultural cultivated land can meet the needs of this study; ② extraction of non-grain cultivated land. Combined with the recursive feature elimination method based on cross validation and the random forest classification method, the cultivated land planted with main grain crops in the study area is extracted. By calculating the sum of the decision coefficients of the feature combination, it is concluded that NDVI and EVI are the optimal feature combination. The random forest classification method is used to obtain the cultivated land planted with grain crops in the study area in four stages, and the accuracy is evaluated to further obtain the cultivated land without grain in four stages. The results show that: combining the recursive feature elimination method based on cross validation and random forest classification method to extract the cultivated land planted with main grain crops in the study area, the overall accuracy is higher than 79%, and the Kappa coefficient is higher than 0.76. The results of non-grain cultivated land can meet the needs of this study.

(2) This paper explores the spatial characteristics of non-agricultural and non-grain cultivated land in Dongxiang Autonomous County from four aspects: land type composition, slope distribution, landscape pattern and spatial adjacency. The results show that: ① the characteristics of land type composition: the non-agricultural cultivated land in Dongxiang Autonomous County is mainly grassland type, and the non-grain cultivated land is mainly cultivated land planted with non-grain crops; ② slope distribution characteristics: the non-agricultural cultivated land in Dongxiang Autonomous County is concentrated in the slope range of 6° ~ 25°, and the non-grain cultivated land is mainly concentrated in the slope range greater than 25°; ③ landscape pattern characteristics: the patch scale and patch fragmentation degree of each non-agricultural cultivated land type in Dongxiang Autonomous County show an increasing trend, the scale of non-grain cultivated land changes slightly, the non-grain cultivated land type of non cultivated crops develops towards the direction of small patch fragmentation degree, and the non-grain cultivated land type of cultivated non-grain crops develops towards the direction of large patch fragmentation degree; ④ spatial adjacency characteristics: the natural suitability of adjusting non-agricultural cultivated land to non cultivated cultivated land in Dongxiang Autonomous County is higher. Among the types of non-grain cultivated land, the natural suitability of adjusting non cultivated cultivated land to grassland is higher, and the natural suitability of adjusting non-grain cultivated land to non cultivated cultivated land is higher.

(3) Based on the prediction model of land use pattern, this paper explores the change trend of non-agricultural and non-grain cultivated land in Dongxiang Autonomous County from 2020 to 2024, and puts forward corresponding optimization and regulation suggestions in combination with its spatial characteristics. The results show that from 2020 to 2024, the non-agricultural transfer of cultivated land in Dongxiang Autonomous County has been restrained to a certain extent, while the non-grain transfer of cultivated land is still in the stage of being promoted. For the optimal regulation of non-agricultural cultivated land in Dongxiang Autonomous County, first is to encourage farmers to use cultivated land correctly from the policy, and second is to guide the transformation of non-agricultural cultivated land to non cultivated land through manual intervention; for the optimal regulation of non-grain cultivated land in Dongxiang Autonomous County, the first is to encourage farmers to plant crops with the same planting attributes as their adjacent cultivated land, the second is to reduce the cost of grain planting and reduce the abandonment rate of cultivated land by improving the mechanization of grain production, and the third is to reasonably plan and layout the cultivated land for planting non-grain crops and centralize the scattered cultivated land for planting non-grain crops.

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