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However, the lack of standardized and highly operational criteria for evaluating their conservation effectiveness, particularly across different ecological types, remains a significant gap in the literature. This study aims to address this gap by constructing a conservation effectiveness evaluation model for two distinct types of PAs in Heilongjiang Province, China: the Zhalong National Nature Reserve (ZlNNR), a wetland ecological reserve; and the Mudanfeng National Nature Reserve (MdfNNR), a forest ecological reserve. We employed various methods, including land use dynamic index, visual analysis of landscape patterns, remote sensing inversion, and a multi-factor comprehensive assessment model, to assess changes in conservation effectiveness from 2000 to 2020. Our findings reveal a contrast between the two PAs. In the ZlNNR, croplands and water bodies increased significantly by 4069.4 ha (K = 1.5820%) and 2541.58 ha (K = 3.2692%). In the MdfNNR, impervious lands increased greatly by 65.35 ha (K = 7.4021%), whereas forest lands decreased by 125 ha (K = \u22120.067%). The core area of the two PAs displayed increased landscape regularity, whereas the experimental area showed heightened landscape diversity. In ZlNNR, the MPSL value increased by 134.91%, whereas the PDL value decreased by 57.43%, indicating a more regular landscape pattern. In MdfNNR, the SHDIL value decreased by 110.7%, whereas the PDL value increased by 52.55%, indicating a more fragmented landscape pattern. The area with improved vegetation trends in ZlNNR was 8.59% larger than in MdfNNR, whereas the area with degraded vegetation trends was 4.86% smaller than in MdfNNR. In all years, the high effectiveness area was larger in ZlNNR than in MdfNNR, whereas the medium and low effectiveness areas were smaller in ZlNNR compared to MdfNNR. This study provides a scientifically rigorous assessment method for evaluating the conservation effectiveness of different types of PAs, laying a solid theoretical foundation and practical guidance for future conservation strategies.<\/jats:p>","DOI":"10.3390\/rs15184594","type":"journal-article","created":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T02:47:52Z","timestamp":1695091672000},"page":"4594","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multi-Factor Collaborative Analysis of Conservation Effectiveness of Nature Reserves Based on Remote Sensing Data and Google Earth Engine"],"prefix":"10.3390","volume":"15","author":[{"given":"Jin","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Cunyong","family":"Ju","sequence":"additional","affiliation":[{"name":"School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Tijiu","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Houcai","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Xia","family":"Jing","sequence":"additional","affiliation":[{"name":"College of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dudley, N. 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