【免费】景观生态学-空间格局分析_景观连通性资源-CSDN文库

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《景观生态学：深入探索空间格局分析》景观生态学是一门综合了地理学、生态学、遥感技术和GIS（地理信息系统）等多学科知识的领域，它关注的是地球表面不同生态系统的分布、相互作用以及空间格局。在景观生态学中，空间格局分析是至关重要的研究方法，它能够揭示生态系统复杂性的内在规律，为资源管理、环境保护和可持续发展提供科学依据。 RookCASE，作为景观格局分析的一种工具或方法，其名称中的“Rook”来源于国际象棋中的车棋子，它代表了分析时考虑相邻关系的方式。在景观格局分析中，"Rook"连接是指一个斑块的边缘与另一个斑块的边缘直接相邻，就像车棋子可以沿着棋盘的行或列移动。这种连接方式强调了相邻斑块之间的直接接触，有助于我们理解空间上的连续性和相邻生态系统间的相互影响。空间格局分析主要包括以下几个核心内容： 1. **斑块分析**：这是景观格局分析的基础，涉及斑块的形状、大小、数量和分布特征。形状指数如形状系数、紧凑度和周长-面积比，可评估斑块的复杂性和边缘效应；大小分布则反映了斑块的多样性；斑块的数量揭示了景观的破碎化程度。 2. **边缘分析**：边缘是斑块间相互接触的部分，具有独特的生态过程。边缘分析关注边缘的长度、密度和比例，以理解不同生态系统间的交互作用和能量流动。 3. **连通性分析**：连通性是生态系统健康和生物多样性的重要指标。RookCASE可以评估景观中的走廊和生态网络，确保物种迁移和种群扩散，维护生态系统的动态平衡。 4. **多样性指数**：景观多样性不仅包括物种多样性，还有斑块多样性、类型多样性和格局多样性等。这些指数可以反映景观的异质性，预测其稳定性。 5. **空间自相关分析**：通过检测景观元素的空间分布模式，了解景观格局的聚集或随机性，这有助于发现潜在的环境驱动力和生态过程。 6. **景观镶嵌模型**：模拟和预测景观变化，例如通过模型II（文件名提及的modelii）进行动态模拟，评估不同情景下的景观演变趋势。在实际应用中，景观生态学家会利用GIS和专门的软件，如FRAGSTATS或GIS工具箱，进行上述分析。这些工具可以帮助科学家处理大量数据，提取关键信息，从而对景观进行综合评价，为决策者提供科学的规划建议。景观生态学的RookCASE空间格局分析是对地球表面生态系统格局的深入探究，它揭示了生态系统的空间结构和动态，对生态保护和可持续管理具有重大意义。通过综合运用多种分析方法，我们可以更好地理解和保护我们的自然环境，实现人与自然的和谐共生。

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<html> <head> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1"> <meta name="GENERATOR" content="Microsoft FrontPage 3.0"> <title>Validation of the Join-Count Statistic</title> </head> <body background="rcgifs/back2.gif"> <div align="left"> <table border="0" cellpadding="0" cellspacing="0" width="530"> <tr> <td><a name="top"></a><img src="rcgifs/rookcase.gif" WIDTH="523" HEIGHT="100"></td> <td width="50"><img src="rcgifs/rkthmb.gif" alt="rkthmb.gif (8444 bytes)" WIDTH="142" HEIGHT="100"></td> </tr> </table> </div><div align="left"> <table border="1" cellpadding="0" cellspacing="0" width="525" bgcolor="#000000" bordercolor="#FFFFFF"> <tr> <td align="center" width="110"><a href="usrmanul.htm">USERS MANUAL</a></td> <td align="center" width="80" nowrap><a href="install.htm">INSTALLING</a></td> <td align="center" width="50" nowrap><a href="icstats.htm">I & C</a></td> <td align="center" width="75" nowrap><a href="join.htm">JOIN-COUNT</a></td> <td align="center" width="75" nowrap><a href="gistats.htm">LOCAL SA</a></td> <td align="center" width="50" nowrap><a href="idrisi.htm">IMPORT</a></td> <td align="center" width="85" nowrap><a href="../lpcdown.htm">DOWNLOAD</a></td> </tr> </table> </div> <table border="0"> <tr> <td align="right" width="70"><img src="rcgifs/thispg2.gif" WIDTH="65" HEIGHT="25"></td> <td><a href="validate.htm#Validation of Morans I and Gearys C">Validation of Morans I and Gearys C</a></td> </tr> <tr> <td align="right" width="70"><img src="rcgifs/button.gif" WIDTH="28" HEIGHT="21"></td> <td><a href="validate.htm#Validation of the Join-Count Statistic">Validation of the Join-Count Statistic</a></td> </tr> <tr> <td align="right" width="70"><img src="rcgifs/button.gif" WIDTH="28" HEIGHT="21"></td> <td><a href="validate.htm#Validation of the Local Spatial Autocorrelation (LSA) Statistics Gi, G*i">Verification of the Local Spatial Autocorrelation (LSA) Statistics</a></td> </tr> <tr> <td align="right" width="70"><img src="rcgifs/button.gif" WIDTH="28" HEIGHT="21"></td> <td><a href="validate.htm#References:">References</a></td> </tr> </table> <hr> <h1>Rooks Case Program and Algorithm Validation</h1> The following outlines the published datasets that are used to verify the operation and correctness of the calculations within Rooks Case v0.9. Each time Rooks Case is modified or altered by myself these datasets are re-analyzed in order to ensure that the computations are kept correct therein and through the development process. <h2><a name="Validation of Morans I and Gearys C">Validation of Morans I and Gearys C</a> ||| <a href="validate.htm#top">Top</a> |||</h2> Validation of the calculation of Morans I and Gearys C is most easily done since many other programs calculate Morans I and/or Gearys C. First, Griffith (1987:37) provides three 3x3 matrices for which he manually calculates Morans I and Gearys C. <div align="center"><center> <table border="1" cellpadding="0" cellspacing="1" bordercolor="#000000"> <tr> <td align="center" valign="top" width="34%">A</td> <td align="center" valign="top" width="33%">B</td> <td align="center" valign="top" width="33%">C</td> </tr> <tr> <td valign="top" width="34%"><img src="rcgifs/image33.gif" WIDTH="94" HEIGHT="80"></td> <td valign="top" width="33%"><img src="rcgifs/image34.gif" WIDTH="90" HEIGHT="79"></td> <td valign="top" width="33%"><img src="rcgifs/image35.gif" WIDTH="92" HEIGHT="82"></td> </tr> </table> </center></div>   <div align="center"><center> <table border="1" cellpadding="2" cellspacing="1" bordercolor="#000000"> <tr> <td valign="top" width="13%">Scenario</td> <td valign="top" width="10%">I</td> <td valign="top" width="13%">z-Normal</td> <td valign="top" width="21%">z-Randomization</td> <td valign="top" width="9%">C</td> <td valign="top" width="13%">z-Normal</td> <td valign="top" width="21%">z-Randomization</td> </tr> <tr> <td valign="top" width="13%">a</td> <td valign="top" width="10%">0.5, </td> <td valign="top" width="13%">2.7116</td> <td valign="top" width="21%">2.6726</td> <td valign="top" width="9%">0.333</td> <td valign="top" width="13%">2.8284</td> <td valign="top" width="21%">2.8341</td> </tr> <tr> <td valign="top" width="13%">b</td> <td valign="top" width="10%">-0.25</td> <td valign="top" width="13%">-0.5423</td> <td valign="top" width="21%">-0.5345</td> <td valign="top" width="9%">1</td> <td valign="top" width="13%">0</td> <td valign="top" width="21%">0</td> </tr> <tr> <td valign="top" width="13%">c</td> <td valign="top" width="10%">-0.875</td> <td valign="top" width="13%">-3.2540</td> <td valign="top" width="21%">-3.207</td> <td valign="top" width="9%">1.8333</td> <td valign="top" width="13%">-3.5355</td> <td valign="top" width="21%">-3.5426</td> </tr> </table> </center></div> The Results From Rooks Case v0.9 are: Scenario A <img src="rcgifs/ver1.gif" alt="ver1.gif (33849 bytes)" WIDTH="400" HEIGHT="327"> Scenario B <img src="rcgifs/ver2.gif" alt="ver2.gif (31767 bytes)" WIDTH="400" HEIGHT="337"> Scenario C <img src="rcgifs/ver3.gif" alt="ver3.gif (32438 bytes)" WIDTH="400" HEIGHT="341"> NOTE: You may notice a small discrepancy with the z-scores between Rooks Case v0.9 and the z-scores reported by Griffith, in that, the z-scores for Gearys C are positive as reported by Rooks Case and negative as reported by Griffith but the absolute values are identical. This is because Griffith uses the negation of the observed minus the mean divided by the standard deviation. Rooks Case above doesnt use the negation. Griffith presumably uses the negation so that spatial fields which are negatively autocorrelated (C between 0 and 1) have a negative z-value and vice-versa. This seems to make sense and so Rooks Case now reports the negation of the z-values for Gearys C, however, either way is correct. As a second test of the Rooks Case v0.9 calculation, a small section of a DEM