Characterize the spatial heterogeneity of fragmented land-surface and its relationship with spatial scale in southwest china

HUANG Yajun; ZHOU Wei; MA Mingguo

doi:10.11834/jrs.20232134

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Characterize the spatial heterogeneity of fragmented land-surface and its relationship with spatial scale in southwest china
Vol. 27, Issue 3, Pages: 802-809(2023)
Received：12 April 2022，

Published：07 March 2023
DOI： 10.11834/jrs.20232134
稿件说明：

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黄雅君，周伟，马明国.2023.西南地区破碎地表空间异质性刻画与空间尺度关系初探.遥感学报，27（3）： 802-809 DOI： 10.11834/jrs.20232134.

Huang Y J，Zhou W and Ma M G. 2023. Characterize the spatial heterogeneity of fragmented land-surface and its relationship with spatial scale in southwest china. National Remote Sensing Bulletin， 27（3）：802-809 DOI： 10.11834/jrs.20232134.

摘要

尺度效应是定量遥感领域的经典且重要问题之一，其中地表异质性的判断和明确对地表真实性检验和场站优化布设问题的前置工作。并且地表异质性的判断和计算，一般是通过一景低分辨率待检验产品与同步获取的地面测量结果或者高分辨率产品进行尺度转换实现间接表达。然而，由于待检低分辨率与高分辨率遥感影像之间几乎很难做到完全同步。那么如何在缺乏同步产品的基础上，仅利用高分辨率产品去刻画地表异质性，是为下一步对空间异质性进行进一步探索和分析的前提条件。本文针对该问题使用优于0.2 m空间分辨率的无人机光谱反射率数据，计算得到归一化差值植被指数NDVI（Normalized Difference Vegetation Index）数据，通过三次卷积升尺度算法计算获取了0.2—30 m共39个不同空间分辨率结果，通过目视解译获得土地利用/覆盖变化LULC（Land Use and Land Cover change）数据，结合地理探测器对1 km×1 km图幅内的空间异质性行评价。结果表明：3个地形破碎的喀斯特槽谷区，其空间异质性评价值

的阈值存在差异，但总体上

值都随着空间分辨率的提高（30—0.2 m）由震荡趋于平稳； Mann-Kendall突变检测发现，柑橘研究所和虎头村的空间异质性突变点和

值震荡曲线的稳点阈值基本一致。

Abstract

Scale effect is one of the classical and important problems in the field of quantitative remote sensing especially in surface validation field

in which the judgment of surface heterogeneity is a precursor to the problems of surface validation and station optimized layout

and is also one of the important error sources of surface parameters validation. The first way is to calculate the accuracy evaluation of the scale transformation results between the medium resolution remote sensing products and the ground measurement results or the very high resolution products acquired at the same time to express spatial heterogeneity indirectly

and a series of errors

such as different sensors optical parameters

different measurement angles

spatial and temporal scale inconsistency

geometric mismatching etc.

they all affect the results directly or jointly

and the error contributions are difficult to quantitatively

it means that is difficult to describe the spatial heterogeneity clearly. The second way is to use geostatistical methods to describe the images for evaluation the spatial heterogeneity directly. Then how to express the surface heterogeneity with only very high resolution remote sensing measurement image based on the lack of moderation satellite retrieval products is a workable way to describe to spatial heterogeneity for further exploration and analysis of spatial heterogeneity in the next step. Therefore

this paper uses a typical algorithm to portray spatial heterogeneity and discusses the relationship between spatial resolution and spatial heterogeneity in the absence of a reference base of medium-resolution data

with a view to reflecting the relationship between resolution and spatial heterogeneity and conducting a preliminary analysis. Specifically

this paper calculates Normalized Difference Vegetation Index (NDVI) data using Unmanned Aerial Vehicle（UAV） spectral reflectance data with spatial resolution better than 0.2 m that has been Radiation calibration by reflector plates

and obtains results for 39 different spatial resolutions from 0.2 m to 30 m by cubic convolution upscaling algorithm

and obtains land use and land cover change (LULC) by visual interpretation. The spatial heterogeneity of the 1km×1km map area was evaluated with GeoDetector algorithm

and then the regional spatial heterogeneity was described to explore the relationship between resolution and spatial heterogeneity. The results showed that the thresholds of spatial heterogeneity evaluation q value were different in three regions with fragmented land-surface

but the overall q value tended were oscillate to stable with the increase of spatial resolution (30 m to 0.2 m)

and the minimum threshold from oscillation to stability was 2 m resolution; then the change curve of

value with spatial resolution and done M-K mutation detection found that the thresholds and q values of spatial heterogeneity mutation points in Ganyansuo and Hutou Village oscillation curve existed for the oscillation to stable points basically matched

but there were multiple mutation points and mismatched in the Caoshang. There were pass the 5% significance test of M-K test for all three areas

which tested the relationship between

value and spatial resolution in the aforementioned in statistical significance. In conclusion

all this classification system was now regionally stable when the resolution was lower than 2 m

i.e.

when the resolution was higher than 2 m

its spatial heterogeneity tends to stable

and its could provide some reference for the sampling of ground and space-based platforms.

关键词

Keywords

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